ORIGINAL PAPER

Mapping species differences for adventitious rootingin a Corymbia torelliana × Corymbia citriodora subspeciesvariegata hybrid

Mervyn Shepherd & Shabana Kasem & David J. Lee &

Robert Henry

Received: 15 August 2007 /Revised: 9 January 2008 /Accepted: 19 February 2008 / Published online: 19 March 2008# Springer-Verlag 2008

Abstract Quantitative trait loci (QTL) detection was carriedout for adventitious rooting and associated propagation traitsin a second-generation outbred Corymbia torelliana ×Corymbia citriodora subspecies variegata hybrid family(n=186). The parental species of this cross are divergent intheir capacity to develop roots adventitiously on stemcuttings and their propensity to form lignotubers. For theten traits studied, there was one or two QTL detected, withsome QTL explaining large amounts of phenotypic varia-tion (e.g. 66% for one QTL for percentage rooting),suggesting that major effects influence rooting in this cross.Collocation of QTL for many strongly genetically correlat-ed rooting traits to a single region on linkage group 12suggested pleiotropy. A three locus model was mostparsimonious for linkage group 12, however, as differencesin QTL position and lower genetic correlations suggestedseparate loci for each of the traits of shoot production androot initiation. Species differences were thought to be themajor source of phenotypic variation for some rooting rate

and root quality traits because of the major QTL effects andup to 59-fold larger homospecific deviations (attributed tospecies differences) relative to heterospecific deviations(attributed to standing variation within species) evident atsome QTL for these traits. A large homospecific/hetero-specific ratio at major QTL suggested that the gene actionevident in one cross may be indicative of gene action morebroadly in hybrids between these species for some traits.

Keywords QTLmapping . Propagation . Species effects

Introduction

Adaptation and speciation may give rise to differences inmorphology or behaviour that separate species but whichare not necessarily involved in species isolation and theblock of gene flow (Orr 2001). Knowledge of the geneticsof these species effects primarily comes from quantitativetrait loci (QTL) studies in interspecific hybrids (Doebleyand Lukens 1998; Orr 2001). When summarised acrossplants and animals and a range of traits under natural orsexual selection, not surprisingly, the genetic architecture ofspecies differences is variable (Orr 2001). Nonetheless,species difference tends to involve modest numbers of QTL(1–20) and, when measured against standing variationwithin species, almost invariably involve genes of majoreffect (Orr 2001).

The existence of such large effects segregating ininterspecific hybrids, and the ability to associate them withgenetic markers, has provided new approaches (i.e. deter-ministic variety development (Tanksley et al. 1989)) forimprovement of domesticated crops (Lorz and Wenzel2005; Paterson 1998). Studies of species differencesbetween outcrossing tree species has also suggested

Tree Genetics & Genomes (2008) 4:715–725DOI 10.1007/s11295-008-0145-1

Communicated by D. Grattapaglia

M. Shepherd (*) : S. Kasem : R. HenryCentre for Plant Conservation Genetics,Southern Cross University,P.O. Box 157, Lismore, NSW 2480, Australiae-mail: mervyn.shepherd@scu.edu.au

M. Shepherd : R. HenryCooperative Research Centre for Forestry,Southern Cross University,P.O. Box 157, Lismore, NSW 2480, Australia

D. J. LeeDepartment of Primary Industries and Fisheries,Horticulture and Forestry Science,LB 16 Fraser Road,Gympie, QLD 4570, Australia

strategies for hybrid tree improvement. For example, thestudy of species differences in an interspecific second-generation (F2) cross revealed the complementary geneaction mechanism underlying heterosis evident in the F1 ofinterspecific poplars (Bradshaw 1998; Bradshaw andGrattapaglia 1994). The predictable heterosis of thesehybrids suggested that natural selection has substantially“fixed” parental species for contrasting alleles; hence, forthese traits, parental species may approximate inbred linecrosses (Bradshaw and Stettler 1995). Further advantages ofmanipulating species differences for hybrid breeding mayaccrue where hybrid breeding is based on synthetic hybridpopulations. In the case of the Populus genus, it may bepossible to treat the whole genus as a single large gene pooland identify the best alleles from each species to createcomposite genotypes (Bradshaw 1998). Species differencesthat are molecularly characterised also make ideal targets forgene-assisted selection (Lexer et al. 2004). If speciesdifferences derive from strong natural selection in one ormore parental species that creates strong linkage disequilib-rium, those may be exploited for marker-assisted selection insome breeding populations associated with the formation ofsynthetic hybrids (Shepherd et al. 2006a).

We are interested in the genetic improvement of anintersectional tree hybrid between Corymbia torelliana(Section Cadagaria) and Corymbia citriodora subspeciesvariegata. Spotted gums (Section Politaria; formerly Euca-lyptus maculata and Eucalyptus citriodora) are the mostpromising tree species for commercial hardwood plantationsin the marginal-rainfall areas (700–1000 mm/year) oftropical and subtropical regions of Eastern Australia becauseof their superior survival and growth (Johnson et al. 2004;Lee 2007; Lee et al. 2004). Planting of spotted gums (mostlyC. c. variegata) on a commercial scale has been constrainedboth by susceptibility to a fungal disease, QuambalariaShoot Blight, and a low amenability to vegetative propaga-tion (Carnegie 2007; Lee 2007). The development andtesting of the intersectional hybrid with C. torelliana overthe past decade has largely been in response to theselimitations in deploying C. c. variegata. Spotted gums area notoriously difficult group to root from stem cuttings withrates of less than 10% typical (Baker and Walker 2005;Campinhos and Ikemori 1983; de Assis 2000). The hybrid,on the other hand, tends to follow the C. torelliana parent,which has comparatively high rooting rates in stem cuttings(Lee et al. 2005) and has been the focus of spotted gumimprovement in Queensland in recent years (Lee 2007).

