Levels and Patterns of Genetic Diversity in Wild Populations and … · 2010-06-09 · Levels and Patterns of Genetic Diversity in Wild Populations and Cultured Stocks of Cherax quadricarinatus

Levels and Patterns of Genetic Diversity in Wild Populations and Cultured Stocks of Cherax quadricarinatus (von Martens, 1868)

(Decapoda: Parastacidae)

Natalie Baker B. App. Sci. (Hons)

Queensland University of Technology

Submitted in fulfilment of the requirement of the degree of Doctor of Philosophy, October 2005

ii

Keywords

Cherax quadricarinatus, mitochondrial DNA, microsatellites, population genetics,

phylogeography, aquaculture.

ii

Abstract Studying species at the molecular level can provide insights into how ecological and

biological processes interrelate resulting in the diversity we see today. This

information can be applied to conserve species at risk of extinction, or to better

manage genetic diversity in species of economic importance. Species that inhabit

freshwater riverine systems commonly exhibit population structures that are related

to their relative dispersal capability, contemporary stream structure and/or historical

stream structure. This thesis examined the populations genetic structure of wild and

cultured stocks of the commercially farmed freshwater crayfish, C. quadricarinatus

(von Martens), using genetic markers characterized by different modes of

inheritance. C. quadricarinatus is distributed naturally in riverine systems in

northern Australia, and southern Paupa New Guinea (PNG) and inhabits a variety of

freshwater ecosystems ranging from ephemeral to permanent. Life history

characteristics of C. quadricarinatus suggest a high level of genetic structuring

among wild stocks might exist. However, seasonal flooding coupled with low

topography across its distribution in northern Australia may promote sufficient gene

flow among rivers to produce genetic homogeneity. Historical gene flow may also

influence modern genetic structure as many distinct riverine catchments that C.

quadricarinatus inhabits, were once connected at times of lower sea level. Insight

into genetic relationships among C. quadricarinatus populations will allow for better

management practices of wild populations in the future.

The study investigated phylogenetic relationships among C. quadricarinatus

representing 17 discrete natural drainages across the natural range in Australia and

PNG, using 16s and COI gene sequences. Sequence analysis of both genes

resolved two distinct genealogical lineages in Australia and three in PNG. The two

divergent Australian lineages concur with original taxonomic descriptions of Reik

(1969) based on external morphological differences. The three C. quadricarinatus

populations sampled in PNG were all genetically distinct from each other, with one

exhibiting a close association with an Australia lineage. The immense physical

barriers (rugged mountain ranges) to gene flow in PNG will almost certainly have

reduced dispersal capabilities for C. quadricarinatus. During times of lowered sea

levels in the past, Australia and southern PNG were a single landmass with

terrestrial and freshwater organisms theoretically able to disperse over associated

land and via freshwater connections. The close genetic relationship between PNG

and Australian C. quadricarinatus support a recent freshwater connection and hence

gene flow between northern Australia and PNG C. quadricarinatus populations.

iii

Genetic differentiation among some C. quadricarinatus lineages exhibit as much

genetic divergence at 16s RNA sequences as taxonomically recognised sub-species

in the Cherax genus. Since C. quadricarinatus was originally described as different

species based on external morphological differences (Reik, 1969), it is

recommended that the taxonomy of C. quadricarinatus in Australia and PNG be re-

evaluated.

C. quadricarinatus specific microsatellite markers were developed for this study.

Five variable loci were employed to investigate the extent of contemporary gene

flow among fourteen C. quadricarinatus wild river populations in northern Australia.

High FST and genetic distance estimates observed among pair wise comparisons of

C. quadricarinatus populations are consistent with limited or no gene flow occurring

among drainages. Speculation that C. quadricarinatus may disperse between

adjacent or nearby drainages at times of flood, either across floodplains, or via flood

plumes therefore seems highly unlikely among the populations examined in the

current study. No significant correlation was observed between geographic distance

and genetic distance among C. quadricarinatus populations here. C. quadricarinatus

populations most closely resemble an island-like model, where gene flow is

independent of geographic distance among populations and where genetic

divergence occurs to a greater or lesser extent as a result of genetic drift within

otherwise isolated populations.

A significant number of C. quadricarinatus populations showed deviations from

expected Hardy-Weinberg equilibrium (HWE). Samples sizes may not have been

sufficiently large to reflect a true representation of genotypic proportions present in

the sampled populations due to the highly variable nature of microsatellite loci.

Deviations from HWE equilibrium, however, can also result from null alleles. Null

allele estimates suggested a large proportion of null alleles were present in the C.

quadricarinatus populations analysed. This may be a result of C. quadricarinatus

populations confined to discrete drainages experiencing independent evolution,

resulting in mutations in primer binding sites.

The growing economic potential of C. quadricarinatus culture, both domestically and

internationally, prompted expanding the current study to examine genetic diversity

levels in commercial C. quadricarinatus stocks. The study employed five

microsatellite markers to quantify genetic diversity in four Australian and three C.

quadricarinatus culture stocks from overseas. Many C. quadricarinatus culture

stocks also showed deviations from HWE expectations. This was not a surprising

iv

result given that the wild populations also deviated and domestication can also

influence HWE. Relatively high levels of genetic diversity were observed. This

probably results from intentional mixing of discrete river strains for production of the

first commercial stock. Genetic differentiation estimates among culture stocks and

assignment tests indicated that overseas culture stocks are most likely derived from

the first commercial culture stock developed in Australia and then disseminated

widely (the Hutchings stock). Robin Hutchings was a known supplier of live C.

quadricarinatus to many international culture initiatives. Assignment of culture stocks

back to their wild origins indicated that all C. quadricarinatus culture stocks sampled

possess alleles that originate from the Flinders River (proportions ranged from 33-

94%).

Domestication of C. quadricarinatus to date has not resulted in significant reductions

in levels of genetic diversity (heterozygosity or alleles richness) when compared to

wild populations sampled in this study. Comparing culture stocks to wild populations

to gauge their ‘genetic health’ may not be a suitable scale for evaluating genetic

diversity in culture stocks. Wild populations are essentially evolving independently,

are subjected to harsh seasonal environmental fluctuations resulting in periodic

population crashes (genetic bottlenecks), with little or no recruitment from

neighbouring drainages (gene flow). This study does however indicate that there is a

large amount of genetic diversity distributed among wild populations that has yet to

be exploited in culture. Genetic diversity in wild populations provides a resource for

future stock improvement programs for C. quadricarinatus culture and thus requires

careful conservation and appropriate management.

v

Table of Contents Keywords.................................................................................................................... ii Abstract ...................................................................................................................... ii Statement of Original Authorship .............................................................................. xi Acknowledgements .................................................................................................. xii 1 .0 General Introduction............................................................................................1

1.1 Australian aquaculture – an overview...............................................................1 1.2 Domestication of aquatic species: lessons from agriculture .............................3

1.2.1 Genetic improvement of aquaculture species ............................................4 1.3 Evolution of genetic variation in wild populations..............................................8

1.3.1 Population structure in riverine systems...................................................10 1.4 Culture of Australian freshwater crayfish species ...........................................11

1.4.1 C. quadricarinatus culture ........................................................................12 1.4.2 C. quadricarinatus taxonomy ...................................................................14

1.5 Research Objectives.......................................................................................16 1.6 Research Plan ................................................................................................17 1.7 Thesis structure ..............................................................................................17

2 .0 General Methods...............................................................................................19 2.1 Sample Collection and Storage ......................................................................19 2.2 Genetic Markers .............................................................................................22

2.2.1 Mitochondrial DNA ...................................................................................22 2.2.2 Microsatellite DNA....................................................................................23

2.3 Geographic distance among sampled wild populations..................................24 3 .0 Phylogenetic relationships among wild C. quadricarinatus populations ............23

3.1 Introduction .....................................................................................................23 3.2 Mitochondrial DNA Methodology ....................................................................26

3.2.1 Samples ...................................................................................................26 3.2.2 DNA Extraction.........................................................................................26 3.2.3 Mitochondrial DNA Extraction ..................................................................27 3.2.4 PCR Analysis ...........................................................................................27 3.2.5 Sequencing of mtDNA Haplotypes...........................................................28

3.3 Statistical Analysis ..........................................................................................28 3.3.1 Neutrality Tests ........................................................................................28 3.3.2 Testing for saturation ...............................................................................28 3.3.3 Phylogenetic reconstruction of wild C. quadricarinatus populations ........28 3.3.4 Isolation by distance.................................................................................29 3.3.5 Molecular clock estimates ........................................................................29

3.4 Mitochondrial Results .....................................................................................30 3.4.1 Analysis of 16s Sequence diversity..........................................................30

3.4.1.1 Neutrality tests .............................................................................32 3.4.1.2 16s saturation plots......................................................................32 3.4.1.3 Phylogenetic analysis of 16s sequences.....................................34 3.4.1.4 Isolation by distance ....................................................................34 3.4.1.5 16s molecular clock estimates.....................................................35

3.4.2 Analysis of COI haplotype diversity..........................................................36 3.4.2.1 COI Neutrality Test ......................................................................38 3.4.2.2 COI Saturation Plot......................................................................38 3.4.2.3 Phylogenetic analysis of COI.......................................................40 3.4.2.4 Isolation by distance ....................................................................42 3.4.2.5 COI molecular clock estimates ....................................................42

3.5 Discussion ......................................................................................................43 3.5.1 Reconstruction of the evolution of modern C. quadricarinatus lineages ..46

4 .0 The Extent of Contemporary Gene Flow among Wild Australian C. quadricarinatus Populations .....................................................................................49

4.1 Introduction .....................................................................................................49 4.2 Microsatellite Methods ....................................................................................51

vi

4.2.1 Sample sites.............................................................................................51 4.2.2 DNA Extraction.........................................................................................51 4.2.3 Microsatellite Isolation and Characterisation............................................52 4.2.4 Radioisotope Analysis of C. quadricarinatus Microsatellites ....................53 4.2.5 Fluorescent Analysis of C. quadricarinatus Microsatellites ......................54 4.2.6 Statistical Analysis ...................................................................................56

4.2.6.1 Linkage disequilibrium .................................................................56 4.2.6.2 Tests for Hardy-Weinberg Equilibrium (HWE) .............................56 4.2.6.3 Molecular diversity .......................................................................56 4.2.6.4 Null allele analysis .......................................................................56 4.2.6.5 Population differentiation .............................................................57 4.2.6.6 Genetic distance..........................................................................57 4.2.6.7 Isolation by distance measures ...................................................58 4.2.6.8 AMOVA analysis of molecular variance.......................................59 4.2.6.9 Detection of recent population bottlenecks..................................59 4.2.6.10 Shannon-Weaver Index of genetic diversity ................................60

4.3 Results............................................................................................................61 4.3.1 Microsatellite analyses of Eastern Populations ........................................61

4.3.1.1 Linkage Disequilibrium.................................................................61 4.3.1.2 Hardy Weinberg Departures ........................................................61

4.3.2 Molecular Diversity ...................................................................................61 4.3.3 Null Alleles ...............................................................................................62 4.3.4 Population differentiation..........................................................................64 4.3.5 Genetic Distance......................................................................................64 4.3.6 Isolation by Distance ................................................................................65

4.3.6.1 Mantel tests .................................................................................65 4.3.6.2 FST values graphed against geographic distance ........................65

4.3.7 AMOVA ....................................................................................................66 4.3.8 Bottleneck analysis ..................................................................................66 4.3.9 Genetic Diversity Estimates .....................................................................67 4.3.10 Microsatellite Analysis of Western Populations......................................67

4.3.10.1 Linkage Disequilibrium.................................................................67 4.3.10.2 Hardy Weinberg Departures ........................................................67 4.3.10.3 Molecular Diversity ......................................................................67

4.3.11 Null Alleles .............................................................................................68 4.3.12 Population differentiation........................................................................68 4.3.13 Genetic Distance....................................................................................69 4.3.14 Isolation by Distance ..............................................................................69

4.3.14.1 Mantel tests .................................................................................69 4.3.14.2 FST values graphed against geographic distance ........................69

4.3.15 AMOVA ..................................................................................................70 4.3.16 Bottleneck analysis.................................................................................70 4.3.17 Genetic Diversity Estimates ...................................................................71 4.3.18 Gene Flow Estimates .............................................................................71

4.4 Discussion ......................................................................................................72 5 .0 Genetic diversity in cultured C. quadricarinatus stocks compared with wild populations ...............................................................................................................78

5.1 Introduction .....................................................................................................78 5.1.1 Current status of C. quadricarinatus culture stocks..................................79

5.2 Methods ..........................................................................................................81 5.2.1 Sampling of cultured stocks .....................................................................81 5.2.1 Analysis of genetic diversity in cultured C. quadricarinatus stocks ..........83

5.2.1.1 DNA extraction and microsatellite analysis..................................83 5.2.2 Statistical analyses...................................................................................83

5.2.2.1 Molecular diversity of cultured stocks ..........................................83 5.2.2.2 Linkage disequilibrium of cultured stocks ....................................83 5.2.2.3 Hardy-Weinberg Equilibrium (HWE) of cultured stocks ...............83 5.2.2.4 Testing for bottlenecks.................................................................84

vii

5.2.2.5 Shannon-Weaver Index of genetic diversity ................................84 5.2.2.6 Origins of culture stocks – assignment testing ............................84 5.2.2.7 Comparison of culture stocks and wild populations.....................84

5.3 Results............................................................................................................85 5.3.1 Molecular diversity of culture stocks.........................................................85 5.3.2 Linkage Disequilibrium .............................................................................85 5.3.3 Hardy Weinberg Equilibrium ....................................................................87 5.3.4 Genetic distance among cultured stocks..................................................87 5.3.5 Testing for genetic bottlenecks.................................................................88 5.3.6 Genetic diversity estimates: Shannon’s Index..........................................88 5.3.7 Comparing genetic diversity between Australian and overseas culture stocks ................................................................................................................89

5.3.7.1 Number of alleles per locus .........................................................89 5.3.7.2 Levels of heterozygosity ..............................................................89 5.3.7.3 Shannon Index estimates ............................................................89

5.3.8 Assignment of C. quadricarinatus stocks to wild populations sampled ....89 5.4 Discussion ......................................................................................................91

6 .0 General Discussion ...........................................................................................95 6.1 Significance for wild populations.....................................................................96 6.2 Significance for aquaculture/fisheries policy ...................................................97

6.2.1 Aquaculture ..............................................................................................97 6.2.2 Fisheries...................................................................................................98

6.3 Recommendations for C. quadricarinatus culture industry .............................98 6.4 Future research ..............................................................................................99

7 .0 Conclusions.....................................................................................................101 8 .0 Appendix 1 ......................................................................................................103 9 Bibliography.........................................................................................................105

viii

Table of Figures Figure 1-1: Reik’s (1969) classification based on morphological differences of Cherax in northern Australia and southern PNG……………………………………..15 Figure 2-1: Shaded areas illustrate the natural distribution of C. quadricarinatus in Australia and New Guinea (Austin, 1986). ..……….………………………………...20 Figure 3-1: 1) Ancient river system at -120m sea level contour, 2) Lake Carpentaria shown at the-75m sea level contour…………………………………………………..24 Figure 3-2: Neighbour joining tree for 16s sequences of C. quadricarinatus, with C. destructor as an outgroup………………………………………………………………35 Figure 3-3: Parsimony network for C. quadricarinatus 16s haplotypes constructed in TCS……………………………………………………………………………………….36 Figure 3-4: Neighbour joining tree of Australian COI C. quadricarinatus haplotypes………………………………………………………………………………..40 Figure 3-5: Parsimony network for C. quadricarinatus COI haplotypes constructed in TCS reveals evolutionary relationships among haplotypes………………………41 Figure 4-1: Graphical representation of genetic differentiation, estimated by FST and geographic distances (km) of eastern population pairs……………………………..65 Figure 4-2: Graphic relationship between genetic differentiation FST and geographic distances (km) of western population pairs…………………………………………..70

ix

Table of Tables Table 1-1 Improvement programs applied to aquaculture species ………………….5 Table 2-1 Sampling sites, drainage system, number of individuals analysed for mtDNA and microsatellites and date collected for the present study. ………..21 Table 2-2 Stock name, location, sample size and date collected of farmed C. quadricarinatus stock sampled in this study. ………………………………………. 22 Table 3-1: Site Location, river drainage, abbreviation used in following tables and sample size for 16s and COI mtDNA gene analysis. ……………………………….26 Table 3-2: Informative sites among sampled C. quadricarinatus river populations from 482bp of 16s mtDNA identified by sequencing. ………………………………31 Table 3-3: Relationship among sampled populations based on 16sRNA sequences. ………………………………………………………………………………………………33 Table 3-4: Informative sites among C. quadricarinatus COI haplotypes …………..37 Table 3-5: Relationship among sampled populations based on COI sequences …39 Table 4-1: Site Location, river drainage, abbreviation, sample size of C. quadricarinatus populations used for microsatellite analysis ……………………..51 Table 4-2: Locus name, primer sequences (5’ to 3’ direction), repeat type and size, and PCR conditions for microsatellite loci used in this study ……………………53 Table 4-3: Locus name, repeat type/size, annealing temperature, magnesium chloride concentration and amplification success of C. quadricarinatus microsatellite loci used in this study ………………………………………………………………..53 Table 4-4: Common indices for eastern C. quadricarinatus populations…………..63 Table 4-5: Population differentiation for eastern C. quadricarinatus populations. ..64 Table 4-6: Chord distance estimates using data from five microsatellite loci for ‘eastern’ C. quadricarinatus populations. ……………………………………….…….65 Table 4-7: AMOVA showing the partitioning of variation within and among eastern populations of C. quadricarinatus. ……………………………………………………. .66 Table 4-8: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ ………………………….66 Table 4-9: Shannon's Information index (Shannon and Weaver 1949) of eastern C. quadricarinatus populations for five microsatellite loci, their mean value and standard deviation. ……………………………………………………………………… 67 Table 4-10: Common indices for western C. quadricarinatus populations.….……. 68 Table 4-11: Population differentiation for western C. quadricarinatus populations. 69 Table 4-12: Chord distance estimates using data from three microsatellite loci for western C. quadricarinatus populations. ………………………………………….….. 69

x

Table 4-13: AMOVA showing the partitioning of variation within and among western populations of C. quadricarinatus.………………………………………………..…… 70 Table 4-14: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’. …………….…………. 71 Table 4-15: Shannon's Information index (Shannon and Weaver 1949) of western C. quadricarinatus populations for three microsatellite loci………………………………71 Table 5-1: Five C. quadricarinatus microsatellite loci were successfully used to determine the levels of genetic variability in C. quadricarinatus cultured stocks. ….83 Table 5-2: Common indices for cultured C. quadricarinatus stocks. ……………….86 Table 5-3: Results of Hardy-Weinberg equilibrium exact tests. …………………….87 Table 5-4: Genetic distance measures of C. quadricarinatus culture stocks using Chord distance algorithm. ……………………………………………………….………87 Table 5-5: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’. …………………………88 Table 5-6: Shannon Index of genetic diversity of cultured populations for five microsatellite loci and their mean. ……………………………….…………………….89 Table 5-7: Proportion of C. quadricarinatus culture individuals assigned a river drainage based on 5 microsatellite loci performed in GENECLASS. …………..… 90

xi

Statement of Original Authorship The work contained in this thesis has not been previously submitted for a degree or diploma at any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made. Signed: Date:

xii

Acknowledgements “She who asks a question is a fool for a minute; she who does not remains a fool forever” (Chinese Proverb) My minute lasted many years, along the way I gained strength, motivation, encouragement and support from many people I need to thank. Special thanks to my supervisors, Peter Mather and John Wilson, especially Peter - without your support and belief in me I would not have taken on or completed this challenge. Thank you to colleagues at the School of Natural Resource Sciences; to friends who have kept me sane, given encouragement and motivation along the way, in particular: Andrew Baker, Sam Bremner, Amanda Dimmock, Angela Duffy, Martin Elphinstone, Lia Gill, Kerrilee Horskins, Maria Hughes, Rosaleen Hynes, Corinna Lange, Julie Macaranas, Justin Meager, Juanita Renwick, Monique and Nigel Wray. For reading drafts, maps and statistical advice - Andrew Baker, Mark de Bryun, Sally Dillon, Amanda Dimmock, Angela Duffy, Adam Liedloff, Peter Mather, Peter Prentis, Juanita Renwick, Alicia Toon. And lastly, my internal examiners Tony Clarke and Susan Fuller for improvements, suggestions and encouragement. I dedicate this thesis to my parents, for without their support and encouragement, I would not have started or completed this thesis. I would like to thank the following people for their help collecting samples: Wild C. quadricarinatus samples: C. quadricarinatus from the Flinders, Gilbert and Mitchell Rivers were provided by Clive Jones from the Queensland Department of Primary Industries and Fisheries, Walkamin Station, Queensland. Tracey and David Kostecki collected and sent crayfish from an undisclosed location near Weipa. Mr Peter Hurley in Darwin collected and sent Adelaide and Howard River populations. Field trips to northern Australia were made by myself and fellow QUT students: Amanda Dimmock, Shaun Meredith, Steve Caldwell, Sonja Parsonage, Mark de Bruyn, Kerrilee Horskins, Craig Streatfeild and David Elmoutie. Ian Middleton provided C. quadricarinatus samples from the Bensbach River in PNG. Jim Belford collected samples from the Oriomo River, PNG. Peter Davies at the Queensland Museum generously allowed me to remove a small portion of tissue from C. quadricarinatus specimens in their collection. Cultured stocks: Three C. quadricarinatus farms local to the Brisbane area were sampled personally. Overseas culture C. quadricarinatus samples were obtained in 2002 from with generosity from Ilan Karplus (Israel), Anthony Garcia (Mexico) and Xavier Romero (Ecuador). And thanks to Dean Jerry (CSIRO) for providing Cherax destructor and Cherax tenuimanus tissue samples as outgroup references.

1

1.0 General Introduction 1.1 Australian aquaculture – an overview Aquaculture is one of Australia’s fastest growing rural industries (AFFA, 2002).

Demand for farmed aquatic species has increased significantly as wild fish stocks

decline worldwide due to unstainable fishing practices (Carey, 1998; Pauly &

Watson, 2003). Harvesting of many aquatic species is currently at, or above, their

maximum capacity. As demand for aquatic foodstuffs rises beyond the capacity of

wild fisheries to supply markets, the Food and Agriculture Organisation (FAO)

predicts that any further increases in global consumption of seafood will need to be

met by increased production from aquaculture (FAO, 2002). In response to growing

world demand, there has been a concerted and coordinated effort by the Australian

government and industry to develop and promote aquaculture production. In doing

so, government and industry are working together to promote Australia’s clean

waters image, encourage aquaculture investment and to identify possible

alternatives for future expansion including offshore aquaculture, the use of inland

saline waters and the re-use of irrigation waters (AFFA, 2002).

Cultured pearls and bluefin tuna dominate Australian aquaculture exports.

Production of these two species represents nearly 60% of the total current value of

aquaculture production in Australia (AFFA, 2002). Other key aquaculture products

include Atlantic salmon, edible oysters, farmed prawns and trout. The Australian

pearl industry is an example of a lucrative sustainable aquaculture venture with a

promising future. The industry is based on Pinctada maxima, a pearl oyster native to

the waters of northern Australia. Although collection of wild pearl oysters occurs, the

industry has developed and operates a centralised hatchery, distributing spat to

producers for grow out on pearl farm leases. Strong investment in research and

development and ongoing technological advances ensures that the P. maxima

industry in Australia produces the highest quality cultured pearls in the world (AFFA,

2002).

Southern Bluefin tuna (Thunnus thynnus) is another economically important

Australian culture species (AFFA, 2002), but this industry may not have the capacity

to sustain long term economic growth like the pearl industry. Currently, wild juvenile

Southern Bluefin tuna are caught in the Southern Ocean and towed in special

purpose-built cages to offshore farms in South Australia where they are placed in

floating sea pontoons in coastal waters. Tuna are fed wild pilchards, jack mackerel

and squid (Holland & Brown, 1999) a practice that places additional pressure on wild

2

fish stocks and challenges the sustainability of culture production industries. With

little potential for developing improved culture breeds or the ability to adapt to culture

environments and a reliance on wild stocks to provide juveniles for grow out, the

long term viability of this species in culture is potentially compromised.

Exotic salmonids are Australia’s third most valuable culture species, first imported

during the late 1800s for the purpose of farming or recreational fishing (Ovenden et

al, 1993. Rainbow trout, (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar)

are cultured in fresh and seawater respectively to supply local and international food

markets. Brown trout (S. trutta) and to a lesser extent brook trout (Salvelinus

fontinalis) are sustained by natural spawning for recreational fishing in temperate

areas in southern Australia (ABARE, 2002). In 2000-2001, the Australian salmon

industry was valued at $95.3 million (third in value after tuna, $263.8 mil; and pearl

oysters, $171.5 mil) (ABARE, 2001). Studies of salmonid genetic diversity in

Tasmania however, have found no variation in mitochondrial DNA in Atlantic

salmon, rainbow trout or brown trout and only two mitochondrial haplotypes were

found in brook trout samples (Ovenden et al., 1993). Quarantine policies are now in

place to ensure Australia remains disease free and this means farmers are not able

to access new germplasm from overseas to improve existing salmonid culture

stocks. The lack of genetic diversity in cultured salmonids is a concern, as high

levels of genetic diversity allow populations to adapt to and resist environmental

change and disease. Currently, a marine protozoan pathogen Neoparamoeba pemaquidensis, occurs seasonally in Atlantic salmon in Tasmania, and is regarded

as a major problem that costs the industry $10m to $15m annually (State of the

Environment, 2001). With little genetic diversity remaining the long term viability of

the salmonid industry is challenged by the inability to introduce new germplasm or

the availability of an improved stock with disease resistance.

Aquatic pest species (native or exotic) have the potential to adversely affect native

fish stocks and their environment when they escape from captivity. Escaped fish

can, for instance, interbreed with wild fish, and this may have detrimental effects on

the genetic integrity and viability of wild stocks (McConnell et al., 1997); (McGinnity

et al., 2003); (Holland & Brown, 1999). Escaped fish may also contribute to the

transfer of disease or may be in direct competition for preferred habitat with wild

individuals (Youngson & Verspoor, 1998). Farmed fish commonly escape into the

wild as a result of human error, storm and/or predator damage to net cages or

inadvertent release during transport. Australia has a unique aquatic fauna and

ecosystems and introductions of foreign aquatic or terrestrial species is not

3

permitted due to the risk of escapees becoming established in our waterways and

endangering native species. Thus, essentially, Australia is restricted to developing

aquaculture industries based on indigenous species, and we must use existing wild

genetic resources to improve culture stocks.

Given these limitations, Australian aquaculture producers are still well placed to

capitalise on increasing world demand for high quality seafood. Due to strict

quarantine policies, Australia remains relatively disease free, and has not been

affected by many of the diseases that have decimated aquaculture industries

overseas (AFFA, 2002). For example, Australia is free of crayfish plague, a disease

that has decimated European and Asian crayfish culture industries (Holdich, 1993).

Technologies for efficient production and rearing have also been developed for

many native aquatic species. The future application of genetic breeding programs

are likely therefore to contribute significantly to increasing productivity of a number

of Australian native aquatic cultured species.

1.2 Domestication of aquatic species: lessons from agriculture As aquaculture of most native Australian aquatic species is relatively new, much can

be learned from advances made in agriculture. Terrestrial plants and animals of

agricultural importance have been subjected to intense domestication and artificial

selection for more than 10 000 years. Improvement in growth rates, yield and

disease resistance have been dramatic and were achieved largely through

application of artificial selection and appropriate genetic management practices

(Johnson, 1997; Gjedrem, 2000; Hulata, 2001). Improved culture stocks of terrestrial

plants and animals have been achieved in a number of ways: selection and

breeding of superior individuals or families (Daud & Ang, 1995; Bentsen et al., 1998;

Garduno-Lugo et al., 2004), the production of hybrids (Wada, 1994; Lawrence,

2004; Senanan et al., 2004) and more recently, the development and use of genetic

mapping studies that aid in the early detection of genetic loci that are linked to

desired quantitative traits (Lee & Kocher, 1996; Martinez et al., 1999; Davis &

Hetzel, 2000; Su et al., 2002; Fjalestad et al., 2003a; Li et al., 2003). Even though

the farming of aquatic species dates back nearly 4 000 years (Hulata, 1995a), most

aquaculture industries until recently, have been based on broodstock that were

essentially wild or only recently brought into captivity (eg. European carp stocks

Vandeputte, 2003). Unimproved stocks cannot guarantee productivity over time,

since captive populations may lose productivity due to inbreeding and genetic drift

effects over generations, because effective population sizes are generally low

(Lymbery, 2000; Doyle et al., 2001).

4

It is widely recognised, however, that prospects for significant genetic gains in

aquaculture species are more promising than for most terrestrial species (Gjedrem,

1997). The basic theory underlying the development of breeding plans for

aquaculture production was summarised by Gall (1991). The high reproductive

potential of most aquatic species allows high genetic gains to be achieved over a

relatively short period of time via application of intense selection. This means that

potentially a very small number of individuals can make a large contribution to the

genetic make up of successive generations, increasing the rate of inbreeding.

Consequently, restrictions on inbreeding to limit potential negative effects need to be

considered when implementing any selective breeding programme on aquatic

species. Inbreeding potential is high, due to high fecundity and short generation

times in most aquatic species (Wilkins, 1981). In contrast to the situation in

terrestrial livestock, a potential disadvantage of the high fecundity of aquatic species

is that they can be maintained from a relatively small number of broodstock (a small

effective population size). Low numbers of broodstock are often capable of

producing a large number of offspring, which can lead to loss of genetic variation by

chance (genetic drift).

1.2.1 Genetic improvement of aquaculture species

Significant and sustained genetic improvement of any domesticated species simply

exploits the natural genetic variation present in a population. Genetic gains are

obtained by increasing the proportion of desirable allelic forms of genes for desirable

quantitative trait loci (QTL) in the target populations. Many breeding programs and

selection strategies have proven highly successful in many aquatic species (see

Table 1-1 for examples).

Success in breeding programs does not necessarily translate into sustained

improvement if broodstock are not managed correctly. Poor genetic management

practices including small broodstock numbers or kinship among breeders can

quickly erode levels of genetic diversity in captive stocks over time, and this poses a

significant threat to the long term success of any culture industry (Wolfus et al.,

1997; Lymbery, 2000; Doyle et al., 2001).

5

Table 1-1 Improvement programs applied to aquaculture species

Method Species Outcome Mass selection Atlantic Salmon

Salmo salar Up to 18% increase in body weight after a single generation

(Dunham & Smitherman, 1983; Gjedrem, 1985)

Channel catfish, Ictalurus punctatus

Increases in disease resistance and cold tolerance

(Dunham & Brummett, 1999; Vandeputte, 2003)

Kuruma, Penaeus japonicus

14% increase in weight (Preston et al., 2004)

Marker assisted selection

Kuruma, Penaeus japonicus

AFLP markers for pedigree identification

(Moore et al., 1999)

Ranbow trout, Oncorhynchus mykiss

Temperature tolerant QTLs identified

(Jackson et al., 1998; Danzmann et al., 1999)

Rainbow and cutthroat trout hybrids

Markers associated with IHN virus resistance

(Palti et al., 1999)

Catfish (Ictalurus sp.) QTL Linkage mapping (Liu et al., 1999) Hybridisation of strains

Nile tilapia, Oreochromis niloticus L

10% increase in body weight (Eknath et al., 1993; Bentsen et al., 1998; Longalong et al., 1999);

Chinese big-belly x European common carp

Positive culture qualities of the European strain and the hardiness of the Chinese strain

(Hulata, 2001)

Common carp crossbreds About 20% better performance than parental lines and other control strains.

(Hulata, 1995b; Bakos & Gorda, 2001)

Pearl oyster strains, Pinctada fucata

Improvements in shell width and survival rate.

(Wada, 1994)

Hybridisation of species

Female channel catfish x male blue catfish.

Superior for commercial culture

(Smitherman & Dunham, 1985)

Female Oreochromis mossambicus x male O. hornorum

All-male offspring. Male channel catfish outperform female growth rate

Female white bass (Morone chrysops Rafinesque) x male striped bass (M. saxatilis Walbaum)

Grows faster and higher thermal tolerance, improved resistance to stress and disease

(Van Olst & Carlberg, 1990)

Female Cherax rotundus, and male C. albidus

All male offspring; monosex hybrid grew nearly twice as fast as mixed sex C. albidus

(Lawrence, 2004)

6

Studies of inbreeding in fish have been few, but reduced growth, lower viability

and/or survival and an increase in frequency of abnormalities in inbred fish stocks

has been reported (Tave, 1991; Gjerde et al., 1996; Nakadate et al., 2003). Studies

of poor performing culture stocks have often been correlated with relatively low

levels of genetic diversity when compared to the wild relatives from which culture

stocks were derived eg Salmo salar (Norris et al., 1999); Penaeus monodon (Xu et

al., 2001); Crassostrea gigas (Hedgecock & Sly, 1990). A number of strategies can

be employed to combat detrimental effects of inbreeding; one common practice is to

add new germplasm periodically from unrelated individuals. However, many

hatchery managers are unwilling to incorporate new wild individuals into their

hatcheries as it can increase the risk of introducing new diseases, parasites or

pathogens (Davis & Hetzel, 2000; Gjedrem, 2000; Knibb, 2000).

Crossing divergent inbred lines or closely related species has been practiced to

produce offspring with hybrid vigour, however, crossing genetically divergent strains

or species can also result in offspring with reduced fitness (productivity) of F1 or

later generation hybrids (Gharrett et al., 1999). This phenomenon is known as

outbreeding depression and occurs when introgression of divergent gene pools

disrupt locally co-adapted gene complexes resulting in lowered fitness. Evidence of

outbreeding depression has been reported in a variety of species where genetically

divergent strains were crossed; Drosophila (Deng & Lynch, 1996); plants (Waser &

Price, 1989), and fish (Leberg, 1993; Gharrett et al., 1999). Second generation

offspring of crosses between even and odd year pink salmon (Oncorhynchus

gorbuscha) exhibited reduced survival, when compared to pure lines. Outbreeding

depression may not occur until the second, subsequent or even backcross

generations following assortment of alleles at different loci (Templeton, 1986;

Gharrett et al., 1999). The potential for the delay of the effect until subsequent

generations makes this phenomenon often difficult to detect and perhaps impossible

to reverse.

An important lesson learned from some early aquaculture ventures is the

importance of developing a founder stock with diverse genetic attributes. For

sustainable genetic improvement it is essential to maximise genetic diversity in

founding populations. Characterising genetic diversity, by directly measuring levels

and patterns of genetic variation using appropriate genetic markers, provides the

best possible starting point for achieving this goal (Lymbery, 2000; Rao & Hodgkin,

2002; Silverstein et al., 2004). In economic terms, maximizing diversity can provide

insurance against changes in production circumstances, a new disease, or changes

7

in market demands (Oldenbroek, 1999; Rao & Hodgkin, 2002). Diversity also has an

ecological value: environmentally well-adapted breeds (e.g., trypanotolerant cattle)

allow sustainable food production in lower-input farming systems (Reist-Marti et al.,

2003), which have a reduced impact on the environment. Diversity is also a basic

prerequisite for genetic improvement of economically important traits such as

disease resistance, or livestock productivity (Frankham, 1994; Rao & Hodgkin,

2002; Gao, 2003). Wild stocks can provide the genetic resource needed for

successful and sustainable culture industries, therefore conserving wild progenitors

of domesticated breeds should warrant a high conservation priority (Frankham,

1994).

Conserving the genetic resources of wild species for domestic plants and animals

can be achieved both in situ and ex situ. Theoretically, in situ conservation is the

best method for conserving wild genetic resources (Heywood, 1992) and has many

advantages, the most notable of which is that it is dynamic and permits natural

populations of the species concerned to continue to evolve. However, this practice

may not necessarily conserve the genetic resources of the species adequately.

