Landscape and oceanic barriers shape dispersal and ...€¦ · Landscape and oceanic barriers shape dispersal and population structure in the island nematode Pristionchus paciﬁcus

Landscape and oceanic barriers shape dispersal andpopulation structure in the island nematodePristionchus pacificus

KATY MORGAN1, ANGELA MCGAUGHRAN1, SEELAVARN GANESHAN2,MATTHIAS HERRMANN1 and RALF J. SOMMER1*

1Department of Evolutionary Biology, Max Planck Institute for Developmental Biology, Spemannstr.37, Tübingen, Germany2Mauritius Sugarcane Industry Research Institute, Réduit, Mauritius

Received 9 October 2013; revised 12 December 2013; accepted for publication 12 December 2013

Despite the biological importance and diversity of nematodes, little is known of the factors influencing theirdispersal and shaping their evolutionary history. Populations of the cosmopolitan species Pristionchus pacificus arecharacterized by high genetic diversity and strong spatial structure, which contrasts with patterns detected innematode species such as Caenorhabditis elegans. The environmentally heterogeneous volcanic Mascarene Islandsprovide an ideal setting for investigating fine-scale patterns of nematode migration and gene flow. Based on theanalysis of data from 19 nuclear microsatellites and one mitochondrial marker, we infer support for the colonizationof both La Réunion Island and Mauritius from similar multiple geographical sources. Although the long-termpersistence of populations on both islands is well supported, the historical colonization of one island from theother cannot be discounted. In fact, periodic, bi-directional migration between the islands following their initialcolonization is strongly supported in isolation with migration analyses, supporting the occurrence of raretrans-oceanic dispersal events in P. pacificus. Through a combination of population and landscape genetic analyseswe also infer non-uniform dispersal across the landscape on the island of La Réunion, probably mediated by themovements of beetle hosts. Collectively, we show that gene flow in P. pacificus is limited by environmental andoceanic barriers, and shaped by the intricacies of the nematode–beetle host interaction. © 2014 The LinneanSociety of London, Biological Journal of the Linnean Society, 2014, 112, 1–15.

ADDITIONAL KEYWORDS: island biogeography – population genetics.

INTRODUCTION

Nematodes are among the most diverse of all animalphyla, occupying a vast area of the earth’s surfaceand exhibiting considerable diversity in terms ofreproductive strategy and life history (Boucher &Lambshead, 1995; De Ley, 2006). The development ofnematode species such as Pristionchus pacificus andCaenorhabditis elegans as model systems in evolu-tionary biology has greatly advanced understandingof developmental processes (e.g. Hong & Sommer,

2006), and an integration of population genetics to theP. pacificus system now enables investigation of howphenotypic and developmental changes are initiatedat the micro-evolutionary level (Sommer, 2009).However, despite their biological importance nema-todes have been relatively neglected in populationgenetic and biogeographical studies, and the factorsshaping their evolutionary history remain a substan-tial gap in our understanding of global biodiversity. Inparticular, the capacity for nematode dispersal com-bined with the role of landscape barriers in limitinggene flow and shaping population structure and dis-tribution are key aspects of nematode ecology aboutwhich little is known.

Most of the nematode species that have beenstudied in terms of population genetics are parasitic

*Corresponding author:E-mail: [email protected] first two authors contributed equally to this work and arelisted as joint first authors.

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Biological Journal of the Linnean Society, 2014, 112, 1–15. With 4 figures

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species of agricultural or medical importance. Highmigration and the consequent homogenization ofspatial genetic structure is often detected, and attrib-uted to the anthropogenically mediated movement ofhost individuals and populations (e.g. Blouin et al.,1995; Grillo et al., 2007; Wielgoss et al., 2008). Thesepatterns are not shared by all nematodes, however;restricted gene flow and strong spatial structurehave been reported in both the Antarctic nematodeScottnema lindsayae (Courtright et al., 2000) andseveral species of marine nematodes (Deryckeet al., 2005, 2008) – species that lack clear anthropo-genic associations. The model species P. pacificusand C. elegans also lack an association with livestockhosts, although C. elegans is commonly found incompost heaps and rotting vegetation and fruit –habitats that tend to be associated with humans(Andersen et al., 2012). Although P. pacificus andC. elegans share an androdioecious lifestyle and theability to live freely within the soil column, they differconsiderably in terms of population structure, withlow genetic variation and weak population structurein global populations of C. elegans contrasting withhigh diversity and strong population structuredetected in P. pacificus (Zauner et al., 2007; Andersenet al., 2012; Morgan et al., 2012). In C. elegans, long-distance dispersal in association with human andagricultural transport is thought to have been fol-lowed by global selective sweeps, homogenizingspatial genetic structure (Andersen et al., 2012).

Dispersal in P. pacificus is likely to be largely medi-ated by the movement of scarab beetle hosts, withwhich it has a necromenic association (Herrmannet al., 2006, 2010; Morgan et al., 2012). This involvesthe nematodes infesting a host and entering a state ofarrested development until host death, upon whichthe nematodes emerge and begin feeding on themicrobes that grow on the beetle carcass. Unlike themajority of Pristionchus species, which are host-specific, P. pacificus is found in association with anumber of scarab beetle species and is generallyfound with different host species across the four con-tinents that encompass its distribution (Asia, Europe,Africa, America; see Herrmann et al., 2007, 2010).Although the widespread distribution of P. pacificussuggests a high capacity for long-distance dispersal,strong population structure detected on a finescale, using mitochondrial and nuclear microsatellitemarkers, suggests limited gene flow between geo-graphically proximate populations (Morgan et al.,2012). Landscape barriers are likely to play animportant role in restricting gene flow, and thusmaintaining the strong population structure withinP. pacificus. Volcanic islands are ideal settings forinvestigating such scenarios, as their landscape isoften characterized by dramatic altitudinal and envi-

ronmental changes. Additionally, as they have neverbeen connected to one another or to the mainland,colonization of and dispersal between the islandsnecessitates trans-oceanic dispersal events.