The aim of the present study was to detect andcharacterise QTL for adventitious rooting and associatedpropagation characteristics in Corymbia spp. hybrids.Studies of QTL in second-generation hybrid populationsof several tree species and a horticultural species (PopulusHan et al. (1994), Pinus Shepherd et al. (2006a) and

Lactuca Johnson et al. (1999)) indicate that large effects areassociated with species differences for rooting in a range ofplants. In addition, the repeatable detection and collocationof QTL for propagation traits in interspecific F1 ofEucalyptus spp. (Grattapaglia et al. 1995; Marques et al.1999, 2002, 2005) support a common genetic basis forpropagation traits in Eucalyptus spp. and, furthermore, thatsome species retain considerable standing allelic variationat loci affecting propagation-related traits. Here, we explorethe relative contributions of species differences and within-species standing variation to phenotypic variation (PV) inthe Corymbia hybrid population by estimating homospe-cific and heterospecific deviations for each QTL. Thehomospecific deviation for a QTL was defined as thedifference between the two homospecific genotypic classes,i.e. between the C. c. variegata parental species genotypicclass (VV) and C. torelliana parental species genotypicclass (TT). The heterospecific deviation was defined as thedifference between the two heterospecific genotypic clas-ses. QTL of major effect and large homospecific relative toheterospecific deviations for some rooting traits, suggestedspecies differences were major contributors to PV in theCorymbia hybrid.

Methods

Population

An outbred F2 hybrid family was used both in generatinga genetic linkage map and for the phenotyping of vegetativepropagation characteristics. Initially, two intersectional F1hybrids were created by controlled pollination of two C.torelliana with pollen from two C. c. variegata individuals(the grandparents). Seedlings of the two F1 families wereplanted in a Queensland Department of Primary Industriesand Fisheries (QDPI&F) trial at Coolabunia near Kingaroy,Queensland. The outbred F2 family was generated byintermating a select F1 from each family. Four hundred F2seeds were sown in QDPI&F glasshouse at Gympie on the12th of November 2004. Seed germination and earlyseedling survival was low with only 208 and 154 seedlingssurviving at 2.5 and 6 months post setting, respectively. InJanuary 2005, foliage was collected from each of the 208seedlings, the two F1 parent trees and the four grandparents,and stored frozen at -20°C until required for DNA extraction.

Phenotypic assessments of vegetative propagation traits

The assessment of propagation traits for 208 seedlings hasbeen described in detail elsewhere (Shepherd et al. 2007).In brief, propagation traits were assessed on a series of foursettings of cuttings made from the F2 seedlings between

716 Tree Genetics & Genomes (2008) 4:715–725

January and June 2005. Seedlings were cropped to promotea hedge structure and retained in a single block within theglasshouse to minimise environmental variation and “C”effects. At each setting, all cuttings from a seedling were setinto adjacent cells within columns of 8×5 cell trays. Cloneswere arranged sequentially in trays and trays were arrangedsequentially along the glasshouse bench, except for setting3, where the order of clones was randomised.

A total of ten propagation traits were assessed (Table 1).Shoot production (SP) was assessed as the total number ofcuttings set for a clone in a setting and was obtained for allfour settings. Rooting initiation (RI) was derived from theregression of the proportion of cuttings rooted upon thenumber of days post setting. The regression equation wasused to predict the number of days post setting at which 25%of cuttings were rooted for each clone. Rooting percentage(PER) was the proportion of cuttings from a clone rooted ona plot basis, assessed by counting root emergence from thebase of the pot or tray. Six root quality parameters were alsorecorded for each cutting (RAT, LTH, NO, VOL, QD, WT).A rating (RAT) of between 1 and 5 was given to each cuttingbased on a visual assessment of the bare root “quality”: arating of 1=no roots or callus, 2=callus only, 3=main root<20 mm, 4=main root 20–60 mm and 5=main root >60 mm.Following Foster et al. (1984), five other root quality

parameters were recorded to study different quality aspectsof root systems:

LTH length of longest main root on each cutting (mm)NO number of primary roots per cutting (count)VOL root volume index (mm3)QD quadrants occupied by roots (value of 1–4).WT dry biomass of root system. Roots were dissected

from the cutting and oven dried at 40°C for severaldays before weighting.

The presence or absence of a lignotuber (LIG) on aseedling was assessed on 30 May 2005 at around 7 monthsof age and, again, on the 10 March 2006 when seedlingswere 17 months of age. The variable used in QTL analysiswas a composite of data from both assessments to maximisethe number of seedlings assessed.

Propagation traits tended to have low to moderate clonalrepeatabilities (Shepherd et al. 2007). Rooting traits (rootingrate variables (PER and RAT), rooting quality variables(LTH-WT) and root initiation time (RI)), in general,exhibited moderate to strong favourable correlations; thetwo rooting rate variables (PER and RAT) were particularlystrongly correlated. Shoot production tended to be weaklycorrelated with rooting traits and represented a second,

Table 1 Data types, distribution parameters and QTL analysis methods for ten propagation traits

Trait Meas.units

Observationbasisa

Number of clonesor seedlingsassessed per settingb

Numberof reps

Mean SD Min. Max. Approx.Normalc

QTL analysismethod

EWERMethod

SP count Plot 208 4 8.22 7.31 0 40 Yes KW,IM PermPER % Plot 154–194 3 16.56 24.87 0 100 No KW,IM PermRAT 1–5 Cutting 174–194 3 1.92 0.94 1 5 No KW BonfRI days Plot 154–194 4 64.4 53.9 7 338 No KW BonfNO Integer Cutting 175–194 2 0.33 0.62 0 4 No KW BonfLTH mm Cutting 175–194 2 20.11 35.34 0 265 No KW BonfVOL mm3 Cutting 175–194 2 30.77 58.95 0 462.5 No KW BonfQD 1–4 Cutting 175–194 2 0.26 0.45 0 2.5 No KW BonfWT g Cutting 175–193 2 0.01 0.016 0 0.15 No KW BonfLIG Y/N Seedling 100 1 – – – – – CT FDR

Both parametric (Interval Mapping) and nonparametric (Kruskal-Wallis and Contingency table analysis with Fishers Exact Test) were used forQTL analysis depending on a trait’s distribution.IM Interval Mapping, KW Kruskal-Wallis, CT contingency table analysis, RI root initiation time, SP shoot production, PER rooting percentage,RAT root rating, NO number of roots, LTH length of main root, VOL root volume index, QD number of Quadrants occupied by roots, WT drybiomass of root system, LIG presence/absence of lignotuber on seedling, EWER experiment-wise error rate, Perm permutation test, BonfBonferroni’s method, FDR false discovery ratea Observation basis: seedlings, cuttings or plots of cuttings were the unit of observation. Cuttings were obtained from up to 208 seedlings and wereassessed in up to four settings. A plot represents all the cuttings from one seedling in one setting and varied from one to 40 cuttings (av. ± SD 8.2±7.3)depending on the number set. Observations on cuttings were reduced to plot values (or plot means) for estimation of genetic parameters and clonalmeansb Number of clones assessed in each setting expressed as a range; the number varied as different numbers were set and some seedlings died duringthe course of the experimentc Distribution normality tested at 95% level using Kolmogorov–Smirnov test

Tree Genetics & Genomes (2008) 4:715–725 717

largely independent variable class. Genetic correlationsbetween LIG and other traits could not be calculated, butthere was some evidence that the presence of lignotubers wasweakly associated with poor rooting (Shepherd et al. 2007).