Many horticultural and agricultural sectors do not rely on in situ conservation now,

but focus on ex situ methods. Horticulture has practised conservation of genetic

diversity of domesticated plants by actively collecting germplasm from wild relatives

that have resulted in comprehensive gene banks for seed, tissue or pollen, or as

growing collections in plantations, field gene banks and/or botanic gardens (van

Vuren & Hedrick, 1998). In livestock production, live animals are the most common

and best known method for conserving genes, but can also be supplemented with

frozen semen and frozen embryos. Frozen tissue has the advantage that the risk of

genetic drift, inbreeding and genetic contamination from other populations is absent,

but regenerating a breed can take a long time from frozen material. Aquaculture

industries are also investing in live gene banks. For example, the Fish Culture

Research Institute, Hungary, established a live gene bank for domesticated carp in

1963. Common carp strains were collected and are maintained and supplemented

periodically with additional wild collections. This gene bank contributes significantly

to the preservation of unique gene pools of an important cultured aquatic species

(Gorda et al., 1995).

For many domesticated terrestrial livestock species nearly all wild relatives have

been lost over time (Small, 1997; Gao, 2003; Long et al., 2003). As a consequence,

unique breeds and feral stock (eg cattle, pigs and goats) now offer the only potential

sources of new genetic variation for domesticated breeds for many such species.

8

Many wild stocks of aquatic organisms are under threat from unmonitored fishing

efforts, translocation of species, introduction of exotic species and habitat

degradation (Allendorf et al., 1997; Cross, 2000; Crozier, 2000; Bakos & Gorda,

2001). Some wild stocks of aquatic species used in culture are near extinction (eg

Atlantic salmon, trout, cod (Ferguson et al., 1995; Allendorf & Waples, 1996;

Allendorf et al., 1997; Nielsen, 1998; Shaklee et al., 1999)). For example, the

Atlantic salmon Salmo salar L. is now extinct, or in critical condition, in over 27% of

rivers, and endangered or vulnerable in a further 30% of rivers in the North Atlantic

region (WWF, 2001). Like extinctions of species, the loss of wild genetic resources

is irreversible. This is a concern as this genetic variation is not only the raw material

for evolution, but is also an important resource for future improvement of domestic

animals and cultivated plants.

The extent to which individual traits or sets of attributes can be improved for

economic gain will depend on the extent of genetic variation that exists for the trait/

trait complex. In theory, populations with the highest levels of genetic diversity

possess the greatest adaptive potential and should respond best to artificial

selection programs (Wilkins, 1981; Davis & Hetzel, 2000). Wild populations, the

primary source of genetic variation, are therefore important resources for many

culture industries. The distribution of genetic resources in natural populations

depends on the interaction of life history processes, such as fecundity, social

structure and dispersal potential in present and past environments and; on genetic

processes such mutation, drift and selection (Slatkin, 1994). Understanding the

levels and patterns of genetic variation in wild populations is therefore an integral

part of any sustainable stock improvement program.

1.3 Evolution of genetic variation in wild populations Species are rarely panmictic. Rather, they are often structured into individual demes

or subpopulations of randomly interbreeding population units (Frankel & Soulé,

1981). Partial reproductive isolation coupled with restricted distributions of

subpopulations of aquatic species in time and space provides the basis for local

adaptation via selection. Thus, overall productivity and evolutionary potential of a

species will depend on maintaining the abundance and diversity of its component

subpopulations or demes. This perspective, known as the ‘stock concept’, was

initially developed for Pacific salmon Oncorhynchus spp. and is now a central theme

in the management and study of most fish and shellfish species (Berst & Simon,

1981; Dizon et al., 1992).

9

Evolutionary and biological processes combine to shape the population structure of

any organism. Evolutionary processes including natural selection, mutation, gene

flow and genetic drift largely determine the genetic structure of organisms while

biological processes associated with reproduction, life history, mating systems and

dispersal affect their demographic structures (Slatkin, 1994).

Two demographic factors, effective population size and migration rate (gene flow),

have a major impact on the degree of divergence that can develop among local

populations of most freshwater organisms (Bunn & Hughes, 1997; Costello, 2003).

Populations diverge from one another as a consequence of local selection

pressures, mutation and random genetic drift; with drift alone capable of causing

considerable divergence among populations (Galvin et al., 1996; Loertscher et al.,

1998). The rate of divergence due to drift in turn will depend largely on the genetic

effective size of local populations (Ne). Ne represents the number of breeding adults

contributing to the next generation and is affected by sex ratio, mating patterns and

individual variance in reproductive output (Crow & Kimura, 1970). Gene flow by

means of migration (m, or the proportion of individuals exchanged between

populations per generation) maintains genetic variation within populations and

retards divergence among populations. Divergence occurs as a product of Ne and

m. If Ne is small, populations tend to diverge rapidly as a result of random processes

(eg. genetic drift). However, gene flow (m) can counteract local effects of drift that

lead to divergence (Slatkin, 1987; 1994).

Two major classes of population genetic structure have been identified. The first is

found in most species with continuous distributions and the second in those

composed of discrete populations. Genetic structure of continuously distributed

populations generally takes the form of (1) panmixia, which is the free genetic

interchange of individuals across the population or (2) isolation by distance, where

interchange is local and is a function of individual lifetime dispersal distance (Slatkin

1985, Richardson et al. 1986). Levels of gene flow in continuous distribution models

are defined by the geographical spread of lifetime dispersal distances. Discrete

subpopulation models do not have an inherent geographic structure; what is more

important is the extent of gene flow among subpopulations (Slatkin, 1985). Models

of gene flow include the Island Model (Wright, 1931), which in more recent usage

represents a situation where a particular subpopulation is equally likely to send or

receive individuals from a finite number of other subpopulations (Slatkin, 1985). The

Stepping Stone model of Kimura (Kimura, 1953) describes a set of subpopulations

arranged in a one-, two-, or three- or more dimensional lattice in which individuals

10

can only move among adjacent subpopulations. These models of genetic structure

are based on the assumption that populations are dispersed geographically as if

they were islands in a matrix and gene flow can occur equally among all islands

(Kimura, 1953). However, for most freshwater organisms, riverine habitats are likely

to impose a more complex population structure.

1.3.1 Population structure in riverine systems

Recognition that obligate freshwater species often show high levels of genetic

structuring among drainages has been attributed to the isolating effects of drainage

structure, and to their relatively small populations sizes (Ward et al., 1994). High

levels of population structuring have been reported in many organisms that inhabit

freshwater systems including, fish (Waters & Burridge, 1999; McGlashan & Hughes,

2002), insects (Hughes et al., 1999; Chapman et al., 2003), molluscs (Hughes et al.,

2004) and crustaceans (Hughes, 1996; Bohonak, 1998; Cook, 2002). This has

usually been attributed to the level of fragmentation and isolation of discrete riverine

systems.

Meffe and Vrijenhoek (1988) proposed the Stream Hierarchy Model (SHM) as a

means for summarising the relationships among populations within and among

freshwater drainages. Due to the hierarchical nature of river drainages they

proposed that the probability of connectivity was related to the location of a

population in a particular drainage, such that populations within the same stream are

more likely to be genetically similar than populations in different subcatchments

irrespective of geographical distance, with most differentiation occurring at the level

of discrete drainages.

Freshwater species are inherently vulnerable to extinction when local habitat

destruction and impoundments etc erode population connectivity (Meffe and

Vrijenhoek, 1988). Reduced dispersal and gene flow will eventually change the

genetic architecture within and among natural populations. Genetic drift will cause a

progressive loss of diversity within isolated populations and increase the extent that

genetic differentiation develops among them. Local populations may go extinct in

drought years and habitats may be recolonised from more permanent populations.

Depending on the pattern of recolonisation, diversity may also decline rapidly within

and among populations. If local extinction and recolonisation events are frequent,

11

the populations will coalesce rapidly, and differences within and among populations

will be lost as Ht1 approaches zero (Meffe and Vrijenhoek, 1988).

Thus, natural populations of freshwater aquatic species are likely to show population

structuring related to the architecture and connectivity of the natural drainage

systems they occupy. This natural genetic diversity is seldom considered when new

species are brought into culture and this may limit the potential for a long term

sustainable industry. New culture industries can benefit from understanding the

levels and patterns of natural genetic diversity that are present in wild stocks, such

knowledge of population genetic structuring and the distribution of genetic diversity

can aid culturists when sourcing broodstock or new germplasm.

1.4 Culture of Australian freshwater crayfish species Australian freshwater crayfish are decapod crustaceans belonging to the Family

Parastacidae (Riek, 1969). Four species of the genus Cherax are suitable for

culture, Cherax tenuimanus or ‘marron’, one of the largest freshwater crayfish in the

world, is native to the rivers of southwest Western Australia. C. albidus and C.

destructor are collectively known by the common name of ‘yabby’ and are found in

south eastern and central Australia, respectively (Austin, 1987; Holdich, 1993;

Ackefors, 1994). C. quadricarinatus or ‘redclaw’ is found in rivers of northern

Australia, east of Darwin flowing into the Timor Sea and Gulf of Carpentaria and

southern rivers in Paupa New Guinea (PNG) and Irian Jaya (Austin, 1996). The

increase in popularity of Australian freshwater crayfish in culture in Australia, and

overseas, in recent years has prompted research into improving existing culture

stocks of those species.

The high degree of morphological variability exhibited by many Cherax species has

led to problems with their systematics that, until recently, has been based largely on

comparisons of external morphological characteristics (Riek, 1969; Austin, 1986). A

comprehensive morphometric and allozyme study of C. destructor revealed two

distinct morphotypes that corresponded with significant genetic divergence,

supporting subspecies status for C. albidus (Campbell et al., 1994). Similarly, two

genetically distinct allopatric forms of C. tenuimanus have been described recently

(Austin, 1986; Nguyen et al., 2002), although these findings are currently being

questioned. The existence of discrete forms within what was previously considered

to be a single species of C. destructor, and potentially C. tenuimanus, has important

implications for the conservation management of these species, and the design of 1 Ht = Hs + Dsr + Drt (where Hs is the average gene diversity (heterozygosity) within; Dsr is the variance between tributaries within rivers, and Drt is the variance between different rivers)

12

aquaculture improvement programs. The taxonomy of C. quadricarinatus, the focal

species of the present study, is also uncertain and requires resolution so that wild

and culture stocks can be managed appropriately.

1.4.1 C. quadricarinatus culture

C. quadricarinatus has been farmed in Australia since the mid 1980s. The culture

potential of this species has also been recognised outside Australia and C.

quadricarinatus is now also cultured in the United States, South Africa, New

Zealand, China, Israel and Ecuador (Rubino, 1992; Karplus et al., 1995; Macaranas

et al., 1995; Rouse, 1995).

C. tenuimanus was the primary freshwater crayfish farmed in Queensland during the

1980s (pers. comm. Hutchings). However, C. tenuimanus proved unsuitable for the

tropical summers of southeast Queensland and many stocks were lost to heat stress

during one unusually hot summer (pers. comm. Hutchings). C. tenuimanus stocks

were quickly replaced with the tropical species C. quadricarinatus, that was being

cultured on a single farm. Originating from northern Australia, C. quadricarinatus are

well suited to tropical environments in Queensland and the Northern Territory. Only

limited C. quadricarinatus numbers of broodstock were collected from two southern

Gulf of Carpentaria rivers and crossed in the hope of producing hybrid vigour to

produce the original founding culture stock (pers. comm. Hutchings). The precise

natural origin of C. quadricarinatus broodstock and the degree to which they were

hybridised, however, remains unknown.

Variation in morphology, behaviour, habitat preference and some quantitative traits,

such as maximum body size, growth rate, and salinity tolerance, have been reported

among wild C. quadricarinatus stocks in Australia (Austin, 1986). Gu et al. (1995)

demonstrated significant variation for growth performance and differences in body

weight of juveniles at post-release ages among inbred lines developed from discrete

wild populations from three geographically discrete Gulf river stocks. He also

demonstrated that this variation was genetically based and could potentially be of

commercial value to the culture industry if the variation could be exploited in

systematic ways in culture (Gu et al, 1995). In parallel, there have been reports of

reduced productivity and physical abnormalities in cultured C. quadricarinatus

stocks in Israel which may be indicative of inbreeding depression resulting from low

genetic diversity caused by exposure to successive genetic bottlenecks (pers.

comm. Hulata). While industry development has occurred rapidly overseas

(compared to the Australian industry), there is little ability for international producers

13

to access new genetic material from the wild, so genetic resources in their culture

industries are likely to remain depauperate (and to depend on availability of

Australian culture stocks). In contrast, if genetic variation is high in wild populations,

then the Australian industry could benefit from a systematic resampling of wild

stocks for culture.

C. quadricarinatus has responded well to genetic selection programs. In 1993 a

limited selective breeding program for C. quadricarinatus was implemented at the

QDPI Freshwater Fisheries and Aquaculture Centre, Walkamin (Jones et al., 2000).

Strains were chosen from the five major catchments at the base of the Gulf of

Carpentaria. From east to west, these included stocks from the Mitchell, Gilbert,

Flinders, Leichhardt and Gregory rivers. Captive reproduction and pond grow out

revealed substantial variation in culture traits within strains, but little variation among

them. Flinders and Gilbert River stocks were chosen to develop a synthetic

‘Walkamin’ strain. Subsequent combined family selection of the Walkamin strain has

realised a significant improvement in growth rate (~9.5% increase) when compared

to existing culture stocks (Jones et al., 2000). The improved strain is currently being

evaluated under commercial farm conditions. This project deliberately targeted wild

stocks for the breeding program as levels of genetic variation in culture stocks were

unknown but considered likely to be deficient.

Ogden (2000) investigated juvenile growth performance among inbred lines of

divergent wild C. quadricarinatus stocks and their crosses under experimental tank

conditions. Although results were not conclusive due to a low number of replicates,

Ogden (2000) reported the potential for better performance of offspring of Flinders

and Weipa crosses and relatively poor performance in offspring of Flinders and

Howard crosses. Although crossing divergent individuals can result in heterosis,

introgression of divergent populations can also disrupt locally co-adapted gene

complexes resulting in unwanted outcomes. The breakdown of these complexes

may not be seen until the second or later generations when assortment of alleles at

different loci takes place. Ogden (2000) also reported that attempted crosses

between C. quadricarinatus from extreme ends of the species natural distribution

were unsuccessful, as no Weipa/Howard crosses were produced in his trials. While

this result is preliminary, one possible interpretation of this result may be that this

could be evidence for outbreeding depression.

14

1.4.2 C. quadricarinatus taxonomy

C. quadricarinatus as it is known currently was originally described as three taxa

(see Figure 3.1), based on external morphology (Reik, 1969). Eastern populations in

Queensland were classified as C. quadricarinatus (von Martens), western

populations in the Northern Territory were classified as C. bicarinatus (Gray, 1845)

and PNG populations as C. albertisii (Nobili, 1901), based on small differences in

the male genitalia, cephalothorax, number of rostral spines, chelae and body shape

(Reik, 1969). C. bicarinatus differed from C. quadricarinatus in the shape of the

areola and length of the rostral carinae combined with a slight difference in the

number of rostral spines (Reik, 1969). C. albertisii was described as possessing

narrower claws relative to the other two ‘species’ (Nobili, 1901). The natural

distributions of the three taxa were considered to be disjunct, and this was used to

support their recognition as discrete species.

Reik’s (1969) classification remained unchallenged until Austin (1996) carried out an

allozyme study of the three taxa. The 23 variable allozyme loci Austin used could

not distinguish between C. bicarinatus, C. albertsii and C. quadricarinatus and so he

regarded them as belonging to a single morphologically variable species (Austin,

1996). Austin (1996) concluded that morphological differentiation observed among

the species was most likely a reflection of morphological plasticity in response to

difference in regional environmental conditions, rather than evidence for discrete

species.

One important discovery since Reik’s (1969) classification is that the allopatric

‘species’ distributions he described (Figure 3.1) were not accurate. C.

quadricarinatus are found almost ‘continuously’ across many of the rivers flowing

into the Gulf of Carpentaria and the Timor Sea east of Darwin and the southern

rivers of PNG (Austin, 1996). Since only low levels of genetic differentiation were

evident among allopatric crayfish species, Austin argued that the three species

described by Reik (1969) should be reclassified under the single name C.

quadricarinatus.

15

Figure 1-1: Reik’s (1969) classification based on morphological differences of Cherax in northern Australia and southern PNG.

Macaranas et al. (1995) subsequently identified a single fixed allelic allozyme

difference, at the Carbonic Anhydrase locus (CA), between ‘western’ and ‘eastern’

C. quadricarinatus populations across northern Australia. Austin did not examine

this locus. Detection of a fixed allozyme difference contrasts with Austin’s

suggestion that C. quadricarinatus was genetically homogenous across its natural

range in northern Australia. Carbonic anhydrase catalyses the hydration of CO2 to

provides H+ and HCO3- for use in sodium and chloride uptake (Henry, 1988). This is

an important metabolic process during ion exchange in freshwater crayfish,

especially during crayfish intermoult stages (Wheatly and Gannon 1995).

Macaranas et al. (1995) suggested that the fixed difference was related to

differences in local water chemistry (pH) experienced by western (alkaline water)

versus eastern (acidic water) populations in northern Australia. Whether this

difference reflects historical isolation and independent evolution, or is the result of

extreme selection on pH regulation associated with environmental water chemistry,

is still unresolved, but it would be unwise to use this difference (in isolation) to

endorse the existence of discrete biological species.

As phenotype can be affected by environment, taxonomic delineations based solely

on morphometrics need to be interpreted with caution. Since allozyme studies of

most decapod crustaceans have generally revealed low levels of genetic variation

(Busack, 1988) even among discrete taxa, the use of allozyme data to characterise

AUSTRALIA

PAPUA NEWGUINEA

C. albertsii C. bicarinatus C. quadricarinatus

16

systematic relationships among decapods also needs to be treated with caution.

There now exists a vast body of literature that has demonstrated the ability of

molecular data (DNA) to delineate species boundaries (Avise, 1994; Bouchon et al.,

1994; Horovitz & Meyer, 1995) for sympatric taxa that display little or limited

morphological variation (Moritz & Joseph, 1993; Daniels et al., 2003; Gouws et al.,

2004).

A large amount of direct and indirect evidence suggests that extensive genetic

diversity may be present in wild C. quadricarinatus populations. However, it is not

currently known how much genetic variation has been exploited in existing culture

stocks, or how much genetic diversity is distributed among wild populations. The C.

quadricarinatus culture industry could benefit substantially from the application of

genetic diversity studies and this information could also assist in design of detailed

management policies for conservation of wild genetic resources for the species in

Australia.

Commercial culture of C. quadricarinatus, like many aquaculture ventures, began in

a haphazard way, without a systematic analysis of wild populations to generate a

genetically diverse founding culture stock. Furthermore, many C. quadricarinatus

farms have obtained their stocks from other farms, a process that exposes culture

stocks to sequential bottlenecks that could negatively impact on genetic diversity

levels. Ideally, development of a healthy commercial C. quadricarinatus culture

stock would have involved the evaluation of wild stocks under culture conditions,

initiation of large broodstock populations and a centrally based hatchery that

monitored and maintained genetic diversity in stocks from which new farms could

obtain high quality broodstock. At this stage the industry has little knowledge of the

genetic diversity in wild or cultured C. quadricarinatus stocks. As most C.

quadricarinatus farmers began as hobby farmers and husbandry practices are still

being optimised, long term issues of genetic diversity were of little concern at the

time. The C. quadricarinatus industry is now expanding in Australia, so low genetic

diversity in C. quadricarinatus culture stocks could represent a major impediment to

productivity for farmers both domestically and internationally in the future.

1.5 Research Objectives The current study is the first comprehensive evaluation of genetic diversity in wild

populations of an economically important Australian native aquaculture species. A

detailed genetic inventory and description of stocks is essential for meaningful stock

management and conservation programs. Optimal long term management and

17

conservation of wild C. quadricarinatus will depend on knowing the distribution of

genetic resources for culture so that their integrity and diversity can be sustained.

The study aims to provide a detailed description of the levels and patterns of genetic

diversity in wild C. quadricarinatus populations and to compare them with the

genetic diversity in representative commercial stocks in Australia and from

overseas.

1.6 Research Plan Collection of wild C. quadricarinatus population were carried out across the species’

natural distribution in Australia and PNG by field collections, samples obtained by

collaborators and by access to museum collections. Sampling was hierarchical in

nature and assessed variation broadly across the species range, among major

drainage basins, among rivers within major drainage basins, and within single major

river systems. Cultured populations of C. quadricarinatus were also sourced from

Australian and overseas farms, allowing for comparisons of genetic diversity levels

to be made between wild and domesticated stocks. The analysis was also

structured to identify the likely wild origins of sampled culture stocks. Genetic

markers were also used to assess the likely effects of past culture practices on

genetic diversity levels in this species.

1.7 Thesis structure General methodologies are described in Chapter 2, where information regarding the

sampling design, location of collection sites and genetic markers used are

presented. Before new germplasm can be sourced from wild stocks, C.

quadricarinatus systematics requires clarification. Since, results of morphometric

and allozyme studies have proven contradictory and ineffective for unambiguous

systematic designation, mitochondrial DNA markers were employed to investigate

phylogenetic relationships among wild C. quadricarinatus populations; the results of

this analysis are presented in Chapter 3. The identification of evolutionary significant

lineages is essential if new germplasm is likely to be sourced systematically for use

in culture in the future, especially when the taxonomy of C. quadricarinatus is in

doubt.

Knowledge of stock structure is an important prerequisite for developing a diverse

founder stock that will have the necessary genetic attributes and diversity to respond

positively to artificial selection programs. Although mtDNA markers are powerful

tools for determining historical relationships among C. quadricarinatus populations,

contemporary gene flow can also influence stock structure. Microsatellite markers

18

are ideal candidates for quantifying population genetic structure of wild C.

quadricarinatus populations; results of this analysis are presented in Chapter 4.

The process of domestication can sometimes rapidly compromise levels of genetic

diversity resulting in reduced fitness of culture stocks that may affect productivity.

Chapter 5 investigates the levels of genetic diversity in Australian and overseas

cultured C. quadricarinatus stocks, these data were compared to levels of genetic

diversity detected in wild populations. Microsatellite markers can be used routinely

to monitor levels of genetic diversity. Chapter 6 provides a general discussion of the

major findings of the study and discusses their consequences and applications for

the C. quadricarinatus culture industry in the future.

Chapter Two: General Methods

19

2.0 General Methods

2.1 Sample Collection and Storage Wild C. quadricarinatus populations occur in rivers flowing into the Gulf of

Carpentaria and the Timor Sea east of Darwin, (Figure 2-1), and unconfirmed

reports suggest C. quadricarinatus may also occur naturally in some rivers to the

west of Darwin. Wild populations are also found in some southern flowing rivers in

Papua New Guinea (Austin, 1986). A large population of C. quadricarinatus found

outside the described natural range in Australia was also included from the Ord

River (Kununurra, WA). The remoteness of rivers in the Northern Territory and the

Ord River in WA means that wild C. quadricarinatus populations in this region may

have remained undocumented until recently. However, there has been potential for

translocations of C. quadricarinatus populations among rivers in recent times. Due

to the popularity of C. quadricarinatus as a recreational fishing species, some

populations have been translocated intentionally to waterways and impoundments

where they do not occur naturally. Therefore, while presence of populations in the

Ord may be natural, they may also have resulted from translocation events

associated with efforts to develop the species in culture in the region or as bait used

by recreational fisherman for freshwater sport fishing (eg barramundi).

Wild populations of C. quadricarinatus from across the natural range in northern

Australia were collected according to the following criteria: 1) they consisted of

essentially natural, undisturbed populations, 2) major regions/drainage systems

across the natural distribution were represented and 3) in order to identify the

distribution of genetic variation at various levels of scale, a hierarchical method of

sampling was employed to investigate genetic variation among sites within individual

drainages, among major drainages within a region and among regions in northern

Australia and PNG.

C. quadricarinatus in the wild have a large natural distribution, however, much of this

region consists of ephemeral rivers. Finding significant permanent water bodies in

some river systems proved difficult during field trips. Also, large numbers of

Macrobrachium rosenbergii (the giant freshwater prawn) were observed at many

sites where C. quadricarinatus were apparently absent. In general, field

observations found that where M. rosenbergii were present, C. quadricarinatus were

often absent and vice versa.


20

Figure 2-1: Shaded areas illustrate the natural distribution of C. quadricarinatus in Australia and New Guinea (Austin, 1986). Rivers shown here have been sampled for this study; please note these are not all rivers in this region and those shown may be ephemeral.

Crayfish were caught in two ways; 1) Traps were set in the late afternoon, left

overnight and checked first thing the next day. At least ten ‘Opera House’ traps

baited with dry dog biscuits (pers. comm. Clive Jones) were used at each location,

placed 10 – 20m apart. If no crayfish were caught over two consecutive nights, the

site was abandoned. 2) Shallow water bodies with little vegetation near the edge

were also sampled with a cast net. This method proved successful in obtaining a

complete sample from a shallow pool in the Norman River. After tail clips were

taken, individuals were returned live to the their catch site. C. quadricarinatus tissue

(muscle tissue or tail clips) were preserved in 70% ethanol. Table 2-1 describes

location, population size and collection date for sampled wild C. quadricarinatus

populations.

halla

This figure is not available online. Please consult the hardcopy thesis available from the QUT Library


21

Table 2-1 Sampling sites, drainage system, number of individuals analysed for mtDNA and microsatellites and date collected for the present study. Sample sites are listed from west to east. *Samples supplied from the Queensland Museum. ^Refer to acknowledgements for collectors.

Population Name

Site Location Drainage n (mtDNA)

n (microsat)

Date Collected

Kununurra Kununurra Dam, WA^ Ord 2 22 June, 2002 Howard Near Howard Springs, NT^ Howard 2 30 Dec, 1996 Adelaide 50km east of Humpty Doo, Adelaide

River, NT^ Adelaide 2 24 Dec, 1996

Roper Mataranka, Roper River, NT Roper 2 11 Oct, 1999 McArthur Cape Crawford, McArthur River, NT McArthur 2 25 Oct, 1999 Calvert ‘Pungalina’, Calvert River, NT Calvert 2 23 Oct, 1999 Gregory ‘Gregory Downs’, Gregory River,

QLD Gregory 2 33 Oct, 1999

Louie Louie Creek, QLD* Gregory 2 - June, 1995 Leichhardt Near Leichhardt Falls, Leichhardt

River, QLD Leichhardt 2 - Nov, 2002

Flinders Near Richmond, Flinders River, QLD^ Flinders 2 32 Aug, 1996

Norman Croydon, Norman River, QLD Norman 2 32 Sept, 2002 Gilbert Developmental Road Crossing,

Gilbert River, QLD^ Gilbert 2 34 Aug, 1996

Einsleigh Einsleigh, Einsleigh River, QLD Gilbert 2 - Sept, 2002 Elizabeth Mount Surprise, Elizabeth River,

QLD Gilbert 2 18 Sept, 2002

Mitchell ‘Lake Mitchell’, Mitchell River, QLD^ Mitchell 2 34 Aug, 1996 Chillagoe Chillagoe, Chillagoe River, QLD Mitchell 2 32 Sept, 2002 Weipa 50km east of Weipa, QLD^ Mission 2 30 Aug, 1996 Lockerbie Lockerbie River, QLD* Jardine 2 - Oct, 1990 Bensbach Bensbach River, PNG^ Bensbach 2 - Sept, 1999 Oriomo Oriomo River, PNG^ Oriomo 2 - Dec, 1999 MtBosavi MtBosavi, PNG* Kikori 2 - Oct, 1995

Three C. quadricarinatus culture stocks, Yandina, Parkridge and Hutchings, and the

DPI improved hybrid strain ‘Walkamin Strain’ were sampled as representatives of

southeast Queensland culture stocks. Table 2-2 describes farm location, population

size and collection date for farmed C. quadricarinatus stocks.

The Hutchings farm at Aratula in south-east Queensland was the first C.

quadricarinatus farm in Queensland and this farm has subsequently supplied stock

to many other farms. Robin Hutchings (pers comm) developed a farmed stock from

a mixture of wild stock collected from at least two Queensland rivers – Flinders and

Gilbert Rivers. C. quadricarinatus has become a popular culture species overseas

and is now farmed in the USA, South Africa, China, Israel, Mexico and Ecuador

(Karplus et al., 1995; Macaranas et al., 1995; Rouse, 1995). C. quadricarinatus

producers overseas were contacted and tail clip samples preserved in 70% ethanol

were obtained from them.


22

Table 2-2 Stock name, location, sample size and date collected of farmed C. quadricarinatus stock sampled in this study. Please see acknowledgements for collaborators.

Stock Name Location n Date Collected

Yandina 1996 South East Qld, Australia 30 1996 Yandina 2002 South East Qld, Australia 30 2002 Parkridge South East Qld, Australia 30 1996 Walkamin North East Qld, Australia 25 2002 Hutchings South East Qld, Australia 30 2002 Israel Israel 25 2002 Mexico Mexico 40 2002 Ecuador Ecuador 25 2002

Reference samples of closely related Cherax taxa to be used as outgroups for

phylogenetic analyses - C. destructor and C. tenuimanus were obtained from Dean

Jerry at CSIRO and C. rhynchotus was sourced from the Queensland Museum

courtesy of Peter Davies.

2.2 Genetic Markers Two classes of genetic marker (mitochondrial and microsatellite DNA markers) have

dominated the field of population genetics since the development of the polymerase

chain reaction (PCR). MtDNA has proven to be very powerful for genealogical and

evolutionary studies of animal populations (Avise et al., 1987; Bernatchez &

Guyomard, 1994; Crandall & Fitzpatrick, 1996) and microsatellites have become the

most widely used genetic marker in recent times used to infer population genetic

structure and for population dynamic studies (Bruford & Wayne, 1993; Paetkau et

al., 1995; King et al., 2001).

2.2.1 Mitochondrial DNA

Crustacean mtDNA was first isolated by Batuecas et al. (1988) in a study of the

genome organisation of the mitochondrial organelle in Artemia. Since this time, a

number of mtDNA genes have been targeted in crustaceans for phylogenetic

purposes. These include the ribosomal RNA genes 16S and 12S, cytochrome

oxidase I (COI) and Cytochrome b (Cyt-b). While COI and Cyt-b are mitochondrial

protein coding genes, the 12S and 16S genes are structural rRNA, non-protein

coding genes.

The combination of both variable and conserved regions within the same gene is

most likely the major reason why 16s rRNA has become one of the most popular

genes used for reconstructing phylogenies in many decapod crustaceans (Crandall


23

et al., 1999; Crandall et al., 2000). In parallel, COI has revealed high levels of

variation in many arthropods, and has also proven successful for delineating

divergent clades in many crustacean taxa (Cook, 2002). Estimates of mutation rates

and molecular clocks used to infer time since divergence of independent clades in

crustaceans can be calculated using both 16S and COI sequences (Schneider-

Broussard et al., 1998). Such time frames for cladogenesis can allow insights into

earth history events which may have influenced divergence among monophyletic

lineages identified in genetic studies.

PCR enables the amplification of specific DNA sequences for analysis. Specific

primers have been published for an array of taxa, targeting many different

mitochondrial genes, which makes the study of the mitochondrial genome attractive.

A number of universal primers allow the amplification of genes across divergent taxa

possible, enabling the design of species-specific primers if required. Universal

primers targeting 16s, 12s, Cyt-b, COI, COII/III, ATPase and control region were

trialled on C. quadricarinatus DNA for PCR repeatability. 16S and COI were

selected for further investigation in this study

2.2.2 Microsatellite DNA

Microsatellites are iterations of 1-6bp nucleotide motifs, also known as simple

sequence repeats (SSRs) or short tandem repeats. They have been detected in the

genomes of every organism examined so far and they are distributed randomly or

almost randomly over the euchromatic genome in both coding and non-coding

regions (Jarne & Lagoda, 1996; Estoup et al., 1998). They are inherited in a co-

dominant pattern and are usually characterised by a high degree of length

polymorphism (Li et al., 2002). The origin of polymorphism is still debated, though

most appear likely to be due to slippage events during DNA replication (Schlötterer

& Tautz, 1992). Despite the fact that the mechanism(s) of microsatellite evolution

are still unresolved, they are considered to be the most powerful genetic markers

currently available due to their high variability and amenability to population genetic

analysis (Ruzzante et al., 1998). Microsatellites are also among the fastest evolving

DNA sequences with mutational rates varying from 10-2 to 10-6 events per locus per

generation. The mutation rate of a particular microsatellite is usually unknown and

the mutation process can display distinct differences among species, repeat types,

loci and alleles (Ellegren, 2000; Schlötterer, 2000; Li et al., 2002). Microsatellite

variation is manifested predominantly as changes in the number of repeats and so

alleles can be screened by electrophoresis to separate different fragment sizes.


24

Microsatellites are mostly species specific, however, conservation of primer

sequences across closely related taxa has been observed (Moore et al., 1991;

FitzSimmons et al., 1995; Chapuisat, 1996; Coltman et al., 1996). However, cross

amplification in related taxa can often result in null alleles where mutations in primer

sites lead to a failure in amplification of some alleles in a closely related species

(Pienkowska & Schelling, 2001). To overcome this potential problem, most studies

develop species-specific primer sets. Microsatellite primers were not available for

any Cherax species at the time of commencement of this study so C.

quadricarinatus specific microsatellite primers were developed from first principles

(Baker et al., 2000).

2.3 Geographic distance among sampled wild populations Two distance measures were employed. Coastal distance, measuring the real

distance between river mouths; and overland distance, measuring the minimum

distance between tributaries of neighbouring rivers.

Chapter Three: Phylogenetics of wild C. quadricarinatus

23

3.0 Phylogenetic relationships among wild C. quadricarinatus populations 3.1 Introduction Organisms that inhabit riverine systems can show a variety of population structures

that are usually related to relative dispersal capability and/or past earth history events

(Heads, 1999; Nagel, 2000; Waters et al., 2001a; Glaubrecht & von Rintelen, 2003; de

Bruyn et al., 2004). Zink et al. (1996) studied the evolutionary genetics of Hawaiian

freshwater fish and reported a lack of phylogenetic structure, even though fish were

confined to islands surrounded by ocean. They suggested that the amphidromous

(marine) larval phase of these fish facilitated extensive gene flow among islands. In

contrast, Bernatchez and Wilson (1998) observed that populations in different

freshwater drainages are effectively ‘islands’, as unfavourable habitat conditions

(terrestrial or unsuitable aquatic) among separate drainages restrict obligate freshwater

species to single drainage systems. Geomorphological events, such as uplift that result

in waterfalls or changes in flow direction, can also play an important role in shaping

genetic relationships among populations of freshwater species (Hughes, 1996;

Hurwood & Hughes, 1998; Waters et al., 2001a; de Bruyn et al., 2004). Earth history

events can interrupt gene flow for long periods and play a role in the eventual formation

of new species, assuming allopatric models of speciation (Mayr, 1942; Otte & Endler,

1989; Avise & Wollenberg, 1997).

Evidence suggests that past fluctuations in sea level have influenced the genetic

structure of a number of terrestrial and aquatic species across northern Australia and

PNG (Chenoweth et al., 1998; Keogh, 1998; McGuigan et al., 2000; Unmack, 2001;

Ladiges et al., 2003; de Bruyn et al., 2004). In contrast to present day sea levels that

have broken freshwater connections between Australia and New Guinea, sea levels

have been lower in the past and would have facilitated connectivity for terrestrial and

freshwater taxa in Australia. For example, rainbow fish (McGuigan et al., 2000) and the

green python, Morelia viridis (Rawlings & Donnellan, 2003) are believed to have

dispersed between northern Queensland and PNG when sea levels were lower.