The Mascarenes, although less intensively studiedthan the Galapagos and Hawaiian Islands, representan important volcanic island system (Fig. 1). Thechain consists of three islands, Rodriguez, Mauritiusand La Réunion, which arose from the Indian Oceanbetween 15 Mya (Rodriguez) and 2 Mya (La Réunion).As the youngest of the islands, La Réunion is thelargest and most environmentally heterogeneous,with steep altitudinal gradients and a maximumaltitude of 3070 m above sea level (a.s.l.) (Strasberget al., 2005). La Réunion is also the only MascareneIsland with a currently active volcano. The islandharbours a high genetic diversity of P. pacificus,which has been found in association with several ofthe species comprising La Réunion’s scarab beetlefauna (Herrmann et al., 2010; Morgan et al., 2012).

Population genetic analyses of P. pacificus on LaRéunion Island have detected four highly divergentmitochondrial and nuclear (microsatellite) lineages(Herrmann et al., 2010; Morgan et al., 2012), whichmodelling analyses have shown to be the result of atleast four independent colonizations (McGaughran,Morgan & Sommer, 2013). Morgan et al. (2012)detected differences in the distributions of theselineages on La Réunion, which are differentiallyrestricted to the humid, eastern region of the island,to arid western areas, or to high-altitude sites of morethan 2000 m a.s.l. This suggests that barriers causedby environmental and altitudinal variation may beplaying a role in restricting dispersal and migrationbetween populations. In addition, approximately200 km separate La Réunion from the neighbouringisland of Mauritius, and both the expanse of oceanand environmental differences between the islandsare potential barriers to inter-island dispersal andmay play a role in defining population structure inP. pacificus. Indeed, a prolonged period of independ-ent evolution, together with different selection pres-sures driven by environmental differences betweenthe islands, is thought to have led to the considerablegenetic and phenotypic differentiation of La Réunionand Mauritius populations of the Mascarene greywhite-eye Zosterops borbonicus, a small passerinebird endemic to the islands of La Réunion and Mau-ritius (Mila et al., 2010).

Here, we sample the beetle fauna of the remainingMascarene Islands, Mauritius and Rodriguez, as wellas two other islands within the Indian Ocean – theSeychelles and Mayotte – with the aim of more pre-cisely defining the distribution and dispersal patternsof P. pacificus within the Mascarene region (Fig. 1).Despite extensive sampling, we find P. pacificus only

2 K. MORGAN ET AL.

© 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 112, 1–15

on La Réunion Island’s geographically closest island,Mauritius. We subsequently compare the new Mau-ritius samples with our existing La Réunion dataset,performing landscape genetic analyses to investigatepatterns of migration between these two islands, aswell as between populations on La Réunion Islandto identify specific barriers to dispersal. Using 19microsatellite (‘single tandem repeat’; STR) markers,designed and utilized in Morgan et al. (2012), wegenerate an STR dataset for the new Mauritiussamples. In addition, we use STR and mitochondrial(mt) data from Herrmann et al. (2010) and Morganet al. (2012) to address the following specific ques-tions: (1) Do Mauritius and La Réunion Islandharbour a similar diversity of P. pacificus? (2) Follow-ing colonization, have geographical and oceanicbarriers effectively reduced genetic contact betweenislands, or is there evidence for historical and/orcurrent gene flow? (3) How much gene flow currentlyoccurs between geographical regions within LaRéunion Island, and what role do landscape barriersplay in facilitating or preventing this?

METHODSSAMPLE COLLECTION

A variety of beetle species were sampled from severallocations across Mauritius, Rodriguez, Mayotte andthe Seychelles (Fig. 1; Table 1; Table S1). All islandswere sampled by collecting beetles from a number oflocations and variety of habitat types across the land-scape over a 2-year period (Table S1). Specific localitiesand abbreviations used throughout the text, as wellas the date of sample collection, are given in Table 1. Inmost cases sampling used light traps, although onMauritius several samples were also obtained fromsugarcane fields across the island by employees ofthe Mauritius Sugarcane Industry Research Institute(Table 1). Samples were processed according to theprotocols of Herrmann et al. (2006). Briefly, the freshlykilled carcasses of beetles were placed on individualnematode growth medium (NGM) plates (Brenner,1974), seeded with the Escherichia coli strain OP50and monitored daily over a period of 3 weeks for theemergence of adult nematodes. The nematodes were

Mayotte

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TBTBG

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BIOGEOGRAPHY OF P. PACIFICUS IN THE INDIAN OCEAN 3


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4 K. MORGAN ET AL.


picked individually onto freshly seeded NGM plates onemergence. As in Morgan et al. (2012), isogenic lineswere generated from each adult nematode by allowingthem to reproduce and maintaining their offspring inculture. Throughout this manuscript, the term ‘strain’will refer to these laboratory-maintained, isogeniclines. These isogenic lines were maintained through atleast ten generations of selfing, after which anyheterozygosity present in the original P0 generationwill have been eroded. This was necessary for thepresent study, despite the associated caveat of lostheterozygosity, as a single nematode yields insufficientDNA for sequencing and STR genotyping.