For statistical analysis, the experiment was treated as arandomised complete block design with each setting treatedas a block (up to four blocks in some traits) and cuttingsfrom each clone (up to 208 clones) representing a single plot.Traits distribution, heritability and correlations were basedon plot level values; either the plot mean, e.g. for LTH—themean length of the main root assessed for all cuttings in theplot or the proportion, e.g. PER—the proportion of cuttingsrooted in a plot (Shepherd et al. 2007).

Genetic map based on microsatellites for Corymbia

A comprehensive consensus map of the two F1 parents wasused for QTL analysis. Genetic linkage maps were con-structed using JoinMap Software version 3 (Kyazma,Netherlands) using data from 66 microsatellite loci scoredon a subset of 90 F2 offspring (Shepherd et al., 2006b). Themap consisted of 54 microsatellite markers distributed over13 linkage groups and covered a total distance of 417 cM(K). Microsatellites markers were either developed de novofrom C. c. variegata (Jones et al. 2001; Shepherd et al.2006b) or transferred from Eucalyptus spp. (Brondani et al.1998, 2002; Byrne et al. 1996; Glaubitz and Emebiri 2001;Steane et al. 2001). Conditions for amplification of micro-satellite loci, genotyping and map construction are given inShepherd et al. (2006b).

For the QTL study, an additional 96 F2 offspring weregenotyped to give a total population size of 186. A subsetof 36 well-spaced and informative markers were selectedfor the QTL study. The conditions used for polymerasechain reaction and microsatellite genotyping were identicalto those used to generate the genetic map.

QTL analysis

Three types of QTL tests were used as appropriate for thedisparate trait data types and distributions under investiga-tion (Table 1). Nonparametric Kruskal-Wallis (KW) testswere carried out using the KW module (Van Ooijen et al.1993) in MapQTL version 4 for all traits except for thebinary variable, LIG (Table 1). The significance of the KWtest was used for declaring the detection of a QTL becausethis test could be validly applied to disparate data typesproviding a conservative, standardised test for QTLdetection for all traits except LIG. QTL with significanceat the “suggestive” level experiment-wise error rate (EW-ER; e.g. p=<0.1) or higher are reported according to theconvention suggested by Lander and Kruglyak (1995) forstudies where there is no a priori data on QTL. Experiment-

wise error rates for KW tests were determined usingBonferroni’s corrections (Milliken and Johnson 1984).

Interval mapping (IM) was conducted for traits assessed asscalar and approximately continuous variables (all exceptRATand LIG; Table 1) to provide additional QTL parametersnot available from the KW test (i.e. percentage varianceexplained; increased accuracy of QTL position). The positionand magnitude of QTL effects were estimated at 5-cMintervals along the map information using MapQTL version4 (Kyazma, Netherlands; Van Ooijen et al. 2002). EWER forIM tests were determined on a genome-wide basis bypermutation tests (Churchill and Doerge 1994) using 1,000permutations in the permutation test module of MapQTL.Gene action at QTL was estimated by testing for differencesbetween genotypic classes at the closest linked markers usinganalysis of variance and least significant difference tests inthe General Linear Model module of Statistical Package forthe Social Sciences (SPSS) version 11 (SPSS Inc. Chicago,IL, USA). QTL positions are reported with a confidenceinterval defined by a 1.0± logarithm of odds (LOD) supportinterval (Grattapaglia et al. 1995).

QTL detection for the bivariate trait, LIG, was carried usingcontingency tables combined with Fisher’s exact chi-squareusing the Crosstabs module of SPSS. Experiment-wise errorrates for the contingency table analyses were determined usingthe False Discovery Rate method (Benjamini and Hockberg1995).

Results

12 QTL distributed on four linkage groups were detectedby Kruskal-Wallis or contingency table tests

QTL detection was carried out using nonparametric methods,the Kruskal-Wallis or contingency table tests. Eleven QTLwere detected using Kruskal-Wallis tests at the EWER of 0.1(Table 2). All traits had a single QTL on CM12 except PERand SP, which had a second QTL on CM8 and CM10,respectively. Application of contingency table analysis to thebinary trait LIG indicated that a QTL was associated withboth markers on CM11 at the EWER of 0.1 (Table 3).Therefore, a minimum of 12 QTL were detected, distributedon four linkage groups, CM8, CM10, CM11 and CM12,with one or two QTL identified for each of the ten traitsstudied.

Position estimates for QTL from IM indicated a largecluster of QTL on CM12

The effect size, position and gene action for QTL detected byKW were estimated by interval mapping (Table 4). Althoughthe IM test significance was not used as a criterion for QTL

718 Tree Genetics & Genomes (2008) 4:715–725

detection, the LOD and EWER significance are provided forcomparison to KW results. Most QTL detected by KW werenot significant by IM, except the two QTL for SP (CM12and CM10) and one QTL for RAT on CM12 (Table 4).Genome scans using interval mapping did not identify anynew QTL beyond those already identified by KW tests.

The 1.0 LOD support intervals for the QTL mapping ontoCM12 indicated that the QTL positions for all traits (exceptRI) encompassed the same region 20–30 cM (K) left ofEMCRC_0047 (Table 4). Only the 1.0 LOD support intervalfor QTL for RI (0–10 cM (K) left of EMCRC_0047) did notoverlap this region (Table 4). This suggested that there maybe as few as two loci on CM12, a pleiotropic locus influenc-

ing all traits except RI (and LIG) located approximately 20–30 cM (K) distant from EMCRC_0047, and a second locusbetween 0 and 10 cM (K) from EMCRC_0047 influencingRI.