The southern half of New Guinea forms part of the Australian tectonic plate and has

been an integral part of continental Australia since the Australian plate split from the

Antarctic core of Gondwana about 95 MYA (Veevers, 1984). As sea levels fluctuated

periodically, Australia and New Guinea have been alternately linked by terrestrial

corridors or separated by marine incursions on a number of occasions over millions of

years (Chappell, 1983). Voris (2000) hypothesized that a large ancient river system


24

existed at times of lower sea levels that linked major rivers in southern New Guinea to

northern Australia (Figure 3.1a). There is also evidence to suggest that throughout

much of the Pleistocene, a large freshwater to brackish water lake, Lake Carpentaria,

formed in what is today the Gulf of Carpentaria (Torgersen et al., 1985; Jones &

Torgersen, 1988) (Figure 3.1b). This lake existed periodically at times of low sea level

until about 8500 years ago (Chappell, 1983).

Figure 3-1: 1) Ancient river system at -120m sea level contour, 2) Lake Carpentaria shown at the-75m sea level contour. Present day sea level also indicated in dark grey. The ancient shorelines are based on present day depth contours; the major Pleistocene river systems are depicted (Voris, 2000).

Interestingly, across the same distribution of C. quadricarinatus in northern

Australia/PNG, four discrete genealogical lineages of the giant freshwater prawn

(Macrobrachium rosenbergii) have been identified recently: (i) a Western Australian

lineage; (ii) a Gulf of Carpentaria/Northern Territory lineage; (iii) an Irian Jayan lineage;

and (iv) a Papua New Guinean/NE Australian (Cape York) lineage (de Bruyn et al.,

2004). de Bruyn et al(2004) also hypothesised that the intermittent existence of Lake

Carpentaria facilitated dispersal of M. rosenbergii among Gulf of Carpentaria rivers. M.

rosenbergii can survive approximately 3 weeks as post larvae in sea water. Adults can

survive in brackish water for extended periods of time, but individuals will not tolerate

full marine conditions for more than a week (de Bruyn et al. 2004). C. quadricarinatus

spends its whole life in freshwater, unlike M. rosenbergii that has a short brackish

water larval phase, therefore more genetic divergence among populations isolated in

the same drainage system could be expected in C. quadricarinatus.

halla

This figure is not available online. Please consult the hardcopy thesis available from the QUT Library


25

Mitochondrial DNA (mtDNA), by virtue of maternal inheritance and a non-recombining

haploid nature, has a four-fold smaller effective population size than equivalent nuclear

genes which make it a powerful tool for detecting population structure in natural

systems (Wollenburg & Avise, 1998). The control region has the highest mutation rate

of any mitochondrial gene, whereas the ribosomal genes (12s and 16s) are generally

considered to be the most highly conserved regions (Parker et al., 1998).

Monophyletic lineages in intraspecific gene trees can be detected using mtDNA, and

the degree of molecular divergence among lineages estimated from mtDNA haplotypes

can be dated using a molecular clock approach (Brown et al., 1979). Estimates of time

frames for cladogenesis will allow insight into potential earth history events that may

have influenced any divergence observed among C. quadricarinatus populations.

Combining the results of two mtDNA loci that evolve at different evolutionary rates, will

allow for a comprehensive interpretation of the levels and patterns of genetic

divergence that may exist among wild C. quadricarinatus populations. The aim of this

study was, therefore, to determine phylogenetic relationships among wild stocks of the

putative single species of C. quadricarinatus in northern Australia and southern PNG.

Sequences of two mtDNA genes (16s and COI) from crayfish sampled from river

systems collected across the natural distribution of C. quadricarinatus in Australia and

PNG were examined to determine genetic differentiation and phylogenetic relationships

among wild stocks.


26

3.2 Mitochondrial DNA Methodology

3.2.1 Samples

Wild C. quadricarinatus were sampled from 17 drainages across northern Australia and

southern PNG. Two individuals from each location were sampled for use in 16s and

COI analyses.

Table 3-1: Site Location, river drainage, abbreviation used in following tables and sample size for 16s and COI mtDNA gene analysis of C. quadricarinatus used in this phylogenetic study.

Site Location Drainage Abbrev. n (16s) n (COI) Kununurra Dam, WA Ord Ord 2 2 Howard River, NT Howard How 2 2 Adelaide River, NT Adelaide Ade 2 2 Roper River, NT Roper Rop 2 2 McArthur River, NT McArthur McA 2 2 Calvert River, NT Calvert Cal 2 2 Nicholson River, NT&QLD Gregory Nic 2 - Gregory River, QLD Gregory Gre 2 2 Louie Creek, QLD Gregory Lou - 2 Leichhardt River, QLD Leichhardt Lei 2 - Flinders River, QLD Flinders Fli 2 2 Norman River, QLD Norman Nor 2 2 Gilbert River, QLD Gilbert Gil 2 2 Little River, QLD Gilbert LR - 2 Einsleigh River, QLD Gilbert Ein - 2 Elizabeth River, QLD Gilbert Eli - 2 Mitchell River, QLD Mitchell Mit 2 2 Lower Mitchell, QLD Mitchell LMit - 2 Rosser Creek Mitchell RC - 2 Chillagoe River, QLD Mitchell Chi - 2 Weipa, QLD Mission Wei 2 2 Lockerbie, QLD Jardine Loc 2 2 Bensbach River, PNG Bensbach Ben 2 2 Oriomo River, PNG Oriomo Ori 2 2 MtBosavi, PNG Kikori MtB 2 2

3.2.2 DNA Extraction

Initial sequence data from Cytochrome Oxidase I (COI) obtained using whole genomic

C. quadricarinatus DNA, suggested that variation may result from a pseudogene. This

phenomenon has been reported in a wide range of organisms, including a closely

related species, C. destructor (duplication of 16s gene region) (Nguyen et al., 2002).

To overcome the potential for amplifying translocated genes a specific mtDNA

extraction protocol was employed to isolate mtDNA and remove nDNA before

amplification.


27

3.2.3 Mitochondrial DNA Extraction

Mitochondrial DNA (mtDNA) was extracted using a modified procedure developed by

Tamura and Aotsuka (1988). This extraction method was carried out as follows:

approximately 100mg of C. quadricarinatus muscle tissue or tail clip was digested in

1mL homogenising buffer (0.25M sucrose, 10mM EDTA, and 30mM Tris-HCl, pH 7.5)

and 10μl of 20mg/mL Proteinase K for 1–2 hours. This solution was centrifuged at

1000g for 1 min to pellet nuclei and cellular debris. The supernatant was recovered and

centrifuged at 12 000g for 10mins to pellet the mitochondria. The pellet was

resuspended in 100μl 10mM tris- EDTA pH 8.0, and 10mM EDTA. To this, 200μl of

freshly prepared 0.18M NaOH containing 1% sodium dodecyl acetate (SDS) was

added and incubated on ice for 5min. 150μl of ice-cold solution of 3M potassium and

5M acetate was added and the sample incubated on ice for a further 5 min. This

mixture was centrifuged at 12 000g for 5 min and the supernatant recovered. Equal

volumes of phenol:chloroform/isoamyl was added, the sample mixed thoroughly and

centrifuged for 2 min at 12 000g. The aqueous layer was transferred to a fresh tube

and twice the volume of ethanol added and the sample then stored at –20oC for 15min

to precipitate the mtDNA. After centrifugation at 12 000g for 15 – 20 minutes the

resulting mtDNA pellet was washed with 1ml 70% ethanol and then dried at room

temperature. The pellet was suspended in 50μl of water and stored at -20oC until

required for genetic analysis.

3.2.4 PCR Analysis

Universal crustacean ribosomal 16s (Crandall & Fitzpatrick, 1996) primers were

utilised, in combination with published cytochrome oxidase I primers (Palumbi et al.,

1991) to successfully amplify C. quadricarinatus mtDNA. The degenerate primer (COf-

L) was replaced with a specific primer designed here for C. quadricarinatus to ensure

specificity during PCR and unambiguous sequence results.

16s ribosomal DNA Primers (Crandall and Fitzpatrick, 1996)

16S71 (forward): ATA ARG TCT RAC CTG CCC 1472 (reverse): AGA TAG AAA CCA ACC TGG

Cytochrome Oxidase I Primers (Palumbi et al, 1991)

COa-H: AGT ATA AGC GTC TGG GTA GTC COf-L (replaced): CCT GCA GGA GGA GGA GAY2 COcq-L (this study): CGG CAT AGT CTC ACA CAT CG

2 Y=C/T


28

3.2.5 Sequencing of mtDNA Haplotypes

PCR products for sequencing were purified according to the protocols of QIAquick

PCR Purification Preps (QIAGEN Inc.). Approximately 50ng of purified DNA template

was combined with 3.2 pmoles of each forward or reverse primer, 1μl of ABI (Applied

Biosystems Incorporated) Big Dye version 3.1, 3μl dilution buffer (400mM Tris, pH 9.0,

10mM MgCl2) and made up to 12μl volume with ddH20. Sequencing reactions were

then amplified under the following conditions: initial denaturation at 94oC for 5 mins

followed by 30 cycles of 96oC for 10 secs, 50oC for 5 secs, 60oC for 4 mins and 10mins

at 4oC. Each sequencing reaction was mixed with 2μl 3M sodium acetate (pH4.6) and

50μl of 95% ethanol. Tubes were vortexed briefly and left at room temperature for

15mins. Tubes were then centrifuged for 20mins at 13000rpm. The supernatant was

removed and the pellet washed with 250μl of 70% ethanol and centrifuged for a further

5 mins at 13,000rpm. The supernatant was then removed and the pellet air dried.

Sequencing was conducted at AGRF (Australian Genetic Research Facility, Brisbane).

C. quadricarinatus sequences were edited in Chromas 2.13 (Technelysium Pty Ltd)

and aligned with the ClustalW analysis (Thompson et al. 1994) using the Australian

National Genomic Information Service (ANGIS) online computer package.

3.3 Statistical Analysis

3.3.1 Neutrality Tests

Fu and Li’s (1993) D and F tests were performed on the C. quadricarinatus sequences

using DNASP version 3.99 (Rozas & Rozas, 2003).

3.3.2 Testing for saturation

The probability that nucleotides are the same due to chance convergence increases

with time since divergence. Testing for saturation involves plotting uncorrected against

corrected genetic distance. When a scatter plot of uncorrected versus corrected

distances is made, the degree to which points deviate from the line of best fit indicates

saturation and the degree of homoplasy (Reed & Sperling, 1999). In faster evolving

DNA regions (eg. COI), the level of saturation is usually greater than that evident in

slower evolving (eg. 16s) regions.

3.3.3 Phylogenetic reconstruction of wild C. quadricarinatus populations

Pairwise nucleotide differences among mtDNA haplotypes were calculated in MEGA

version 2.1 (Kumar et al., 2001) using an appropriate substitution model as determined


29

in Modeltest (Posada & Crandall, 1998). A gamma value (for each gene sequence

determined using PAUP* version 4 (Swofford, 2003)) was used to account for variable

rates of substitutions at different nucleotide sites. The resulting distance matrix was

used to construct trees with Neighbour Joining and Maximum Likelihood algorithms.

Statistical support for trees were tested using 1000 bootstrap replicates (Felsenstein,

1985). A closely related Cherax species, C. destructor, was used as an outgroup for

resolving C. quadricarinatus relationships.

Minimum spanning networks were constructed using TCS 1.11 (Clement et al., 2000).

TCS implements the estimation of gene genealogies from DNA sequence data

described by Templeton et al. (1992). The advantage of this approach is that it allows

haplotypes to form nodes in the network, which is important for intraspecific data

because ancestral haplotypes can be identified in samples, which may themselves

have given rise to more derived (recent) haplotypes.

3.3.4 Isolation by distance

To determine whether population structure was influenced by geographic distance,

isolation by distance analysis was carried out using IBD ver 1.5 (Bohonak, 2002).

Pairwise distance estimates were calculated in MEGA and correlated with geographic

distance using the matrix correlation methods of the Mantel test. The genetic and

geographic distance estimates were both log transformed.

3.3.5 Molecular clock estimates

A molecular clock approach proposes that genes evolve at rates that are roughly

constant over time and across evolutionary lineages (Brown et al., 1979). If divergence

accumulates in a relatively clockwise fashion, then time scales can be estimated for

important evolutionary events in the absence of fossil evidence. Based on molecular

clock theory, each specific gene or protein of an organism can serve as an

independent molecular clock. This is based on the fact that each protein has a distinct

rate of evolution depending on individual level of functional constraint. The less

functional constraint on a molecule, the faster it will evolve in terms of substitution rate

compared with molecules subject to stronger constraints (Nei & Koehn, 1983).

A chi-square test for homogeneity of base composition was implemented in TREE-

PUZZLE 5.2 (Schmidt et al., 2002) to test the clock like evolution of C. quadricarinatus

mtDNA sequences. TREE-PUZZLE compared trees generated under the assumption

of a molecular clock with trees unconstrained by a molecular clock (Felsenstein, 1988).


30

Molecular clocks have been calibrated for many taxa, primarily within the bounds of

particular genes (Swofford et al., 1996). 16s mtDNA in crustacean has been estimated

to accumulate mutations a 0.53 – 0.96% per million years (Myr) (Sturmbauer et al.,

1996; Stillman & Reeb, 2001)) and COI at 1.4 – 2.6% MYR (Knowlton & Weigt, 1998;

Schneider-Broussard et al., 1998).

3.4 Mitochondrial Results

3.4.1 Analysis of 16s Sequence diversity

Sequence data for 36 C. quadricarinatus individuals from 482bp of 16s rRNA sequence

revealed 38 variable nucleotide positions resulting in 11 unique haplotypes. Haplotypes

were distributed among 18 populations from discrete drainages across northern

Australia and PNG. Table 3-2 details the informative nucleotide sites among the 16s C.

quadricarinatus sequences; populations are listed in a geographical, sequential fashion

with Australian rivers from west to east, followed by PNG rivers from west to east. No

variation was detected between any two individuals sequenced from the same site and

some haplotypes were shared among neighbouring rivers. For example Adelaide and

Howard exhibited the same 16s haplotype; the five ‘western gulf’ rivers, McArthur,

Calvert, Gregory, Nicholson and Leichhardt also shared a single common haplotype.


31

Table 3-2: Informative sites among sampled C. quadricarinatus river populations from 482bp of 16s mtDNA identified by sequencing. Dots indicate homology to the Ord River haplotype. (WGC – western Gulf of Carpentaria; SGC – southern Gulf of Carpentaria)

Position of variable site (482bp) Haplotype River population 50 91 93 95 96 97 98 134 145 158 167 174 177 180 189 213 265 279 283 284 288 290 293 295 299 316 323 325 342 370 410 418 419 427 477 478 478 482

West 1 Ord A A C C G A A G A A A T T G G C C G T T T G T A T G A T A A T T A A G C G A West 2 Howard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . C G A G West 2 Adelaide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . C G A G West 3 Roper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . East 1 McArthur G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Calvert G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Gregory G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Nicholson G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 1 Leichhardt G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G . . . . East 2 Flinders G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 2 Norman G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 2 Gilbert G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G . . . . East 3 Mitchell G . . . . G G A . . . A . . . T T . . . . A . G C A . . . G . C G G C G A G

East 4 Weipa G . . . . G . A . . . A . . . T T . . . . A . . C A . . . G . C G G C G A G East 5 Jardine G . . . . G . A . . . A . . . T T . . . . A . G C A . . . G . C G G C G A G PNG 1 Bensbach G . . . . G . A . . T A . . . T T . . . . A . G C A . . . G . C G G C G A G PNG 2 Oriomo G G . . . G . . . . G A . A . T T . . . . A . . C A . . . . . C . . . . T . PNG 3 MtBosavi G . T T C G . . G T . A C . A T T A C C C A G . C A T C G . . C . . . . . .


32

Pairwise haplotype distances are presented in Table 3-3. Modeltest results suggest

that the Tamura and Nei (1993) model of nucleotide substitution was appropriate for

the C. quadricarinatus 16s data. This model accounts for variable substitution rates

between purines and pyrimidines and GC content. The greatest pairwise haplotype

divergence found among Australian C. quadricarinatus populations was evident

between the southern gulf haplotype, shared by Flinders, Norman, Gilbert rivers and

the western haplotype of the Adelaide and Howard rivers (3.9% difference). A large

divergence of 3.5% was also evident between populations from Weipa and the

Roper River located on opposite sides of the Gulf. Mt Bosavi in PNG showed a large

divergence (ranging from 3.9 – 6%) from all Australian and other PNG C.

quadricarinatus populations. Oriomo also showed a relatively large divergence from

other C. quadricarinatus populations (ranging from 1.7 – 3.5%); whereas, Bensbach

(PNG) samples shared a very close relationship with northern Queensland, being

only 0.2% and 0.4% different from Jardine and Weipa haplotypes, respectively. Like

northern Queensland populations, Bensbach samples were also divergent from

western Australian haplotypes, up to 3.9% (Ord).

3.4.1.1 Neutrality tests

Both Fu and Li tests were non-significant, therefore, C. quadricarinatus 16s

sequences were assumed to be evolving according to a neutral model (Fu and Li's

D: -1.18030: (P > 0.10); Fu and Li's F: -1.15721: (P > 0.10)).

3.4.1.2 16s saturation plots

After plotting uncorrected (p distance) versus corrected (Tamura Nei (1993) gamma

= 0.11) distance measures for C. quadricarinatus 16s haplotypes revealed no

evidence of saturation (R2 = 0.9839: data not shown).


33

Table 3-3: Relationship among sampled populations based on 16sRNA sequences. Number of base pair differences between C. quadricarinatus river 16s haplotypes in the upper matrix; p distance of C. quadricarinatus 16s haplotypes in the lower matrix. Rivers are listed west to east. Highest and lowest values are in the bold.

Ord Howard Adelaide Roper McArthur Calvert Gregory Nicholson Leichhardt Flinders Norman Gilbert Mitchell Weipa Jardine Bensbach Oriomo MtBosavi Ord 5 5 1 13 13 13 13 13 14 14 14 19 17 18 19 13 24 Howard 0.010 0 5 18 18 18 18 18 19 19 19 16 14 15 16 17 29 Adelaide 0.010 0.000 5 18 18 18 18 18 19 19 19 16 14 15 16 17 29 Roper 0.002 0.010 0.010 14 14 14 14 14 15 15 15 19 17 18 19 13 25 McArthur 0.027 0.037 0.037 0.029 0 0 0 0 1 1 1 6 4 5 6 8 19 Calvert 0.027 0.037 0.037 0.029 0.000 0 0 0 1 1 1 6 4 5 6 8 19 Gregory 0.027 0.037 0.037 0.029 0.000 0.000 0 0 1 1 1 6 4 5 6 8 19 Nicholson 0.027 0.037 0.037 0.029 0.000 0.000 0.000 0 1 1 1 6 4 5 6 8 19 Leichhardt 0.027 0.037 0.037 0.029 0.000 0.000 0.000 0.000 1 1 1 6 4 5 6 8 19 Flinders 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0 0 5 5 4 5 9 20 Norman 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0.000 0 5 5 4 5 9 20 Gilbert 0.029 0.039 0.039 0.031 0.002 0.002 0.002 0.002 0.002 0.000 0.000 5 5 4 5 9 20 Mitchell 0.039 0.033 0.033 0.039 0.012 0.012 0.012 0.012 0.012 0.010 0.010 0.010 2 1 2 13 25 Weipa 0.035 0.029 0.029 0.035 0.008 0.008 0.008 0.008 0.008 0.010 0.010 0.010 0.004 1 2 11 23 Jardine 0.037 0.031 0.031 0.037 0.010 0.010 0.010 0.010 0.010 0.008 0.008 0.008 0.002 0.002 1 12 24 Bensbach 0.039 0.033 0.033 0.039 0.012 0.012 0.012 0.012 0.012 0.010 0.01 0.010 0.004 0.004 0.002 12 25 Oriomo 0.027 0.035 0.035 0.027 0.017 0.017 0.017 0.017 0.017 0.019 0.019 0.019 0.027 0.023 0.025 0.025 19 MtBosavi 0.050 0.060 0.060 0.052 0.039 0.039 0.039 0.039 0.039 0.041 0.041 0.041 0.052 0.048 0.050 0.052 0.039


34

3.4.1.3 Phylogenetic analysis of 16s sequences

All methods of phylogenetic reconstruction (NJ and ML) used here consistently

resolved four discrete C. quadricarinatus lineages. Figure 3-2 presents a

Neighbour-Joining tree of unique 16s haplotypes from Australia and PNG with

C. destructor as an outgroup. Mt Bosavi (PNG) and Oriomo (PNG) haplotypes

formed separate independent lineages and fell outside all other C.

quadricarinatus haplotypes. There was a strong relationship between

phylogenetic structuring of Australian haplotypes and their relative geographic

position. Haplotypes from rivers found in the west of northern Australia formed a

third lineage, and haplotypes from the eastern river systems in Australia formed

a fourth lineage. A striking genetic transition (over ~200km) was evident in

northern Australia between the Roper and McArthur Rivers (in the south west

Gulf of Carpentaria). Interestingly Bensbach (PNG) clustered within the eastern

Australia river lineage and most closely with haplotypes found in northern

Queensland (Weipa, Jardine and Mitchell). The tree clearly supports two

monophyletic C. quadricarinatus lineages in Australia with unique lineages

corresponding geographically to all western rivers (Ord, Roper, Howard,

Adelaide) versus all eastern rivers (McArthur, Leichhardt, Calvert, Gregory,

Nicholson, Flinders, Gilbert, Norman, Mitchell, Weipa, Jardine). The boundary

between the two clades occurs between the McArthur and Roper Rivers in south

east Northern Territory.

Four discrete haplotype networks were generated in TCS, Mt Bosavi (PNG),

Oriomo (PNG), western Australia and eastern Australia/ Bensbach (PNG).

Networks are presented in Table 3-3. Individual networks could not be joined

because divergence among haplotype networks exceeded the 95% confidence

limits derived from the parsimony estimation procedure in TCS (Templeton et

al., 1992). This relationship accords well with the topology of the phylogenetic

trees.

3.4.1.4 Isolation by distance

A significant isolation by distance relationship among 16s C. quadricarinatus

haplotypes was observed (Z = -872.8494, r = 0.6602, one-sided p <= 0.0010

from 1000 randomizations).


35

3.4.1.5 16s molecular clock estimates

For the total dataset, the log likelihood ratio test rejected the hypothesis that 16s

haplotypes were evolving according to a clock like model of evolution. However,

clock like evolution could not be rejected for the eastern Australian lineage (-ln

L= -703.52 with molecular clock enforced vs. –ln L = -701.45 without the

molecular clock enforced, χ2= 4.13, d.f= 4, P> 0.10). Clock like evolution within

the western clade could not be tested, as insufficient haplotypes were available.

Using molecular clock estimates of 16s evolution for crustaceans from the

literature (0.53 – 0.96% Stillman and Reeb, 2001, Sturmbauer et al, 1996), a

2.7–3.9% sequence divergence between eastern and western Australian C.

quadricarinatus clades translates into an estimated time of divergence of 7.3

(Pliocene) - 2.8 (Pleistocene) million years before present. Divergence time

among individual populations within clades extends back to 1.88 MYA.

East 3

PNG 1

East 5

East 4

East 2

East 1

West 1

West 2

West 3

PNG 2

PNG 3

C. destructor

2286

54

44

41

30

85

5971

0.05

Figure 3-2: Neighbour joining tree for 16s sequences of C. quadricarinatus, with C. destructor as an outgroup. Tree constructed in MEGA version 2.1 employing the Tamura-Nei (1993) (0.11 gamma) model of evolution. Values at nodes represent bootstrap confidence levels (1000 replicates) if greater than 50.


36

Figure 3-3: Parsimony network for C. quadricarinatus 16s haplotypes constructed in TCS. Individual networks are not joined because divergence between haplotypes exceeds the 95% confidence limits derived from the parsimony estimation procedure (Templeton et al1992). (WGC – western Gulf of Carpentaria; SGC – southern Gulf of Carpentaria; Mt B – Mt Bosavi)

3.4.2 Analysis of COI haplotype diversity

Sequence analysis of 48 C. quadricarinatus individuals for a 524bp region of the

COI gene revealed 46 variable nucleotide positions resulting in 17 unique

haplotypes from C. quadricarinatus populations sampled from 23 major

freshwater drainages across northern Australia and PNG. Several observations

confirm that the DNA sequences generated were unlikely to be nuclear

psuedogenes of the mitochondrial 16s gene. COI sequences showed a strand

bias against guanine on the light strand (T= 33.2% C= 23.4% A= 28.0% G=

15.4%), which is characteristic of the mitochondrial genome but not the nuclear

genome (Macey et al., 1999). Furthermore, no insertions or deletions were

present, most mutations were silent and no stop codons were evident in the

amino acid sequence alignment.

East 5 East 4

East 2

East 3

PNG 1

East 1

PNG 2 PNG 3

West 2

West 1 West 3


37

Table 3-4: Informative sites among C. quadricarinatus COI haplotypes. 49 variable nucleotide positions among river haplotypes of a 524bp of C. quadricarinatus COI mtDNA as determined by sequencing. Dots indicate homology to the Ord River haplotype. River haplotypes have been segregated and named according to geographic origin - West, East and PNG.

Base pair position of variable site (total 524bp) Haplotype Drainage

13 3 2

3 3

4 3

4 9

58

64

94

124

148

181

190

205

206

214

217

229

239

243

244

274

289

292

293

2 9 8

3 0 2

3 1 2

319

337

361

385

409

412

415

427

430

431

449

460

471

491

496

499

501

502

504

506

517

520

West1 Ord G G A T G C C C C C C C A T C T G A C T C T T C A G C C C T A G G T C C C C A C C G A C T A C T A

West2 Howard . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G

West3 Adelaide . . . . . . . T . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G

West4 Roper . A G . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . T . . . . . . . G A C T A . G

East1 McArthur Weipa Gregory

A . . C A . . . T . . T . C T C A T . . . . C T . . . T T C G A T . . T T . . . T . G A C T A . .

East2 Calvert A . . C A . . . T . . T G C T C A T . . . . C T . . . T T C G A T . . T T . G . T . G A C T A . .

East3 Gregory A . . C A T . . T . . T . C T C A T . . T . C T . . . T T C G A T . . T . T . . T . G A C T A . .

East4 Flinders A . . C A . . . T . . T . C T C A T . C . . C T . . . T T . G A T . . . T . . . T . . A C T A . .

East5 Norman A . . C A . . . T . . T . C T C A T . . . . C T . . . T T . G A T C . . T . . . T . . A C T A . .

East6 Norman A . . C A . . . T . . T . C T C A T . . . . C T G . . T T . G A T . . . T . . . T . . A C T A . .

East7 Gilbert Norman Mitchell

A . . C A . . . T . . T . C T C A T . . . . C T . . . T T C G A T . . . T . . . T . . A C T A . .

East8 Gilbert A . . C A . . . T . . T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . G A C T A . .

East9 Mitchell A . . C A . T . T . . T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . . A C T A . .

East10 Jardine A . . C A . . . T . . T . C T . A T . . . . C T . A . T T . G A T . T . T . . . T . . A C T A . .

PNG1 Bensbach A . . C A . . . T . T T . C T C A T . . . . C T . . . T T . G A T . . . T . . . T . . A C T A . .

PNG2 Oriomo A . . C A . . . T . . T . . T C A T . . . . C T . . . T T . G A T . . . . . . . T . . A C T A . .

PNG3 MtBosavi A . . C A T . T . T . T . . T . A T . . . . C T . . . . T . . A T . . . . . . . T A . A C T A C .


38

Table 3-5 details divergence estimates using the Tamura-Nei (1993) substitution

rate and a gamma value of 0.22. The greatest pairwise haplotype difference was

evident between East 2/East 3 and West1/West4 haplotypes - a net divergence

of 5.2%.

Translation of the nucleotide sequence into amino acid sequence for this coding

gene indicated that most polymorphisms were silent with a single fixed amino

acid difference observed between western and eastern Australian lineages and

two single amino acid changes in West 4 and East 10. C. quadricarinatus and C.

destructor amino acid sequences were aligned to determine a comparative level

of variability of amino acid sequences between two Cherax species. The

alignment produced 5 and 4 amino acid changes (across a total of 174 amino

acids) in eastern and western lineage sequences, respectively.

3.4.2.1 COI Neutrality Test

Both Fu and Li tests proved non-significant and therefore C. quadricarinatus COI

appears to be evolving according to a neutral model (Fu and Li's D: -0.66579: (P

> 0.10); Fu and Li's F: -0.71281: (P > 0.10)).

3.4.2.2 COI Saturation Plot

Plotting uncorrected versus corrected (Tamura Nei (1993); gamma = 0.22)

distance measures for C. quadricarinatus COI haplotypes revealed no evidence

for saturation (R2 = 0.9937; data not shown).


39

Table 3-5: Relationship among sampled populations based on COI sequences; the upper matrix shows the number of base pairs different between COI haplotypes from the river indicated; the lower matrix shows the p distance between COI haplotypes from the river indicated.

West1 West2 West3 West4 East1 East2 East3 East4 East5 East6 East7 East8 East9 East10 PNG1 PNG2 PNG3 West1 8 9 10 25 27 27 23 23 23 23 23 23 23 23 20 21 West2 0.015 1 2 23 25 25 23 23 23 23 21 23 21 23 20 21 West3 0.017 0.002 3 24 26 26 24 24 24 24 22 24 22 24 21 20 West4 0.019 0.004 0.006 25 27 27 25 25 25 25 23 25 23 25 22 23 East1 0.048 0.044 0.046 0.048 2 4 4 4 4 2 2 4 6 4 5 14 East2 0.052 0.048 0.050 0.052 0.004 6 6 6 6 4 4 6 8 6 7 16 East3 0.052 0.048 0.050 0.052 0.008 0.012 8 8 8 6 6 8 10 8 7 14 East4 0.044 0.044 0.046 0.048 0.008 0.012 0.015 2 2 2 2 2 4 2 3 12 East5 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 2 2 2 2 4 2 3 12 East6 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 2 2 2 4 2 3 12 East7 0.044 0.044 0.046 0.048 0.004 0.008 0.012 0.004 0.004 0.004 2 2 4 2 3 12 East8 0.044 0.040 0.042 0.044 0.004 0.008 0.012 0.004 0.004 0.004 0.004 2 4 2 3 12 East9 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 0.004 0.004 0.004 4 2 3 12 East10 0.044 0.040 0.042 0.044 0.012 0.015 0.019 0.008 0.008 0.008 0.008 0.008 0.008 4 5 12 PNG1 0.044 0.044 0.046 0.048 0.008 0.012 0.015 0.004 0.004 0.004 0.004 0.004 0.004 0.008 3 12 PNG2 0.038 0.038 0.040 0.042 0.010 0.013 0.013 0.006 0.006 0.006 0.006 0.006 0.006 0.010 0.006 9 PNG3 0.040 0.040 0.038 0.044 0.027 0.031 0.027 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.017


40

3.4.2.3 Phylogenetic analysis of COI

A neighbour-joining tree of all COI river haplotypes revealed four distinct lineages

(Figure 3-4) and is similar to the topology of 16s haplotypes. Populations from

western Australian rivers formed a well supported lineage, populations from eastern

Australian, Bensbach (PNG) and Oriomo (PNG) rivers formed a second lineage and

MtBosavi (PNG) formed a third lineage. Within the eastern lineage haplotypes East

1, East 2 and East 3 formed a clade encompassing the western Gulf rivers of

McArthur, Gregory, Calvert, Louie Creek, and Weipa in the north east.

East1

East2 East3

East7

East8

East4

East5

East6

East9

PNG1

East10

PNG2

PNG3

West1

West2 West3

West4 75

97

100

61

74

93

47

54

28

58

44

0.005

Figure 3-4: Neighbour joining tree of Australian COI C. quadricarinatus haplotypes. Tree constructed in MEGA using Tamura-Nei (1993) (0.22 gamma) model of evolution. Values at nodes represent bootstrap confidence levels (1000 replicates).


41

Haplotype networks constructed in TCS, allow evolutionary relationships among

haplotypes to be visualised (Figure 3-5). Four networks were generated. Individual

networks could not be joined because divergence among haplotypes exceeded the

95% confidence limits derived from the parsimonious estimation procedure

(Templeton et al1992). The first network includes haplotypes from western Australia

(rivers); the second network is made up of eastern Australian rivers and includes the

Bensbach population from PNG. The third and fourth networks consist of single

haplotypes PNG 2 (Oriomo) and PNG 3 (Mt Bosavi) respectively.

Figure 3-5: Parsimony network for C. quadricarinatus COI haplotypes constructed in TCS reveals evolutionary relationships among haplotypes. Individual networks are not joined because divergence between haplotypes exceeds the 95% confidence limits derived from the parsimonious estimation procedure (Templeton et al. 1992).

East 9

East 3

East 2

East 1

East 4

East 5

East 6

East 7 East 8

PNG 1

East 10

West 1 West 2

West 3

West 4

PNG 2

PNG 3


42

3.4.2.4 Isolation by distance

A significant isolation by distance relationship among COI C. quadricarinatus

haplotypes was observed (Z = -706.3913, r = 0.6300, one-sided p <= 0.0010 from

1000 randomizations).

3.4.2.5 COI molecular clock estimates

A log likelihood ratio test rejected the hypothesis that lineages were evolving

according to a clock like model of evolution. However, clock like evolution was not

rejected within each lineage (eastern: -ln L= -920.43 with molecular clock enforced

vs. –ln L –911.11 without the molecular clock enforced, χ2=18.65, d.f=11, P> 0.10;

western: -ln L= -920.41 with molecular clock enforced vs. –ln L –919.58 without the

molecular clock enforced, χ2=1.67, d.f=2, P> 0.10)

Using the molecular clock estimates for crustacean COI (1.4% per million years;

Knowlton and Weight 1998), 3.8 - 5.4% divergence between eastern and western C.

quadricarinatus lineages translates into an estimated time of divergence of 7.56-

5.32 million years before present.


43

3.5 Discussion Phylogenetic analysis of 16s and COI mtDNA gene sequences from C.

quadricarinatus populations in northern Australia and southern PNG resolved two

distinct genealogical lineages in Australia and three in PNG. Both mitochondrial

genes were evolving according to neutral expectations and did not show evidence of

saturation, making them suitable for investigating evolutionary relationships among

wild C. quadricarinatus populations.

The two discrete Australian lineages accord with Reik’s (1969) description of two

morphologically distinct species that he designated C. quadricarinatus and C.

bicarinatus, described geographically from eastern and western populations,

respectively. The divergence at a single allozyme locus (Carbonic anhydrase)

detected among Australian C. quadricarinatus populations by Macaranas et al.

(1995) adds further support to their recognition as monophyletic clades. Further, an

unpublished QUT honours study reported that no successful matings were achieved

between Weipa (eastern) and Howard (western) C. quadricarinatus individuals in a

laboratory breeding trial (Ogden, 2000), suggesting that C. quadricarinatus from the

geographic extremes of the species natural distribution may not recognise each

other as potential mates. While this experiment was undertaken under artificial

conditions, it provides additional support that eastern and western C.

quadricarinatus lineages are highly divergent. These data do, however contradict

Austin’s (1996) allozyme study that found no significant difference among Australian

and PNG C. quadricarinatus populations. Austin used allozyme data to reject Reik’s

(1969) conclusions, and consequently, C. quadricarinatus, C. bicarinatus and C.

albertsii are treated as a single taxon.

The existence of two distinct lineages of C. quadricarinatus in Australia raises the

question as to whether the lineages represent two distinct biological species.

Specific status of allopatric lineages can be difficult to assess, so the evolutionary

species concept (Simpson, 1951; Wiley, 1978) has become a popular choice for

assessing whether a group of organisms is a phyletic lineage (an ancestral-

descendent sequence of interbreeding populations, evolving independently of

others, with its own separate and unitary evolutionary role and tendencies (Simpson,

1951)).