DNA SEQUENCING AND GENOTYPING

STR genotypes were available at 19 loci for 223 strains,sampled from 11 localities across La Réunion in aprevious study (Morgan et al., 2012; see Table 1). Allbeetles collected from Rodriguez, Mayotte and theSeychelles were negative for P. pacificus (Table S1).Thirty-five P. pacificus strains were isolated from Mau-ritius beetles collected at a number of sampling locali-ties, after sampling over a 2-year period. These strains(Table 1) were genotyped at the same 19 loci (whichincluded 14 di-nucleotide, four tri-nucleotide, onetetra-nucleotide and one penta-nucleotide repeat) asthe available La Réunion strains, using theprimer pairs, protocol and cycling conditions detailedin Morgan et al. (2012). Although it is possiblethat mutations could occur during the formation ofisogenic lines, given the low mutation rate estimatedfor STR mutations using mutation accumulation lines(31 mutations identified in 41 STR markers, after 142generations in 82 lines; Molnar et al., 2012), this isunlikely to have had a significant impact on ourdataset. Our final STR dataset includes 258 strainsfrom 14 and five sampling localities on La Réunionand Mauritius, respectively. Sequence data fromthe ND4 and ND6L mt genes were available for272 strains sampled from 17 localities on La RéunionIsland (Morgan et al., 2012). These loci, which togetherform a 760-bp fragment, were also sequenced for the 35new Mauritius strains using the primers, protocol andcycling conditions detailed in Herrmann et al. (2010).All newly generated mt sequences were deposited inGenBank, with accession numbers KJ577661–KJ577695. STR data generated in this study (for theMauritius strains) are available from Dryad, withaccession numbers, doi:10.5061/dryad.7194t.

POPULATION GENETIC ANALYSIS

Characterizing the diversity of P. pacificus onMauritius and La RéunionOur first aim was to determine whether the samegenetic lineages are present on Mauritius and La

Réunion islands, and how Mauritius populationsdiffer from those on La Réunion. A neighbour-netnetwork was constructed from the STR datasetusing Splitstree ver. 4.11.3 (Huson & Bryant, 2006).Network ver. 4.500 (Bandelt, Forster & Röhl, 1999)was used to construct a median-joining haplotypenetwork with the mt data, using the weight param-eters at their default of 10, and a connection costof ε = 10. Population structure within the STRdataset was further examined using InStruct (Gao,Williamson & Bustamante, 2007), an extension of thecommonly used program STRUCTURE (Pritchard,Stephens & Donnelly, 2000) designed especially forself-fertilizing or highly inbred species or populations.The software uses a Bayesian algorithm to infer thenumber of distinct populations present within asample, and to probabilistically assign individuals topopulations without any prior sampling information.Rather than assuming random mating and Hardy–Weinberg equilibrium, assumptions of STRUCTUREthat are likely to be violated in selfing or inbredpopulations, InStruct accounts for selfing and/orinbreeding and allows their rates to vary betweeninferred clusters (Gao et al., 2007). InStruct haspreviously been used alongside STRUCTURE ver.2.2 and was found to return consistent resultsfor P. pacificus (Morgan et al., 2012). The InStructanalysis was used to infer the most likely numberof genetic clusters (K) in the dataset, and toprobabilistically assign individual strains to each ofthese clusters. Five replicate runs were performed forvalues of K between 1 and 20, each with a burn-in of10 000 generations and 100 000 iterations, andresults were checked for concordance.

To statistically evaluate levels of genetic differen-tiation between Mauritius and La Réunion popula-tions, we estimated pair-wise genetic differentiationbetween populations with four samples or more usingRST (significance determined over 1000 permutations)and Jost’s D statistics, as estimated using Arlequinver. 3.0 (Excoffier & Schneider, 2005) and SMOGDver. 1.2.5 (Crawford, 2010), respectively. Previousresults indicated that geography has a stronger influ-ence on population structure than host beetle species,and that strains collected from different beetle specieswithin a sampling locality show minimal differentia-tion from one another (Morgan et al., 2012). Thus, wedefine populations according to sampling locality. Thestandard diversity statistics, allelic richness and genediversity (HE), were estimated from the STR data foreach sampling locality using Arlequin. Rarefied allelicrichness (Ar4), which controls for the effect of samplesize on estimates of allelic richness, was also calcu-lated using ADZE ver. 1.0 (Szpiech, Jakobsson &Rosenberg, 2008). These analyses were repeated afterpooling samples more broadly into island-specific



populations (i.e. La Réunion: 14 localities vs. Mauri-tius: five localities).

Gene flow between La Réunion and MauritiusNext, to investigate divergence and gene flow betweenMauritius and La Réunion populations, an isolationwith migration (IM) model was fitted to the combinedSTR and mt dataset using IMA2 (Hey & Nielsen,2007). This approach is designed to detect any histori-cal migration that has occurred between populationssince their initial separation. The IMA2 approachinvolves the simultaneous estimation of six param-eters using a Markov chain Monte Carlo (MCMC)sampling strategy. These parameters include: threeq parameters, corresponding to θ, one for each of theancestral and two daughter populations (whereθ = 4Neμ, Ne is the effective population size and μ is thegeometric mean of the mutation rates of all markersanalysed); t, the time since the initial divergence of thedaughter populations; and m1 and m2, the migrationfrom population 2 into population 1 and vice versa,respectively. Analyses were performed using pooledMauritius and La Réunion populations as the twodaughter populations. As the La Réunion dataset issubstantially larger than the Mauritius dataset, toreduce computational complexity 35 individuals weresampled from the La Réunion population at random foranalysis. Analyses were repeated using five independ-ent sub-samples of the La Réunion population, toensure no bias was introduced by the sub-samplingprocedure.

Several preliminary runs were carried out for eachdataset to optimize heating schemes and define theupper boundaries for the parameter priors. The per-formance of these runs was assessed through exami-nation of the swapping rates between chains, theeffective sample sizes (ESSs) and the trend plots. Ageometric heating scheme was used with 40 chains,and the parameters ha and hb set to 0.975 and 0.75,respectively (-hfg -hn40 -ha0.975 -hb0.75). Runs werecontinued until at least 1 000 000 genealogies weresampled through the MCMC procedure (at least100 000 000 MCMC steps with 100 steps betweensaved genealogies). Three independent runs were con-ducted for each dataset and convergence confirmed.An mt mutation rate of 7.6 × 10−8 mutations per bpper generation, as estimated for P. pacificus usingmutation accumulation lines (Molnar et al., 2011),was used to calibrate divergence estimates.