QTL parameters estimated by IM indicated that the effectsize of some QTL was large

Estimates of the effect size for the QTLs on CM12 indicatedthat they typically had large effects, explaining as much as62–71% of the PV for some root quality or rooting rate traits(i.e. PER; RAT; LTH, NO, VOL and QD; Table 4). The QTLfor SP also had a large effect, explaining around 38% of the

Table 3 QTL for LIG detected using contingency table analyses

Marker LIG V1V2/V-a V1T2/T- V2T1 T1T2 Total FET p-value EWER sign

EMCRC_0040 No 0 7 3 2 12Yes 36 14 19 16 85

Total 36 21 22 18 97 0.002 **EMBRA_0040 No 3 9 – – 12

Yes 60 28 – – 88Total 63 37 – – 100 0.005 *

Individual markers were tested for association with LIG using Fisher’s exact tests and the EWER was determined using a False Discovery Rate.Only QTL with EWER<0.1 are shownFET Fisher’s exact testa Offspring Genotypic classes. C. c. variegata and C. torelliana alleles were designated Vor T and 1 or 2 for maternal or paternal parental origins,respectively. Therefore, the interspecific F1 maternal and paternal parents of the cross were V1T1 and V2T2, respectively. For loci with MIC4configurations, four offspring genotypic classes were evident: V1V2, V1T2, V2T1 and T1T2. For loci with BC configuration with dominance,two parental classes were evident (either V1T- or V2T-) where the “-” represented pooling over the two T allele(s)*p<0.1, **p<0.05

Table 2 QTL detected by nonparametric Kruskal-Wallis tests in MapQTL

QTL# Trait Mating conf.a Groupb Locus Kc KW EWERd

1 PER BC dom CM8 EMBRA_0164a 12.4 **2 PER MIC4 CM12 EMCRC_0047 16.7 *3 RAT MIC4 CM12 EMCRC_0047 24.5 ***4 RI MIC4 CM12 EMCRC_0047 26.9 ***5 LTH MIC4 CM12 EMCRC_0047 19.7 **6 NO MIC4 CM12 EMCRC_0047 18.8 **7 VOL MIC4 CM12 EMCRC_0047 19.9 **8 QD MIC4 CM12 EMCRC_0047 19.6 **9 WT MIC4 CM12 EMCRC_0047 19.2 **10 SP MIC4 CM12 EMCRC_0047 27.3 ***11 SP IC CM10 EMBRA_0195 15.2 **

Only QTL significant at the EWER of 0.1 are shown. Trait names abbreviated as per Table 1BC Backcross, MIC4 multiple intercross with four alleles, IC intercross, KW EWER Kruskal-Wallis experiment-wise error rateaMarker mating configurations are analysed on a locus by locus basis. See Haseman and Elston (1972) for scheme. In the case ofEMBRA_0164a, the marker was mapped as dominant locus as there was a null allele in the maternal parentb Linkage group on Corymbia map (See Shepherd et al. 2006b); test is performed at each markerc Kruskal-Wallis test statistic (K) valued Kruskal-Wallis experiment-wise error rate determined by applying Bonferroni corrections.*p<0.1, **p<0.05, ***p<0.01

Tree Genetics & Genomes (2008) 4:715–725 719

Tab

le4

QTLparametersdeterm

ined

byInterval

Mapping

Trait

Group

aLocus

bLOD

QTL

Peak

cM(K

)

1.0LOD

supp

ort

interval

cM(K

)c

IM EWER

sign

d

V1V

2eV1T

2T1V

2T1T

2%

Var

expl

fAg

DD/A

Hom

hHet

Hom

/Het

PER

CM8

EMBRA_0

207

2.72

50–10

ns13

.218

.415

.332

.911.3

9.9

-6.2

-0.6

19.7

3.1

6.4

PER

CM12

EMCRC_0

047

7.08

2520

–30

ns7.3

11.6

10.8

54.2

66.0

23.5

-19.6

-0.8

46.9

0.8

58.6

RAT

CM12

EMCRC_0

047

4.99

2520

–30

*0.3

0.3

0.4

0.8

62.5

0.2

-0.2

-1.0

0.5

0.0

-12.1

RI

CM12

EMCRC_0

047

4.59

00–10

ns19

.536

.120

.842

.411.6

11.4

-2.5

-0.2

22.9

15.3

1.5

LTH

CM12

EMCRC_0

047

9.88

2520

–30

ns6.3

8.4

12.3

80.6

70.9

37.2

-33.1

-0.9

74.3

-3.8

-19.3

NO

CM12

EMCRC_0

047

14.97

3525

–40

ns0.1

0.1

1.8

0.3

73.2

0.1

0.8

8.1

0.2

-1.7

-0.1

VOL

CM12

EMCRC_0

047

11.88

2520

–35

ns9.8

14.4

19.8

147.5

70.8

68.9

-61.6

-0.9

137.8

-5.4

-25.4

QD

CM12

EMCRC_0

047

11.05

3530

–35

ns0.1

0.1

1.3

0.2

70.4

0.1

0.6

8.0

0.1

-1.2

-0.1

WT

CM12

EMCRC_0

047

1.07

400–49

.4ns

3.55

E-

035.54

E-

031.30

E-

026.14

E-

037.3

0.0

0.0

3.4

0.0

0.0

-0.3

SP

CM12

EMCRC_0

047

7.44

205–35

***

3.8

9.4

4.6

8.3

37.8

2.3

0.9

0.4

4.5

4.8

0.9

SP

CM10

EMBRA_0

195

3.47

10.5

0–10

.5*

5.3

7.7

6.6

8.2

8.9

1.5

0.4

0.3

2.9

1.1

2.6

OnlyQTLsign

ificantat

EWER≤0

.1by

KW

testsareshow

nIM

EWER

Interval

mapping

experiment-wiseerrorrate,ns

notsign

ificant,Aadditiv

eeffect,D

dominance,D/A

dominance

toadditiv

eratio

,Hom

Hom

ospecificdeviation,

Het

Heterospecific

deviation,

Hom

/Het

Hom

ospecific/Heterospecificratio

aLinkage

grou

pon

Corym

biamap;seeSheph

erdet

al.(200

6b)

bQTLpeak

positio

nindicatedby

distance

incentim

organ(K

osam

bi)from

themarkeron

theleftof

interval

cQTLinterval

specifiedas

therang

ein

centim

organ(K

)foradrop

inLOD

valueof

oneeither

side

oftheQTLpeak

locatio

ndInterval

mapping

experiment-wisesign

ificance

leveldeterm

ined

byPermutationtestingin

MapQTL

eGenotyp

icclassesas

perTable

3fPercentagevariance

explainedby

theQTL

gFollowingBradshaw

andStettler

1995,gene

actio

nwas

estim

ated

asifparentswereinbred

lines;A=(T1T

2-V1V

2)/2;D=(V

1T2+V2T

1)/2-(V1V

2+T1T

2)/2

hHom

=(T1T

2-V1V

2);Het=(V

1T2-V2T

1)*p

<0.1,

**p<0.05

,**

*p<0.01

720 Tree Genetics & Genomes (2008) 4:715–725

PV (Table 4). The effect size for the remaining QTL wasrelatively small (i.e. >12% PV; Table 4).