Unless the two C. quadricarinatus lineages can be found in sympatry it is difficult to

assess whether the two lineages are reproductively isolated and do not recognise

each other as potential mates under natural conditions. The amount of genetic


44

divergence detected among C. quadricarinatus lineages is large and similar levels of

divergence have been documented between other Cherax populations that are

recognised as subspecies. C. destructor destructor and C. destructor albidus exhibit

4.7% sequence divergence at 16s RNA (Campbell et al., 1994), therefore a 3.9%

16s sequence difference between the Australian eastern and western lineages

suggests the current taxonomic designation should be revised. Possibly the eastern

and western lineages of C. quadricarinatus may require re-classification into

subspecies. If sequence data were the only criterion for species/subspecies

boundaries, the Mt Bosavi population should also be designated as a subspecies,

as it is up to 6% divergent from all Australian C. quadricarinatus sequences.

The three C. quadricarinatus populations sampled in PNG were all genetically

distinct lineages. PNG unlike northern Australia is very mountainous. Such immense

physical barriers (rugged mountain ranges) will almost certainly reduce dispersal

capabilities for any freshwater species. Interestingly, a close genetic relationship

was evident between one PNG C. quadricarinatus lineage (Bensbach) and the

eastern Australian lineage. While more comprehensive sampling will be required to

fully resolve C. quadricarinatus phylogeography in PNG, the close genetic

relationship of a PNG C. quadricarinatus population and northern Australia C.

quadricarinatus provides evidence for a recent freshwater connection between

northern Australia and PNG. The most recent land bridge between northern

Australia and PNG was present until 8500 years ago (Torgersen et al., 1985; Chivas

et al., 2001). During times of lowered sea level, Australia and southern PNG were a

single landmass with terrestrial and freshwater organisms theoretically then able to

disperse among the two areas over land and via freshwater connections (Figure 3-

1). Relationships among sequences as shown by the haplotype networks (Figure

3-3 and Figure 3-5) suggest that the most recent ancestor, if still extant, was not

sampled (by chance) in the current study.

When all Australian C. quadricarinatus sampled populations were considered

together there was a positive correlation between geographical distance and genetic

distance, suggesting an ‘isolation by distance’ effect. This was largely due to the

significant divergence between eastern and western lineages across the natural

distribution of C. quadricarinatus in Australia. However, if populations within eastern

and western regions are considered separately, no correlation with geographic

distance was evident. If contemporary gene flow occurs between populations of the

two lineages, eastern and western haplotypes should be found in the same

geographic area. However, the probability of detecting haplotypes of both lineages


45

within a site was low given the small sample sizes examined here (n=2). A contact

or hybrid zone could potentially exist somewhere within the 200km transition zone

between the Roper and McArthur Rivers. Unfortunately, while sites were sought in

this area (Limmen Bight catchment) no C. quadricarinatus populations were found

there.

Clock like evolution for C. quadricarinatus sequences was evident in the current

study, although log likelihood tests rejected the hypothesis of clock like evolution for

16s and COI data sets when all populations were considered together. Clock like

evolution was confirmed however within eastern and western lineages respectively.

This indicates that while populations within each lineage are evolving in a clock like

fashion, independent lineages have not been evolving in unison. Dates for time to

common ancestor hypothesised for C. quadricarinatus are estimates calibrated for

marine decapods (16s - porcelain crabs; 0.53%/MY, Stillman and Reeb, 2001 and

fiddler crabs; 0.96%/MY, Sturmbauer et al., 1996 and COI - 1.4%MY; Knowlton and

Weight, 1998) and should be interpreted as indicating only a range of time during

which the evolutionary events may have occurred. Divergence of Australian C.

quadricarinatus lineages using 16s sequence data suggest this occurred 2.8 – 7.3

million years ago, while COI sequence estimates suggest coalescence of eastern

and western lineages between 5.32 – 7.56 million years ago. This dates back to the

Tertiary (late Miocene, 23.8 – 5.3 MYA; Pliocene, 5.3 – 1.8MYA). 16s data

estimates divergence within eastern and western lineages up to 1.88MYA,

corresponding to the beginning of the Pleistocene, an epoch characterised by four

major glacial advances and significant eustatic events in northern Australia.

Substantial geomorphological events such as the rapid uplift of PNG’s central

mountain range (Dow, 1977; Pigram & Davies, 1987), and dramatic climate

oscillations (Axelrod and Raven, 1982) occurred during the Tertiary and Quaternary

periods (Dow, 1977; Hill & Gleadow, 1989). The uplift of PNG’s cordillera has been

episodic rather than a gradual continuous event, with an initial major burst of uplift at

5.8–5.3 MYA and less intense episodes of folding and thrusting spanning the period

5.3–4.7 MYA. The degree of sequence divergence detected between Australian and

PNG C. quadricarinatus conspecifics is compatible with the timing of these tectonic

events and so they provide a potential causative agent for distinct C. quadricarinatus

lineages evolving in PNG.


46

3.5.1 Reconstruction of the evolution of modern C. quadricarinatus lineages

Two alternative scenarios can be hypothesised to explain the presence of two C.

quadricarinatus lineages in Australia. Firstly, following evolution of C.

quadricarinatus in northern Australia, alteration of ancient river drainage watersheds

and eustatic changes resulted in geographical barriers that restricted gene flow

between eastern and western populations. Subsequently, C. quadricarinatus

populations evolved independently and diverged under the influences of genetic

drift, selection, probable colonisation/founder events and population expansion

events post separation. In support of this theory, Macaranas et al. (1995) proposed

that strong selection pressure related to water pH may have influenced the genetic

structure C. quadricarinatus across northern Australia. Basalt soils in eastern

northern Australia produce acidic waters, and ancient coral reef, that are now

exposed limestone escarpments have produced alkaline waters in western northern

Australia. Following isolation, this major environmental difference could have

influenced the evolution of two geographically adapted gene pools corresponding to

the modern eastern and western C. quadricarinatus lineages.

A second scenario is that C. quadricarinatus evolved in PNG and two independent

colonisation events of divergent C. quadricarinatus lineages from PNG occurred at

times of lowered sea levels when northern Australia was connected to PNG via a

land bridge. Divergent lineages of C. quadricarinatus in PNG resulted from

substantial geomorphological events such as the rapid uplift of PNG’s central

mountain range (Dow, 1977; Pigram and Davies, 1987). In addition, dramatic

climatic oscillations (Axelrod & Raven, 1982) during the Tertiary and Quaternary

makes it highly likely that populations of C. quadricarinatus may have become

isolated and restricted to discrete habitat refugia by these events, allowing divergent

lineages to evolve in New Guinea. Later, during times of lowered sea levels with

freshwater rivers coalescing, C. quadricarinatus may have colonised Australia via

two routes: one route west into Arnhem Land across the Arafura Sill and the other

route from PNG south along the Cape York peninsular, into gulf rivers. Colonisations

would have been followed by range expansions into their current distributions.

Subsequent rises in sea level later severed connections between PNG and

Australian rivers.

The division between eastern and western lineages in Australia occurs over a

relatively small geographic distance (a distance of less than 200km of coastline

between the river mouths of the Roper and McArthur Rivers) in the south west

corner of the Gulf of Carpentaria. The two evolutionary lineages found in Australia


47

continue to evolve independently perhaps due to extrinsic factors such as

environmental adaptation (eg. influence of different water chemistry), or perhaps

intrinsic factors such as behavioural differences (eg. different mate recognition cues,

Paterson, 1985).

A close genetic relationship between C. quadricarinatus from northern Australian

and populations in PNG has been observed in other terrestrial (green python,

Morelia viridis, Rawlings & Donnellan, 2003) and aquatic species (rainbow fish,

McGuigan et al., 2000; prawns,de Bruyn et al., 2004). A hypothesis for two

independent colonisations of Melanotaeniid rainbow fish into Australia from PNG

was based on monophyletic relationships among Australian and southern New

Guinea rainbow fish (McGuigan et al. 2000). McGuigan et al. (2000) suggested

contemporary distributions of Melanotaeniid rainbow fish clades reflect episodic

connections via the ancient freshwater Lake Carpentaria during periods of low sea

level when routes for dispersal from PNG to northern Australia were present.

Patterns of genetic structuring of C. quadricarinatus populations concur with that of

another decapod crustacean Macrobrachium rosenbergii that share a similar

distribution in Australia and PNG (de Bruyn et al, 2004). Studies by de Bruyn et al.

(2004) have revealed distinct lineages in PNG, eastern and western Australia, as

well a PNG clade that has a close genetic relationship with an eastern Australian

clade. de Bruyn et al. (2004) also concluded that the intermittent existence of Lake

Carpentaria in the past may have facilitated dispersal of M. rosenbergii among Gulf

of Carpentaria rivers. Lake Carpentaria could have also facilitated dispersal by C.

quadricarinatus, however, since the salinity levels of Lake Carpentaria remain

unknown, and because ancient river systems have been hypothesised to historically

connect some gulf rivers (Voris, 2000), such an inference cannot be made here.

Across C. quadricarinatus’ natural distribution, ancient watercourses are once likely

to have linked populations that are now disjunct. However, geomorphological events

during the Tertiary, coupled with sea level changes during the Pleistocene, have

resulted in modern C. quadricarinatus populations that show significant populations

today.

Chapter 4 – Microsatellite analysis of C. quadricarinatus population

49

4.0 The Extent of Contemporary Gene Flow among Wild Australian C. quadricarinatus Populations

4.1 Introduction

Spatial, physical, temporal and/or biological limitations on gene flow can promote

genetic subdivision among populations of a species (Paetaku et al., 1998; Prodohl et

al., 1998; Luikart et al., 1999; Balloux & Lugon-Moulin, 2002; Costello, 2003). Natural

distributions that exceed the normal dispersal or migrational capacity of individuals can

contribute to spatial patterns of genetic heterogeneity (and even lead to speciation)

(Waters et al., 2001b). The island model (Wright, 1931) is a geographical null

hypothesis of population structure, in which dispersal is unbiased with respect to

distance between habitat islands, but is unlikely to be relevant for freshwater species

with extensive distributions that extend across discrete drainages. A stepping-stone

model (Kimura, 1953) therefore, may better approximate dispersal of most freshwater

species. Stepping-stone dispersal occurs between neighbouring populations where long

distance dispersal is assumed to be rare. Unlike the island model, stepping-stone

dispersal is a correlation of gene frequencies that decreases as the number of steps

between populations increases (Kimura & Weiss, 1964). A similar decline is expected

under an isolation by distance model among continuously distributed populations.

Consequently, gene flow among populations is expected to decline with geographic

distance under stepping-stone dispersal or isolation by distance models of dispersal,

but not under the island model.

Problems with the utility of the above genetic models to explain likely patterns of genetic

variation in freshwater systems led Meffe and Vrijenhoek (1988) to propose the Stream

Hierarchy Model (SHM) as a means for summarising the relationships among

freshwater populations within and among drainages. Due to the complex hierarchical

branching patterns of most riverine drainages, the SHM proposes that the probability of

connectivity among populations was related to the position of a population in a

particular drainage, such that populations within the same stream are likely to be

genetically more similar than populations in different subcatchments and so on

hierarchically, with most differentiation occurring among discrete drainages.

C. quadricarinatus have a simple lifecycle that is completed in freshwater, although

juveniles can tolerate salinities up to 20ppt (brackish) (Jones, 1995) for short periods of


50

time. Being devoid of a free-swimming larval stage, C. quadricarinatus are not expected

to disperse widely as juveniles, compared with some marine crayfish, where larvae are

known to travel great distances via ocean currents (Ward et al., 1994). Local C.

quadricarinatus populations may sometimes even go extinct in drought years with some

ephemeral habitats recolonised from more permanent populations. Depending on the

pattern of recolonisation, genetic diversity could as a consequence decline rapidly

within and among wild populations. If local extinction and recolonisation (bottleneck)

events are frequent, the populations will tend to coalesce rapidly. Genetic drift

combined with local selection effects, in contrast, are likely to increase the extent of

genetic differentiation among isolated populations.

Most natural drainage systems inhabited by C. quadricarinatus in northern Australia are

subject to seasonal flooding, thus dispersal of C. quadricarinatus between neighbouring

rivers may be possible where topography is low. Grimes and Kingford (1996) have also

documented freshwater fish larvae dispersing between discrete drainages when flood

plumes from rivers provide freshwater or low salinity water connections between river

mouths. Salinity is known to reduce significantly in coastal areas in the Gulf of

Carpentaria following extensive rainfall during the wet season (Wolanski, 1993). C.

quadricarinatus may also be capable of limited terrestrial dispersal across drainage

boundaries during humid conditions. Terrestrial dispersal has been documented in

Cherax destructor (Hughes & Hillyer, 2003), where topography between catchments

was minimal and the occurrence of flooding across drainage boundaries was low.

Although individual dispersal capabilities of C. quadricarinatus are essentially unknown,

evidence from other closely related Cherax species suggests that dispersal among

drainages might be possible, at least at small geographic scales.

Mitochondrial DNA analysis of C. quadricarinatus populations identified two divergent

phylogenetic lineages in northern Australia indicating that gene flow between western

and eastern regions has been disrupted in the past for a significant period of

evolutionary time. However, within the two lineages, some haplotypes were shared

among geographically close drainage systems. Across C. quadricarinatus’ natural

distribution, ancient watercourses are once likely to have connected some populations,

however a rise in sea level to its modern day level has severed these historical

freshwater connections.


51

This chapter investigates whether gene flow is occurring among contemporary C.

quadricarinatus populations in northern Australia. To assess if present day genetic

structuring of C. quadricarinatus is due to historical events, or if contemporary gene flow

has played a role in shaping genetic patterns, microsatellite markers were developed.

Microsatellites have proven useful for detecting variation in species that exhibit little

allozyme variation (Hughes & Queller, 1993), are co-dominant and are assumed to be

selectively neutral (Bowcock et al., 1994). The specific objectives of this study were to

(1) examine the levels and patterns of microsatellite variation in wild populations of C.

quadricarinatus in Australia; and (2) given the existence of discrete western and eastern

mtDNA lineages, to determine the extent of contemporary gene flow within and among

wild Australian C. quadricarinatus lineages using nuclear markers.

4.2 Microsatellite Methods

4.2.1 Sample sites

Fourteen populations were used in the microsatellite analysis (Table 4-1). Some

populations used in the mtDNA study were excluded due to small sample sizes (Louie

Creek (n=2), Lockerbie (n=6), Bensbach (n=4), Oriomo (n=6) and MtBosavi (n=4)).

Table 4-1: Site Location, river drainage, abbreviation, sample size of C. quadricarinatus populations used for microsatellite analysis

Site Location Drainage Abbrev. n Kununurra Dam, WA Ord Ord 22 Howard River, NT Howard How 30 Adelaide River, NT Adelaide Ade 24 Roper River, NT Roper Rop 11 McArthur River, NT McArthur McA 22 Calvert River, NT Calvert Cal 22 Gregory River, QLD Gregory Gre 33 Flinders River, QLD Flinders Fli 32 Norman River, QLD Norman Nor 32 Gilbert River, QLD Gilbert Gil 34 Elizabeth River, QLD Gilbert Eli 18 Mitchell River, QLD Mitchell Mit 34 Chillagoe River, QLD Mitchell Chi 32 Weipa, QLD Mission Wei 30

4.2.2 DNA Extraction

Approximately 100mg of abdominal muscle or pleopod tissue was soaked in GTE buffer

for at least 30mins to remove excess ethanol, tissue samples were then placed in 500μl


52

of 2x CTAB3 buffer (1M Tris HCl, 4M NaCl, 0.5M EDTA, 0.5M CTAB, 0.5M 2-

mercaptoethanal) with 15μl of Proteinase K (20mg/ml), and samples incubated in a

water bath at 55oC overnight. Following digestion, 500μl of chloroform:iso-amyl alcohol

(24:1) was added to each tube and mixed thoroughly by gentle inversion of the tube

and this mixture centrifuged at 13 000rpm for 15mins. The aqueous layer was then

removed and samples transferred to a clean tube and the extraction repeated with

phenol:chloroform:iso-amyl alcohol (25:24:1), followed by chloroform:iso-amyl alcohol

(24:1). Precipitation of genomic DNA was carried out using 1ml of cold (-20) 100% iso-

propanol and samples incubated at -20 for one hour. DNA was then centrifuged at 13

000rpm for 15 min, the alcohol decanted and the pellet resuspended in cold (-20) 70%

ethanol. The DNA was again centrifuged at 13 000rpm for a further 5 min. The ethanol

was then decanted and the pellet left to dry at room temperature for 5-10 min. The

pellet was then dissolved in 100-200μl of 1x TE (0.001M Tris-HCL pH7.5, 0.0001M

EDTA4). DNA was electrophoresed through a 1% TBE (1M Tris/.83M Boric Acid/ 10mM

EDTA) agarose gel and visualised under ethidium bromide. Genomic DNA

concentration in each sample was determined using a GeneQuant (RNA/DNA

Calculator, The Australian Chromatography Company). DNA was diluted with distilled

water to approximately 100ng/μl for PCR and stored at –20oC when not in use.

4.2.3 Microsatellite Isolation and Characterisation

The genomic library used to develop C. quadricarinatus microsatellite loci was

developed from a C. quadricarinatus individual collected from the Flinders River

(eastern lineage). Procedures for the construction and screening of the genomic library

are outlined in Baker et al. (2000) (see Appendix 1). Table 4.2 characterises the C.

quadricarinatus microsatellite loci developed for this study.

3 Hexadecyltrimethylammonium Bromide 4 Ethylenediaminetetraacetic acid


53

Table 4-2: Locus name, primer sequences (5’ to 3’ direction), repeat type and size, and PCR conditions for microsatellite loci used in this study.

In the early stages of screening it became evident that western C. quadricarinatus

populations would not amplify with all C. quadricarinatus primer sets developed from an

‘eastern’ lineage individual. After extensive experimental manipulation that involved

changing PCR conditions and redesigning primers, western C. quadricarinatus

populations would amplify with only three of the 12 primer sets developed. While

Koskinen (2004) suggested that 30 microsatellite loci are needed for a comprehensive

population genetic analysis, a much lower number of loci can still be informative and

are used commonly for similar studies in the literature. Five loci were chosen based on

their repeatability and gel separation (clarity of alleles/ stutter bands) and were used to

screen variation in eastern C. quadricarinatus populations, see Table 4.3.

Table 4-3: Locus name, repeat type/size, annealing temperature, magnesium chloride concentration and amplification success of C. quadricarinatus microsatellite loci used in this study.

4.2.4 Radioisotope Analysis of C. quadricarinatus Microsatellites

Microsatellite loci were amplified in 0.5μl Eppendorf tubes using: 50ng of genomic DNA,

1.5x Tth reaction buffer (Pharmacia), 2mM dNTPs (dCTP labelled with 32P), 2/3mM

MgCl2, 16pmol of each primer 0.02U Tth polymerase (Pharmacia); and ddH20 to a

Primer Name Primer Sequence Repeat Size (bp) TA (oC) MgCl2 (mM)

CQU.001-FOR GCA TCA TCT GCA AAC AAG GAT AC (CA)11~(CA)18 178 55 3 CQU.001-REV GTG ACG GGA CCA AGA ATA TGA AG CQU.002-FOR TGT CAG TGT ATG CGG TAG CCA CG (CA)27 179 50 2 CQU.002-REV TGC CGT TCT TCC ATA ACC TCA GG CQU.003-FOR GGG AGA GGG TGG ATT TAC TAC CG (CA)29 219 50 2 CQU.003-REV CCA TGA GAA ATG CTC TGA GAC TCG CQU.004-FOR AAG CCG ACC ATA AA GAA ATC AG (CA)32 218 50 3 CQU.004-REV TTT GCA CTT GGT GGG ATT GAA C CQU.006-FOR AAC TGC CAC CAA ATA CTG CAA GC (CT)11 164 55 3 CQU.006-REV TTG CTC GGG ACA CCT TAC TAG ACG

Amplified Locus Eastern Western

CQU.001 Yes No CQU.002 Yes No CQU.003 Yes Yes CQU.004 Yes Yes CQU.006 Yes Yes


54

volume of 20μl, using the following cycles: 1 min at 94oC, 1min at TA (see Table 2.3)

and 2min at 72oC, for 33 cycles with a 10 min extension at 72oC

Following amplification, 40μl of 95% formamide, 50mM EDTA dye was added to each

sample and the products denatured at 94oC for 3 min and then placed immediately on

ice. 1μl of PCR product was then electrophoresed at 70 watts through a 5% denaturing

polyacrylamide sequencing gel. Gels were dried for 45min at 80oC and visualised using

autoradiography. Reference individuals possessing unique alleles, were included on

each gel run. Individuals were genotyped in comparison to these reference alleles.

Allele frequencies were tabulated for each population.

During the screening process for allelic diversity at C. quadricarinatus microsatellite loci,

a GelScan 2000 (Corbett Research) which is an integrated electrophoretic and

computerised system using a laser to detect fluorescently labelled PCR products was

purchased by the SNRS Genetics Laboratory. Reverse primers were fluorescently hex-

labelled and electrophoretic running conditions re-optimised for GelScan microsatellite

analysis.

4.2.5 Fluorescent Analysis of C. quadricarinatus Microsatellites

Microsatellite loci were amplified in 96-well plates using the following conditions: 50ng

of genomic DNA, 1.5x Tth reaction buffer (Pharmacia), 2/3mM dNTPs 3mM MgCl2,

10pmol of each primer (reverse primer hex-labelled), 0.02U Tth polymerase

(Pharmacia); and ddH20 to a volume of 12μl. PCR reactions were cycled using the

optimised annealing temperature in an Eppendorf Mastercycler PCR machine using the

following conditions: one extended denaturation at 94oC for 2 min, then 40 sec at 94oC,

40 sec at TA (see Table 2-3) and 1 min at 72oC, for 29 cycles with a 10 min extension at

72oC.

Following amplification, 12μl of 95% formamide, 50mM EDTA dye were added to each

sample and the products denatured at 94oC for 3 min and samples placed immediately

on ice. Samples were electrophoresed through a 5% acrylamide gel at 1200volts using

a GelScan 2000 (Corbett Research). A 350bp size ladder (Genetix) combined with C.

quadricarinatus alleles of known size were run at either end and in the middle of the

unknown samples on each gel. Representative alleles scored using P32 methods were


55

re-amplified and run on the GelScan to confirm reproducibility and to assign a repeat

size.

Within each plate two tubes were left empty to allow control (reference) samples to be

loaded. Because alleles at dinucleotide loci differ by as little 2bp, a misalignment with

size markers, or ‘frowns’ in gel running conditions can easily lead to scoring errors, so

controls (known genotypes) were used routinely on all gels.

Gel images were analysed using OneDScan (Scanalytics). To reduce error during

genotyping using OneDScan software (Scanalytics), gel images were double-checked.

The digital gel images were scored twice, on different occasions, to ensure accurate

genotype data.


56

4.2.6 Statistical Analysis

4.2.6.1 Linkage disequilibrium Exact P-tests for detecting linkage disequilibrium were used to test the independence of

microsatellite loci using a Markov chain approach, as performed in GENEPOP ver. 3.1

(Raymond & Rousset, 1995). A Bonferonni approach (Rice, 1989) was used to correct

for multiple simultaneous tests.

4.2.6.2 Tests for Hardy-Weinberg Equilibrium (HWE)

Observed genotypic frequencies were compared with those expected under Hardy-

Weinberg equilibrium using exact tests (Louis and Dempster 1987) using a Markov

chain method (Guo and Thompson 1992) for loci with five or more alleles. Tests were

performed in GENEPOP ver. 3.1 (Raymond and Rousset, 1995). The Bonferonni

correction (Rice 1989) was used to correct for multiple simultaneous tests.

4.2.6.3 Molecular diversity

Common indices of genetic variation including: number of alleles per locus, number of

effective alleles and mean heterozygosity (HO and HE) and fixation indices were

estimated for each locus using GenAlEx Ver 1.5 (Peakall & Smouse, 2001). A fixation

index value (F) close to zero is expected under random mating. Positive values indicate

inbreeding (or null alleles), while negative values indicate an excess of heterozygotes,

due to assortative mating or selection acting at the locus.

4.2.6.4 Null allele analysis The relatively large number of alleles that microsatellite loci commonly reveal will

inherently cause departures from HW if sample sizes are low. Null alleles that are not

amplified create an apparent heterozygote deficit because they produce pseudo-

homozygotes (Brookfield, 1996). If a null allele has a frequency of p, the mean number

of individuals that have to be sampled in order to observe one homozygote is E(n)=1/p2.

Brookfield (1996) described a method for estimating the frequency of null alleles, r, from

the deficiency of heterozygotes that they induce. The expected frequency of

heterozygotes, from HWE formula is:


57

Σpi.pj= Σpi

.pj/(1-r)2=He

Thus, D=(He-Ho)/He=2r/(1+r)

Thus, r=D/(2-D)

4.2.6.5 Population differentiation

Most microsatellite alleles are believed to evolve by the addition or deletion of single

repeats, and less frequently by mutations involving two or more repeats (Weber &

Wong, 1993; DiRienzo et al., 1994; Primmer & Ellegren, 1998). Understanding the

mutation model underlying microsatellite evolution is crucial for the development of

statistics to accurately define population genetic structures. Two general models have

been proposed to account for variation at a genetic locus, the infinite allele’s model

(IAM, (Kimura & Crow, 1964)) and the stepwise mutation model (SMM, (Kimura & Otha,

1978)).

FST is a decreasing function of N(m + u), the product of local population size and the

sum of migration and mutation. FST becomes a simple function of the number of

migrants when mutation is negligible, although this is often not the case for

microsatellites. An additional difficulty arises when the mutation model cannot be

assumed to an IAM. Under mutation models generating homoplasy, such as SMM, the

relationship between FST and the number of migrants may no longer hold (Rousset,

1996). Slatkin (1995) proposed RST as an analogue to FST for microsatellite loci

assuming a stepwise mutation model. Recently however, questions have been raised

about the reliability of RST (Balloux & Goudet, 2002). The drawback with RST is its high

variance, even under the strictest SMM, FST estimates therefore may outperform their

RST counterparts (Gaggiotti et al., 1999). Given that the mutation model for C.

quadricarinatus microsatellite loci is unknown, the conservative method for estimating

extent of population differentiation (FST) was implemented. FST was calculated (Weir &

Cockerham, 1984) and tested for significance using 1000 random permutations in

GenAlEx ver 5.1 (Peakall and Smouse, 2001).

4.2.6.6 Genetic distance FST, a pairwise comparison between populations, only takes into account data from two

populations, not all populations simultaneously. This can be done with genetic distance

measures of which there are two types; (i) without biological assumptions or models


58

known as geometric distances, and (ii) with biological models taking into account

mutation and drift, but assuming no selection.

Genetic divergence among populations was first quantified using Cavalli-Sforza and

Edwards’ (1967) chord distance (DCE), which makes no assumptions about constant

population size or relative mutation rates among loci. Takezaki and Nei (1996)

evaluated DCE in simulations of tree-building algorithms for microsatellite loci and

concluded that this distance measure usually performed well. DCE is thus re-emerging

as the preferred algorithm for microsatellite analyses as it makes no assumptions about

mode of microsatellite mutation. Cavalli-Sforza’s DCE (Cavalli-Sforza and Edwards1967)

was calculated uisng GENDIST from gene frequencies in PHYLIP ver 3.57

(Felsenstein, 1995).

4.2.6.7 Isolation by distance measures

Isolation by distance refers to the increase in genetic differentiation among sites with

increasing geographic distance, under restricted levels of gene flow (Wright, 1943). At

equilibrium, gene flow and genetic drift, and hence the level of genetic differentiation

should be inversely correlated with distance among populations.

Isolation by distance was estimated using IBD Ver 1.5 (Bohonak, 2002). Chord distance

estimates were correlated with coastline geographic distance between river mouths

using matrix correlation methods of the Mantel test in the IBD Ver 1.5 program.

Because C. quadricarinatus populations are distributed in two dimensions rather than

along linear habitat features, I used log-transformed genetic and geographic distances

were used here as advocated by Rousset (1997).

Hutchison and Templeton (1999) suggested a graphical technique for determining the

influence of gene flow and drift on genetic variability. Traditional attempts to relate

estimates of regional FST to gene flow and drift via Wright’s (1931) equation FST

(1/(4Nm+1)) are often inappropriate because most natural populations may not have

reached equilibrium. Hutchison and Templeton’s (1999) graphical representation of

theoretical relationships between genetic (FST) and geographical distance describes

four possible outcomes resulting from the evolutionary dynamics that may have affected

populations historically. These include 1) equilibrium between gene flow and drift; 2)

gene flow more influential than drift; 3) drift more influential than gene flow; and 4) gene


59

flow and drift influence population structure differently depending on scale. A

scatterplot of the pairwise genetic and geographic distances among populations

sampled here was produced in Excel and the resulting graph compared to hypothetical

graphs in Hutchison and Templeton (1999) to infer the relative influences that gene flow

and drift could have had on the distribution of genetic variability in wild C.

quadricarinatus populations.

4.2.6.8 AMOVA analysis of molecular variance

The hierarchical population genetic structure of wild C. quadricarinatus stocks were

examined using analysis of molecular variance and the results tested for significance

using 1000 random permutations in GenAlEx (Peakall & Smouse, 2001). The AMOVA

analysis procedure follows the methods of Excoffier et al(1992).

4.2.6.9 Detection of recent population bottlenecks

Populations that have experienced a recent reduction in effective population size

(bottleneck) exhibit a correlated reduction in allele number (k) and gene diversity (HE) at

polymorphic loci. But allele number will reduce faster than gene diversity. Thus in

recently bottlenecked populations, observed gene diversity will be higher than the

expected equilibrium gene diversity (Heq) which is computed from the observed

number of alleles (k), under the assumption of constant-size (equilibrium) populations

(Luikart et al., 1998).

Gene diversity excesses (HE >Heq) have only been demonstrated for loci evolving

under an infinite allele model (IAM) (Maruyama & Fuerst, 1985). If the locus evolves

under a strict stepwise mutation model (SMM), there can be situations where gene

diversity excess is not observed (Cornuet & Luikart, 1996). Few loci however, follow a

strict SMM, and as soon as they depart slightly from this mutation model towards IAM,

they will exhibit a gene diversity excess as a consequence of any past genetic

bottleneck. Because few microsatellite loci follow a strict (one-step) SMM, a two-phase

model of mutation (TPM) is considered more appropriate. The TPM is intermediate to

the SMM and IAM (Luikart, 1998).

A second method to test for recent population bottlenecks implements a qualitative

descriptor of allele frequency distributions (‘mode-shift’ Indicator) that can discriminate

bottlenecked populations from stable populations. In a population at mutation-drift


60

equilibrium (the effective size of which has remained constant in the recent past), there

is approximately an equal probability that a locus will show a gene diversity excess or a

gene diversity deficit.

A Wilcoxon’s signed rank test was implemented to test for excess heterozygosity

developed by Cornuet & Luikart (1996): Simulation of Heq distributions assumed the

two-phase mutation model (TPM). The second method is a graphical representation of

the mode-shift indicator originally proposed by Luikart et al. (1998). Loss of rare alleles

in bottlenecked populations is detected when one or more of the common allele classes

have a higher number of alleles than the rare allele class (Luikart et al. 1998).

Bottleneck events were tested using both methods discussed above and were

conducted using ‘BOTTLENECK’ version 1.2.02 (Piry & Luikart, 1999).

4.2.6.10 Shannon-Weaver Index of genetic diversity Genetic diversity within a population may be lost via four related processes: founder

effect, demographic population bottlenecks, genetic drift, or inbreeding. Loss of genetic

diversity is believed to have implications for population persistence over various

temporal scales (Crozier, 1992). In the short term (e.g. generations), inbreeding

resulting from small population size may cause inbreeding depression with

corresponding reductions in mean population fitness. In the long term (hundreds or

thousands of years), reduced genetic diversity within a population may lower

evolutionary potential (ability to adapt to future environmental circumstances) or

decrease the probability of future speciation events. Shannon's Information index

provides a numerical value for relative estimate of genetic diversity with high values

representing greater amounts of genetic diversity (Peakall and Smouse, 2001). Unlike

HE, this information index value is not bounded by 1 and may therefore be a better

measure of allelic and genetic diversity. Estimates of genetic diversity are based on

frequencies of genotypic variants and can be used to assess diversity occurring not

only within populations, but also within different geographical regions or different

germplasm collections.

The Shannon-Weaver Index (Shannon & Weaver, 1949) formula is: I = - Σpi lnpi

Where ln=the natural logarithm and pi is the frequency of the ith allele.


61

4.3 Results In contrast to eastern populations that were screened at five loci, the four western

populations of C. quadricarinatus, (Ord, Adelaide, Howard and Roper) could only be

screened for diversity at three microsatellite loci designed specifically for C.

quadricarinatus. Failure to amplify entire populations with species-specific

microsatellite primers has not been reported previously in the literature. Due to the

different number of loci examined for western populations (3 loci) versus eastern

populations (5 loci), microsatellite analyses were segregated and the two data sets

treated separately. Also, although the sample size collected from the Gregory River

was relatively large (n=33), low numbers of individuals amplified at most loci,

especially CQU006 where only two individuals amplified. The Gregory population

was therefore excluded from analyses as small sample sizes can bias results (eg

genetic distance).

4.3.1 Microsatellite analyses of Eastern Populations

4.3.1.1 Linkage Disequilibrium

Permutation tests indicated that no significant linkage disequilibrium was evident in

eastern populations. This confirms that results from different loci are independent

markers of underlying genetic variation in the sampled populations.

4.3.1.2 Hardy Weinberg Departures

After Bonferroni correction 18 of the 45 tests were found to have significant p-values

at the 0.001 level (Appendix 3). Populations that deviated from HWE included:

CQU001: Chillagoe, Mitchell; CQU002: Norman, Mitchell, Weipa and McArthur;

CQU003: Gilbert, Mitchell and Calvert; CQU004: Norman, Elizabeth, Gilbert,

Chillagoe, Mitchell and Calvert; CQU006: Norman, Chillagoe, and Mitchell. Mitchell

was the only site that showed consistently significant values at all five microsatellite

loci, while six of the eastern populations did not conform at locus CQU004.

4.3.2 Molecular Diversity

Common indices for eastern C. quadricarinatus populations computed in GenAlex

are presented in Table 4-4. Actual population sizes range from 18 (Elizabeth) to 34

(Mitchell) however, sample sizes (n) varied as amplification success varied at each

locus. Observed heterozygosity in eastern populations ranged from 0.00 – 0.94 and

was usually lower than expected heterozygosity (Table 4.4). Most loci exhibit lower

estimates of observed heterozygosity compared to expected heterozygosity. This

suggests that factors like selection, inbreeding or null alleles were influencing C.


62

quadricarinatus microsatellite diversity in eastern populations. The majority of

fixation values (F) were strongly positive suggesting possible inbreeding, selection

or undetected alleles. A few populations exhibited negative fixation values, indicative

of an excess of heterozygosity under HW equilibrium.

4.3.3 Null Alleles

Proportions of null alleles of up to 79% (locus CQU002; Elizabeth population) were

detected, as shown in Table 4-4. This high number of null alleles detected in some

populations is likely to explain the relatively high level of HWE deviations observed

here.


63

Table 4-4: Common indices for eastern C. quadricarinatus populations; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F) and Brookfield’s (1996) estimate of null allele proportions (r). Values in bold indicate upper values for each locus. N/A-monomorphic at that locus.