Gene flow and barriers to recent migration withinLa Réunion populationsHere, we aimed to detect recent migration betweenpopulations and across the landscape, restricting ouranalysis to the more densely sampled La RéunionIsland and using the STR dataset for all analyses. We

used BAYESASS ver. 3.0 (Wilson & Rannala, 2003)to perform Bayesian inference of recent migration(i.e. within the last one to three generations) in a rela-tively assumption-free manner. Recent immigrantsdisplay temporary disequilibrium in their multi-locusgenotypes relative to the population where they werecaptured; because this approach relates only to thepast one to three generations, there are no assump-tions needed regarding Hardy–Weinberg equilibrium,mutation or effective population size. For a given run,BAYESASS provides an estimate of the mean posteriordistribution of m (migration), for all population pairs,which is the proportion of individuals in population ithat have population j as their ancestral (past one tothree generations) location. This provides both theproportion of residents and the proportion of immi-grants in each population. To generate mixing param-eters for migration (-m), allele frequency (-a) andinbreeding coefficients (-f) between the recommended20 and 60%, BAYEASS was run with these parametersinitially all set to 0.99. Burn-in was set to 1 000 000and 10 000 000 iterations were performed, with a sam-pling interval of 100. A trace file was generated at theend of each run, and this was checked for convergencein TRACER ver. 1.5 (Rambaut & Drummond, 2007).

Several methods were used to detect the presence ofbarriers to dispersal within the Réunion landscape.ALLELES IN SPACE ver. 1.0 (‘AIS’; Miller, 2005) isa program for the joint analysis of inter-individualspatial and genetic information using genotypic (STR)data and spatial/coordinate (utm) information. AllelicAggregation Index analysis (AAIA) was performed totest the null hypothesis that each allele at a locus isdistributed at random across a landscape (i.e. withoutaggregation/genetic structure). An index, Rj, is calcu-lated, where Rj = 1 indicates a random distribu-tion and Rj < 1 indicates clumping or aggregation.This analysis was run with 1000 permutations,with the area encompassed by each sample definedby both maximum and minimum utm coordinates,and by an empirical estimate derived from thePlotSampleLocations function in AIS. Next, landscapeshape interpolation analysis was performed. This pro-cedure produces a 3D surface plot, where x- and y-axescorrespond to geographical locations and surfaceheights (z-axes) represent genetic distances. The plotcontains peaks in areas where there are large geneticdifferences and in this way can be used to identifylandscape barriers to gene flow. This analysis usedDelaunay’s triangulation method (Watson, 1992;Brouns, De Wulf & Constales, 2003) to derive a con-nectivity network and residual genetic distances. Afterthese calculations, the plot was opened in the GeneticLandscape Interpolation Editor/Viewer of AIS using adistance weighting parameter (a) of 1, and grid set-tings of 80 × 80.

6 K. MORGAN ET AL.


Another multivariate method, the spatial principalcomponents analysis (sPCA) of Jombart, Devillard& Balloux (2010), was also performed using theadegenet package in R to identify spatial geneticpatterns. This technique is often used in conjunctionwith traditional PCA approaches because it is morepowerful at retrieving non-trivial spatial genetic pat-terns. In particular, the sPCA method can be used toidentify genetic clines. Here, genetic data and utmcoordinates were used to produce a Delaunay trian-gulation network and sPCA.

To complete the Boundary analyses, WOMBSOFT(Crida & Manel, 2007), which is a collection ofWombling-based R functions that analyse individu-ally geo-referenced multilocus genotypes for the infer-ence of genetic boundaries, was used. WOMBSOFTrequires geo-coordinates to be different for each indi-vidual, and thus a ‘jitter’ function was applied to utmcoordinates in R to vary population-specific coordi-nates by a null factor. The output from WOMBSOFTincludes two maps, the first of which shows variationsin the systemic function and in the mean directionof the barrier/gradient in the studied area. Thesecond map shows candidate boundary elements thatare significant at the chosen level. Before producingmaps, the Mirror function in WOMBSOFT (m = 1.2)was used to add points just outside the convex hullthat are similar to the points just inside the convexhull, thus reducing potential border effects due toa low density of individuals close to the border. TheWombling function was then applied using a band-width (h) of 1.4. Finally, the CandidateBoundariesfunction was employed using h = 1.4 and a 30 percen-tile (i.e. pB = 0.3) at each point of the grid.

RESULTS

Despite sampling of additional Indian Ocean Islands,Mauritius, Rodriguez, Mayotte and the Seychelles(Fig. 1; Table S1), P. pacificus isolates were found onlyon Mauritius and La Réunion. A variety of scarabbeetle species were captured on all islands (Table S1).On both Mauritius and La Réunion Island, thebeetle-associated nematode fauna was dominated byP. pacificus, whereas the majority of nematode speciesdetected on Mayotte were gonochoristic (in contrast tothe Mascarene Islands, on which gonochoristic nema-todes have never been detected). Beetle-associatednematode fauna was rare on the Seychelles andRodriguez (Table S1). On Mauritius, sample sizeswere regrettably smaller than those obtained from LaRéunion, although P. pacificus was isolated fromfour species of scarab beetle (Heteronychus licas,Hyposerica sp., Clemora smithi and Alissonotumpiceum). All four beetle species that were positive for P.pacificus are sugarcane pests that were hand-collected

from sugarcane fields. Light trap-collected scarabbeetles on Mauritius, including several Adoretusspecies, were negative for P. pacificus although relatedAdoretus species on La Réunion are known to beinfested with P. pacificus. Further sampling will berequired to determine whether differences in infesta-tion rates between the islands are significant. With theexception of Alissonotum piceum, the host speciesdetected on Mauritius differ from those with whichP. pacificus is associated on La Réunion (Table 1;Table S1).