Direction and gene action of QTL

At all QTL detected, there was a tendency for C. torellianaalleles to increase the genotypic class value relative to theC. c. variegata homospecific genotype value (Table 4).Usually, the C. torelliana homospecific class had thehighest genotypic value of any genotype class; however,in a few cases, for some of the QTL located on CM12, oneor other of the heterospecific classes had the highest values(i.e. The V1T2 class for RI and SP and the T1V2 class forNO, QD and WT; Table 4). For most traits, the C. torellianaalleles had a favourable effect, but because the RI variablerepresented the length of time in days for 25% of cuttings ina clone to root, larger values were unfavourable. For theQTL for RI on CM12, therefore, the most favourable classwas the C. c. variegata type (V1V2; Table 4).

Most QTL exhibited at least partial dominance (D/Aratio>0), with overdominance (D/A>1) indicated at threeQTL (one QTL on CM12 each for NO, QD and WT;Table 4). Almost entirely, additive gene action (D/A<0.5)was evident at the single QTL for RI on CM12 and the twoQTL for SP (one each on CM12 and CM10; Table 4).

Homospecific deviations may exceed heterospecificdeviations up to 59-fold

Homospecific and heterospecific deviations were estimatedto compare the relative importance of standing variationwithin parental species to variation due to species differ-ences. For seven out of eleven QTL, homospecific devia-tions exceeded heterospecific deviations at the QTLdetected (Table 4 absolute values of homospecific/hetero-specific ratios>1). This suggested that for these QTL,species differences had a larger effect on PV than standingallelic variation within parental species. The extreme casewas the QTL for PER on CM12, which had a 58.6-foldlarger homospecific to heterospecific deviation (Table 4).Large absolute ratios were also found for some other QTLlocating to CM12: VOL (-25.4), LTH (-19.3), RAT (-12.1)and the QTL for PER on CM8 (6.4). The homo- toheterospecific deviation ratios were less than 1 at four QTL(QTL for NO, QD, WT and SP on CM12), suggesting thatat these QTL, the PV was determined to a similar extent bystanding variation and species differences (Table 4).

Lignotuber development may be multigenic with dominantgene action

The trait LIG had at least one QTL associated with themarkers EMCRC_40 and EMBRA_0040, which were

separated by 13.8 cM (K) on CM11 (Table 3). The analysisof the contingency table for EMCRC_40 indicated that alloffspring homospecific for C. c. variegata at this locuspossessed lignotubers, and those few individuals withoutlignotubers always had some C. torelliana parentage (i.e.possessed either one or two C. torelliana alleles) at thisregion. Heterospecific genotypes at this QTL also predom-inantly developed lignotubers (33 out of 43). Theseobservations were generally consistent with the lignotuber-ous conditions observed in the parental species of this crossand dominant inheritance observed for lignotubers inhybrids of other eucalypts (Pryor and Byrne 1969). Notall PV was explained by this QTL alone, however, as someheterospecific types lacked lignotubers and some individu-als with C. torelliana homospecific genotypes also pos-sessed lignotubers.

Discussion

Major QTL effects for propagation traits were consistentwith the genetic architecture of species differences

In this study, we describe the genetic architecture for traitsassociated with rooting on stem cuttings in an interspecificoutbred F2 family. Major findings were that most traits hada QTL that clustered to one location onto linkage groupCM12 and that many of these QTL, including those forshoot production and the rooting percentage, were majoreffects. This suggested that many of the traits associatedwith rooting were affected by a single pleiotropic genelocated at this region of the genome. We also contend thatthis genetic architecture was consistent with the mapping ofa species difference between the two parental species, C. c.variegata and C. torelliana. Species differences wereimplicated because of the magnitude of the homospecificto heterospecific deviation ratios for some traits and thecongruence in genetic architecture observed for these traitswith that of species differences detected in other studies.

In an outbred F2 cross derived from outcrossing parentalspecies, PV due to each locus will be a consequence of bothspecies differences and the standing allelic variation withinparental species. In our study, we used QTL architecture tosupport the hypothesis that species differences explainedmuch of the PV for some rooting traits. The accumulatedevidence over a range of studies in both plant and animals,including morphological, physiological or life history traits,suggests that, almost without exception, species differencesare associated with major gene effects (Orr 2001). Therooting rate and associated root quality and shoot produc-tion traits in this study were no exception, with many of thetraits influenced by major effect of QTL explaining morethan 60% of the PV.

Tree Genetics & Genomes (2008) 4:715–725 721

Clustering of QTL suggested pleiotropy for rooting rateand quality traits

Clustering of QTL for rooting traits on the same region onlinkage group CM12, some with large effect, was consistentwith pleiotropy, as pleiotropy is often associated with lociresponsible for major morphological differences amongstspecies (Barrier et al. 2001; Doebley and Lukens 1998;Flatt et al. 2005; Purugganan 1998). Evolutionary changetends to occur by modification to a few regulatory genesrather than large-scale diversification of structural genes(Barrier et al. 2001). Transcriptional regulators are thoughtto be ideal targets for this evolutionary change, becausethey modify an entire developmental “module” via moder-ate pleiotropic effects (Doebley and Lukens 1998). Thisconclusion is supported by experiments which find thatchanges to transcription regulation pathways approximatethe differences found between natural species (Doebley andLukens 1998). Considering the type of cross we havestudied (second-generation hybrid) and the type of factorslikely to be segregating in this cross (species differences), itseemed that pleiotropy, rather than linkage, explained thestrong genetic correlations amongst these variables (Shep-herd et al. 2007) and the clustering of QTL for most rootingtraits on CM12. The exceptions to this may be the QTL forRI and SP. The positioning of the 1.0 LOD support intervalfor the QTL for RI to a different location on CM12 to thatof other QTL, along with its weaker genetic correlationswith other rooting variables, suggests that it may becontrolled by a second, linked locus. Similarly, althoughthe QTL for SP on CM12 overlapped the region believed tocontain a pleiotropic locus, different gene action (largelyadditive) and lower genetic correlations between SP androoting traits suggest the existence of a third locus closelylinked with the pleiotropic locus may be a more parsimo-nious explanation in this case.