N Na Ne HO HE F r CQU001 Flinders 31 2 1.290 0.258 0.225 -0.148 -0.069 Norman 32 6 2.955 0.563 0.662 0.150 0.081 Elizabeth 18 2 1.528 0.333 0.346 0.036 0.018 Gilbert 33 5 1.424 0.212 0.298 0.288 0.168 Chillagoe 32 4 2.528 0.281 0.604 0.535 0.365 Mitchell 34 7 4.718 0.441 0.788 0.440 0.282 Weipa 30 3 1.835 0.533 0.455 -0.172 -0.079 Calvert 22 5 3.163 0.591 0.684 0.136 0.073 Gregory 21 9 6.682 0.714 0.850 0.160 0.087 McArthur 8 6 3.765 0.625 0.734 0.149 0.080 CQU002 Flinders 31 1 1.000 0.000 0.000 N/A N/A Norman 32 6 4.312 0.813 0.768 -0.058 -0.028 Elizabeth 18 3 1.982 0.056 0.495 0.888 0.798 Gilbert 34 8 4.827 0.765 0.793 0.035 0.018 Chillagoe 32 8 4.055 0.750 0.753 0.005 0.002 Mitchell 32 9 3.779 0.469 0.735 0.363 0.221 Weipa 27 4 1.997 0.222 0.499 0.555 0.384 Calvert 21 6 2.706 0.524 0.630 0.169 0.092 Gregory 20 7 4.444 0.650 0.775 0.161 0.088 McArthur 13 7 5.930 0.615 0.831 0.260 0.149 CQU003 Flinders 32 1 1.000 0.000 0.000 N/A N/A Norman 32 15 7.186 0.781 0.861 0.092 0.048 Elizabeth 18 5 3.661 0.944 0.727 -0.299 -0.130 Gilbert 34 16 8.996 0.647 0.889 0.272 0.157 Chillagoe 32 15 9.022 0.875 0.889 0.016 0.008 Mitchell 33 16 8.442 0.879 0.882 0.003 0.002 Weipa 28 8 3.950 0.821 0.747 -0.100 -0.048 Calvert 21 12 9.910 0.476 0.899 0.470 0.308 Gregory 16 11 7.758 0.438 0.871 0.498 0.331 McArthur 20 12 6.897 0.750 0.855 0.123 0.065 CQU004 Flinders 31 5 3.593 0.677 0.722 0.061 0.032 Norman 30 12 5.000 0.667 0.800 0.167 0.091 Elizabeth 18 5 2.723 0.167 0.633 0.737 0.583 Gilbert 34 7 2.181 0.324 0.542 0.403 0.252 Chillagoe 32 12 6.990 0.656 0.857 0.234 0.133 Mitchell 34 13 7.837 0.471 0.872 0.461 0.299 Weipa 26 7 3.654 0.692 0.726 0.047 0.024 Calvert 16 4 2.381 0.125 0.580 0.785 0.645 Gregory 6 7 5.143 0.333 0.806 0.586 0.415 McArthur 19 5 2.625 0.526 0.619 0.150 0.081 CQU006 Flinders 31 5 2.458 0.548 0.593 0.075 0.039 Norman 30 8 4.390 0.133 0.772 0.827 0.706 Elizabeth 18 3 2.418 0.444 0.586 0.242 0.138 Gilbert 34 8 3.899 0.853 0.744 -0.147 -0.069 Chillagoe 31 9 5.018 0.484 0.801 0.396 0.247 Mitchell 34 11 4.129 0.353 0.758 0.534 0.364 Weipa 30 5 2.308 0.600 0.567 -0.059 -0.029 Calvert 18 6 2.132 0.444 0.531 0.163 0.089 Gregory 2 2 1.600 0.500 0.375 -0.333 -0.143 McArthur 22 6 1.820 0.364 0.450 0.193 0.107


64

4.3.4 Population differentiation

Given that the mutation model for C. quadricarinatus microsatellites was unknown,

FST estimates to determine population differentiation were employed. Table 4-5

details pairwise FST estimates for eastern C. quadricarinatus populations. An FST of

1 indicates fixation of alternate alleles in subpopulations and an FST of 0 indicates

the same alleles occur in both populations at identical frequencies. FST values

among paired eastern sites ranged from 0.046 between Chillagoe and Mitchell

(populations within the same river system) to 0.545 between Flinders and Elizabeth.

Table 4-5: Population differentiation for eastern C. quadricarinatus populations. FST values are below the diagonal. Probability values based on 1000 permutations showed significant differentiation (p<0.01) at all pairwise comparisons. Values in bold represent highest and lowest values.

Flinders Norman Elizabeth Gilbert Chillagoe Mitchell Weipa Calvert McArthurFlinders Norman 0.334 Elizabeth 0.545 0.225 Gilbert 0.445 0.141 0.198 Chillagoe 0.405 0.116 0.145 0.120 Mitchell 0.387 0.121 0.161 0.148 0.046 Weipa 0.509 0.264 0.338 0.308 0.212 0.149 Calvert 0.465 0.188 0.314 0.272 0.195 0.172 0.247 McArthur 0.474 0.223 0.341 0.275 0.221 0.194 0.276 0.193

4.3.5 Genetic Distance

Chord distance (Cavalli-Sforza and Edwards 1967) was estimated to determine how

genetically similar C. quadricarinatus populations were to each other. Table 4-6

shows the chord distance estimates among eastern C. quadricarinatus populations.

Values close to zero imply two populations are genetically very similar.

Chord estimates reveal a pairwise genetic distance measure of 0.037 for Mitchell

and Chillagoe. Since Chillagoe is a tributary within the Mitchell River catchment,

genetic distance estimates were expected to be low. This result concurs with the

observed FST values (Table 4.5). The highest Chord genetic distance seen was

evident between Flinders and Weipa, two ‘eastern’ sites separated by a large

geographic distance (~700km).


65

Table 4-6: Chord distance estimates using data from five microsatellite loci for ‘eastern’ C. quadricarinatus populations. Figures in bold highlight the highest and lowest values.

Flinders Norman Elizabeth Gilbert Chillagoe Mitchell Weipa Calvert McArthurFlinders Norman 0.0855 Elizabeth 0.1292 0.0939 Gilbert 0.1030 0.0553 0.0709 Chillagoe 0.1191 0.0666 0.0589 0.0426 Mitchell 0.1174 0.0713 0.0587 0.0567 0.037 Weipa 0.1499 0.1236 0.1177 0.1110 0.099 0.0815 Calvert 0.1459 0.1132 0.1198 0.1113 0.103 0.0885 0.1005 McArthur 0.1176 0.0928 0.1074 0.0803 0.082 0.0777 0.0955 0.0736

4.3.6 Isolation by Distance

4.3.6.1 Mantel tests

Chord distance was used to determine if coastline distance was correlated with

genetic distance among sampled ‘eastern’ C. quadricarinatus populations. A

significant p value was negated by the very small R2 value so the hypothesis of

isolation by distance among eastern C. quadricarinatus populations was rejected (Z

= -78.9221, r = 0.4835, one-sided p = 0.0150). 4.3.6.2 FST values graphed against geographic distance A scatterplot pattern for coastline distance against FST estimates among eastern

populations (Figure 4-1) shows allele frequencies in each population have drifted

independently and are not correlated with the geographic distances separating

sampled populations.

Figure 4-1: Graphical representation of genetic differentiation, estimated by FST and geographic distances (km) of eastern population pairs.

Eastern C. quadricarinatus populations

R2 = 0.0043

0

0.1

0.2

0.3

0.4

0.5

0.6

0 200 400 600 800 1000 1200 1400

coastline distance (km)

Fst


66

4.3.7 AMOVA

Variation within and among populations/regions was partitioned by Analysis of

Molecular Variance - AMOVA. Within population variation accounted for 73% of the

total genetic variation for the eastern lineages. Of the remaining 27%, 22% was

accounted for by variation among populations within regions. Variation among

regions accounted for only 4.6% (Table 4-7).

Table 4-7: AMOVA showing the partitioning of variation within and among eastern populations of C. quadricarinatus. The populations were grouped into western Gulf (McArthur and Calvert), southern Gulf (Flinders, Norman, Gilbert and Elizabeth) and northern Gulf (Chillagoe, Mitchell and Weipa) NB Gregory was not included in this analysis

Source of Variation (eastern) d.f. Variance % Φ statistic P Among Regions (ΦCT) 3 4.65 0.04644 < 0.010 Among Pops./ Within Regions (ΦSC) 5 22.03 0.23105 < 0.010 Within Populations. (ΦST) 511 73.32 0.26677 < 0.010

4.3.8 Bottleneck analysis

Populations were tested for heterozygosity excess and loss of allelic diversity at

microsatellite loci as might occur immediately following a severe bottleneck or

founder event, see Table 4-8.

Excess heterozygosity was statistically significant for the Wilcoxon’s signed rank test

for Norman (p= 0.031), Elizabeth (p=0.015), Chillagoe (p=0.015), Weipa (p=0.015)

and Gregory (p=0.046). A population contraction in the Flinders population was also

detected by the second method, the mode-shift indicator. Furthermore, the Flinders

population exhibited significant distortion of allele frequency distribution, but did not

reach significance with a Wilcoxon’s sign rank test (Table 4-8).

Table 4-8: Evidence for recent bottlenecks was indicated by significant heterozygosity excess or an allele distribution ‘mode shift’ (#graphs not shown).

Wilcoxon’s (p value)

‘mode-shift’ indicating bottleneck#

Flinders 0.062 yes Norman 0.031* no Elizabeth 0.015* no Gilbert 0.593 no Chillagoe 0.015* no Mitchell 0.046 no Weipa 0.015* no McArthur 0.312 no Calvert 0.312 no Gregory 0.046* no


67

4.3.9 Genetic Diversity Estimates

Average microsatellite diversity for each population was calculated using the

Shannon information index (Table 4-9). Genetic diversity in the eastern populations

ranged from 0.584 to 1.8188.

Table 4-9: Shannon's Information index (Shannon and Weaver 1949) of eastern C. quadricarinatus populations for five microsatellite loci, their mean value and standard deviation. Values in bold are highest and lowest mean values (n/a – monomorphic)

CQU001 CQU002 CQU003 CQU004 CQU006 Mean St. Dev Flinders 0.3845 n/a n/a 1.3702 1.1653 0.7130 ±0.520 Norman 1.2710 1.6044 2.2746 1.9611 1.6829 1.7588 ±0.379 Elizabeth 0.5297 0.7683 1.4158 1.189 0.9810 0.9768 ±0.346 Gilbert 0.6742 1.7272 2.4148 1.1452 1.6051 1.5133 ±0.653 Chillagoe 1.0298 1.6812 2.4124 2.1364 1.8342 1.8188 ±0.523 Mitchell 1.6493 1.6281 2.3791 2.2923 1.8471 1.9592 ±0.355 Weipa 0.7027 0.8713 1.5863 1.5187 1.0993 1.1557 ±0.389 Calvert 1.3478 1.2242 2.3837 0.9941 1.1568 1.4213 ±0.552 McArthur 1.5111 1.8420 2.1510 1.2577 0.9744 1.5472 ±0.465

4.3.10 Microsatellite Analysis of Western Populations

4.3.10.1 Linkage Disequilibrium

Significant disequilibrium was found for 1 out of 12 tests (8.3%; after Bonferroni

correction). The loci CQU004 – CQU006 were found to be linked in the Howard

population (p=0. 00058; α=000416). The low number of populations in this group

makes this pair statistically significant, however, this result is most probably due to

chance.

4.3.10.2 Hardy Weinberg Departures

Four out of twelve tests (33%) in the western group were found to have p-values

significant at the 0.004 level after Bonferroni corrections (Appendix 3):

CQU006: Howard and Roper; CQU003: Howard; CQU004: Howard.

In the western populations, Howard deviated from HWE at all three loci, and 50% of

the populations deviating at CQU006.

4.3.10.3 Molecular Diversity

Common indices for western C. quadricarinatus populations are presented in Table

4-10. Actual population sizes range from 11 (Roper) to 30 (Howard), however,

sample sizes (n) varied as amplification success varied among loci. Observed

heterozygosity for western populations ranged from 0.25 – 0.79.


68

Most loci exhibited lower estimates of observed heterozygosity compared with

expected heterozygosity, suggesting factors such as selection, inbreeding or null

alleles had influenced C. quadricarinatus populations. This result concurred with

that observed for eastern populations (Table 4.4).

4.3.11 Null Alleles

Null allele proportions of up to 51% were estimated (locus CQU004; Roper

population) in western C. quadricarinatus populations, as shown in Table 4-10. The

proportion of null alleles detected in western populations was lower than that

detected in eastern populations (when comparing estimates of amplifiable loci in

western populations). Because western populations did not amplify at most

microsatellite loci, this was a surprising result

Table 4-10: Common indices for western C. quadricarinatus populations; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F), and Brookfield’s (1996) estimate of null allele proportion (r). Values in bold indicate upper values for each locus.

N Na Ne HO HE F r CQU003 Ord 22 5 2.367 0.682 0.577 -0.181 -0.082 Adelaide 24 10 5.731 0.792 0.826 0.041 0.020 Howard 29 12 7.680 0.483 0.870 0.445 0.286 Roper 8 6 4.923 0.750 0.797 0.059 0.030 CQU004 Ord 22 8 3.585 0.727 0.721 -0.009 -0.004 Adelaide 24 9 4.085 0.583 0.755 0.228 0.128 Howard 30 11 7.895 0.500 0.873 0.427 0.271 Roper 4 5 4.571 0.250 0.781 0.680 0.515 CQU006 Ord 22 3 1.909 0.364 0.476 0.236 0.134 Adelaide 24 7 4.299 0.750 0.767 0.023 0.011 Howard 28 11 7.293 0.750 0.863 0.131 0.069 Roper 9 7 4.765 0.444 0.790 0.438 0.280

4.3.12 Population differentiation

FST estimates to determine population differentiation are shown in Table 4-11.

Western FST values range from 0.108 between Roper and Howard, and 0.304

between Roper and Ord, the two most geographically distant (in terms of coastline

distance) populations.


69

Table 4-11: Population differentiation for western C. quadricarinatus populations. FST values are below the diagonal. Probability values based on 1000 permutations and all were significant (p<0.01). Values in bold represent highest and lowest values.

Ord Adelaide Howard Roper Ord Adelaide 0.274 Howard 0.159 0.116 Roper 0.304 0.184 0.108

4.3.13 Genetic Distance

Genetic distance estimates for western C. quadricarinatus populations are

presented in Table 4-12. Genetic distance estimates among western populations

were generally lower than eastern populations. Chord genetic distance estimates

correspond to FST measures, indicating Ord and Roper Rivers (0.927) are the most

genetically differentiated, while Ord and Howard (0.0526) were the most similar

populations.

Table 4-12: Chord distance estimates using data from three microsatellite loci for western C. quadricarinatus populations. Figures in bold indicate the highest and lowest values.

Ord Adelaide Howard Roper Ord Adelaide 0.0875 Howard 0.0526 0.0633 Roper 0.0927 0.0808 0.0594

4.3.14 Isolation by Distance

4.3.14.1 Mantel tests

An isolation by distance model was rejected among western C. quadricarinatus

populations (Z = -22.8130, r = 0.3822, one-sided p = 0.3440).

4.3.14.2 FST values graphed against geographic distance

The scatterplot pattern of western populations was inconclusive as sample size was

low, but the few points reflect genetic structuring similar to that observed for eastern

populations, where allele frequencies in each population have drifted independently

without relation to the geographic distances separating populations (Figure 4-2).


70

Figure 4-2: Graphic relationship between genetic differentiation FST and geographic distances (km) of western population pairs.

4.3.15 AMOVA

Analysis of molecular variance examined the partitioning of variation across various

scales of pooled samples and indicated that microsatellite allelic variation within

population variation accounted for 80% of the total genetic variation for the western

lineages. Of the remaining 20%, 11% was accounted for by variation among

populations within regions. Variation among the regions accounted for only 8%

(Table 4-13). This trend was also seen in AMOVA analyses for eastern populations.

Table 4-13: AMOVA showing the partitioning of variation within and among western populations of C. quadricarinatus. The western populations were grouped as western (Ord), northern (Adelaide and Howard) and eastern (Roper).

Source of Variation (western) d.f. Variance % Φ statistic P Among Regions (ΦCT) 2 8.04 0.0804 < 0.010 Among Pops./ Within Regions (ΦSC) 1 11.67 0.1268 < 0.010 Within Populations. (ΦST) 170 80.29 0.1970 < 0.010

4.3.16 Bottleneck analysis

Excess heterozygosity was statistically significant for the Wilcoxon’s signed rank test

for Howard (p=0.031), see Table 4-14. A bottleneck in the Roper population was

also detected by the second method, the mode-shift indicator. Loss of rare alleles

caused the allelic distribution to shift for the Roper population, and this was

statistically significant at the 5% level, see Table 4-14. The Roper population

exhibited significant distortion of allele frequency distribution, but did not reach

significance with a Wilcoxon’s sign rank test.

Western C. quadricarinatus populations

R2 = 0.08

00.050.1

0.150.2

0.250.3

0.35

0 2000 4000 6000 8000

coastline distance (km)Fs

t


71


Wilcoxon’s test

p value ‘mode-shift’ indicating

bottleneck# Ord 0.937 no Adelaide 0.906 no Howard 0.031* no Roper 0.062 yes

4.3.17 Genetic Diversity Estimates

Average microsatellite diversity was calculated using the Shannon Information index

for each population (Table 4-15). Genetic diversity in the western populations

ranged from 1.1531 to 2.1978. Values were generally higher than those seen in

eastern populations.

Table 4-15: Shannon's Information index (Shannon and Weaver 1949) of western C. quadricarinatus populations for three microsatellite loci, their mean value and standard deviation. Values in bold are highest mean values

CQU003 CQU004 CQU006 Mean St. Dev Ord 1.1471 1.5366 0.7755 1.1531 ±0.3806 Adelaide 1.9794 1.7157 1.6178 1.7710 ±0.1870 Howard 2.2421 2.2012 2.1501 2.1978 ±0.0461 Roper 1.6675 1.5596 1.7249 1.6507 ±0.0839

4.3.18 Gene Flow Estimates

In some studies a value for gene flow among populations is often calculated on the

basis of the relationship between FST and Nem. This model assumes, however, that

populations are at equilibrium with respect to gene flow and genetic drift, i.e. that the

divergence due to drift is equal to the convergence due to gene flow (Nei et al.,

1977; Rousset, 1996). A significant number of C. quadricarinatus populations

deviated from expected Hardy-Weinberg equilibrium, thus it is not appropriate to

estimate gene flow here.


72

4.4 Discussion Genetic markers with intrinsically different rates of mutation and/or mode of

inheritance provide greater power for hypothesis testing when levels and patterns of

genetic structuring among populations are examined. Microsatellite data generated

here concur with mtDNA results reported earlier (Chapter 3), and add further

support to the existence of two highly divergent C. quadricarinatus gene pools in

Australia; referred to as an ‘eastern’ lineage and a ‘western’ lineage. Western

populations (Ord, Howard, Adelaide and Roper Rivers) failed to amplify at 75% of

the C. quadricarinatus specific microsatellite loci developed from an ‘eastern’ C.

quadricarinatus individual. This is an unusual outcome as microsatellite loci have

even been reported to amplify across divergent taxa such as bovine specific loci

amplifying sheep and goat DNA (Moore et al., 1991); and marine turtle markers

amplifying in freshwater turtles (FitzSimmons et al., 1995). The failure to amplify

some loci in western populations probably reflects ancient mutations in the priming

sites (assumed conserved regions) of microsatellites developed for eastern C.

quadricarinatus stocks.

Until now, the few genetic studies of wild C. quadricarinatus populations have

revealed relatively low levels of genetic variation. Austin (1996) used five variable

allozyme loci to detect an average of 2.2 alleles per locus across eleven C.

quadricarinatus populations, including one population from PNG. Macaranas et al.

(1996) used six variable allozyme loci to reveal a mean number of 2.5 alleles per

locus, heterozygosity estimates of up to 0.058 and FST estimates between 0.000 –

0.075 for 12 Australian C. quadricarinatus populations. In the same study RAPDs

detected relatively high levels of variation among C. quadricarinatus populations

(13.3 variable loci/primer pair), but problems with PCR amplification and

repeatability proved problematic for this method (Macaranas et al. 1996). Despite

the western lineage of populations not amplifying at all loci in this study,

microsatellite loci have proven informative and identified a high level of genetic

structuring among Australian C. quadricarinatus populations. C. quadricarinatus

populations sampled across northern Australia possessed a mean number of 30.6

alleles/locus and 7.3 alleles/population (eastern: 7.2; western 7.8), high levels of

heterozygosity (up to 0.944; average of 0.523) and significant levels of differentiation

among populations (FST values up to 0.545; average of 0.25). The mean number of

alleles per locus and heterozygosity levels detected by microsatellite loci were about

10 times as high as those for allozyme data, suggesting that the C. quadricarinatus

microsatellite loci developed here have a high resolving power for detecting genetic

diversity.


73

Approximately one third of the alleles detected here were shared between eastern

and western lineages. Microsatellite loci, by virtue of their high mutation rate, are

susceptible to problems of homoplasy, where alleles of identical size result from

independent mutational processes (Schlötterer et al., 1998). Queney et al. (2001)

observed homoplasy at microsatellite loci between two well-supported phylogenetic

clades of rabbit populations on the Iberian Peninsula. Considering the high level of

divergence detected at two mtDNA loci and microsatellite markers here, it is unlikely

that all shared alleles at microsatellite loci are identical by descent as a direct

consequence of dispersal. Instead, the occurrence of some identical sized alleles

probably results from homoplasy.

The high level of genetic variation detected in C. quadricarinatus using

microsatellites is consistent with microsatellite studies in other species, including

other freshwater crayfish. Five microsatellite markers used to assess the population

genetic structure of the European white-clawed crayfish (Austropotamobius pallipes)

revealed a mean heterozygosity value of 0.394 (Gouin et al. 2000; Gouin et al,

2002). Microsatellites also detected a high level of heterozygosity (ranging from 0.25

- 1.0) in the red swamp crayfish, Procambarus clarkii (Beliore and May, 2000).

Extensive polymorphism (heterozygosity up to 0.799) was also detected in Cherax

tenuimanus using two microsatellite loci (Imgrund et al., 1997).

A significant number of C. quadricarinatus populations deviated from expected

Hardy-Weinberg equilibrium (HWE). Samples sizes may not have been sufficiently

large to reflect a true representation of genotypic proportions present in the sampled

populations due to the highly variable nature of microsatellite loci. However,

deviations from HWE equilibrium can also result from null alleles, such that many

apparent homozygotes are, in reality, heterozygotes between a visible and a null

allele (Callen et al., 1993; Pemberton et al., 1995). Null alleles estimates (Table 4-4

and 4-3) indicate a large proportion of null alleles may be present in the C.

quadricarinatus populations analysed here. Null alleles may also explain ‘dropouts’ -

the inability to amplify some individuals at some loci even though PCR conditions

were re-optimised and the same DNA sample amplified at other loci inferring that

DNA quality was not the problem.

Non-amplifying alleles are thought to occur when mutations prevent primers from

binding (Callen et al, 1993), and have been observed in a wide variety of species

(white shrimp, (Ball et al., 2003); humans, Callen et al, 1993; bears, (Paetkau &


74

Strobeck, 1995). Null allele frequencies of up to 25% have been reported in the

literature (swallow Hirundo rustica; (Primmer et al., 1995)). Frequency estimates for

null alleles in C. quadricarinatus were extremely high, up to 71% in eastern

population and 51% in western populations. These frequencies are based on HW

expectations; if C. quadricarinatus populations are not at equilibrium (for any other

reason) then estimates will be biased. Wolfus et al. (1997) observed null alleles in

breeding trials of the Penaeid shrimp, P. vannamei. Offspring from homozygote

parents for their respective alleles were not all heterozygous for maternal and

paternal alleles. Many studies however do not have the advantage of pedigree

information to determine if null alleles are present in their datasets and this can

potentially lead to false assumptions about inferred population structure. A family

pedigree analysis of C. quadricarinatus is needed to confirm the existence and

extent of null alleles in these populations. This action will be particularly important

before the markers are considered for application in breeding programs for cultured

stocks.

Even if proportions of null alleles in C. quadricarinatus populations have been

overestimated, it is obvious from the data that populations are carrying mutations in

priming sites that influence the level of differentiation among populations. Null alleles

can bias statistics that assume HWE. While caution should be taken interpreting the

results as it could be argued that high proportions of null alleles could compromise

the integrity of the C. quadricarinatus microsatellite data. However, the levels and

patterns of genetic variation across C. quadricarinatus microsatellite loci is

essentially consistent and indicates populations of C. quadricarinatus from discrete

drainages are highly divergent. Also the results are consistent with other genetic

markers (nDMA, mtDNA). The high mutation rate at microsatellite loci, that makes

them attractive markers for population and pedigree studies in itself will produce null

alleles in divergent populations over evolutionary time.. With little or no gene flow,

there is no exchange of alleles among populations, and this can increase the levels

of null alleles in a population by allowing mutations in priming sites to accumulate.

Although FST and other statistical estimates may be over inflated, these

microsatellite data indicate C. quadricarinatus populations are highly divergent. This

high degree of divergence is in agreement with 16s and COI genes (Chapter 3),

which also revealed a high degree of divergence, where a western and an eastern

form of C. quadricarinatus were detected. The western form failed to amplify at two

C. quadricarinatus specific microsatellite loci. Although there is potential for null

alleles to overstate the degree of divergence among C. quadricarinatus populations,


75

there is a clear and consistent argument that populations are evolving

independently. These microsatellite data are also in accord with genetic divergence

detected among populations of other freshwater organisms. High levels of genetic

divergence are indicative of populations that are evolving independently like those of

freshwater organisms inhabiting dendritic rivers systems.

Genetic diversity among the sampled C. quadricarinatus populations may have been

underestimated due to the high levels of null alleles observed here. Flinders River

had the lowest genetic diversity estimate, which corresponds with a recent

bottleneck detected. In comparison with genetic diversity estimates for the European

freshwater crayfish A. pallipes (using RAPDs (Gouin et al., 2001)), sampled C.

quadricarinatus populations had four times the amount of genetic diversity. A.

pallipes is, however, endangered, due to overfishing, making it difficult to draw

comparisons with wild C. quadricarinatus populations. Diversity values can,

however, provide a baseline for future reference for managing and monitoring the

‘genetic health’ of wild C. quadricarinatus populations and/or when sourcing

broodstock for culture purposes.

High FST and genetic distance estimates observed among pair wise analyses of C.

quadricarinatus populations is consistent with limited or no gene flow occurring

among river drainages within regions. Speculation that C. quadricarinatus may

disperse between adjacent or nearby drainages at times of flood, either across

floodplains, or via flood plumes therefore seems highly unlikely in populations

examined here. A wide variety of freshwater taxa including fish (Waples, 1991;

Hughes, 1996; McGlashan & Hughes, 2002; Costello, 2003), insects (Hughes et al.,

1999), molluscs (Hughes et al., 2004) and crustaceans (Campbell et al., 1994;

Hughes, 1996; Daniels et al., 1999) also exhibit high levels of genetic subdivision

due to the isolating effects of independent riverine drainages. Although

metapopulation processes such as extinction and colonisation events can result in

elevated estimates of FST (Whitlock & McCauley, 1990), and lead to inaccurate

estimates of real gene flow rates, the extensive and consistently high levels of

differentiation observed here among drainages argue for a high degree of genetic

isolation of C. quadricarinatus populations present in discrete drainages.

Seasonal harsh climatic conditions experienced in ephemeral rivers across C.

quadricarinatus’ distribution could induce bottleneck events. Recent genetic

bottlenecks were detected in six eastern populations (Norman, Elizabeth, Chillagoe,

Weipa, Gregory and Flinders Rivers) and two western populations (Howard and


76

Roper Rivers) supporting the hypothesis that C. quadricarinatus populations have

been subjected to periodic population crashes in the recent past.

AMOVA results indicated that there are high levels of genetic diversity in the wild

populations of C. quadricarinatus studied here and that this diversity was higher

within rather than between populations. Results of AMOVA revealed significant

differences (p<0.01) in genetic variation within populations for both eastern and

western lineages. This coupled with high FST estimates suggest wild C.

quadricarinatus populations are evolving independently. It is difficult to assess the

individual effects of gene flow and drift on populations, especially when most natural

populations, including C. quadricarinatus are not at equilibrium (McCauley, 1993).

Both Mantel tests calculated in IBD and Hutchison and Templeton’s (1999) method

for evaluating relative historical influences of gene flow and drift showed no

significant correlation between geographical distance and genetic distance among

populations within eastern or western lineages. Thus C. quadricarinatus populations

apparently follow an island-like model where gene flow is independent of geographic

distance among populations and where genetic divergence occurs to a greater or

lesser extent as a result of genetic drift. The river systems that C. quadricarinatus

inhabit are generally large, with the confluence of branches near the mouth of the

drainage, essentially making branches within a drainage, discrete rivers. More

extensive sampling within drainages and along branches would be needed to test

for a Stream Hierarchy Model of genetic isolation, but it is likely that C.

quadricarinatus individuals disperse within a drainage rather than between discrete

drainages.

Both intrinsic and extrinsic factors appear to limit contemporary gene flow among C.

quadricarinatus populations inhabiting different drainages. Intrinsic characteristics of

C. quadricarinatus include life history traits and low dispersal capabilities. Due to

the recognition that C. quadricarinatus do not apparently migrate to mate, fully

formed larvae hatch on the mothers’ abdomen (in contrast to pelagic larvae that

disperse on water currents) and because they are intolerant to prolonged salinity, C.

quadricarinatus have low dispersal capabilities and hence wild populations are

structured. Extrinsic factors reinforce the low vagility of C. quadricarinatus’ life

history traits. With a rise in sea level to present day sea levels, land connections

between Australia and PNG were broken and the Gulf of Carpentaria formed. This

severed freshwater connections among rivers where C. quadricarinatus occurred,

leaving obligate freshwater inhabitants of the outer branches of extensive ancient


77

river systems to evolve in isolation. One potential consequence of the evolution of

discrete populations is the potential for inbreeding. The patterns observed here,

however, suggest that any deleterious effects of inbreeding are not significant under

natural conditions. Perhaps the effective size of most populations is sufficiently large

to minimise inbreeding, or populations may be able to tolerate raised inbreeding

levels if inbreeding accumulates at a slow rate.

A number of wild C. quadricarinatus populations are under threat from

anthropogenic practices such as impoundment, overfishing, and pollution from

agricultural run off (Yen & Butcher, 1997). With limited (if any) gene flow occurring

among sampled C. quadricarinatus populations, independent evolution C.

quadricarinatus in drainage catchments have important management repercussions

for conserving genetic diversity in situ. Since genetic diversity is partitioned among

drainages, if populations within a drainage go extinct, it is likely that they will only be

recolonised by individuals from within the same drainage. This is an important

consideration if restocking of wild populations was considered as a conservation

strategy. Drainages would need to be restocked with individuals from the same

drainage, to not only conserve and maintain genetic integrity of wild C.

quadricarinatus, but because independent evolution probably reflects local

adaptation within drainages. Admixture of genetic divergent individuals of the same

species can have detrimental consequences on the fitness of offspring and speed

up extinction rather than enhance populations that are being restocked (McGinnity

et al., 2004).

Chapter Five: Genetic diversity of cultured stocks

78

5.0 Genetic diversity in cultured C. quadricarinatus stocks compared with wild populations 5.1 Introduction Many studies that have investigated genetic diversity in hatchery fish stocks and

their wild relatives have reported that farmed stocks possess much lower levels

of genetic diversity when compared with that present in their wild progenitors

(Allendorf & Phelps, 1980; Cross & King, 1983; Garcia-Marin et al., 1991;

Coughlan et al., 1998). In small populations, like most that are brought into

culture, genetic drift will tend to reduce allelic diversity over time by

approximately ½ Ne per generation, where Ne is the effective population size

(Frankham, 1996). Effective population size is influenced by a number of factors

including, family size, sex ratio and changes in population size across

generations (Lande & Barrowclough, 1987). Small effective population sizes are

of particular concern when fecundity is high, as is the case for many aquatic

species, because a few breeding individuals are capable of producing large

numbers of offspring, only a small number of founders are usually brought into

captivity. This can accelerate the loss of genetic variation, if not managed

appropriately. Small effective population sizes can also lead to increased levels

of inbreeding, which may further erode genetic variation. Loss of genetic

diversity can limit, or even reduce the productivity of culture stocks, particularly if

subsequent breeding management strategies are not aimed at maintaining or

enhancing genetic diversity.

In culture, it is just as important to prevent production losses due to inbreeding,

as it is to actively promote productivity via genetic improvement practices.

Implementation of selective breeding will reduce levels of genetic variation in the

target stocks via two major processes. First, most domesticated terrestrial

species are highly selected for a few economically important traits (eg growth

rate), which decreases overall genetic diversity as a consequence of directional

selection. Secondly, most populations within particular breeds tend to be almost

genetically uniform as a result of high levels of inbreeding and artificial selection

favouring high-performing reproductive individuals. The high levels of artificial

selection and intensive use of elite broodstock have greatly reduced the

effective population size of many terrestrial domestic breeds. For example, the

USA Holstein cattle population of approximately 10 million individuals has an

effective population size smaller than 1000 individuals (Georges & Anderson,

1996). While productivity may remain high, future improvement in important


79

traits are likely to be small as levels of exploitable variation decline each

generation and is not supplemented from outside (eg. by periodically introducing

unrelated individuals). Unfortunately, in the past little attention has been paid to

the levels of genetic diversity in initial broodstock populations for most

aquaculture species and these issues are seldom considered until much later

when serious problems may already have developed (eg Oreochromis niloticus,

(Eknath et al., 1993); Cyprinus carpio (Hulata, 1995b); Paralichthys olivaceus

(Sekino et al., 2002))

Low levels of genetic variation in broodstocks can limit the potential for future

genetic gains from artificial selection. The extent to which genetic improvement

can be achieved for any single quantitative trait in a breeding program will

depend on the amount of genetic variation that exists for the desired trait/s

(Davis & Hetzel, 2000). Wild populations offer a range of genetic diversity

distributed both within and among populations as they will have been exposed to

the natural process of evolution. As a consequence of evolution, populations

become locally adapted to a wide range of environments and often show high

levels of phenotypic variability and high fitness in natural environments. Utilising

this genetic diversity in culture stocks effectively is the key to sustainable

aquaculture because it enables farmers to adapt stocks to suit their own

ecological needs and culture conditions. Without extensive genetic diversity in

the founding brood stock at the beginning however, options for long term

productivity of culture stocks in a variety of environments are likely to be

compromised.

5.1.1 Current status of C. quadricarinatus culture stocks

C. quadricarinatus has many attributes that make it well suited to aquaculture.

The species is physically robust, possesses a simple life cycle, requires basic

production technology, a simple diet and is economical to produce (Jones &

Curtis, 1994). In Australia, C. quadricarinatus are commonly marketed in 20g

size grades ranging from 30-50g (at approximately $11.50/kg) to greater than

120g (at approximately $19.00/kg) (AFFA, 2002). At present 60% of C.

quadricarinatus are sold within Queensland, 10% interstate and 30% are

exported. While current production in Australia is primarily marketed

domestically, the growth potential for the industry lies largely with an expanding

export demand for this species. Potential export markets for C. quadricarinatus

have been reported to be capable of absorbing as much as 2000 tonnes


80

p.a. (AFFA, 2002). Existing export markets are in Europe and South East Asia,

but additional market development activity has also focussed on Japan, Korea,

Taiwan and the USA (Piper, 2000). International sales to date, however, have

been limited by Australia’s small production volume and the consequent risk of

an inconsistent supply of product.

Culture methodologies are well developed for C. quadricarinatus and include

polyculture with finfish (Brummett & Alon, 1994; Karplus et al., 1995; Rouse &

Kahn, 1998), monosex grow out for improved growth (pers. comm. Rouse) and

a selective line with improved growth rate (Jones et al., 2000). Since culture

practices have essentially been optimised, the next step will be to improve the

productivity of culture breeds. In most new species brought into culture, founder

effects, genetic drift, intentional selection and inadvertent selection as a result of

culture practices are likely to have reduced background genetic diversity levels.