DIVERSITY OF P. PACIFICUS POPULATIONS ON LA

RÉUNION AND MAURITIUS

Analyses were performed with the aim of characteriz-ing the diversity of P. pacificus on La Réunion andMauritius, as well as levels of differentiation anddivergence between populations on the differentislands. Strong population structure and high geneticdiversity within both Mauritius and La Réunion popu-lations is evident from the STR network (Fig. 2A). TheMauritius genotypes mainly cluster within the diver-gent La Réunion lineages, although there are severalinstances of individual Mauritius genotypes occurringin clusters throughout the STR network. Although thecomplexity of the STR network makes designatingindividual lineages problematic, correspondence withthe mt haplotype network can be detected (Fig. 2).

Of the four mt lineages identified in previous workand designated as ‘A’, ‘B’, ‘C’ and ‘D’ (Herrmann et al.,2010; Morgan et al., 2012), lineages ‘A’, ‘C’ and ‘D’were found to be common to both islands, and onlylineage ‘B’ was apparently restricted to La Réunion(Fig. 2). Lineage B consists exclusively of strains iso-lated from the high-altitude La Réunion localities CCand NB, and from the beetle species Amneidusgodefroyi. Neither this beetle species, nor similar alti-tudes are present on Mauritius. Matching previouspatterns on La Réunion Island (see Morgan et al.,2012), a correspondence between mt lineage and sam-pling locality was detected in the new Mauritiussamples, as can be seen in both the STR and the mtnetworks (Fig. 2). Specifically, lineage ‘A’ was detectedin greatest frequency at the southern location LAC,lineage ‘D’ is limited to the southern and more east-erly location BRG, and the more central samplinglocalities FERN and ALMA consist mainly of lineage‘C’ individuals (Fig. 2b). A total of 54 and 12 uniquemt haplotypes were detected on La Réunion andMauritius, respectively, and four haplotypes werecommon to both islands. Hence both islands contain asimilar assemblage of highly divergent STR and mtlineages, and although some degree of haplotypesharing is evident, both islands also harbour a collec-tion of unique haplotypes.



InStruct infers the optimal number of clusters in adataset using the deviance information criterion(DIC). The DIC values obtained here for each value ofK are displayed in Supplementary Figure S1. Theoptimal value of K was inferred to be 15, althoughexamination of the DIC values shows a clear decreasebetween K = 1 and K = 8, followed by a plateau fromvalues of K = 11 and above (Fig. S1). In agreementwith the results of Morgan et al. (2012), K = 2 split LaRéunion populations into clear eastern (blue) andwestern (orange) clusters, with both clusters includ-ing strains from Mauritius (Fig. 3). Some distinctionbetween Mauritius and La Réunion populationsbecame apparent at K = 6. The black cluster, corre-sponding to strains isolated from the high-altitude LaRéunion localities CC and NB (mt lineage ‘B’), wasthe only unique cluster (present only on Réunion).All clusters detected on Mauritius were detected inhigh frequency on La Réunion, with the exception of

the pink cluster, which was represented by only twoLa Réunion strains from the locality GE. There isclear correspondence between genetic clusters on bothislands, with the orange cluster representing theMauritius locality BRG + MT and the north-easternLa Réunion localities GE, BV and PL; the green andblue clusters representing the Mauritius clustersALMA and FERN and the south-western La Réunionlocalities CO, PC, SS and TB; the yellow clusterrepresenting the Mauritius localities LAK and FERNas well as the La Réunion locality SB; and the pinkcluster primarily representing the Mauritius localityLAK, but also containing two individuals from the LaRéunion locality GE. Increasing K further generallyreveals additional structure within the La Réunionsample, although at K = 11 and above the Mauritiuslocality BRG + MT forms a distinct and exclusivecluster. Hence although there is often greater geneticdistinction between localities within an island than

TB

Key:

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Figure 2. A, neighbour-net network constructed using STR data. The approximate correspondence with the mt clades isindicated. Clusters of haplotypes containing Mauritius strains are indicated with a star. B, median-joining haplotypenetwork constructed using mt sequence data from ND4 and ND6L loci. Each circle represents a haplotype and the sizeof the circle is proportional to the number of strains with that haplotype. The length of the branch between circles isapproximately proportional to the number of mutational steps between haplotypes, except where indicated. The scale barillustrates the branch length for one mutation.

8 K. MORGAN ET AL.


between localities on different islands, some distinc-tion between Mauritius and La Réunion does becomeapparent at higher K values.

Similar patterns of diversity and differentiationwere detected using STR and mt loci, and using RST

and Jost’s D for the STR loci, so only the RST resultsfrom the STR loci are presented. Genetic diversityat STR loci within La Réunion populations rangedfrom HE = 0.202 and Ar4 = 1.388 (PL population) toHE = 0.682 and Ar4 = 2.776 (at GE), with a mean HE of0.441 and Ar4 of 2.215 (Table 2; Fig. 1). Diversitystatistics for the Mauritius populations fall within asimilar range to those estimated for La Réunion (HE

range 0.369–0.626, mean = 0.515; Ar4 range 2.094–2.831, mean = 2.405).

The RST values reveal generally high levels of differ-entiation between populations on both islands, whichin most cases remain significant after Bonferroni’scorrection for multiple tests (Table 2). The mean dif-ferentiation between populations on different islands(RST = 0.462) is not substantially different from thatbetween populations on the same island (RST = 0.460and 0.355 for populations on La Réunion and Mauri-tius, respectively). Indeed, several pairs of populationsthat are isolated on different islands show RST statis-tics that are considerably lower than the average for

the within-island comparisons, for example the LaRéunion population GE and both the Mauritius popu-lations ALMA (RST = 0.105) and FERN (0.034), and theLa Réunion population BRG and the Mauritius popu-lation SB (RST = 0.136).