Natural selection in divergent environments may producecontrasting alleles for adventitious rooting in the twoparental species

In the present study, the divergent environments inhabitedby the parental species may promote directional selectioncausing species differences in adventitious rooting. The twoparental species differ in their capacity to produce rootedcuttings: C. torelliana is regarded as the high parentwhereas C. c. variegata has poor rooting. Adventitiousrooting is an adaptation to cope with flooding and otherstresses, and a propensity for adventitious rooting has beenfound in tree species or populations that inhabit environ-ments with high soil moisture (Lewty 1990; Marcet 1961;Miller et al. 2003). C. torelliana may be predisposed for thedevelopment of adventitious roots because of high soil

moisture conditions in its natural habitat as a rainforestmargin tree in North Queensland. In contrast, C. c.variegata inhabits lower rainfall environments in SoutheastQueensland and Northern New South Wales (Hill andJohnson 1995) where a capacity to root adventitiously maynot be survival advantage.

Homospecific deviations typically exceeded heterospecificdeviations suggesting species effects for some rooting traits

A combination of interspecific F2 crosses and codominantmarkers provided an approach for quantifying the relativemagnitude of homospecific and heterospecific deviations atindividual QTL. If these deviations can be equated to effectsdue to species effects and standing variation within parentalspecies, they may be informative about the source ofvariation at the QTL, i.e. whether it is due to a speciesdifference or not. Furthermore, the ratio may be predictive ofthe applicability of an inbred line model approximation foranalysis and manipulation of QTL. The homospecificdeviation at a QTL was attributed to species differencesand was determined as the difference between the twohomospecific genotypic classes, i.e. between the C. c.variegata VV and C. torelliana TT. The heterospecificdeviation was attributed to standing variation within theparental species and any heterospecific allelic interactioneffects and was determined as the difference between the twoheterospecific genotypic classes. For “ordinary” morpholog-ical differences between species, heterospecific interactioneffects (intralocus incompatibilities between particular allelesfrom the two parental species) are not thought to be large,although large, negative heterospecific interaction may beassociated with species isolation factors (Orr 2001). Thepropagation traits we studied were not believed to beassociated with species isolation; therefore, we expect theheterospecific deviations to largely represent variation due tostanding variation in this study.

The idea that interspecific tree crosses may be treated asinbred lines for QTL that are substantially fixed foralternative alleles was suggested in the context of hybridpoplars where predictable heterosis occurs for growth insome interspecific combinations (p971 Bradshaw andStettler 1995; Stettler et al. 1988). In their study of growthand adaptive traits, Bradshaw and Stettler assumed that theeffects due to allelic variation within each parental speciesat a QTL were much less than that due to allelic variationbetween parental species. It was argued that naturalselection may produce parents fixed for alternative QTLalleles in a similar way that domestication producesdivergent parents. Hence, for the purposes of QTL analysis,within-species allelic variation was considered negligibleand ignored in the analysis. Subsequent studies in a rangeof species and traits in second-generation hybrids have

722 Tree Genetics & Genomes (2008) 4:715–725

supported the notion that species differences are often dueto genes of major effect (Orr 2001), but the validity of theassumption that effects due to standing allelic variationwithin parental species are small compared to those due tospecies differences remains largely untested. An exceptionis a recent study of both inter- and intraspecific QTL for arange of morphological, physiological or life historyspecies differences in wild annual sunflowers, whereintraspecific QTL were generally smaller than interspecificQTL (Lexer et al. 2005).

In our study, we used the ratio of homospecific toheterospecific deviations at QTL to quantify the relativecontributions of species differences and standing variationin parental species to PV within the same cross. For QTLanalysis, homospecific deviations typically exceeded heter-ospecific deviations (ratio >1), and, for some traits, thehomospecific deviation was large, up to 20–59-fold largerthan the heterospecific deviation, consistent with these QTLrepresenting species differences (See Table 3).

Ratio of homo- to heterospecific deviations—a guideto the predictability of gene action

Where PV is primarily determined by species differences ofmajor effect, the homo- to heterospecific deviation ratio(and, thus, the D/A ratio) for a single major QTL maylargely determine gene action for the trait. Hence, the D/Aratio estimated from this major QTL in one cross may beindicative of gene action in other crosses between theseparental species. Estimates of additive intralocus geneaction in this cross were based on homospecific deviationsand were not influenced by the heterospecific deviations.Dominance deviations, on the other hand, were affected bythe heterospecific genotypic class averages, which contrib-ute to the “heterozygote” value. Hence, for a trait-like shootproduction, where standing allelic variation and speciesdifferences were of a similar order of magnitude (i.e. thehomospecific/heterospecific deviation ratios were relativelylow (0–3)), large fluctuations in the “heterozygote” valuemight arise in different crosses depending on the particularinterspecific allelic combinations that arise between theindividual parents. Shoot production was not thought to bea trait under strong divergent selection in the parentalspecies; hence, large allelic variation probably still existswithin both parental species. It might be expected then, thatwithin-species allelic differences would contribute similarlevels of variance as species differences at QTL for thistrait. By comparison, PER, RAT, LTH and VOL, all hadratios larger than 10, suggesting that species differenceswere much greater determinates of PV in these traits. Forthese traits, an inbred line approximation may be inferred,and, assuming the sampled standing allele variation isrepresentative of the parental species, fluctuation in the

“heterozygote” value and, hence, the D/A ratio, may berelatively insignificant. Therefore, the D/A ratio estimatedfrom this cross may be predictive of other crosses betweenthese parental species.

The power of the homospecific to heterospecific ratio forinference at the population or species level has not yet beentested. Clearly, there are limitations using ratios based onpoint estimates and small samples of allelic variation withineach parental species. But, in crosses where species differ-ences are expected and large homospecific to heterospecificratio are found, then an inbred line cross approximation maybe applicable and the D/A ratio estimated from one crossshould be representative of other crosses. Where lowhomospecific to heterospecific ratios are found, however,this suggests that species differences are not the majordeterminants of cross PV and, hence, an inbred line crossapproximation will not be applicable. In these cases, the D/Aratio from the study cross may not be indicative of the D/Aratio of other crosses from the parental species.