Currently little is known about the genetic diversity levels that exist in cultured C.

quadricarinatus stocks in Australia compared with that present in the wild. No

systematic approaches were adopted to capture broad genetic diversity when

initial culture stocks were sourced, suggesting that genetic variation is likely to

be low compared with natural genetic variation in wild populations. Furthermore,

the practice of new producers sourcing their stock from existing producers, thus

imposing sequential bottlenecks on culture stocks is likely to have eroded the

remaining genetic variation further in many culture stocks and lead theoretically

at least to high levels of inbreeding. Some circumstantial evidence from

overseas producers has suggested that this scenario may already have

eventuated in some places with reports of declines in stock productivity, early

onset of maturation and morphological abnormalities occurring in increasing

frequency (Hulata pers. comm.)

Many Queensland C. quadricarinatus farm stocks were derived from a single C.

quadricarinatus producer in south east Queensland. This stock was developed

originally from wild collections of individuals from several southern Gulf Rivers

(pers. comm. Hutchings). Understanding how the levels of genetic diversity in

culture stocks compare with those present in wild stocks will therefore provide

baseline information on which to base future choices about how productivity of

cultured stocks can be enhanced.

The current study used microsatellite markers to compare the levels and

patterns of genetic diversity in a number of Australian and overseas cultured C.


81

quadricarinatus stocks. Estimates of genetic diversity were also compared with

data from wild C. quadricarinatus populations in an attempt to determine how

much genetic variation has been exploited in culture stocks to date and how

much may remain to be exploited in the future.

5.2 Methods

5.2.1 Sampling of cultured stocks

Samples of culture stocks were taken from four local farms or Research

Agencies and three major producers outside Australia.

Yandina 1996 (sampled in 1996) – Yandina on the Sunshine coast, south east

Queensland. Ross Rickard, manager/owner of this stock, collected broodstock

personally from the wild. This stock was sourced directly from the wild to

maximise the genetic diversity in the founding stock, unlike most other

producers in Australia who have obtained cultured stock from established farms.

Yandina 2002 (sampled in 2002) – the Yandina stock was sampled 6 years later

to investigate temporal effects of culture on genetic diversity levels.

Parkridge (sampled in 1996) – situated south west of Brisbane in south east

Queensland. A relatively small hobby farm in a ‘rural’ suburb of Brisbane. A

second sample in 2002 was sought, but by this time the farm had ceased

operation. The origins of farm broodstock are unknown.

Walkamin (sampled in 2002) - Second generation of the Walkamin selected

strain from Queensland Department of Primary Industries (QDPI) at Walkamin.

In 1993, a strain evaluation of wild C. quadricarinatus populations from the

southern Gulf of Carpentaria was undertaken by QDPI. Later a selective

breeding programme was initiated that resulted in a significant improvement in

growth rate compared with existing culture stocks. Wild Flinders and Gilbert

River strains exhibited the best culture performance in comparative trials and

were chosen consequently for inclusion in the selective breeding experiment.

Approximately 500 crayfish (100 males and 400 females) representing

unselected stocks of a mixture of Flinders and Gilbert River strains were crossed

reciprocally to create a synthetic ‘Walkamin Strain’. The aim was to cross the

chosen lines of the Flinders and Gilbert strains, to minimise inbreeding and to

maximise any potential heterotic attributes. This study was initiated without any


82

knowledge of the relative levels of genetic diversity within or between the wild

stocks chosen for inclusion.

Hutchings (sampled in 2002) – Aratula, southeast Queensland. Robin

Hutchings was the first farmer to trial farming C. quadricarinatus commercially in

the mid 1980s, after a failed attempt to culture C. tenuimanus, a species that

proved intolerant of the extreme Queensland summer temperatures. The

Hutchings farm has supplied many of the farms in southeast Queensland with

broodstock after C. tenuimanus stocks failed and has also supplied live C.

quadricarinatus broodstock to many overseas producers. Hutchings collected

and crossed C. quadricarinatus from the southern Gulf of Carpentaria to

produce the stock that many SE Queensland farms use today (Hutchings pers

comm.). No reports were made, of the number, locality or sex of individuals that

comprised his original founding broodstock.

In addition to Australia, C. quadricarinatus are also farmed in the United States,

South Africa, Mexico, New Zealand, China, Israel and Ecuador (Rouse, 1995,

Karplus et al, 1995, Rubino, 1992; Macaranas et al, 1995). Tissue samples

were obtained from the following farms overseas:

Israel (samples obtained in 2002) – an unknown number of C. quadricarinatus

from Hutchings farm (Karplus, pers com) were introduced to Israel in 1993.

There have been reports of loss of stock productivity and physical abnormalities

in this culture stock that could reflect negative effects of inbreeding (Hulata, pers

com). The stock is kept essentially for research but there has been interest from

Israeli fish farmers in developing the species in culture there.

Ecuador (samples obtained in 2003) – Also sourced originally from Hutchings

farm, precise number and sex of broodstock could not be confirmed. Many large

farms are being developed in Ecuador to meet rising demand from the US

market.

Mexico (samples obtained in 2003) – C. quadricarinatus were imported into

Mexico in the early 90’s and are believed to have originated indirectly via

Switzerland (Garcia, pers com). C. quadricarinatus culture is still an expanding

industry in Mexico (Garcia, pers. com). Additional information about the likely

origins of the Mexican C. quadricarinatus could not be confirmed.


83

Producers in Europe could not be identified to supply tissue samples for genetic

analysis for this study.

5.2.1 Analysis of genetic diversity in cultured C. quadricarinatus stocks

5.2.1.1 DNA extraction and microsatellite analysis

DNA extraction and microsatellite amplification procedures were the same as

used for wild populations (see Chapter 4.2.2). All five microsatellite loci used to

assess genetic diversity in the wild eastern Australian populations amplified

culture populations successfully, indicating that the culture stocks examined

here had most likely been derived originally from wild ‘eastern’ populations (see

Table 5-1).

Table 5-1: Five C. quadricarinatus microsatellite loci were successfully used to determine the levels of genetic variability in C. quadricarinatus cultured stocks.

5.2.2 Statistical analyses

5.2.2.1 Molecular diversity of cultured stocks

Common indices of genetic variation including: mean number of alleles per

locus, number of effective alleles and mean heterozygosity (Ho and He) were

estimated for culture stocks for each microsatellite locus using GenAlEx (Peakall

and Smouse, 2001). Brookfield’s (1996) equation (as described in Chapter

4.2.6.3) was implemented to estimate null allele frequencies (r).

5.2.2.2 Linkage disequilibrium of cultured stocks

Linkage disequilibrium measures the statistical dependence of two loci. Tests

were performed using GENEPOP ver. 3.1 (Raymond and Rousset, 1995).

5.2.2.3 Hardy-Weinberg Equilibrium (HWE) of cultured stocks

HWE departures can be measured using Wright’s F-indices (Wright, 1965). FIS

and FIT measure such a departure within subpopulations and in the whole

populations, respectively. These indices were estimated according to Weir and

Cockerham (1984) and unbiased estimates of the exact P-values calculated

Locus Repeat TA (oC) MgCl2 mM Amplified

CQU.001 (GT)11~(GT)18 55 3 Yes CQU.002 (CA)27 50 2 Yes CQU.003 (CA)29 50 2 Yes CQU.004 (CA)32 50 3 Yes CQU.006 (CT)11 55 3 Yes


84

using a Markov chain randomisation method to determine if Hardy-Weinberg

expectations were met (Guo & Thompson, 1992). All results were adjusted for

multiple simultaneous comparisons using a sequential Bonferroni correction

(Rice 1989) implemented in GENEPOP ver. 3.1 (Raymond and Rousset 1995).

5.2.2.4 Testing for bottlenecks

To determine if C. quadricarinatus culture stocks had experienced a recent

bottleneck, a Wilcoxon’s sign-rank test was implemented and a qualitative

descriptor of allele frequency distributions (‘mode-shift’ Indicator) that can

discriminate bottlenecked populations from stable populations were conducted

using ‘BOTTLENECK’ (Piry et al, 1999).

5.2.2.5 Shannon-Weaver Index of genetic diversity

Loss of genetic diversity in domesticated stocks can impact negatively on the

long term productivity of culture stocks. The Shannon-Weaver Index (Shannon

and Weaver 1949) was calculated in GenAlEx (Peakall and Smouse, 2001).

5.2.2.6 Origins of culture stocks – assignment testing

Multi locus genotypes from individuals can be used to build up genetic profiles to

identify exclusive groups within a sample and to assign individuals to the group

from which it is most likely to have been derived. The power of assignment

testing using multiple independent microsatellite loci is positively correlated with

the degree of genetic structure present among groups in a sample (Maudet et

al., 2002). Assignment testing in this study was conducted using Cornuet et al’s

(1999) exclusion-simulation method to obtain likelihood probabilities for each

individual assignment as implemented in GENECLASS 1.0.02 (Cornuet et al.,

1999). Since each locus is assumed to be independent, the likelihood of an

individual’s multi locus genotype occurring in a given population is calculated as

the product of likelihood estimates measured at each of the separate loci.

Assignment probabilities by this method are however confounded by the

presence of alleles endemic to a single population and can be overcome by

artificially inserting a single representative of endemic alleles to all samples

where it is absent (“Add one in”) as recommended by Cornuet et al. (1999).

5.2.2.7 Comparison of culture stocks and wild populations

Differences in the mean number of alleles per locus, mean heterozygosity and

mean diversity index estimates were compared among wild C. quadricarinatus

populations, Australian and C. quadricarinatus culture stocks obtained from


85

overseas using a one-way analysis of variance in SPSS for Windows Version

11.5 (Lead Technologies).

5.3 Results

5.3.1 Molecular diversity of culture stocks

Common indices derived from five microsatellite loci in five Australian and three

overseas cultured C. quadricarinatus stocks are presented in Table 5-2. Mean

number of alleles per locus for all culture stocks ranged from 3 – 14, averaging

6.9 alleles/population. Australian C. quadricarinatus culture stocks contained an

average of 7.6 alleles/stock per locus, while overseas C. quadricarinatus culture

stocks contained only 5.4 alleles/stock. The effective number of alleles (Ne),

ranged from 1.4 – 6.8 and observed heterozygosity ranged from 0.219 – 1.00,

averaging 0.56. Heterozygosity is a measure of individual diversity. While

observed heterozygosity levels were relatively high, in most cases they were

less than the expected heterozygosity estimates based on observed allelic

diversity. Such deficiencies can indicate inbreeding, selection or presence of null

alleles, but since expected heterozygosity is based on populations at HW

equilibrium (and most C. quadricarinatus stocks did not conform to HWE), such

interpretations may not be appropriate here.

The majority of fixation values (F) were positive also suggesting inbreeding,

selection or undetected alleles; negative values indicate an excess of

heterozygosity, (Table 5-2). Since culture stocks have been derived from wild

populations where null alleles are likely (see Chapter 4), and exposed during

domestication to processes of selection and small effective population sizes,

random breeding was not expected. Null allele proportions of up to 45% (locus

CQU004; Yandina) were detected, presented as ‘r’ in Table 5-2. Brookfield’s

(1996) method for estimating null alleles assumes populations are in HW

equilibrium, since the artificial populations here probably violate HW

assumptions (ie no selection, and random mating), the number of null alleles

may be an overestimation. A pedigree study could directly measure the

proportion of null alleles if necessary.

5.3.2 Linkage Disequilibrium

Linkage disequilibrium was observed at only one pair of loci (Israel cqu002-

cqu006 p= 0.000) out of a possible 40 tests, a result expected by chance.


86

Table 5-2: Common indices for cultured C. quadricarinatus stocks; sample size (N), number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (HO), expected heterozygosity (HE), and Fixation Index (F) and Brookfield’s (1996) ‘r’ estimating the frequency of null alleles. Values in bold indicate upper values for each locus.

N Na Ne Ho HE F r CQU001 Yandina 1996 30 6 2.970 0.633 0.663 0.045 0.023 Yandina 2002 30 6 2.594 0.500 0.614 0.186 0.103 Parkridge 30 6 3.403 0.567 0.706 0.197 0.110 Walkamin 30 6 4.545 0.700 0.780 0.103 0.054 Hutchings 32 6 3.717 0.750 0.731 -0.026 -0.013 Israel 25 6 5.482 0.680 0.818 0.168 0.092 Ecuador 20 7 3.361 0.850 0.702 -0.210 -0.095 Mexico 39 6 2.878 0.385 0.653 0.411 0.258 CQU002 Yandina 1996 29 7 2.010 0.310 0.502 0.382 0.236 Yandina 2002 28 5 3.638 0.500 0.725 0.310 0.184 Parkridge 30 5 2.651 0.533 0.623 0.144 0.077 Walkamin 30 7 4.206 0.633 0.762 0.169 0.092 Hutchings 32 3 1.373 0.219 0.271 0.194 0.108 Israel 25 5 2.809 0.520 0.644 0.193 0.107 Ecuador 20 3 1.766 0.300 0.434 0.308 0.182 Mexico 40 2 1.694 0.425 0.410 -0.037 -0.018 CQU003 Yandina 1996 30 14 3.766 1.000 0.734 -0.362 -0.153 Yandina 2002 30 14 5.158 0.867 0.806 -0.075 -0.036 Parkridge 30 3 1.869 0.533 0.465 -0.147 -0.068 Walkamin 30 10 4.762 0.733 0.790 0.072 0.037 Hutchings 32 3 1.474 0.313 0.322 0.029 0.015 Israel 25 5 2.306 0.440 0.566 0.223 0.126 Ecuador 20 3 1.956 0.450 0.489 0.079 0.041 Mexico 40 4 2.341 0.550 0.573 0.040 0.020 CQU004 Yandina 1996 30 7 5.114 0.300 0.804 0.627 0.457 Yandina 2002 30 7 4.592 0.600 0.782 0.233 0.132 Parkridge 30 7 5.921 0.333 0.831 0.599 0.427 Walkamin 29 4 3.609 0.276 0.723 0.618 0.448 Hutchings 32 9 6.225 0.656 0.839 0.218 0.122 Israel 23 7 4.898 0.348 0.796 0.563 0.392 Ecuador 20 9 5.369 0.650 0.814 0.201 0.112 Mexico 40 8 3.628 0.400 0.724 0.448 0.288 CQU006 Yandina 1996 30 12 6.498 0.700 0.846 0.173 0.095 Yandina 2002 30 13 6.844 0.700 0.854 0.180 0.099 Parkridge 30 6 3.523 0.533 0.716 0.255 0.146 Walkamin 30 14 5.921 0.767 0.831 0.078 0.040 Hutchings 32 9 5.520 0.469 0.819 0.428 0.272 Israel 23 8 5.658 0.652 0.823 0.208 0.116 Ecuador 20 6 4.255 0.750 0.765 0.020 0.010 Mexico 39 9 4.899 0.821 0.796 -0.031 -0.015


87

5.3.3 Hardy Weinberg Equilibrium

Deviations for Hardy-Weinberg equilibrium were observed in seventeen out of

forty comparisons (42%), (Table 5-3). Significant deficiencies of heterozygotes

were observed in the sampled culture stocks. While null alleles are probably the

likely explanation in wild C. quadricarinatus populations, cultured stocks are

likely to also be influenced by artificial admixture, intentional or unintentional

selection, inbreeding, or a combination of all of these factors to some extent.

Table 5-3: Results of Hardy-Weinberg equilibrium exact tests given as p-values (significance indicated by * after Bonferroni adjustment p= 0.01)

Yandina

1996 Yandina

2002 Parkridge Walkamin Hutchings Israel Ecuador Mexico CQU001 0.5076 0.3581 0.0163 0.3737 0.0182 0.0000* 0.1483 0.0000* CQU002 0.0000* 0.0000* 0.0089* 0.0032* 0.1497 0.0207 0.2414 1.0000 CQU003 0.0467 0.6631 1.0000 0.0022* 0.2022 0.0214 0.5176 0.0579 CQU004 0.0000* 0.0466 0.0000* 0.0000* 0.0000* 0.0000* 0.0364 0.0000* CQU006 0.0592 0.0000* 0.0000* 0.1840 0.0000* 0.0000* 0.6617 0.0169

5.3.4 Genetic distance among cultured stocks

Cavalli-Sforza and Edwards’ (1967) Chord distance (DCE) estimates are

presented in Table 5-4. The Walkamin stock displayed was most divergent

(0.067) from both the Parkridge and Hutching stocks. Overseas stocks (in

Italics), Israel, Ecuador and Mexico show little genetic divergence from each

other and were most similar to the Hutchings stock (0.042, 0.013, 0.017

respectively), adding weight to the preconception that they had been derived

from the Hutchings stock.

Table 5-4: Genetic distance measures of C. quadricarinatus culture stocks using Chord distance algorithm. Values in bold indicate the largest values.

Yandina

1996 Yandina

2002 Parkridge Walkamin Hutching Israel Ecuador Mexico Yandina 96 0.000 Yandina 02 0.030 0.000 Parkridge 0.034 0.032 0.000 Walkamin 0.051 0.043 0.067 0.000 Hutching 0.040 0.057 0.047 0.067 0.000 Israel 0.035 0.048 0.040 0.064 0.042 0.000 Ecuador 0.040 0.050 0.042 0.065 0.013 0.042 0.000 Mexico 0.038 0.048 0.047 0.058 0.017 0.036 0.010 0.000


88

5.3.5 Testing for genetic bottlenecks

Significant heterozygosity was detected Parkridge (p=0.015), Israel (p=0.015),

Ecuador (p=0.015) and Mexico (p=0.015) cultured stocks, see Table 5-5. A

significant distortion of allele frequency distribution further supports a recent

bottleneck occurred in the Parkridge stock (Table 5-5).


Wilcoxon’s test p valuemode-shift indicating a

bottleneck# Yandina 96 0.687 no Yandina 02 0.078 no Parkridge 0.015* yes Walkamin 0.031* no Hutchings 0.078 no Israel 0.015* no Ecuador 0.015* no Mexico 0.015* no

5.3.6 Genetic diversity estimates: Shannon’s Index

Shannon's Information index (Peakall and Smouse, 2001) calculated for C.

quadricarinatus culture stocks are presented in Table 5-6. Shannon’s index is a

numerical value that estimates genetic diversity; higher values represent higher

genetic diversity. The Yandina, Yandina 2002 and Walkamin stocks possess the

highest diversity, while Parkridge, Hutchings, and the overseas stocks contain

reduced amounts of genetic diversity. Diversity in the Yandina stock apparently

increased over time, but the increase was not statistically significant and so may

be a sampling issue. Walkamin, the intentionally hybridised and selected strain

and the Yandina stocks, where management strategies were employed to

actively maintain or increase allelic diversity (via wild collections), contained the

highest amount of allelic richness at all loci screened expect for locus CQU004.


89

Table 5-6: Shannon Index (Shannon and Weaver 1949) of genetic diversity of cultured populations for 5 microsatellite loci and their mean. Values in bold are highest mean values

CQU001 CQU002 CQU003 CQU004 CQU006 Mean St. DevYandina 1996 1.346 1.116 1.836 1.723 2.141 1.6324 ±0.405 Yandina 2002 1.134 1.436 2.092 1.694 2.188 1.7088 ±0.442 Parkridge 1.413 1.243 0.819 1.857 1.437 1.3538 ±0.374 Walkamin 1.602 1.605 1.882 1.332 2.123 1.7088 ±0.302 Hutchings 1.479 0.512 0.61 1.997 1.866 1.2928 ±0.695 Israel 1.744 1.203 1.017 1.705 1.862 1.5062 ±0.372 Ecuador 1.436 0.697 0.847 1.847 1.594 1.2842 ±0.492 Mexico 1.345 0.600 1.049 1.567 1.763 1.2648 ±0.465

5.3.7 Comparing genetic diversity between Australian and overseas culture stocks

ANOVAs were performed to test for differences in mean number of alleles,

observed heterozygosity and Shannon’s Indices of diversity among Australian

and overseas culture stocks. 5.3.7.1 Number of alleles per locus

No significant difference in the number of alleles was observed when comparing

Australian wild populations to overseas C. quadricarinatus culture stocks

(p=0.335; F=1.108).

5.3.7.2 Levels of heterozygosity

A one-way ANOVA to compare levels of heterozygosity among wild C.

quadricarinatus populations and farmed C. quadricarinatus stocks showed no

significant difference, although culture stocks generally exhibited higher levels of

heterozygosity (p=0.538; F=0.624).

5.3.7.3 Shannon Index estimates

No significant difference in diversity indices was observed between Australian

wild and overseas C. quadricarinatus culture stocks (p=0.517; F=0.665).

5.3.8 Assignment of C. quadricarinatus stocks to wild populations sampled

Assignment tests were performed to determine if wild population origins of

cultured stocks could be assigned to discrete wild populations. Results are

presented in Table 5-7.


90

Table 5-7: Proportion of C. quadricarinatus culture individuals assigned a river drainage based on 5 microsatellite loci performed in GENECLASS. (NB: the largest proportion for each farmed stocks is indicated in bold and only estimates larger than 5% are shown)

Yandina Yandina 02 Parkridge Walkamin Hutchings Israel Ecuador MexicoFlinders 0.80 0.63 0.93 0.33 0.94 0.84 0.65 0.88 Norman 0.12 0.05 Gilbert 0.06 0.37 0.50 0.08 0.05 0.05 Mitchell 0.17 Weipa Calvert McArthur 0.08 0.25 0.08


91

5.4 Discussion The growing economic potential of C. quadricarinatus culture, both domestically and

internationally, prompted the current study into relative levels of genetic diversity in

commercial C. quadricarinatus stocks. The study employed five microsatellite

markers to quantify genetic diversity in five Australian and three overseas C.

quadricarinatus culture stocks. Genetic diversity levels were then compared with

those documented for wild populations presented earlier (Chapter 4).

Microsatellite analysis showed that C. quadricarinatus stocks are not at Hardy-

Weinberg equilibrium. Many wild populations analysed in Chapter 4 also deviated

from Hardy-Weinberg equilibrium, however, the impact of domestication can

compound this situation. C. quadricarinatus culture stocks have most probably been

exposed to repeated small effective population sizes, and may have experienced

intentional and/or unintentional selection during domestication, Deviations from HW

equilibrium have been reported in other culture species, including farmed abalone in

Australia, Haliotis rubra and South Africa, H. midae (Evans et al., 2004). This result

suggests that many standard population genetic parameters which assume HWE

may be inappropriate statistics for assessing domesticated stocks. So a comparative

approach could be more informative. One of the major concerns during domestication is loss of genetic diversity because

the small number of individuals commonly brought into culture is unlikely to carry a

true representation of the genetic diversity present in ancestral population/s. Loss of

genetic diversity can induce kinship among breeders and result in inbreeding.

Inbreeding, characterised by an excess of homozygotes, can have negative (ie

costly) impacts on culture stocks including loss of productivity (Gjedrem, 1997;

Doyle et al., 2001; Sugaya, 2002). In contrast, the average level of observed

heterozygosity observed for C. quadricarinatus cultured stocks was not significantly

lower in cultured C. quadricarinatus stocks than for the wild populations. If anything,

culture stocks possess slightly higher average heterozygosity levels (culture stocks

ranged from 0.22 – 1.00; average: 0.56, than wild populations (ranged from 0.00 -

0.944; average: 0.523). This slight increase may be a consequence of the

domestication process where culture stocks when wild individuals from different

drainages were introgressed. Intentional mixing of wild germplasm is a common

practice during the domestication process, as heterosis or an increase in genetic

diversity may result. However, for C. quadricarinatus this practcie should be

undertaken with caution due to the presence of two morphologically similar yet

genetically divergent lineages in northern Australia.


92

Fortunately, wild populations from discrete drainage systems that belong to the

same genetic lineage were hybridised to generate the commercial C.

quadricarinatus stock in Queensland. Recently however efforts have been made to

domesticate wild C. quadricarinatus stocks in the Northern Territory where ‘western’

C. quadricarinatus occur. This increases the potential for contamination of unique

gene pools in the future where ‘eastern’ and ‘western‘ forms could be mixed in

culture or more seriously, individuals of the alternative morph escape into wild

populations after translocation. If this occurred, given the extent of genetic

differentiation between ‘eastern’ and ‘western’ C. quadricarinatus there is potential

for outbreeding depression. A recent example of such an outcome occurred in the

catfish culture industry in Thailand. Breeders had determined that hybrids developed

by artificially crossing males of an alien species, the African catfish (Clarias

gariepinus), with females of a native species, the Thai walking catfish (C.

macrocephalus) grew much faster and possessed high disease resistance in culture

than did individuals of either of the pure species (Senanan et al., 2004), so

enhancing productivity in culture. Although farmed hybrid catfish dominate the

domestic catfish markets in Asia, the native walking catfish (C. macrocephalus) also

remains important in this industry because it provides the broodstock for the females

used to generate hybrid catfish. Recently, concerns have been raised that escapee

hybrid catfish from fish farms could threaten wild populations of Thai walking catfish

due to competition, predation, and genetic introgression due to interbreeding

(Senanan, 2004). It is feared that some escaped hybrids have backcrossed with

native catfish and fish that look like a native catfish may be, in reality, introgressed

individuals bearing genetic material from the introduced African species. This

process of introgressive hybridisation may ultimately cause the loss of genetic

distinctiveness of the native C. macrocephalus, putting wild stocks at risk of

extinction and could result in the use of unrecognized introgressed individuals as

aquaculture broodstock. By inadvertently crossing an introgressed individual of C.

macrocephalus with pure C. gariepinus, fish farmers would be diluting the genetic

contributions of C. macrocephalus, and therefore, could lose desirable traits in the

hybrids. This example may serve as an important warning for mixing ‘eastern’ and

‘western’ lineages of C. quadricarinatus in the future.

Hedgecock and Sly (1990) believe measures for assessing relative genetic diversity,

particularly percent heterozygosity, are insensitive to substantial genetic changes

that may occur in cultivated aquatic stocks. Vuorinen (1984) states that total

extinction of any allele should be considered more harmful than a simple reduction


93

in overall heterozygosity. Loss of unique alleles is probably a more meaningful

measure of how well genetic variation is being maintained in a hatchery/cultured

stock than is changes in heterozygosity levels. Probability predicts that rare or low

frequency alleles are usually first to be lost as genetic diversity declines in a

population. It is crucial to recognise that once started, this process affects all

polymorphic loci in the same way, both coding and non-coding sequences.

Only a small reduction in the mean number of alleles per population/stock was

observed when cultured stocks (6.9 alleles/stock) and wild populations (7.2

alleles/population in ‘eastern’ (5 loci); 7.8 alleles/population in ‘western’ (3 loci))

were compared. It is often expected that domestication erodes genetic diversity, as

seen in a number of cultured species, Atlantic salmon - Salmo salar (Cross & King,

1983) marine prawns - Penaeus japonicus (Sbordoni et al., 1986) and oysters -

Crassostrea gigas (Hedgecock and Sly, 1990). However, other studies have

revealed no significant differences in genetic diversity between wild and hatchery

populations such as for turbot, Scophthalmus maximus (Bouza et al., 1997;

Coughlan et al., 1998). While no statistically significant difference was seen in the

mean number of alleles between wild and cultured C. quadricarinatus stocks, a

slight reduction was apparent in culture, especially if wild stocks were compared

directly to just overseas culture stocks.

Cultured C. quadricarinatus stocks are likely to have experienced population crash

inducing genetic bottlenecks, when a small number of founders were first brought

into captivity. Evidence of recent bottlenecks were observed in the Parkridge and

Walkamin stocks. However, the intentional hybridisation of two wild river populations

to create the Walkamin strain probably accounts for the significant heterozygote

excess in this stock. The bottleneck in the Parkridge stock was detected in both

bottleneck tests and is probably true as it is thought that this population was derived

from the Yandina stock. All three overseas culture stocks indicate recent

bottlenecks, again these are populations derived from an existing stock (the

Hutchings stock). This is suggesting there is an increased risk of the detrimental

effects of small effective population sizes (eg. reduced genetic variation) as new

stocks are obtained from existing ones.

Genetic differentiation estimates among culture stocks and assignment tests (Table

5-4) indicate that overseas culture stocks have been most likely derived from the

Hutchings stock – a known supplier of live C. quadricarinatus to overseas


94

producers. The Parkridge stock is closely related to the Yandina stock (1996)

suggesting Yandina might be the source of the Parkridge stock.

Assignment results indicate that all C. quadricarinatus culture stocks possess alleles

that have originated from the Flinders River (proportions of 33-94%). Alleles

consistent with those from the Gilbert River drainage are also present in significant

proportions in the Yandina 1996 (37%) and Walkamin (50%) culture stocks.

Assignment testing suggested all culture stocks were derived from more than a

single wild population. However note that this test can only conclude the most likely

origin from the set of wild populations sampled, and without extensive sampling

exact origins cannot be confirmed.

In conclusion, domestication of C. quadricarinatus to date has not apparently

resulted in significant reductions in exploitable genetic diversity (heterozygosity or

alleles richness) when compared to the wild populations sampled in this study.

Since wild populations are essentially evolving independently, and are subjected to

harsh seasonal environmental fluctuations, with little or no gene flow, they are also

probably exposed to repeated small effective populations sizes and possible

periodical inbreeding effects. Comparing culture stocks to wild population to gauge

‘genetic health’ may not be a suitable measurement scale for evaluating genetic

diversity in culture stocks. This study does however indicate a large amount of

genetic diversity that has yet to be exploited is distributed among wild populations.

This diversity provides a resource for future stock improvement programs for C.

quadricarinatus culture.

Chapter Six: General Discussion

95

6.0 General Discussion Over exploitation by humans of many wild aquatic resources has resulted in

declines in catches or reduced catch quotas, placing increased pressure on farmed

aquatic resources to meet the demand for seafood (Pauley and Christensen, 1995).

Australia is in a unique position to develop aquaculture as a first rate primary

industry because our environments are relatively unpolluted, policies are in place to

reduce the risk of disease and Australia possesses a suite of native species suitable

for culture that can be marketed domestically and internationally. A major constraint

on aquaculture to meet increasing demand for seafood is the relatively low

productivity of many current aquaculture stocks. Most production is carried out

using stocks recently captured from natural environments. Even though aquatic

species have greater potential for genetic improvement than most terrestrial species

(see Hulata, 2001), aquaculture stocks (mainly from the northern hemisphere) have

only recently begun to benefit from genetic improvement programs (Gjedrem, 2000;

Fjalestad et al., 2003b).

Harnessing wild variants in stock improvement programs can improve efficiency and

make culture stocks more productive and economically viable to ensure the

increasing demand for seafood can be met. Understanding the levels and patterns

of genetic diversity in wild stocks can assist in developing sustainable aquaculture

industries because wild stocks can be an important resource for improving culture

stocks. Currently, such data are either very limited or totally absent for most native

Australian cultured species and has only been investigated in the major culture

species overseas (salmon, carp, some marine prawns etc). This is usually only

investigated out of necessity, for example when performance of culture stocks has

declined (eg. O. niloticus; Eknath,1993). The current study investigated the levels

and patterns of genetic diversity in wild Australian C. quadricarinatus populations

and in culture stocks in Australia and overseas.

Previous systematic studies of C. quadricarinatus have been conflicting. Reik (1969)

investigated morphological differences among wild C. quadricarinatus populations in

Australia and recognised two discrete taxa. Later Austin (1996) used allozyme

electrophoresis to contradict this and conclude C. quadricarinatus in Australia

consisted of a single gene pool. These opposing conclusions have important

ramifications for fisheries and aquaculture policy and management of wild

populations.


96

Molecular markers (mtDNA and microsatellites) examined in the current study

support Reik’s (1969) recognition of the existence of two divergent C.

quadricarinatus gene pools in northern Australia. Analysis of two mtDNA gene

portions (16s and COI) revealed two divergent lineages in northern Australia, that

last shared a common ancestor during the Tertiary (approximately 2.8 – 7.5 million

years ago). The two discrete genealogical lineages in Australia correspond

geographically to a ‘western’ lineage (from the Ord river in WA to the Roper River in

the Northern Territory) and an ‘eastern’ lineage (from the McArthur River in NT to tip

of Cape York in northern QLD). While arguing species/subspecies status was not

the purpose of this study, the results show conclusively that C. quadricarinatus

lineages in Australia are not a single homogenous gene pool and this finding

warrants a reassessment by of C. quadricarinatus systematics. At the very least, the

level of mtDNA divergence observed means that C. quadricarinatus lineages should

be considered as evolutionary significant units (Moritz, 1994).

This study also examined whether contemporary gene flow is ongoing among wild

C. quadricarinatus populations. Genetic parameters estimated from microsatellite

data indicated little if any ongoing gene flow occurs among discrete river drainages

so populations in discrete drainages are evolving independently. The microsatellite

data, in contrast to previous allozyme studies, suggests that genetic diversity is

generally high in wild populations and most diversity is higher within than between

populations.

6.1 Significance for wild populations Genetic analysis of wild C. quadricarinatus populations within the eastern and

western lineages indicate that populations, from major drainage basins, best fit an

island model of population structure i.e. discrete populations with very limited

interchange. This means that management of wild stocks should be based at a

drainage basin level i.e. self-recruiting drainages rather than a broader

metapopulation structure. The management importance of recognising an island

population structure is that if over-harvesting in one drainage occurs, populations

are unlikely to be replenished naturally by recruitment from adjacent drainages in a

meaningful time period, if at all.

Restocking to maintain populations densities of desired species (a common practice

for replenishing depleted recreational fishing species) would therefore need to use

C. quadricarinatus derived from local drainages as opposed to restocking with C.

quadricarinatus sourced from other drainages from within the respective lineage.


97

Any restocking attempts for C. quadricarinatus need to be carefully considered as

outbreeding depression may result when C. quadricarinatus from different drainage

basins are mixed. Although not currently practiced for C. quadricarinatus, re-

stocking wild C. quadricarinatus populations may soon be necessary. Experimental

crosses of even and odd year pink salmon from the same river, demonstrated the

potential negative consequences of restocking, if restocking occurs without a full

understanding of possible genetic incompatibility between the indigenous and

restocked individuals (Gharrett et al, 1999). Gharrett et al. (1999) reported fewer F2

hybrids from even year and odd year broodstock pink salmon (Oncorhynchus

gorbuscha) crosses (two lines that are temporally isolated by Pacific salmon’s strict

two-year life cycle) survived than F2 controls, suggesting a reduction in fitness or

outbreeding depression.

Limited experimental breeding trials between ‘western’ and ‘eastern’ C.

quadricarinatus stocks resulted in either no offspring or offspring that exhibited

reduced fitness (Ogden 2000). Therefore, the long term impact of translocating C.

quadricarinatus river strains and releasing them to the wild to restock depleted wild

populations, could result in irreversible declines in fitness of some wild C.

quadricarinatus populations or even local extinctions of indigenous wild populations.

It is highly recommended therefore, that C. quadricarinatus are only restocked with

indigenous river strains.

6.2 Significance for aquaculture/fisheries policy 6.2.1 Aquaculture

Commercial C. quadricarinatus culture stocks are currently a genetic mix of a few

individuals from river drainages (with the major contributor the Flinders River). Most

have been exposed to some form of selection (intentional or unintentional) and

therefore should not be allowed to interbreed with wild C. quadricarinatus. To avoid

escapees from farms interbreeding with wild C. quadricarinatus, genetic risk

assessments should be carried out on existing and new farms. A genetic risk

assessment is the process of identifying and describing vulnerability to extinction,

loss of genetic diversity within wild populations, loss of genetic diversity among

populations and loss of fitness of wild populations from artificial propagation or other

human intervention (Shaklee et al., 1999; Mace, 2001). The greatest potential

genetic threat to wild C. quadricarinatus, would appear to be the potential for

interbreeding of eastern and western lineages. Therefore, each culture strain should


98

not be farmed outside its ‘natural’ distribution to limit potential for introgression of

discrete genetic lineages if cultured individuals escape.