HISTORICAL MIGRATION BETWEEN MAURITIUS AND

LA RÉUNION

The posterior distributions of the majority of param-eters within the IMA2 analyses, including t0, m1 > 0and q1 and m0 > 1, had clear peaks and boundswithin the prior distributions, indicating reliableinference of these parameters. However, the qa andq2 parameters had flat posterior distributions, indi-cating a lack of information for these parameters. Theresults were consistent across all five independentdraws from the La Réunion population, and remainedconsistent across replicates.

Using the mitochondrial mutation rate of Molnaret al. (2011), the Mauritius and La Réunion popula-tions were estimated to have diverged 129 421generations ago with 95% HPD intervals (whichrepresent the interval in which 95% of the distribu-tion lies, and are analogous to 95% confidenceintervals) supporting a broader divergence range of

Figure 3. The inferred InStruct clusters at K = 2, 6, 8, 11 and 15. The optimal value of K was inferred to be 15, althoughexamination of the DIC values shows a clear decrease between K = 1 and K = 8, followed by a plateau from values ofK = 11 and above (Fig. S1).



between 70 997 and 322 144 generations. Non-zero,bi-directional migration was inferred between Mauri-tius and La Réunion populations since their initialdivergence, and this was higher from Mauritius to LaRéunion than in the opposite direction (m = 5.25, 95%HPD 0.38–25.23 from Mauritius to La Réunion, andm = 1.337, 95% HPD 0.03–13.28 from La Réunion toMauritius).

As no reliable effective population size estimateswere obtained for the Mauritius populations, themigration rate estimates can only be converted intomigrant per generation estimates using the estimatedeffective population size estimate for the La Réunionpopulations (q1 = 4Neμ), and assuming similar effec-tive population sizes for Mauritius and La Réunion.Using this estimate, migration rates were inferredto be 2.97 (95% HPD 0.18–14.51) and 0.76 (95% HPD0.01–7.64) migrants per generation to La Réunionand Mauritius, respectively.

RECENT MIGRATION ON LA RÉUNION ISLAND

Given the high sampling density on La Réunion, wenext aimed to detect recent migrations across thelandscape on La Réunion Island. Patterns of recentimmigration were shown to often be asymmetrical (i.e.greater in one direction than the other) between pairsof populations. The estimated percentage of immi-grants varied from 0.3 to 14.0% across all pair-wisecomparisons using BAYESASS, with the total percent-age of immigrants per population ranging from 10.7to 32.2% (Table 3). There were four instances wherepair-wise migration accounted for over 5% of popula-tion membership; this corresponded to migration fromGE to BV (10.7%) and PL (14%), and from TB to SS(11.8%) and TBG (7%) (Table 3).

AAIA indicated an average Rj value of 0.328, indi-cating significant (P < 0.001) genetic structure amongP. pacificus populations. Landscape shape interpola-tion analysis produced a 3D surface plot, showingpeaks in areas where there are large genetic differ-ences (i.e. landscape barriers to gene flow). In thisplot, differentiation increased from largely smooth(low barriers to gene flow) genetic surfaces at the plotedges towards regions of elevated genetic distance incentral areas. This roughly corresponded to barriersseparating the north/south-east part of the island(locations: NB, CC, GE) from south/north-west areas(CO, SS, TB, TBG, PC, BV) (Fig. 4). To identifygenetic clines, the sPCA method was used. Thisanalysis identified gradual gradients of genetic diver-sity over two main geographical areas: in Figure S2,light areas (corresponding to higher genetic differen-tiation) encompassed north-eastern locations (NB,CC, GE, PL, SB) and darker areas (lower differentia-tion) encompassed south-western areas.T

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To complete the boundary analyses, WOMBSOFTwas used to infer genetic boundaries among geo-graphical locations. This method identified a largeheterogeneous region in the eastern part of the island(Fig. S3a), which corresponded to an area of high

candidate boundary elements significant at 0.05,again dissecting north-eastern and south-westernareas (Fig. S3b).

DISCUSSION

This study investigates patterns of population struc-ture and migration among island populations of thenematode P. pacificus in the Indian Ocean. Our analy-sis allows three major conclusions, which are outlinedbelow.

SIMILARLY HIGH GENETIC DIVERSITY ON BOTH

MAURITIUS AND LA RÉUNION ISLAND, AND THE

APPARENT ABSENCE OF P. PACIFICUS FROM OTHER

INDIAN OCEAN ISLANDS

Previous population genetic and modelling appro-aches revealed that the presence of highly divergentSTR and mt lineages in populations of P. pacificus onLa Réunion island is due to multiple colonizationevents from geographically disparate source popula-tions (Morgan et al., 2012; McGaughran et al., 2013).Here, we demonstrate that both Mauritius and LaRéunion harbour a similar set of highly divergent mtand STR lineages, with mt haplotypes and STR clus-ters being shared between the islands. Populationgenetic statistics reveal a similarly high diversity ofP. pacificus on both islands, supporting long-termestablishment on Mauritius as well as La Réunion(Morgan et al., 2012; McGaughran et al., 2013).