Genetic control of lignotubers

In accord with earlier studies on the inheritance oflignotubers in interspecific F2 hybrids of eucalypts betweenparental species of contrasting phenotypes (Pryor andByrne 1969), we observed segregation and largely domi-nant inheritance (90% of hybrid seedlings had lignotubers)in the second-generation Corymbia hybrid. Our study alsosuggested at least one but probably two or more indepen-dent QTL were involved in lignotuber formation as both asuggestive and significant QTL were detected on differentlinkage groups (a suggestive QTL at comparison wise errorrate p=0.041 was detected on CM7 (test not shown)).Multigenic inheritance was further supported by a lack offit to 3:1 presence: absence that may be evident if controlwas by a single locus with dominant gene action. Althoughmultigenic control of lignotuber formation seems likely,trait penetrance factors or linkage of loci involved in hybridinviability to genes controlling lignotuber development mayalso account for the observed segregation ratio.

Lignotuber formation has been associated with anenhanced ability for coppicing, a process of regenerationvia epicormic shoots of meristematic origin in eucalypts(Burrows 2002). Our study suggested that in the Corymbiahybrid, genetic control of lignotuber formation was inde-pendent of the rooting percentage and shoot production, asQTL for LIG did not reside on linkage groups where QTLwere identified for the other traits. Although weakphenotypic correlations were evident between lignotuberformation and propagation traits (Shepherd et al. 2007), thismay be a consequence of a correlated response due to otherfactors such as seedling vigour. In E. globulus for example,a phenotypic correlation exists such that trees possessing a

Tree Genetics & Genomes (2008) 4:715–725 723

lignotuber also have enhanced coppicing ability; nonethe-less, the two traits are largely genetically independent(Whittock 2003). Phenotypic correlations were believed tobe due to the presence of peripheral vascular tissue inlignotubers acting as a sink for carbohydrate and waterrather than due to a common genetic basis for the two traits(Noble 2001; Whittock 2003).

Acknowledgements This research was supported by funding fromthe Australian Research Council Linkage grant LP0348613, Queens-land Department of Primary Industries and Fisheries (QDPI&F)-Forestry, QDPI&F Horticulture and Forestry Science, and theCooperative Research Centre for Forestry. We thank R. Stokoe andstaff of the QDPI&F Horticulture and Forestry Science for generatingthe F2 cross and conducting the assessments in the nursery, as well asD. Waters and C. Raymond for helpful discussions during thepreparation of the manuscript.

References

Baker A, Walker SM (2005) Assessment of the Relative Amenabilityto Vegetative Propagation by Leafy Cuttings of 14 Tropical andSubtropical Eucalyptus and Corymbia Species. In: Sasaki S, IshiiK, Suzuki K, Sakurai S (eds) Plantation Technology in TropicalForest Science, Tokyo, p 336

Barrier M, Robichaux RH, Purugganan MD (2001) Acceleratedregulatory gene evolution in an adaptive radiation. Proc NatAcad Sci 98:10208–10213

Benjamini Y, Hockberg Y (1995) Controlling the false discovery rate:a practical and powerful approach to multiple testing. J R StatSoc B 57:289–300

Bradshaw HD (1998) Case history in genetics of long-lived plants:molecular approaches to domestication of a fast-growing foresttree: Populus. In: Paterson AH (ed) Molecular Dissection ofComplex Traits. CRC, Boca Raton, pp 219–228

Bradshaw HD, Grattapaglia D (1994) QTL mapping in interspecifichybrids of forest trees. For Genet 1:191–196

Bradshaw HDJ, Stettler RF (1995) Molecular genetics of growth anddevelopment in Populus. IV. Mapping QTLs with large effects ongrowth, form, and phenology traits in a forest tree. Genetics139:963–973

Brondani RPV, Brondani C, Tarchini R, Grattapaglia D (1998)Development, characterisation and mapping of microsatellitemarkers in Eucalyptus grandis and E. urophylla. Theor ApplGenet 97:816–827

Brondani RPV, Brondani C, Grattapaglia D (2002) Towards a genus-wide reference linkage map for Eucalyptus based exclusively onhighly informative microsatellite markers. Molec GenetGenomics 267:338–347

Burrows GE (2002) Epicormic stand structure in Angophora,Eucalyptus and Lophostemon (Myrtaceae) - implications for fireresistance and recovery. New Phytologist 153:111–131

Byrne M, Marquez-Garcia MI, Uren T, Smith DS, Moran GF (1996)Conservation and genetic diversity of microsatellite loci in thegenus Eucalyptus. Aust J Bot 44:331–341

Campinhos E Jr, Ikemori Y (1983) Production of vegetative propagulesof Eucalyptus spp. by rooting of cuttings. In: Norman C (ed)Proceedings of the 2nd symposium on planted forests in theneotropics: a source of energy. IUFRO Working Party 51.07-09.IUFRO, Vicosa, pp 60–67

Carnegie AJ (2007) Forest health condition in New South Wales,Australia, 1996–2005. 2. Fungal damage recorded in eucalypt

plantations during forest health surveys. Australas Plant Pathol36:225–239

Churchill GA, Doerge RW (1994) Empirical threshold values forquantitative trait mapping. Genetics 138:963–971

de Assis TF (2000) Production and use of Eucalyptus hybrids forindustrial purposes. In: Dungey H, Dieters MJ, Nikles DG (eds)Hybrid Breeding and Genetics of Forest Trees. Proceedings ofQFRI/CRC-SPF Symposium. Noosa, Queensland, Australia, pp63–74

Doebley J, Lukens L (1998) Transcriptional regulators and theevolution of plant form. Plant Cell 10:1075–1082

Flatt T, Tu MP, Tatar M (2005) Hormonal pleiotropy and the juvenilehormone regulation of Drosophila development and life history.Bioessays 27:999–1010

Foster G, Campbell R, Adams W (1984) Heritability, gain and Ceffects in rooting of western hemlock cuttings. Can J For Res14:628–638

Glaubitz J, Emebiri MG (2001) Dinucleotide microsatellites inEucalyptus sieberi: inheritance, diversity and improved scoringof single base differences. Genome 44:1041–1045

Grattapaglia D, Bertolucci FL, Sederoff RR (1995) Genetic mappingof QTLs controlling vegetative propagation in Eucalyptusgrandis and E. urophylla using a pseudo-testcross strategy andRAPD Markers. Theor Appl Genet 90:933–947

Han K, Bradshaw HDJ, Gordon MP, Han KH (1994) Adventitious rootand shoot regeneration in vitro is under major gene control in an F2family of hybrid poplar (Populus trichocarpa × P. deltoides). ForGenet 1:139–146

Haseman JK, Elston RC (1972) The investigation of linkage betweenquantitative trait and a marker locus. Behav Genet 2:3–19