6.2.2 Fisheries

Accidental genetic pollution of wild genetic resources can also occur during

transportation of individuals for culture or recreational fishing. Policies currently in

place for using live bait in freshwater systems demand that bait should be caught

locally, with no translocations among rivers. Translocation of C. quadricarinatus into

private water bodies should also adhere to the ‘local’ policy so that floods etc don’t

allow foreign C. quadricarinatus access to the wild.

6.3 Recommendations for C. quadricarinatus culture industry To conserve natural wild stocks, it is recommended that at least two centralised

hatcheries be set up, one for western and one for eastern commercial C.

quadricarinatus stocks. These hatcheries could monitor and maintain genetic

diversity in their broodstocks, conserve economically important strains and initiate

breeding programs independently. This will reduce the need for private hatcheries to

collect wild germplasm for broodstock and limit potential for accidental introgression

of the two discrete C. quadricarinatus lineages.

Each hatchery would evaluate wild C. quadricarinatus populations for desired

economic or indirect economic traits that may allow for the development of culture

strains best suited to different culture environments (eg. cold tolerance). Conserving

as much genetic diversity as possible essentially is an insurance against future

directions not yet known, such as changing market requirements. Currently the main

markets for C. quadricarinatus are within Australia and SE Asia, but European

markets are large and have different market requirements (eg preference for large

head for Europe rather than the large tail for Australia/ SE Asia) (pers. comm.

Hutchings).

Hatcheries could evaluate crosses between various wild C. quadricarinatus

populations for potential heterosis, ideally mono-sex (all-male or all-female) or sterile

offspring. For example, hybrids between female Cherax rotundus, and male Cherax

albidus produced all male progeny. This is a highly desirable result as it offers

considerable potential for eliminating the growth suppressing uncontrolled

reproduction that can occur in commercial ponds prior to harvest. Experiments

concluded that all-male hybrid progeny were almost twice as large (50±2.2g) as

mixed sex C. albidus crayfish (27.2 ±1.7g) (Lawrence et al., 2000) at the same age.


99

In parallel, hatcheries could develop a synthetic C. quadricarinatus culture stock as

the precursor for future stock improvement programs. An important prerequisite for

achieving genetic improvement in breeding studies is that the starting population

has high levels of genetic variation for the traits of interest. An example of a

comprehensive genetic improvement program was conducted for tilapia (O.

niloticus) in the Philippines. The Genetically Improved Farmed Tilapia (GIFT) Project

of ICLARM (now Worldfish Centre) was started in 1988, and intentionally collected

from throughout O. niloticus’ natural range in Africa, to create the starting population

for the selection program (Bentsen et al., 1998). In each generation (excluding the

first) strong selection for growth rate was implemented. The selection response in

growth rate during five generations averaged 13.2% per generation (Eknath et al.,

1993; Bentsen et al., 1998). This level of genetic gain has been repeated for several

fish species (see review by,Hulata, 2001). The GIFT program demonstrated that

strategic exploitation of natural genetic diversity in wild stocks can be a very

effective way of improving culture performance of aquatic species and a similar

approach should be applicable to C. quadricarinatus as high levels of genetic

variation in the wild have been detected here.

6.4 Future research 1) Research into potential heterosis or outbreeding depression among crosses of

eastern and western C. quadricarinatus should be pursued providing the studies are

undertaken in strict quarantine facilities. Correlating level of genetic distance to

potential for hybrid vigour or outbreeding depression will aid future genetic

improvement programs for culture stocks (i.e. aid in choice of compatible wild strains

for combining in breeding programs).

2) A diagnostic test for quantifying introgression of eastern and western genes in

should be evaluated. The current study suggests that a combination of mtDNA and

microsatellite markers could be used for this purpose. The ability to assess

introgression of unwanted genes” in the wild would be of benefit for monitoring and

conservation management of wild populations in the future.

3) The relative level of inbreeding in C. quadricarinatus culture stocks should also be

investigated. An important question, when trying to observe a biologically

meaningful difference in diversity levels, is to determine the degree of inbreeding C.

quadricarinatus can tolerate, as this can vary among species (Frankham, 1995). It

has been suggested that to avoid dramatic inbreeding depression effects, the


100

observed average rate of loss of heterozygosity should not exceed 1% per

generation, which is considered an acceptable level of inbreeding (Franklin, 1980).

Allelic diversity instead of heterozygosity could be used as the test indicator for

monitoring broodstock and ensuring sufficient sample sizes to maintain diversity

levels. However, one important issue to consider first is defining a biologically

meaningful difference in diversity level, as the degree of inbreeding a species can

tolerate varies widely (Frankham, 1995). A species such as C. quadricarinatus,

considering its life history, may be biologically capable of tolerating relatively high

levels of inbreeding as natural populations crashes across evolutionary time frames

in harsh environments, probably mean that local populations have been exposed

naturally to high levels of inbreeding. Acceptable threshold levels for representative

genome sampling could be set. The criteria could determine the proportion of

neutral allelic diversity that should be included in new culture broodstocks. Different

criteria could be set for short term or long term breeding programs and for either

conservation or production purposes.

Chapter Seven: Conclusion

101

7.0 Conclusions Sequence analysis of C. quadricarinatus 16s and COI genes resolved two distinct

genealogical lineages in Australia and three in PNG. The two lineages in Australia,

western and eastern, are in agreement with the original taxonomic description of

Reik (1969), who based taxonomy on external morphological characters. The three

C. quadricarinatus populations sampled in PNG were all genetically distinct from

each other, with one also showing a close genetic relationship with the eastern

Australia lineage. Physical barriers in the form of extensive mountain ranges in PNG

will have reduced dispersal capabilities for C. quadricarinatus allowing genetic

differences to accumulate there over time. The close genetic relationship between

PNG and Australian C. quadricarinatus support a recent freshwater connection

between northern Australia and PNG. During times of lowered sea level, Australia

and southern PNG were linked as a single landmass with terrestrial and freshwater

organisms theoretically were able to disperse over land and via freshwater

connections among the two regions.

Genetic parameters estimated from microsatellite data indicated that there are high

levels of genetic diversity in wild of C. quadricarinatus populations and that this

diversity is higher within than between populations, indicating limited or no gene

flow. Speculation that C. quadricarinatus may disperse between adjacent or nearby

drainages at times of flood, either across floodplains, or via flood plumes seems

highly unlikely given the high genetic differentiation among C. quadricarinatus

populations. No significant correlation was formed between geographic distance and

genetic distance among wild C. quadricarinatus populations. C. quadricarinatus

populations sampled most closely resemble an island-like model, where gene flow is

independent of geographic distance among populations and where genetic

divergence occurs to a greater or lesser extent as a result of genetic drift.

Domestication of C. quadricarinatus to date would appear not to have resulted in

significant reductions in levels of genetic diversity (heterozygosity or alleles

richness) when compared to wild populations sampled in this study. However,

comparing culture stocks to wild populations to gauge their ‘genetic health’ may not

be a suitable measuring scale for evaluating genetic diversity in culture stocks. Wild

populations are essentially evolving independently, and are subjected to harsh

seasonal environmental fluctuations, with little or no gene flow. They are also

probably exposed to small effective population sizes and potentially to periodic

inbreeding as a consequence. The current study does however indicate that there is

Chapter Seven: Conclusion

102

a large amount of genetic diversity distributed among wild populations that has yet

to be exploited in culture. Genetic diversity in wild populations provides a resource

for future stock improvement programs for C. quadricarinatus culture and should be

conserved and managed accordingly. This resource provides Australian producers

with a competitive advantage over the international counterparts, because their

access to wild stocks is limited.

Farming genetically improved C. quadricarinatus stocks (instead of essentially wild

stocks) would mean an increased economic return for a similar outlay for farmers

and potentially provide the Australian C. quadricarinatus industry a chance to better

complete with the cheaper labour and production costs of C. quadricarinatus

industries in developing countries. This competitive advantage relies on access to

wild gene pools as a resource for future stock improvement programs. Wild C.

quadricarinatus populations are a resource the Australian C. quadricarinatus

industry can utilise for a long term improved and sustainable economic return.

Understanding how historical processes have shaped contemporary genetic

structure in the wild allows for better management strategies to conserve the

maximum amount of natural genetic diversity. An economically lucrative C.

quadricarinatus industry should, therefore, ensure the conservation of wild C.

quadricarinatus populations, as wild populations can serve as an important resource

for a culture industry to develop and expand with changing market demands.

103

8.0 Appendix 1 9 no issue no. 2000 865 primer note primer note 1 4 Graphicraft Limited, Hong Kong

Characterization of microsatellite loci in the redclaw crayfish, Cherax quadricarinatus N. BAKER,* K. BYRNE,† S. MOORE† and P. MATHER* *School of Natural Resource Sciences, Queensland University of Technology, Brisbane 4001 Australia, †Tropical Agriculture, CSIRO, University of Queensland, Brisbane 4067 Australia Keywords: aquaculture, Cherax quadricarinatus, cross-species amplification, freshwater crayfish, microsatellites, primers Received 23 September 1999; revision accepted 20 October 1999 Correspondence: P. Mather. Fax: +61-73864-1535; E-mail: [email protected] Redclaw (Cherax quadricarinatus) is a tropical freshwater crayfish native to northern Australia and southern Papua New Guinea. Commercial culture of redclaw began in the early 1980s from an initial small collection of wild crayfish from north Queensland. Today, redclaw are cultured in many countries throughout the world, including the USA, Central America, South Africa, New Zealand, China, Israel and Ecuador (Medley et al. 1994). Knowledge of populations in the wild is limited and it is unlikely that much of the natural variation that exists across the large natural range of this species has been exploited in culture. Genetic markers that can characterize relative levels of population variation and differentiation in both wild and cultured stocks are needed to aid development of the culture industry and to assist con-servation of wild stocks. Decapod crustaceans have commonly displayed low levels of allozyme variation (Busack 1988) and the redclaw crayfish is no exception (Austin 1996; Macaranas et al. 1995). Microsatellite loci have been very useful for documenting genetic diversity in many species with relatively low levels of allozyme variation (Hughes & Queller 1993). Here we present the characterization of seven microsatellite loci developed for redclaw and their amplification in other closely related Cherax species. Redclaw genomic DNA from muscle tissue was digested with Sau3AI. Digested DNA ranging in size from 300 to 600 bp was excised from a 1% agarose gel, purified and ligated into an appropriately cut and phosphatased pUC19 vector (Pharmacia). Plasmids were transformed into Escherichia coli via electroporation (Bio-Rad Gen Pulsar) and the cells grown on Hybond N+ membranes overnight at 37 °C. Duplicate filters were made. Colonies were probed with (dC-dA)n . (dG-dT)n labelled with [α 32 P]-CTP, randomly primed using the Mega Prime Kit (Amersham). After secondary screening, positive clones were purified using an alkaline/PEG precipitation and sequenced using ABI (Applied Biosystems) automated DNA sequencing. Samples for sequencing were prepared according to the procedure in the Perkin-Elmer ABI PRISM dye terminator sequencing reaction kit. Forward and reverse sequences were aligned with the aid of the computer program Sequence Editor (version 1.0.3, Applied Biosystems Inc.). Primers were designed with the aid of MacVector (version 4.5.1 (1993) International Biotechnologies, Inc.). Microsatellite loci primers were optimized using: 50 ng of genomic DNA, 1.5× Biotech Tth Plus reaction buffer, containing 670 mm Tris-HCl (pH 8.8), 166 mm (NH4) 2 SO 4 , 4.5% Triton X-100 and 2 mg/mL gelatin, 2 mm dNTPs (dCTP labelled with α 32P), 3 mm MgCl2, 16 pmol of each primer, 0.02 U Biotech Tth Plus Polymerase; and ddH20 to a volume of 20 mL. PCR cycles were as follows: 1 min at 94 °C, 1 min at annealing temperature (see Table 1) and 2 min at 72 °C,

for 33 cycles with a 10-min extension at 72 °C. PCR products were electrophoresed through a 5% denaturing polyacrylamide sequencing gel, the gel dried and exposed to autoradiography film. Table 1 presents details of allelic diversity and hetero-zygosity estimates in seven loci in representatives of six wild and two cultured redclaw populations. Null alleles were detected at loci CQU.001, CQU.002, CQU.004 in two of the six wild stocks. Cross-species amplification of microsatellite loci has been reported in many closely related species (Moore et al. 1991; Laurent et al. 1995; and FitzSimmons et al. 1995). Limited cross-amplification using the redclaw microsatellite primers was achieved in a closely related Cherax species. Ten C. destructor individuals exhibited polymorphic alleles at the CQU.001 and CQU.007 loci when the annealing temperature was lowered by 5 °C. These trials demonstrate the utility of the seven redclaw microsatellite loci for characterizing levels and patterns of genetic diversity in both wild and cultured stocks. Significant cost benefits may also be achieved if cross-amplification of redclaw loci proves successful in related species of Cherax, a number of which are also important culture species (C. destructor and C. tenuimanus) in Australia. Acknowledgements We would like to thank all those who helped with sample collection: Clive Jones QDPI, Peter Hurley, John Short and Peter Davies at the Queensland Museum. Special thanks for advice and technical assistance from Vicki Whan and all at the Gerhman Labs, CSIRO. This work was funded by a research grant from the Australian Centre for International Agricultural Research (ACIAR-Grant No. Fis/96/165). References Austin C (1996) Systematics of the freshwater crayfish genus Cherax in northern and eastern Australia: electrophoretic and morphological variation. Australian Journal of Zoology, 44, 259–296. Busack C (1988) Electrophoretic variation in the red swamp and white river crayfish. Aquaculture, 69, 211–126. FitzSimmons NN, Moritz C, Moore SS (1995) Conservation and dynamics of microsatellite loci over 300 million years of marine turtle evolution. Molecular Biology and Evolution, 12 (3), 432–440. Hughes CR, Queller DC (1993) Detection of highly polymorphic microsatellite loci in a species with little allozyme polymorphism. Molecular Ecology, 2, 131–137. Laurent P, Amigues Y, Lepingle A, Berthier J, Bensaid A, Vaiman D (1995) Sequence conservation of microsatellites between Bos taurus (cattle) and Capra hircus (goat) and related species: Examples of use in parentage testing and phylogeny analysis. Heredity, 74 (1), 53–61. Macaranas JM, Mather PB, Hoeben P, Capra MF (1995) Allozyme and RAPD-DNA variation in the redclaw crayfish. Australian Journal of Marine and Freshwater Research, 46, 1217–1228. Medley P, Jones C, Avault J (1994) A global perspective of the culture of Australian redclaw crayfish, Cherax quadricarinatus: production, economics and marketing. World Aquaculture, 25 (4), 6–13. Moore SS, Sargeant LL, King TJ, Mattick JS, Georges M, Hetzel JS (1991) The conservation of dinucleotide microsatellites among mammalian genomes allows the use of heterologous PCR primer pairs in closely related species. Genomics, 10, 654–660. 9 no no. 2000 866 primer note primer issuenote 1 4 Graphicraft Limited, Hong Kong

Molecular Ecology (2000), 9(4): 494-495

hoshiko

Rectangle

hoshiko

Rectangle

halla

This article is not available online. Please consult the hardcopy thesis available from the QUT Library

104

Table 1 Microsatellite loci in the redclaw crayfish, Cherax quadricarinatus

Baker, N., Byrne, K., Moore, S., & Mather, P. 2000. Characterization of microsatellite loci in the redclaw crayfish, Cherax quadricarinatus. Molecular Ecology, 9(4): 494-495

halla

This table is not available online. Please consult the hardcopy thesis available from the QUT Library

105

9 Bibliography ABARE. 2001. Australian Fisheries Statistics. Canberra. ABARE. 2002. Australian Fisheries Statistics 2001. Canberra: Australian Bureau of Agricultural and Resource Economics. Ackefors, H. 1994. Recent progress in Australian crayfish culture. World Aquaculture, 25(4): 14-19. AFFA. 2002. Aquaculture, Industry Development – Fisheries. Canberra: Department of Agriculture, Fisheries and Forestry – Australia. Allendorf, F., & Phelps, S. R. 1980. Loss of genetic variation in a hatchery stock of cutthroat trout. Transactions of the American Fisheries Society, 109: 537-543. Allendorf, F. W., Bayles, D., Bottom, D. L., Currens, K. P., Frissell, C. A., Hankin, D., Lichatowich, J. A., Nehlsen, W., Trotter, P. C., & Williams, T. H. 1997. Prioritizing Pacific salmon stocks for conservation. Conservation Biology, 11(1): 140-152. Allendorf, F. W., & Waples, R. S. 1996. Conservation and genetics of salmonid fishes. In J. Avise, & J. L. Hamrick (Eds.), Conservation Genetics: 238-279: Chapman and Hall. Austin, C. 1987. Diversity of Australian Freshwater Crayfish Increases Potential for Aquaculture. Australian Fisheries, 5: 30-31. Austin, C. M. 1986. Electrophoretic and morphological systematic studies of the genus Cherax (Decapoda: Parastacidae) in Australia. Thesis, University of Western Australia, Perth. Austin, C. M. 1996. Systematics of the freshwater crayfish genus Cherax Erichson (Decapoda: Parastacidae) in northern and eastern Australia: Electrophoretic and morphological variation. Australian Journal of Zoology, 44(3): 259-296. Avise, J. 1994. Molecular Markers, Natural History and Evolution. New York: Chapman. Avise, J. C., Arnold, J., Ball, R. M., Bermingham, E., Lamb, T., Neigel, J. E., Reeb, C. A., & Saunders, N. C. 1987. Intraspecific phylogeography: The mitochondrial DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics, 18: 489-522. Avise, J. C., & Wollenberg, K. 1997. Phylogenetics and the origin of species. Proceeding of the National Academy of Science, USA, 94: 7748-7755. Axelrod, D. I., & Raven, P. H. 1982. Paleobiogeography and origin of the New Guinea flora, Biogeography and Ecology of New Guinea: 919-941. The Hague: W. Junk. Baker, N., Byrne, K., Moore, S., & Mather, P. 2000. Characterization of microsatellite loci in the redclaw crayfish, Cherax quadricarinatus. Molecular Ecology, 9(4): 494-495. Bakos, J., & Gorda, S. 2001. Genetic resources of common carp at the Fish Culture Research Institute, Szarvas, Hungary, FAO Fisheries Technical Paper: i.

106

Ball, A. O., Chapman, R. W., & Kocher, T. D. 2003. Population genetic analysis of white shrimp, Litopenaeus setiferus, using microsatellite genetic markers., Molecular Ecology, Vol. 12: 2319: Blackwell Publishing Limited. Balloux, F., & Goudet, J. 2002. Statistical properties of population differentiation estimators under stepwise mutation in a finite island model. Molecular Ecology, 11(4): 771-783. Balloux, F., & Lugon-Moulin, N. 2002. The estimation of population differentiation with microsatellite markers., Molecular Ecology, Vol. 11: 155: Blackwell Publishing Limited. Batuecas, B., Garesse, R., Calleja, M., Valverde, J. R., & Marco, R. 1988. Genome organization of Artemia mitochondrial DNA. Nucleic Acids Research, 16: 6515-6529. Bentsen, H. B., Eknath, A. E., Palada-De Vera, M. S., Danting, J. C., Bolivar, H. L., Reyes, R. A., Dionisio, E. E., Longalong, F. M., Circa, A. V., Tayamen, M. M., & Gjerde, B. 1998. Genetic improvement of farmed tilapias: Growth performance in a complete diallel cross experiment with eight strains of Oreochromis niloticus, Aquaculture, Vol. 160: 145-173. Bernatchez, E. G., & Guyomard, R. 1994. Mitochondrial control region and protein coding gene sequence variation among phenotypic forms of brown trout Salmo trutta from northern Italy. Molecular Ecology, 3: 161-171. Bernatchez, E. G., & WIlson, C. A. 1998. Comparative phylogeography of Nearctic and Palearctic fishes. Molecular Ecology, 7(4): 431-452. Berst, B., & Simon, R. 1981. Proceedings of the stock concept international symposium (STOCS). Canadian Journal of Fisheries and Aquatic Sciences, 38: 1457-1923. Bohonak, A. J. 1998. Genetic population structure of the fairy shrimp Branchinecta coloradensis (Anostraca) in the Rocky Mountains of Colorado. Canadian Journal of Zoology, 76(11): 2049-2057. Bohonak, A. J. 2002. IBD (Isolation by Distance): a program for analyses of isolation by distance. Journal of Heredity, 93: 153-154. Bouchon, D., Souty-Grosset, C., & Raimond, R. 1994. Mitochondrial DNA variation and markers of species identity in two penaeid shrimp species: Penaeus monodon Fabricius and P. japonicus Bate. Aquaculture, 127: 131-144. Bouza, C., Sánchez, L., & Martinez, P. 1997. Genetic diversity analysis in natural populations and cultured stocks of turbot (Scophthalmus maximus L.). Animal Genetics, 28: 28-36. Bowcock, A. M., Ruiz-Linares, A., Tomfohrde, J., Minch, E., Kidd, J. R., & Cavalli-Sforza, L. L. 1994. High resolution of human evolution with polumorphic microsatellites. Nature, 368:: 455-457. Brookfield, J. 1996. A simple new method for estimating null allele frequency from heterozygote deficiency. Molecular Ecology, 5: 453-455. Brown, W. M., George, M. J., & A.C., W. 1979. Rapid evolution of animal mitochondrial DNA. Proceeding of the National Academy of Science, USA, 44: 1967-1971.

107

Bruford, M., & Wayne, R. K. 1993. Micorsatellites and their application to population genetic studies. Current Opinion in Genetics and Development, 3: 939-943. Brummett, R. E., & Alon, N. C. 1994. Polyculture of Nile tilapia (Oreochromis niloticus) and Australian red claw crayfish (Cherax quadricarinatus) in earthen ponds. Aquaculture, 122(1): 47-54. Bunn, S. E., & Hughes, J. M. 1997. Dispersal and recruitment in streams: Evidence from genetic studies. Journal of the North American Benthological Society, 16(2): 338-346. Busack, C. 1988. Electrophoretic Variation in the Red Swamp and White Swamp Crayfish. Aquaculture, 69: 211-226. Callen, D. F., Thompson, A. D., Shen, Y., Phillips, H. A., Richards, R. I., Mulley, J. C., & Sutherland, G. R. 1993. Incidence and origin of 'null' alleles in the (AC)n microsatellite makers. American Journal of Human Genetics, 52: 922-927. Campbell, N. J. H., Geddes, M. C., & Adams, M. 1994. Genetic variation in yabbies, Cherax destructor and C. albidus (Crustacea: Decapoda: Parastacidae), indicates the presence of a single, highly sub-structural species, Australian Journal of Zoology, Vol. 42: 745-760. Carey, J. 1998. Hook, Line, and Extinction., Business Week: 164: McGraw-Hill Companies, Inc. Cavalli-Sforza, L. L., & Edwards, W. F. 1967. Phylogenetic analysis: models and estimation procedures. Evolution, 21: 550-570. Chapman, H. F., Hughes, J. M., Ritchie, S. A., & Kay, B. H. 2003. Population structure and dispersal of the freshwater mosquitoes Culex annulirostris and Culex palpalis (Diptera: Culicidae) in Papua New Guinea and northern Australia, Journal of Medical Entomology, Vol. 40: 165-169. Chappell, J. 1983. A revised sea-level record for the last 300, 000 years from Papua New Guinea. Search, 14(3-4): 99-101. Chapuisat, M. 1996. Characterisation of microsatellite loci in Formica lugubris B and their variabiltiy in other ants species. Molecular Ecology, 5: 599-601. Chenoweth, S. F., Hughes, J. M., Keenan, C. P., & Lavery, S. 1998. When oceans meet: A teleost shows secondary intergradation at an Indian-Pacific interface, Proceedings of the Royal Society of London Series B Biological Sciences, Vol. 265: 415-420. Chivas, A., Garcia, A., van der Kaars, S., Couapel, M., Holt, S., Reeves, J., Wheeler, D., Switzer, A., Murray-Wallace, C., Banerjee, D., Price, D., Wang, S., Pearson, G., Edgar, N., Beaufort, L., De Deckker, P., Lawson, E., & Cecil, C. 2001. Sea-level and environmental changes since the last interglacial in the Gulf of Carpentaria, Australia: an overview. Quaternary International, 83-85: 19-46. Clement, M., Posada, D., & Crandall, K. A. 2000. TCS: a computer program to estimate gene genealogies. Molecular Ecology, 9(10): 1657-1660. Coltman, D., Bowen, W., & Wright, J. 1996. PCR primers of harbour seal (Phoca vitulina concolour) microsatellites amplify polymorphic loci in other pinniped species. Molecular Ecology, 5: 161-163.

108

Cook, B. D. B., Stuart E. Hughes, Jane M. 2002. Genetic structure and dispersal of Macrobrachium australiense (Decapoda: Palaemonidae) in western Queensland, Australia. Freshwater Biology, 47(11): 2098-2112. Cornuet, J., & Luikart, G. 1996. Description and power of analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics, 144: 2001-2014. Cornuet, J. M., Piry, S., Luikart, G., Estoup, A., & Solignac, M. 1999. New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics, 153: 1989-2000. Costello, A. B. D., T. E. Pollard, S. M. Pacas, C. J. Taylor, E. B. 2003. The influence of history and contemporary stream hydrology on the evolution of genetic diversity within species: An examination of microsatellite DNA variation in bull trout, Salvelinus confluentus (Pisces: Salmonidae). Evolution, 57(2): 328-344. Coughlan, J. P., Imsland, A., Galvin, P., Fitzgerald, R., Naevdal, G., & Cross, T. 1998. Microsatellite DNA variation in wild populations and farmed strains of turbot from Ireland and Norway: a preliminary study. Journal of Fish Biology, 52: 916-922. Crandall, K. A., Fetzner James W, Jr., Lawler, S. H., Kinnersley, M., & Austin, C. M. 1999. Phylogenetic relationships among the Australian and New Zealand genera of freshwater crayfishes (Decapoda: Parastacidae). Australian Journal of Zoology, 47(2): 199-214. Crandall, K. A., & Fitzpatrick, J. F., Jr. 1996. Crayfish molecular systematics: Using a combination of procedures to estimate phylogeny. Systematic Biology, 45(1): 1-26. Crandall, K. A., Harris, D. J., & Fetzner, J. W., Jr. 2000. The monophyletic origin of freshwater crayfish estimated from nuclear and mitochondrial DNA sequences. Proceedings of the Royal Society Biological Sciences Series B, 267(1453): 1679-1686. Cross, T., & King, J. 1983. Genetic effects of hatchery rearing in Atlantic salmon. Aquaculture, 33: 33-40. Cross, T. F. 2000. Genetic implications of translocation and stocking of fish species, with particular reference to Western Australia. Aquaculture Research, 31(1): 83-94. Crow, J., & Kimura, M. 1970. An Introduction to Population Genetics Theory. New York: Harper and Row. Crozier, R. H. 1992. Genetic Diversity and the Agony of Choice. Biological Conservation, 61(1): 11-15. Crozier, W. W. 2000. Escaped farmed salmon, Salmo salar L., in the Glenarm River, Northern Ireland: Genetic status of the wild population 7 years on. Fisheries Management & Ecology, 7(5): 437-446. Daniels, S. R., Gibbons, M. J., & Stewart, B. A. 1999. Allozyme variation amongst populations of the freshwater crab, Potamonautes perlatus (Decapoda: Potamonautidae) in the Berg River system, Western Cape. South African Journal of Zoology, 34(2): 64-68. Daniels, S. R., Gouws, G., Stewart, B. A., & Coke, M. 2003. Molecular and morphometric data demonstrate the presence of cryptic lineages among freshwater

109

crabs (Decapoda: Potamonautidae: Potamonautes) from the Drakensberg Mountains, South Africa. Biological Journal of the Linnean Society, 78(1): 129-147. Danzmann, R., Jackson, T. R., & Ferguson, M. 1999. Epistasis in allelic expression at upper temperature tolerance QTL in rainbow trout. Aquaculture, 173: 43-58. Daud, S. K., & Ang, K. J. 1995. Selection of broodstock of tiger prawn, Penaeus monodon Fabricius, on the basis of morphometric traits, Pertanika Journal of Tropical Agricultural Science, Vol. 18: 15-20. Davis, G. P., & Hetzel, D. J. S. 2000. Integrating molecular genetic technology with traditional approaches for genetic improvement in aquaculture species, Aquaculture Research, Vol. 31: 3-10. de Bruyn, M., Wilson, J. C., & Mather, P. B. 2004. Reconciling geography and genealogy: phylogeography of giant freshwater prawns from the Lake Carpentaria region., Molecular Ecology, Vol. 13: 3515-3526: Blackwell Publishing Limited. Deng, H.-W., & Lynch, M. 1996. Estimation of deleterious-mutation parameters in natural populations. Genetics, 144(1): 349-360. DiRienzo, A., Peterson, A. C., Garza, J. C., Valdes, A. M., Slatkin, M., & Freimer, F. 1994. Mutational processes of simple-sequence repeat loci in human populations. Proceeding of the National Academy of Science, USA, 91: 3166-3170. Dizon, A. E., Lockyer, C., Perrin, W. F., DeMaster, D. P., & Sisson, J. 1992. Rethinking the stock concept: A phylogenetic approach. Conservation Biology, 6(1): 24-36. Dow, D. B. 1977. Geological synthesis of Papua New Guinea, Bureau of Mineral Resources. Doyle, R. W., Perez-Enriquez, R., Takagi, M., & Taniguchi, N. 2001. Selective recovery of founder genetic diversity in aquacultural broodstocks and captive, endangered fish populations, Genetica, Vol. 111: 291-304. Dunham, R., & Brummett, R. E. 1999. Response of two generations of selection to increase body weight in channel catfish, Ictalurus punctatus, compared to hybridisation with blue catfish, I. furcatus, males. Journal of Applied Aquaculture, 9: 37-45. Dunham, R., & Smitherman, R. 1983. Response to selection and realised heritability for body weight in three strains of channel catfish, Ictalurus punctatus, grown in earthern ponds. Aquaculture, 33: 89-96. Eknath, A., Tayamen, M., Palada-De Vera, M. S., Danting, J. C., Reyes, R., Dionisio, E. E., Capili, J. B., Bolivar, H. L., Abella, T. A., Circa, A. V., Bentsen, H. B., Gjerde, B., Gjedrem, T., & Pullin, R. S. V. 1993. Genetic improvement of farmed tilapias: the growth performance of eight strains of Oreochromis niloticus tested in different farm environments. Aquaculture, 111: 171-188. Ellegren, H. 2000. Microsatellite mutations in the germline: implications for evolutionary significance. ,. Trends in Genetics, 16: 551-558. Estoup, A., Rousset, F., Michalakis, Y., Cornuet, M., Adriamanga, M., & Guyomard, R. 1998. Comparitive analysis of microsatellite and allozyme markers: a case study investigating microgeographic differentiation in brown trout (Salmo trutta). Molecular Ecology, 7: 339-353.

110

Evans, B., Bartlett, J., Sweijd, N., Cook, P., & Elliott, N. G. 2004. Loss of genetic variation at microsatellite loci in hatchery produced abalone in Australia (Haliotis rubra) and South Africa (Haliotis midae). Aquaculture, 233(1-4): 109-127. Excoffier, L., Smouse, P. E., & Quattro, J. M. 1992. Analyses of molecular variance inferred from metric distances among DNA haplotypes: applicaiton to human mitochondrial DNA restriction data. Genetics, 131: 479-491. FAO. 2002. State of the world fisheries and aquaculture. Rome. Felsenstein, J. 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution, 39: 783-791. Felsenstein, J. 1988. Phylogenies from molecular sequences: inference and reliability. Annual Review of Genetics, 22: 521-565. Felsenstein, J. 1995. PHYLIP (Phylogenetic Inference Package, computer sotfware): Version 3.57c, 3.5 ed. Seattle, WA: University of Washington. Ferguson, A., Taggart, J. B., Prodohl, P. A., McMeel, O., Thompson, C., Stone, C., McGinnity, P., & Hynes, R. A. 1995. The application of molecular markers to the study and conservation of fish populations, with special reference to Salmo. Journal of Fish Biology, 47(Suppl. A): 103-126. FitzSimmons, N., Moritz, C., & Moore, S. 1995. Conservation and dynamics of microsatellite loci over 300 million years of marine turtle evolution. Molecular Biology and Evolution, 12(3): 432-440. Fjalestad, K. T., Moen, T., & Gomez-Raya, L. 2003a. Prospects for genetic technology in salmon breeding programmes. Aquac Research, 34(5): 397-406. Fjalestad, K. T., Moen, T., & Gomez-Raya, L. 2003b. Prospects for genetic technology in salmon breeding programmes., Aquaculture Research, Vol. 34: 397-406. Frankel, O. H., & Soulé, M. E. 1981. Population genetics and conservation. In O. H. Frankel, & M. E. Soulé (Eds.), Population genetics and conservation. Frankham, R. 1994. Conservation of Genetic diversity for animal improvement. Paper presented at the 5th World congress on genetics applied to livestock production, Ottawa. Frankham, R. 1995. Inbreeding and extinction: a threshold effect. Conservation Biology, 9(4): 792-799. Frankham, R. 1996. Relationship of genetic variation to population size in wildlife. Conservation Biology, 10(6): 1500-1508. Gaggiotti, O. E., Lange, O., Rassmann, K., & Gliddon, C. 1999. A comparison of two indirect methods for estimating average levels of gene flow using microsatellite data. Molecular Ecology, 8(9): 1513-1520. Gall, A. 1991. Genetics and reproduction in fish culture. Journal of Animal Science, 69(10): 4216-4220. Galvin, P., Taggart, J., Ferguson, A., O'Farrell, M., & Cross, T. 1996. Population genetics of Atlantic salmon (Salmo salar) in the River Shannon system in Ireland: An

111

appraisal using single locus minisatellite (VNTR) probes. Canadian Journal of Fisheries & Aquatic Sciences, 53(9): 1933-1942. Gao, L.-Z. 2003. The conservation of Chinese rice biodiversity: Genetic erosion, ethnobotany and prospects., Genetic Resources and Crop Evolution, Vol. 50: 17-32. Garcia-Marin, J., Jorde, P., Ryman, N., Utter, F., & Pla, C. 1991. Management implications of genetic differentiation between native and hatchery populations of brown trout (Salmo truta) in Spain. Aquaculture, 95: 235-249. Garduno-Lugo, M., Munoz-Cordova, G., & Olvera-Novoa, M. A. 2004. Mass selection for red colour in Oreochromis niloticus (Linnaeus 1758). Aquaculture Research, Vol. 35: 340-344. Georges, M., & Anderson, L. 1996. Livestock genomics comes of age. Genome Research, 6: 907-921. Gharrett, A. J., Smoker, W. W., Reisenbichler, R. R., & Taylor, S. G. 1999. Outbreeding depression in hybrids between odd- and even-broodyear pink salmon. Aquaculture, 173: 117-129. Gjedrem, T. 1985. Improvement in productivity through breeding schemes. Geojournal, 10(3): 233-241. Gjedrem, T. 1997. Selective breeding to improve aquaculture production. World Aquaculture, 3: 33-45. Gjedrem, T. 2000. Genetic improvement of cold-water fish species, Aquaculture Research, Vol. 31: 25-33. Gjerde, B., Gjoen, H. M., & Villanueva, B. 1996. Optimum designs for fish breeding programmes with constrained inbreeding: Mass selection for a normally distributed trait, Livestock Production Science, Vol. 47: 59-72. Glaubrecht, M., & von Rintelen, T. 2003. Systematics, molecular genetics and historical zoogeography of the viviparous freshwater gastropod Pseudopotamis (Cerithioidea, Pachychilidae): A relic on the Torres Strait Islands, Australia., Zoologica Scripta, Vol. 32: 415-435. Gorda, S., Bakos, J., Liska, J., & Kakuk, C. 1995. Live gene bank of common carp strains at the Fish Culture Research Institute, Szarvas. Aquaculture, 129: 199-202. Gouin, N., Grandjean, F., Bouchon, D., Reynolds, J. D., & Souty-Grosset, C. 2001. Population genetic structure of the endangered freshwater crayfish Austropotamobius pallipes, assessed using RAPD markers. Heredity, 87(1): 80-87. Gouws, G., Stewart, B. A., & Daniels, S. R. 2004. Cryptic species within the freshwater isopod Mesamphisopus capensis (Phreatoicidea: Amphisopodidae) in the Western Cape, South Africa: Allozyme and 12S rRNA sequence data and morphometric evidence. Biological Journal of the Linnean Society, 81(2): 235-253. Gray, J. E. 1845. Description of some new Australian animals. In J. Eyre (Ed.), Journals of Expeditions of Discovery into Central Australia and Overland from Adelaide to King George's Sound in the Year 1840-1841. Vol 1: 405-411. Grimes, C. B., & Kingford, M. J. 1996. How do riverine plumes of different sizes influence fish larvaae: do they enhance recruitment. Marine & Freshwater Research, 47: 191-208.