Table 3. Migration rates in recent generations among Pristionchus pacificus populations as estimated in the programBAYEASS

Population j

Population i BV CC CO GE NB PC PL SB SS TB TBG Imm

BV 0.679 0.012 0.012 0.107 0.012 0.022 0.012 0.012 0.012 0.025 0.012 0.321CC 0.008 0.859 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.141CO 0.006 0.007 0.864 0.007 0.007 0.006 0.006 0.006 0.006 0.032 0.009 0.136GE 0.004 0.004 0.033 0.874 0.004 0.025 0.004 0.004 0.004 0.011 0.004 0.126NB 0.009 0.009 0.009 0.009 0.844 0.009 0.009 0.009 0.009 0.009 0.009 0.156PC 0.008 0.008 0.008 0.008 0.008 0.834 0.008 0.008 0.008 0.038 0.010 0.166PL 0.011 0.011 0.022 0.140 0.011 0.011 0.678 0.011 0.011 0.011 0.011 0.322SB 0.007 0.007 0.007 0.007 0.007 0.041 0.007 0.838 0.007 0.007 0.019 0.162SS 0.011 0.011 0.011 0.021 0.011 0.011 0.011 0.011 0.678 0.118 0.032 0.322TB 0.003 0.003 0.004 0.010 0.003 0.007 0.003 0.003 0.003 0.893 0.042 0.107TBG 0.008 0.008 0.013 0.008 0.008 0.008 0.008 0.008 0.008 0.070 0.804 0.196

Values in rows represent the expected proportions of individuals in population i (bold) that were derived/have migratedfrom population j (italics). Values underlined along the diagonal are the proportions of individuals derived from theirpopulation of capture (i.e. residents) in each generation, while values in the far right column are the total proportion ofimmigrants per population (Imm).

Figure 4. Results of landscape shape interpolation analy-sis, performed in ALLELES IN SPACE on Pristionchuspacificus populations from La Réunion Island. The graphicdepicts a 3D surface plot, where heights represent geneticdistances such that peaks/valleys exist in areas wherethere are large genetic differences and smooth areas rep-resent regions with low barriers to gene flow. Populationlocations are approximations.



However, although mt haplotypes and STR clustersare shared between Mauritius and La Réunion, bothislands harbour a collection of unique mt haplotypes(which typically differ by between one and five muta-tional steps), and the Mauritius haplotypes generallycluster together within the STR network (Fig. 2). TheInStruct analyses also reveal differentiation betweenthe two islands, with the pink cluster being commonon Mauritius, for example, yet represented by onlytwo individuals on La Réunion (Fig. 3). The diver-gence of La Réunion and Mauritius populations isalso supported by high RST values. This differentia-tion suggests that the Mascarene populations ofP. pacificus follow a pattern typically seen in volcanicisland chain systems, in which populations divergefrom one another following colonization due to theincreased strength of genetic drift in isolation (e.g.Jordan & Snell, 2008; Jordaens et al., 2009; Hoecket al., 2010; Kuntner & Agnarsson, 2011). Collectively,this general pattern of shared lineages coupledwith the presence of high genetic diversity, uniquehaplotypes and distinct STR clusters on both islandssuggests that Mauritius and La Réunion are mostlikely to have been colonized on historical vs. recenttime scales, allowing the accumulation of geneticdiversity and inter-island differentiation.

Although negative results must be interpreted withcaution, it is interesting that the two islands appearto differ with respect to the presence of lineage‘B’. However, the habitat (> 2000 m a.s.l.) and beetlespecies (Amneidus godefroyi) with which this ‘high-altitude’ lineage is found in association on La Réunion(Morgan et al., 2012) are lacking on Mauritius. Thus,it is possible that this lineage failed to disperse toMauritius due to the reduced dispersal capacity of itsassociated host, or failed to persist on Mauritius dueto a lack or erosion of suitable environmental condi-tions. Sampling of numerous scarab beetle speciesalso failed to detect evidence of P. pacificus on Rod-riguez, Mayotte and the Seychelles. As P. pacificusdispersal most likely occurs in association with hostbeetles, prevailing wind directions may simply notfavour dispersal to these islands. Alternatively, Mau-ritius and La Réunion differ in a number of physicalparameters from most of the other islands, beingyounger and/or larger than most of the other islandsinvestigated in this study (Fig. 1) – it may be thatPristionchus nematodes were unsuccessful in estab-lishing populations on smaller islands, in accordancewith the classical model of island biogeography(MacArthur & Wilson, 1967). On Mayotte, many othernematodes were found, primarily consisting ofRhabditid species with a gonochoristic mode of repro-duction (M. Herrmann & R. J. Sommer, unpubl. data).Interestingly, Mayotte is substantially older thanLa Réunion and Mauritius, further supporting our

earlier observation that due to the potential for self-fertilization, hermaphroditic nematodes may have anadvantage in early island colonization (Herrmannet al., 2010).

BI-DIRECTIONAL MIGRATION BETWEEN MAURITIUS

AND LA RÉUNION

The hypothesis of historical colonization of both Mau-ritius and La Réunion is further supported by our IManalysis. This method teases apart the signals ofmigration and ancestral polymorphism, which canbe difficult or impossible to distinguish using moretraditional methods, and estimates divergence timetaking both of these factors into account (Hey &Nielsen, 2007). The estimated divergence of popula-tions on the two islands approximately 129 421 gen-erations ago (70 997–322 144 generations including95% confidence intervals) falls within a similar timeperiod to the estimated dates of spatial expansionsof P. pacificus populations on La Réunion, approxi-mately 133 000–191 000 years ago. These expansionsare thought to have coincided with the initial coloni-zation of the Mascarene region (McGaughran et al.,2013), suggesting that the two islands were mostlikely colonized over the same historical time scale.Although colonization of one island following estab-lishment on the other cannot be ruled out entirely,this would have to have occurred within the distant,rather than the recent history of P. pacificus in theMascarenes.

Our migration analysis supports the capacityfor migration between the islands, highlightingbi-directional gene flow since population divergence.Long-distance dispersal events in P. pacificus havepreviously been supported by cases of mt haplotypesharing over large geographical distances in globalpopulations (although this study was based on limitedsampling), suggesting that such events are notlimited to the Mascarene Island system (Herrmannet al., 2010). Homogenizing long-distance dispersalevents in nematodes are generally attributed topassive dispersal, and are often associated with themovements of host individuals (e.g. Blouin et al.,1995; Wielgoss et al., 2008). In the case of P. pacificus,several of the host species are pests of sugarcane, andhence the transport of agricultural produce may belinked to its passive dispersal both to and from theislands, potentially over large geographical distances.