Hill KD, Johnson LAS (1995) Systematic studies in the eucalypts 7. Arevision of the bloodwoods, genus Corymbia (Myrtaceae).Telopea 6:185–504

Johnson WC, Jackson LE, Ochoa O et al. (1999) Lettuce, a shallow-rooted crop, and Lactuca serriola, its wild progenitor, differ atQTL determining root architecture and deep soil water exploita-tion. Theor Appl Genet 101:1066–1073

Johnson IG, Carnegie AJ, Henson M (2004) Selecting for diseasetolerant Corymbia citriodora subsp. variegata in New SouthWales, Australia. In: Borralho N, Pereira J, Marques C et al. (eds)International IUFRO Conference of the SP2.08.03 on Silvicultureand Improvement of Eucalypts. IUFRO, Aveiro, p 184

Jones M, Stokoe R, Cross M et al. (2001) Isolation of microsatellite locifrom spotted gum (Corymbia variegata), and cross-speciesamplification in Corymbia and Eucalyptus. Mol Ecol Notes1:276–278

Lander E, Kruglyak L (1995) Genetic dissection of complex traits:guidelines for interpreting and reporting linkage results. NatureGenet 11:241–247

Lee D (2007) Development of Corymbia species and hybrids forplantations in eastern Australia. Aust For 70:11–17

Lee D, Brawner J, Pomroy P (2004) Genetic variation in early growthand disease resistance of Corymbia citriodora subsp. variegata insouthern Queensland, Australia. In: Borralho N, Pereira JS,Marques C et al. (eds) International IUFRO Conference of theSP2.08.03 on Silviculture and Improvement of Eucalypts.IUFRO, Aveiro, pp 185–186

Lee DJ, Debuse VJ, Pomroy PC, Robson KJ, Nikles DG (2005)Developing eucalypt hybrids for plantations in marginal areas ofnorthern Australia. RIRDC, Canberra, pp 1–55

Lewty MJ (1990) Effects of water logging on the growth and waterrelations of tree Pinus taxa. For Ecol Manag 30:189–201

Lexer C, Heinze B, Alia R, Rieseberg LH (2004) Hybrid zones as atool for identifying adaptive genetic variation in outbreedingforest trees: lessons from wild annual sunflowers (Helianthusspp.). For Ecol Manag 197:49–64

724 Tree Genetics & Genomes (2008) 4:715–725

Lexer C, Rosenthal DM, Raymond O, Donovan LA, Rieseberg LH (2005)Genetics of species differences in the wild annual Sunflowers,Helianthus annuus and H. petiolaris. Genetics 169:2225–2239

Lorz H, Wenzel G (2005) Molecular marker systems in plant breedingand crop improvement. Springer, Heidelberg

Marcet E (1961) Investigation of the geographic variability ofmorphological characteristics in Populus deltoides Bartr. SilvaeGenetica 10:161–172

Marques CM, Vasquez-Kool J, Carocha VJ et al. (1999) Geneticdissection of vegetative propagation traits in Eucalyptus tereti-cornis and E. globulus. Theor Appl Genet 99:936–946

Marques C, Brondani R, Grattapaglia D, Sederoff R (2002) Conserva-tion and synteny of SSR loci and QTLs for vegetative propagationin four Eucalyptus species. Theor Appl Genet 105:474–478

Marques CM, Carocha VJ, Pereira de Sá AR et al. (2005) Verificationof QTL linked markers for propagation traits in Eucalyptus. TreesGenetics and Genomes 1:103–108

Miller CR, Ochoa I, Nielsen KL, Beck D, Lynch JP (2003) Geneticvariation for adventitious rooting in response to low phosphorusavailability: potential utility for phosphorus acquisition fromstratified soils. Functional Plant Biology 30:973–985

Milliken GA, Johnson DE (1984) Analysis of Messy Data. VanNortrand Reinhold, New York

Noble J (2001) Lignotubers and meristem dependence in mallee(Eucalyptus spp.) coppicing after fire. Aust J Bot 49:31–41

Orr HA (2001) The genetics of species differences. Trends in Ecology& Evolution 16:343–350

Paterson AH (1998) QTL Mapping in DNA Marker-Assisted Plantand Animal Improvement. In: Paterson AH (ed) MolecularDissection of Complex Traits. CRC, Boca Raton, pp 131–143

Pryor LD, Byrne OR (1969) Variation and taxonomy in Eucalyptuscamaldulensis. Silvae Genetica 18:64–71

Purugganan MD (1998) The molecular evolution of development.BioEssays 20:700–711

Shepherd M, Huang S, Eggler P et al. (2006a) Congruence in QTL foradventitious rooting in unrelated outbred and inbred-like Pinuselliottii × P. caribaea hybrids resolves between and within specieseffects. Mol Breed 18:11–28

Shepherd M, Kasem S, Lee D, Henry R (2006b) Construction ofmicrosatellite linkage maps for Corymbia. Silvae Genetica 55:228–238

Shepherd M, Pomroy P, Dieters MJ, Lee D (2007) Genetic control ofpropagation traits in a single Corymbia torelliana × C. citriodoraspp variegata family. Can J For Res 37(12):2563–2574

Steane DA, Vaillancourt RE, Russell J et al. (2001) Development andcharacterisation of microsatellite loci in Eucalyptus globulus(Myrtaceae). Silvae Genetica 50:89–91

Stettler RF, Fenn RC, Heilman PE, Stanton BJ (1988) Populustrichocarpa × Populus deltoides hybrids for short-rotation culture:variation patterns and 4-year field performance. Can J For Res18:745–753

Tanksley SD, Young ND, Paterson AH, Bonierbale MW (1989) RFLPmapping in Plant Breeding: New Tools for an Old Science. Bio/Technology 7:257–264

Van Ooijen J, Sandbrink H, Purimahua C et al. (1993) Mappingquantitative genes involved in a trait assessed on an ordinal scale:A case study with bacterial canker in Lycopersicon peruvianum.In: Yoder J (ed) Molecular Biology of Tomato. Technomic,Lancaster, pp 59–74

Van Ooijen J, Boer M, Jansen R, Maliepaard C (2002) MapQTL (tm)Version 4.0, Software for the calculation of QTL positions ongenetic maps. Plant Research International, Wageningen

Whittock SP (2003) Genetic control of coppice and lignotuberdevelopment in Eucalyptus globulus. Aust J Bot 51:57–67

Tree Genetics & Genomes (2008) 4:715–725 725