112

Gu, H., Mather, P. B., & Capra, M. F. 1995. Juvenile growth performance among stocks and families of red claw crayfish, Cherax quadricarinatus (von Martens). Aquaculture, 134(1-2): 29-36. Guo, S. W., & Thompson, E. A. 1992. Performing the exact test of Hardy-Weinberg proportions for multiple alleles. Biometrics, 48: 361-372. Heads, M. 1999. Vicariance biogeography and terrane tectonics in the South Pacific: Analysis of the genus Abrotanella (Compositae), Biological Journal of the Linnean Society, Vol. 67: 391-432. Hedgecock, D., & Sly, F. 1990. Genetic drift and effective population sizes of hatchery propagated stocks of the Pacific oyster, Crassostrea gigas. Aquaculture, 88: 21-38. Heywood, V. H. 1992. Conservation of germplasm of wild species. In O. T. Sandlund, K. Hindar, & A. H. D. Brown (Eds.), Conservation of Biodiversity for Sustainable Development: 189-203. Oslo: Scandinavian University Press. Hill, K. C., & Gleadow, A. J. W. 1989. Uplift and thermal history of the Papuan Fold Belt, Papua New Guinea: Apatite fission track analysis. Australian Journal of Earth Sciences, 36: 515-539. Holdich, D. M. 1993. A review of astaciculture: Freshwater crayfish farming. Aquatic Living Resources, 6(4): 307-317. Holland, P., & Brown, D. 1999. Aquaculture Policy: Selected Experiences From Overseas, ABARE Research Report 99.7. Canberra. Horovitz, I., & Meyer, A. 1995. Systematics of New World monkeys (Platyrrhini, Primates) based on 16S mitochondrial DNA sequences: A comparative analysis of different weighting methods in cladistic analysis. Molecular Phylogenetics & Evolution, 4(4): 448-456. Hughes, C., & Queller, D. C. 1993. Detection of highly polymorphic microsatellite loci in a species with little allozyme polymorphism. Molecular Ecology, 2: 131-137. Hughes, J., Baker, A. M., Bartlett, C., Bunn, S., Goudkamp, K., & Somerville, J. 2004. Past and present patterns of connectivity among populations of four cryptic species of freshwater mussels Velesunio spp. (Hyriidae) in central Australia., Molecular Ecology, Vol. 13: 3197-3212: Blackwell Publishing Limited. Hughes, J. M., & Hillyer, M. J. 2003. Patterns of connectivity among populations of Cherax destructor (Decapoda: Parastacidae) in western Queensland, Australia. Marine & Freshwater Research, 54: 587-596. Hughes, J. M., Mather, P. B., Sheldon, A. L., & Allendorf, F. W. 1999. Genetic structure of the stonefly, Yoraperla brevis, populations: The extent of gene flow among adjacent montane streams. Freshwater Biology, 41(1): 63-72. Hughes, J. M. B., S. E. Hurwood, D. A. Choy, S. Pearson, R. G. 1996. Genetic differentiation among populations of Caridina zebra (Decapoda: Atyidae) in tropical rainforest streams, northern Australia. Freshwater Biology, 36(2): 289-296. Hulata, G. 1995a. The history and current status of aquaculture genetics in Israel, Israeli Journal of Aquaculture Bamidgeh, Vol. 47: 142-154.

113

Hulata, G. 1995b. A review of genetic improvement of the common carp (Cyprinus carpio L.) and other hybrids by crossbreeding, hybridisation and selection. Aquaculture, 129: 143-155. Hulata, G. 2001. Genetic manipulations in aquaculture: a review of stock improvement by classical and modern technologies. Genetica, 111: 155-173. Hurwood, D. A., & Hughes, J. M. 1998. Phylogeography of the freshwater fish, Mogurnda adspersa, in streams of northeastern Queensland, Australia: evidence for altered drainage patterns. Molecular Ecology, 7(11): 1507-1517. Hutchison, D. W., & Templeton, A. R. 1999. Correlation of pairwise genetic and geographic distance measures: Inferring the relative influences of gene flow and drift on the distribution of genetic variability. Evolution, 53(6): 1898-1914. Imgrund, J., Groth, D., & Wetherall, J. 1997. Genetic analysis of the freshwater crayfish Cherax tenuimanus. Electrophoresis, 18(9): 1660-1665. Jackson, T. R., Ferguson, M., Danzmann, R., Fishback, A. G., Ihssen, P. E., O'Connell, M., & Crease, T. J. 1998. Identification of two QTL-influencing upper temperature tolerance in three rainbow trout (Oncorhynchus mykiss) half-sib families. Heredity, 80: 143-151. Jarne, P., & Lagoda, J. 1996. Microsatellites, from molecules to populations and back. Trends in Ecology & Evolution, 11(10): 424-429. Johnson, K. 1997. Genetic Improvement in Aquaculture. Rural Research, 174: 17-19. Jones, C., & Curtis, M. 1994. Redclaw Farming: Fisheries Research and Development Corporation. Jones, C. M. 1995. Production of juvenile redclaw crayfish, Cherax quadricarinatus (von Martens) (Decapoda, Parastacidae) I. Development of hatchery and nursery procedures. Aquaculture, 138(1-4): 221-238. Jones, C. M., McPhee, C. P., & Ruscoe, I. M. 2000. A review of genetic improvement in growth rate in redclaw crayfish Cherax quadricarinatus (von Martens) (Decapoda: Parastacidae). Aquaculture Research, 31(1): 61-67. Jones, M., & Torgersen, T. 1988. Late quaternary evolution of Lake Carpentaria on the Australia-New Guinea continental shelf. Australian Journal of Earth Sciences, 35: 313-324. Karplus, I., Barki, A., Cohen, S., & Hulata, G. 1995. Culture of the Australian Red-Claw Crayfish (Cherax quadricarinatus) in Israel: I. Polyculture with fish in earthen ponds. Israeli Journal of Aquaculture-Bamidgeh, 47(1): 6-16. Keogh, J. S. 1998. Molecular phylogeny of elapid snakes and a consideration of their biogeographic history. Biological Journal of the Linnean Society, 63(2): 177-203. Kimura, M. 1953. 'Stepping-stone' model of populations. Annual Report of the National Institute of Genetics, 3: 62-63. Kimura, M., & Crow, J. 1964. The number of alleles that can be maintained in a finite population. Genetics, 49: 725-738.

114

Kimura, M., & Otha, T. 1978. Stepwise mutation model and distribution of allelic frequencies in a finite population. Proceeding of the National Academy of Science, USA, 75: 2868-2872. Kimura, M., & Weiss, G. H. 1964. The stepping stone model of populations structure and the decrease of genetic correlation with distance. Genetics, 49: 561-576. King, T. L., Kalinowski, S. T., Schill, W. B., Spidle, A. P., & Lubinski, B. A. 2001. Population structure of Altanitc salmon (Salmo salar L.) a range-wide perspective from microsatellite DNA variation. Molecular Ecology, 10: 807-821. Knibb, W. 2000. Genetic improvement of marine fish: Which method for industry?, Aquaculture Research, Vol. 31: 11-23. Knowlton, N., & Weigt, L. A. 1998. New dates and new rates for divergence across the Isthmus of Panama. Proceedings of the Royal Society of London - Series B: Biological Sciences, 265(1412): 2257-2263. Koskinen, M. T., Hirvonen, H., Landry, P. A., & Primmer, C. R. 2004. The benefits of increasing the number of microsatellites utilised in genetic populations studies: an empirical perspective. Hereditas, 141: 61-67. Kumar, S., Tamura, K., Jakobsen, I., & Nei, M. 2001. MEGA2: molecular evolutionary genetic analysis software. Bioinformatics, 17: 1244-1245. Ladiges, P. Y., Udovicic, F., & Nelson, G. 2003. Australian biogeographical connections and the phylogeny of large genera in the plant family Myrtaceae., Journal of Biogeography, Vol. 30: 989-998. Lande, R., & Barrowclough, G. F. 1987. Effective population size, genetic variation, and their use in population management. In M. E. Soulé (Ed.), Viable Populations for Conservation: 87-123. Cambridge: Cambridge University Press. Lawrence, C. S. 2004. All-male hybrid (Cherax albidus x Cherax rotundus) yabbies grow faster than mixed-sex (C. albidus x C. albidus) yabbies. Aquaculture, 236(1-4): 211-220. Lawrence, C. S., Cheng, Y. W., Morrissy, N. M., & Williams, I. H. 2000. A comparison of mixed-sex vs. monosex growout and different diets on the growth rate of freshwater crayfish (Cherax albidus). Aquaculture, 185(3-4): 281-289. Leberg, P. L. 1993. Strategies for population reintroduction: Effects of variability. Conservation Biology, 7(1): 194-199. Lee, W.-J., & Kocher, T. 1996. Microsatellite DNA markers for genetic mapping in Oreochromis niloticus. Journal of Fish Biology, 49: 169-171. Li, M.-H., Zhao, S.-H., Bian, C., Wang, H.-S., Wei, H., Liu, B., Yu, M., Fan, B., Chen, S.-L., Zhu, M.-J., Li, S.-J., Xiong, T.-A., & Li, K. 2002. Genetic relationships among twelve Chinese indigenous goat populations based on microsatellite analysis. Genetics Selection Evolution, 34(6): 729-744. Li, Y., Byrne, K., Miggiano, E., Whan, V., Moore, S., Keys, S., Crocos, P., Preston, N., & Lehnert, S. 2003. Genetic mapping of the Kuruma prawn Penaeus japonicus using AFLP markers., Aquaculture, Vol. 219: 143-156. Liu, Z., Li, P., Kucuktas, H., Nichols, A., Tan, G., Zheng, X., Argue, B. J., & Dunham, R. 1999. Development of amplified fragment length polymorphism (AFLP) markers

115

suitable for genetic linkage mapping of catfish. Transactions of the American Fisheries Society, 128: 317-327. Loertscher, M., Claluna, M., & Scholl, A. 1998. Genetic Population structure of Austropotamobius pallipes (Lereboullet 1858) (Decapoda: Astacidae) in Switzerland, based on allozyme data. Aquatic Sciences, 60(2): 118-129. Long, C.-l., Li, H., Ouyang, Z., Yang, X., Li, Q., & Trangmar, B. 2003. Strategies for agrobiodiversity conservation and promotion: A case from Yunnan, China., Biodiversity and Conservation, Vol. 12: 1145-1156. Longalong, F. M., Eknath, A., & Bentsen, H. B. 1999. Response to bi-directional selection for frequency of early mating females in Nile tilapia (Oreochromis niloticus). Aquaculture, 178: 13-25. Luikart, G., Cornuet, J.-M., & Allendorf, F. W. 1999. Temporal changes in allele frequencies provide estimates of population bottleneck size. Conservation Biology, 13(3): 523-530. Luikart, G. L., Allendrof, F. W., Cornuet, J.-M., & Sherwin, W. B. 1998. Distortion of allele frequency distributions provides a test for recent population bottlenecks. Journal of Heredity, 89(3): 238-247. Lymbery, A. J. 2000. Genetic improvement in the Australian aquaculture industry, Aquaculture Research, Vol. 31: 145-149. Macaranas, J., Mather, P., Hoeben, P., & Capra, M. 1995. Assessment of Genetic Variation in Wild Populations of the Redclaw Crayfish (Cherax quadricarinatus) by Means of Allozyme and RAPD-PCR Markers. Marine and Freshwater Research, 46: 1217-1228. Mace. 2001. A new role for MSY in single-species and ecosystem approaches to fisheries stock assessment and management. Fish Fisheries, 2(1): 2-32. Macey, J. R., Wang, Y., Ananjeva, N. B., Larson, A., & Papenfuss, T. J. 1999. Vicariant Patterns of Fragmentation among Gekkonid Lizards of the Genus Teratoscincus Produced by the Indian Collision: A Molecular Phylogenetic Perspective and an Area Cladogram for Central Asia. Molecular Phylogenetics and Evolution, 12(3): 320-332. Martinez, V., Neira, R., & Gall, G. A. E. 1999. Estimation of genetic parameters from pedigreed populations: Lessons from analysis of alevin weight in Coho salmon (Oncorhynchus kisutch), Aquaculture, Vol. 180: 223-236. Maruyama, T., & Fuerst, P. A. 1985. Populations bottlenecks and noneqilibrium models in population genetics. II. Number of alleles in a small population that was formed by a recent bottleneck. Genetics, 111: 675-689. Maudet, C., Miller, C., Bassano, B., Breitenmoser-Wursten, C., Gauthier, D., Obexer-Ruff, G., Michallet, J., Taberlet, P., & Luikart, G. 2002. Microsatellite DNA and recent statistical methods in wildlife conservation management: Applications in alpine ibex (Capra ibex (ibex)). Molecular Ecology, 11(3): 421-436. Mayr, E. 1942. Systematics and the Origin of Species. New York: Columbia University Press.

116

McCauley, D. E. 1993. Genetic consequences of extinction and recolonisation in fragmented habitats. In P. Kareiva, J. Kingsolver, & R. Huey (Eds.), Biotic interactions and global change. Sunderland, MA: Sinauer. McConnell, S., Ruzzante, D. E., O'Reilly, P., Makilton, L., & Wright, J. 1997. Microsatellite loci reveal highly significant genetic differentiation among Atlantic salmon (Salmo salar L.) stocks from the east coast of Canada. Molecular Ecology, 6: 1075-1089. McGinnity, P., Prodohl, P., Ferguson, K., Hynes, R., O'Maoileidigh, N., Baker, N., Cotter, D., O'Hea, B., Cooke, D., Rogan, G., Taggart, J., & Cross, T. 2003. Fitness reduction and potential extinction of wild populations of Atlantic salmon, Salmo salar, as a result of interactions with escaped farm salmon. Proceedings of the Royal Society of London Series B-Biological Sciences, 270(1532): 2443-2450. McGinnity, P., Prodohl, P. A., O'Maoiléidigh, N., Hynes, R., Cotter, D., Baker, N., O'Hea, B., & Ferguson, A. 2004. Differential lifetime success and performance of native and non-native Atlantic salmon examined under communal natural conditions. Journal of Fish Biology (Supplement A), 65. McGlashan, D. J., & Hughes, J. M. 2002. Extensive genetic divergence among populations of the Australian freshwater fish, Pseudomugil signifer (Pseudomugilidae), at different hierarchical scales, Marine and Freshwater Research, Vol. 53: 897-907. McGuigan, K., Zhu, D., Allen, G. R., & Moritz, C. 2000. Phylogenetic relationships and historical biogeography of melanotaeniid fishes in Australia and New Guinea, Marine and Freshwater Research, Vol. 51: 713-723. Meffe, G. K., & Vrijenhoek, R. C. 1988. Conservation genetics in the management of desert fishes. Conservation Biology, 2: 157-169. Moore, S. S., Sargeant, L. L., King, T. J., Mattick, Georges, M., & JS, H. 1991. The Conservation of Dinucleotide Microsatellites Among Mammalian Genomes Allows the Use of Heterologous PCR Primer Pairs in Closely Related Species. Genomics, 10: 654-669. Moore, S. S., Whan, V., Davis, G. P., Byrne, K., Hetzel, D. J. S., & Preston, N. P. 1999. The development and application of genetic markers for the Kuruma prawn Penaeus japonicus. Aquaculture, 173: 19-32. Moritz, C., & Joseph, L. 1993. Cryptic diversity in an endemic rainforest skink (Gnypetoscincus queenslandiae). Biodiversity and Conservation, 2: 412-425. Nagel, K.-O. 2000. Testing hypotheses on the dispersal and evolutionary history of freshwater mussels (Mollusca: Bivalvia: Unionidae), Journal of Evolutionary Biology, Vol. 13: 854-865. Nakadate, M., Shikano, T., & Taniguchi, N. 2003. Inbreeding depression and heterosis in various quantitative traits of the guppy, Poecilia reticulata, Aquaculture, Vol. 220: 219-226. Nei, M., Chakravarti, A., & Tateno, Y. 1977. Mean and variance of Fst in a finite number of incompletely isolated populations. Theoretical Population Biology, 11: 291-306. Nei, M., & Koehn, R. K. e. 1983. Evolution of genes and proteins. Sunderland, Mass: Sinauer Associates.

117

Nguyen, T. T. T., Meewan, M., Ryan, S., & Austin, C. M. 2002. Genetic diversity and translocation in the marron, (Cherax tenuimanus) (Smith): implications for management and conservation. Fisheries Management and Ecology, 9(3): 163-173. Nielsen, J. L. 1998. Population genetics and the conservation and management of Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences. Nobili, G. 1901. Contibuzioni alla conoscenza della fauna carcinologica della Papuasia, delle Molucche e dell' Australia. Annali Mus. civ Stor. nat. Giacomo Doria, 40: 230-282. Norris, A. T., Bradley, D. G., & Cunningham, E. P. 1999. Microsatellite genetic variation between and within farmed and wild Atlantic salmon (Salmo salar) populations. Aquaculture, 180(3-4): 247-264. Ogden, K. 2000. Juvenile growth performance among stocks and crosses of redclaw, Cherax quadricarinatus (von Martens). Honours Thesis, Queensland University of Technology, Brisbane. Oldenbroek, J. K. 1999. Gene banks and the conservation of farm animal genetic resources. In J. k. Oldenbroek (Ed.): 1-9. Lelystad, The Netherlands: Institute for Animal Science and Health. Otte, D., & Endler, J. A. e. 1989. Speciation and its Consequences. Sunderland, Mass: Sinauer Associates. Ovenden, J. R., Bywater, R., & White, R. W. G. 1993. Mitochondrial DNA nucleotide sequence variation in Atlantic salmon (Salmo salar), brown trout (Salmo trutta), rainbow trout (Oncorhynchus mykiss) and brook trout (Salvelinus fontinalis) from Tasmania, Australia. Aquaculture, 114(3-4): 217-227. Paetaku, D., Shields, G. F., & Strobeck, C. 1998. Gene flow between insular, coastal and interior populations of brown bears in Alaska. Molecular Ecology, 7(10): 1283-1292. Paetkau, D., Calvert, W., Stirling, I., & Strobeck, C. 1995. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology, 4(3): 347-354. Paetkau, D., & Strobeck, C. 1995. The molecular basis and evolutionary history of a microsatellite null allele in bears. Molecular Ecology, 4: 519-520. Palti, Y., Parsons, J. E., & Thorgaard, G. 1999. Identification of candidate DNA markers associated with IHN virus resistance in backcrosses of rainbow and cutthroat trout. Aquaculture, 173: 81-94. Palumbi, S. R., Martin, A. P., Romano, S., McMillan, W. O., Stice, L., & Grabowski, G. 1991. The simple fool's guide to PCR. A collection of PCR protocols, version 2. Honolulu: University of Hawaii. Parker, P., Snow, A. A., Schug, M., Booton, G., & Fuerst, P. 1998. What molecules can tell us about populations: choosing and using a molecular marker. Ecology, 79: 361-382. Paterson, H. E. H. 1985. The recognition concept of species. In E. S. Vrba (Ed.), Species and Speciation: 21-29. Pretoria: Transvaal Museum Monograph No. 4. Transvaal Museum.

118

Pauly, D., & Watson, R. 2003. Counting the Last Fish, Scientific American, Vol. 289: 42: Scientific American Inc. Peakall, R., & Smouse, P. E. 2001. GenAlEx V5.1: Genetic Analysis in Excel. Population genetic software for teaching and research: Australian National University, Canberra, Australia. Pemberton, J. M., Slate, J., Bancroft, D. R., & Barret, J. A. 1995. Nonamplifying alleles at microsatllite loci: a caution for parentage and population studies. Molecular Ecology, 4: 249-252. Pienkowska, A., & Schelling, C. 2001. A G > C transversion within the primer binding site causes a 'null' allele of the microsatellite T2201 in the White Shepherd breed. Journal of Animal Breeding & Genetics, 118(1): 65-68. Pigram, C. J., & Davies, H. L. 1987. Terranes and the accretion history of the New Guinea orogen. Journal of Australian Geology and Geophysics, 10: 193-211. Piper, L. 2000. Potential for Expansion of the Freshwater Crayfish Industry in Australia. Rural Industries Research and Development Corporation, Publication no. 00/142, Canberra. Piry, S., & Luikart, G. 1999. Bottleneck: A Computer Program for Detecting Recent Reductions in the Effective Population Size Reductions from Allele Frequency Data, Journal of Heredity, Vol. 90: 502. Posada, D., & Crandall, K. A. 1998. MODELTEST: Testing the model of DNA substitution. Bioinformatics, 14(9): 817-818. Preston, N. P., Crocos, P. J., Keys, S. J., Coman, G., & Koenig, R. 2004. Comparative growth of selected and non-selected Kuruma shrimp Penaeus (Marsupenaeus) japonicus in commercial farm ponds; implications for broodstock production., Aquaculture, Vol. 231: 73-82. Primmer, C. R., & Ellegren, H. 1998. Patterns of molecular evolution in avian microsatellites. Molecular Biology and Evolution, 15(8): 997-1008. Primmer, C. R., Moller, D., & Ellegren, H. 1995. Resolving genetic relationships with microsatellite markers: a parentage testing system for the swallow Hirundo rustica. Molecular Ecology, 4: 493-4998. Prodohl, P. A., Loughry, W. J., McDonough, C. M., Nelson, W. S., Thompson, E. A., & Avise, J. C. 1998. Genetic maternity and paternity in a local population of armadillos assessed by microsatellite DNA markers and field data. American Naturalist, 151(1): 7-19. Queney, G., Ferrand, N., Weiss, S., & Monnerot, M. 2001. Stationary distributions of microsatellite loci between divergent population groups of the European rabbit (Oryctolagus cuniculus). Molecular Biology and Evolution, 18(2169 - 2178). Rao, V. R., & Hodgkin, T. 2002. Genetic diversity and conservation and utilization of plant genetic resources, Plant Cell Tissue and Organ Culture, Vol. 68: 1-19. Rawlings, L. H., & Donnellan, S. C. 2003. Phylogeographic analysis of the green python, Morelia viridis, reveals cryptic diversity. Molecular Phylogenetics and Evolution, 27(1): 36-44.

119

Raymond, M., & Rousset, F. 1995. GENEPOP (Version 3.1): Populations genetics software for exact tests and ecumenicism. Journal of Heredity, 86: 248-249. Reed, R. D., & Sperling, F. A. H. 1999. Interaction of process partitions in phylogenetic analysis: An example from the swallowtail butterfly genus Papilio. Molecular Biology and Evolution, 16(2): 286-297. Reist-Marti, S. B., Simianer, H., Gibson, J., Hanotte, O., & Rege, E. O. 2003. Weitzman's approach and conservation of breed diversity: an application for African cattle breeds. Conservation Biology, 17(5): 1299-1311. Rice, W. R. 1989. Analysing table of statistical test. Evolution, 43: 223-225. Riek, E. F. 1969. The Australian freshwater crayfish (Crustacea: Decapoda: Parastacidae), with descriptions of new species. Australian Journal of Zoology, 17: 855-918. Rouse, D., & Kahn, B. 1998. Production of Australian red claw Cherax quadricarinatus in polyculture with Nile Tilapia Oreochromis niloticus. Journal of the World Aquaculture Society, 29(3): 340-344. Rouse, D. B. 1995. Australian crayfish culture in the Americas. Journal of Shellfish Research, 14(2): 569-572. Rousset, F. 1996. Equilibrium values of measures of population subdivision for stepwise mutation processes. Genetics, 142: 1357-1362. Rousset, F. 1997. Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance. Genetics, 145: 1219–1228. Rozas, J., & Rozas, R. 2003. DNASP Version 3.99: an integrated program for molecular population genetics and molecular evolution analysis. Bioinformatics, 15: 174-175. Rubino, M. C. 1992. Economics of Redclaw (Cherax quadricarinatus (von Martens 1868)) Aquaculture. Journal of Shellfish Research, 11(1): 157-162. Ruzzante, D. E., Taggart, C. T., & Cook, D. 1998. A nuclear DNA basis for shelf- and bank-scale populations structure in northwest Atlantic cod (Gadus morhua): Labrador to Georges bank. Molecular Ecology, 7: 1663-1680. Sbordoni, V., De Matthaeis, E., Cobolli-Sbordoni, M., La Rosa, G., & Mattoccia, M. 1986. Bottleneck effects and the depression of genetic variability in hatchery stocks of Penaeus japonicus. Aquaculture, 57: 239-251. Schlötterer, C. 2000. Evolutionary dynamics of microsatellite DNA. Chromosoma, 109(365-371). Schlötterer, C., Ritter, R., Harr, B., & Grem, G. 1998. High mutation rate of a long microsatellite allele in Drosophila melanogaster provides evidence for allele specific mutation rates. Molecular Biology and Evolution, 15(10): 1269-1274. Schlötterer, C., & Tautz, D. 1992. Slippage synthesis of simple sequence DNA. Nucleic Acids Research, 20: 211-215. Schmidt, H. A., Strimmer, K., Vingron, M., & von Haeseler, A. 2002. TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics, 18: 502-504.

120

Schneider-Broussard, R., Felder, D. L., Chilan, C. A., & Neigel, J. E. 1998. Tests of phylogeographic models with nuclear and mitochondrial DNA sequence variation in the stone crabs, Menippe adina and Menippe mercenaria. Evolution, 52(6): 1671-1678. Sekino, M., Hara, M., & Taniguchi, N. 2002. Loss of microsatellite and mitochondrial DNA variation in hatchery strains of Japanese flounder Paralichthys olivaceus. Aquaculture, 213(1-4): 101-122. Senanan, W., Kapuscinski, A. R., Na-Nakorn, U., & Miller, L. M. 2004. Genetic impacts of hybrid catfish farming (Clarias macrocephalus x C. gariepinus) on native catfish populations in central Thailand. Aquaculture, 235: 167-184. Shaklee, J. B., Beacham, T. D., Seeb, L., & White, B. A. 1999. Managing fisheries using genetic data: Case studies from four species of Pacific salmon. Fisheries Research, 43(1-3): 45-78. Shannon, C. E., & Weaver, W. 1949. The mathematical theory of communication. Urbana IL: University of Illinois Press. Silverstein, J. T., Rexroad, C. E., & King, T. L. 2004. Genetic variation measured by microsatellites among three strains of domesticated rainbow trout (Oncorhynchus mykiss, Walbaum). Aquaculture Research, 35(1): 40-48. Simpson, G. G. 1951. The species concept. Evolution, 5: 285-298. Slatkin, M. 1985. Gene flow in natural populations. Annual Review of Ecology and Systematics, 16: 393-430. Slatkin, M. 1987. Gene flow and geographic structure of natural populations. Science, 236: 787-792. Slatkin, M. 1994. Gene flow and population structure. In L. A. Real (Ed.), Ecological Genetics. Princeton, New Jersey: Princeton University Press. Slatkin, M. 1995. A measure of population subdivision based on microsatellite allele frequencies. Genetics, 139: 457-462. Small, E. 1997. Biodiversity priorities from the perspective of Canadian agriculture: Ten Commandments, Canadian Field-Naturalist, Vol. 111: 487-505. Smitherman, R., & Dunham, R. 1985. Genetics and breeding. In C. S. Tucker (Ed.), Channel Catfish Culture: 283-316. Amsterdam, The Netherlands: Elsevier Scientific Publishing. State of the Environment. 2001. Coasts and Oceans, Australia State of the Environment Report 2001. Canberra: CSIRO Publishing on behalf of the Department of the Environment and Heritage. Stillman, J. H., & Reeb, C. A. 2001. Molecular phylogeny of eastern Pacific porcelain crabs, genera Petrolisthes and Pachycheles, based on the mtDNA 16s rDNA sequence: Phylogeographic and systematic implications. Molecular Phylogenetics and Evolution, 19(2): 236-245. Sturmbauer, C., Levinton, J. S., & Christy, J. 1996. Molecular phylogeny analysis of fiddler crabs: test of the hypothesis of increasing behavioural complexity in evolution. Proceeding of the National Academy of Science, USA, 93: 10855-10857.

121

Su, G.-S., Liljedahl, L.-E., & Gall, G. A. E. 2002. Genetic correlations between body weight at different ages and with reproductive traits in rainbow trout, Aquaculture, Vol. 213: 85-94. Sugaya, T. I., Minoru Mori, Hideshi Taniguchi, Nobuhiko. 2002. Inheritance mode of microsatellite DNA markers and their use for kinship estimation in kuruma prawn Penaeus japonicus. Fisheries Science (Tokyo), 68(2): 299-305. Swofford, D. L. 2003. PAUP* Version 4: phylogenetic anlaysis using parsimony (*and other methods). Sunderland: Sinauer Associates. Swofford, D. L., Olsen, G. J., Waddell, P. J., & Hillis, D. M. 1996. Phylogenetic inference. In D. M. Hillis, C. Moritz, & B. K. Mable (Eds.), Molecular systematics, 2nd ed.: 407-514. Sunderland, Massachusetts: Sinauer Associates. Tamura, K., & Aotsuka, T. 1988. Rapid isolation method for animal mitochondrial DNA by the alkaline lysis procedure. Biochemical Genetics, 26(11/12): 815-819. Tamura, K., & Nei, M. 1993. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biology and Evolution, 10: 512-526. Tave, D. 1991. Inbreeding, Aquaculture Magazine, Vol. 17: 65: Achill River Corporation. Templeton, A. R. 1986. Coadaption and outbreeding depression. In M. E. Soulé (Ed.), Conservation biology: the science of scarcity and diversity. MA: Sinauer: Sunderland. Templeton, A. R., Crandall, K. A., & Sing, C. F. 1992. A cladistic analsyis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data III: cladogram estimation. Genetics, 132: 619-633. Torgersen, T., Jones, M., Stephens, A., Searle, D., & Ullman, W. 1985. Late quaternary hydrological changes in the Gulf of Carpentaria. Nature, 313: 785-787. Unmack, P. J. 2001. Biogeography of Australian freshwater fishes. Journal of Biogeography, 28(9): 1053-1089. Van Olst, J. C., & Carlberg, J. M. 1990. Commercial culture of hybrid stripped bass: status and potential. Aquaculture Magazine, 16(1): 49-59. van Vuren, D., & Hedrick, P. 1998. Genetic conservation in feral populations of livestock. Conservation Biology. Vandeputte, M. 2003. Selective breeding of quantitative traits in the common carp (Cyprinus carpio): a review. Aquatic Living Resources, 16: 399-407. Veevers, J. J. (Ed.). 1984. Phanerozoic Earth History of Australia. Oxford: Claredon Press. Voris, H. R. 2000. Maps of Pleistocene sea levels in Southeast Asia: shorelines, river systems and time durations. Journal of Biogeography, 27(5): 1153-1167. Vuorinen, J. 1984. Reduction of genetic variability in a hatchery stock of brown trout (Salmo trutta L.). Journal of Fish Biology, 24: 339-348.

122

Wada, K. T. 1994. Genetics of pearl oyster in relation to aquaculture, JARQ, Vol. 28: 276-282. Waples, R. S. 1991. Heterozygosity and life-history variation in bony fishes: an alternative view. Evolution, 45(5): 1275-1280. Ward, R. D., Woodwark, M., & Skibinski, O. 1994. A comparison of genetic diversity levels in marine, freshwater and anadromous fishes. Journal of Fish Biology, 44: 213-232. Waser, N. M., & Price, M. V. 1989. Optimal outcrossing in Ipomopsis aggregata. Seed set and offspring fitness. Evolution, 43(5): 1097-1109. Waters, J. M., & Burridge, C. P. 1999. Extreme intraspecific mitochondrial DNA sequence divergence in Galaxias maculatus (Osteichthys: Galaxiidae), one of the world's most widespread freshwater fish. Molecular Phylogenetics & Evolution, 11(1): 1-12. Waters, J. M., Craw, D., Youngson, J. H., & Wallis, G. P. 2001a. Genes meet geology: Fish phylogeographic pattern reflects ancient, rather than modern, drainage connections. Evolution, 55(9): 1844-1851. Waters, J. M., Esa, Y. B., & Wallis, G. P. 2001b. Genetic and morphological evidence for reproductive isolation between sympatric populations of Galaxias (Teleostei: Galaxiidae) in South Island, New Zealand. Biological Journal of the Linnean Society, 73(3): 287-298. Weber, L., & Wong, C. 1993. Mutation of human short tandem repeats. Human Molecular Genetics, 62(2): 1123-1128. Weir, B. S., & Cockerham, C. C. 1984. Estimating F-Statistics for the Analysis of Population Structure. Evolution, 38(6): 1358-1370. Whitlock, M. C., & McCauley, D. E. 1990. Some population genetic consequences of colony formation and extinction: genetic correlations within founding groups. Evolution, 44: 1717-1724. Wiley, E. O. 1978. The evolutionary species concept resonsidered. Systematic Zoology, 27: 17-26. Wilkins, N. 1981. The Rationale and Relevance of Genetics in Aquaculture: An Overview. Aquaculture, 22: 209-228. Wolanski, E. 1993. Water circulation in the Gulf of Carpentaria. Journal of Marine Systems, 4: 401-120. Wolfus, G., Garcia, D., & Alcivar-Warren, A. 1997. Application of the microsatellite technique for analysing genetic diversity in shrimp breeding programs. aquaculture, 152: 35-47. Wollenburg, K., & Avise, J. 1998. Sampling properties of genealogical pathways underlying population structure. Evolution, 52: 957-966. Wright, S. 1931. Evolution in Mendelian populations. Genetics, 16: 97-159. Wright, S. 1965. The interpretation of population structure by F-statistics with special regard to system of mating. Evolution, 19: 395-420.

123

WWF. 2001. The status of Wild Atlantic Salmon: A River by River Assessment, http://www.wwf.org.uk/filelibrary/pdf/atlanticsalmon.pdf. Xu, Z., Primavera, J. H., de la Pena, L. D., Pettit, P., Belak, J., & Alcivar-Warren, A. 2001. Genetic diversity of wild and cultured Black Tiger Shrimp (Penaeus monodon) in the Philippines using microsatellites. Aquaculture, 199(1-2): 13-40. Yen, A. L., & Butcher, R. J. 1997. An Overview of the Conservation of Non-Marine Invertebrates in Australia. Canberra: Department of Environment and Heritage. Youngson, A. F., & Verspoor, E. 1998. Interactions between wild and introduced Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences, 55: 153-160. Zink, R. M., Fitzsimons, J. M., Dittmann, D. L., Reynolds, D. R., & Nishimoto, R. T. 1996. Evolutionary genetics of Hawaiian freshwater fish. Copeia, 2: 330-335.

Documents

Levels and Patterns of Genetic Diversity in Wild Populations and … · 2010-06-09 · Levels and Patterns of Genetic Diversity in Wild Populations and Cultured Stocks of Cherax quadricarinatus