The supported long-term persistence of P. pacificuspopulations on both Mauritius and La Réunion, aswell as the fact that sugarcane is exported out of theMascarene region from both islands rather than fromone island to the other, suggests the transport ofagricultural produce is unlikely to be responsiblefor either the initial colonization events or the

12 K. MORGAN ET AL.


bi-directional migration of P. pacificus between theislands. Prevailing winds between La Réunion andMauritius probably aid in the dispersal betweenislands of individual host beetles, both pest and non-pest. The capacity for P. pacificus to disperse withthese beetle hosts is probably enhanced by its abilityto self-fertilize, as rare beetle movements betweenislands that fail to result in the establishmentof beetle populations may still result in successfulnematode dispersal. Thus, although the differentassemblage of scarab beetle species on La RéunionIsland and Mauritius suggests limited beetlemovements between the islands (only one species,Alissonotum, was found to act as a host species onboth islands), this does not rule out the beetle hostsas a potential route for P. pacificus dispersal. Flexibil-ity with regard to host beetle species was reported byMorgan et al. (2012), and suggests that after dispersalacross the ocean barrier, P. pacificus populations areable to opportunistically exploit the locally availablesuite of novel host species.

DISPERSAL ACROSS THE LANDSCAPE IS LIMITED BY

STRONG ENVIRONMENTAL BARRIERS ON LA RÉUNION

Landscape genetic analyses performed using the moredensely sampled La Réunion dataset revealed severalbarriers to nematode gene flow across this island. Inparticular, a major barrier was detected separatingthe eastern, windward side of the island from thewest. Each of the landscape analyses supported thepresence of this barrier: the AIS analysis showedgenetic differentiation increasing toward the centralregion dissecting the east and western regions of theisland; sPCA revealed higher genetic differentiationin the north-east of the island, and lower geneticdifferentiation encompassing sampling localities inthe west and south-west; and the WOMBSOFT analy-sis identified a large, heterogeneous region dissectingthe north-eastern and south-western regions of theisland.

Rather than coinciding with an obvious geologicalfeature, such as a mountain range, the barrierappears to coincide with the potential ecologicaldivide discussed in Morgan et al. (2012) and Milaet al. (2010). Specifically, the north-east of the islandis characterized by a humid climate with high rain-fall, while the south-west is considerably more arid.Reduced gene flow between these regions may be dueto either a lack of beetle movement or reduced sur-vival of immigrant nematode individuals after theirdispersal across the divide. Recent species distribu-tion modelling analyses show a strong associationbetween genetic structure and environmental vari-ability in both P. pacificus and its beetle hosts,suggesting that local adaptation may be a particu-

larly important driver of distribution patterns(McGaughran, Morgan & Sommer, 2014).

Genetic differentiation is generally strong betweenpopulations on La Réunion Island, indicating strongspatial structure and supporting reduced gene flowacross the landscape. However, the results of theBAYESASS analysis support non-uniform, recent dis-persal between several pairs of geographically dis-tinct La Réunion populations, including pairs thatare on opposite sides of the identified landscapebarrier, such as GE and TB. These high levels ofinferred migration may seem surprising given thestrong spatial structure on La Réunion, which mightbe expected to become homogenized. However, thedevelopment and persistence of strong spatial struc-ture in nematode populations despite the potential forhigh rates of passive dispersal has been reported inseveral marine species, and attributed to the occur-rence of repeated founder events, followed by rapidreproduction and population growth (Derycke et al.,2005, 2008). Hence, P. pacificus population geneticpatterns show little similarity to those detectedin C. elegans, in which long-distance dispersal isthought to have been followed by repeated selectivesweeps and the consequent homogenization of globalspatial structure (Andersen et al., 2012), and ratherare more similar to those detected in non-parasitic,free-living marine species, in which high spatialgenetic structure is maintained despite frequent long-distance migration events.

ACKNOWLEDGEMENTS

We thank the three anonymous reviews for theircomments on previous versions of this manuscript.In addition, we thank La Réunion Parc National forsupplying collection permits and Jacques Rochat (LaRéunion Insectarium) for his help with the planningand execution of sample collection trips. We wouldalso like to thank members of the Sommer researchgroup at Max Planck Institute for their discussionand advice, and in particular Christian Rödelspergerfor his bioinformatic assistance. Finally, we thank theMax Planck Society and the Alexander von HumboldtFoundation (Research Fellowship for PostdoctoralResearchers to A.M.) for funding.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:

Figure S1. The DIC values obtained here for each value of K.Figure S2. Results of multivariate sPCA performed in R, identifying genetic clines among La RéunionPristionchus pacificus populations, with light areas representing large genetic differences and darker coloursindicating low diversity. Population locations are approximations.Figure S3. Results of the boundary analyses performed with the WOMBSOFT package in R, inferring geneticboundaries among Pristionchus pacificus populations on La Réunion Island: (i) a coloured map on which eachsampled point is a circle and the background is the systemic function – green corresponds to low values of thesystemic function, and light pink to high values of the systemic function, i.e. zones where the population isheterogeneous; (ii) a second map, where boundaries are shown in light grey and homogeneous zones in green.The lines are the directions of the gradient.Table S1. The variety of beetle species sampled from La Réunion, Mauritius, Rodriguez, Mayotte and theSeychelles, and the identity and dominant reproductive strategy of nematode species detected from each island.

ARCHIVED DATA

Data deposited at Dryad (Morgan et al., 2014).



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Landscape and oceanic barriers shape dispersal and ...€¦ · Landscape and oceanic barriers shape dispersal and population structure in the island nematode Pristionchus paciﬁcus