Dendrocalamus sinicus Chia & J.L. Sun as a model species to investigate dispersal or vicariance speciation in woody bamboos. Variation in three chloroplast DNA (cpDNA) fragments and eight simple sequence repeat markers (SSR) among 232 individuals sampled from 18 populations across the known geographic range of D. sinicus was surveyed. D. sinicus populations exhibited a high level of genetic differentiation which divided them into two groups that are consistent with different culm types. Eleven haplotypes and two lineages (Straight-culm and Sinuous-culm lineages) were identified from phylogenetic analyses, and a strong phylogeographic structure across the distribution range was found. The demographic and spatial expansion times of the Straight-culm lineage were calculated as 11.3 Kya and 20.8 Kya, respectively. The populations of D. sinicus had experienced dispersal and long-term isolation, although this trace was diluted by contemporary gene flow revealed by SSR data. Our results provide an phylogeographic insight to better understand the speciation processes of woody bamboos.Evolutionary processes, speciation in woody bamboos are presently little understood. Here we used  These taxa are naturally distributed in all continents except Europe and Antarctica, and their centers of species diversity are the tropical and subtropical regions of Asia, Africa and South America2. Bamboos are a significant natural resource throughout much of the world, providing food and raw materials for construction, paper pulp and manufacturing, etc.3. Many woody bamboos have a life cycle peculiar among angiosperms, in having a very long vegetative period of several decades to even 150 years, followed by gregarious flowering and monocarpy4. So far, due to lack of fossil material, long vegetative growth periods and unpredictable flowering episodes, the evolution and speciation of woody bamboos have always been an interesting but stubbornly difficult topic7.The biggest grasses in the world, bamboos belong to the subfamily Bambusoideae of the Poaceae, and include some 115 genera with more than 1400 species8. On the aspect of non-geographic mode of bamboos, chromosome doubling and hybridization are generally deemed as the main mechanism for modern species diversity of bamboos11. In regard to woody bamboos, the chromosome allopolyploid may account for the origin of major lineages and subsequent radiation speciation10, for example, the diversity of modern temperate and tropical woody bamboos11. Meanwhile, the hybrid speciation among woody bamboos has been observed occasionally in the nature12. On the other hand, vicariance and dispersal speciation are viewed as two main modes of geographic speciation in plant and animal14. Based on the modern distribution pattern in the world, the species diversity of bamboos is generally regarded as the result of vicariance speciation14, which was supported by evidence of molecular bamboo systematics11. However, does dispersal speciation happen at the level of species among woody bamboos? As far as we know, there is little research report in this field. To further understand this question, more comprehensive studies are required, especially at the population level.Speciation is crucial to biodiversity and can be categorized in non-geographic and geographic modesDendrocalamus sinicus Chia & J. L. Sun as a model to gain further insights into this topic. D. sinicus is among the largest bamboos known in the world, with culms reaching over 30 m high and 30 cm in diameter, and has been acknowledged as the strongest bamboo known15. This typical paleotropical woody bamboo occurs naturally only at elevations of 600–1,500 m in south and southwestern Yunnan Province in southwest China16. D. sinicus also seems to have an interesting variation from its more northerly distribution to the south based on culm shape. The more northerly populations in southwestern Yunnan have the typically straight culms of erect clumped bamboos, whereas in the more southerly populations, clumps often develop culms that are not straight, with the lower half frequently including curved portions giving somewhat sinuous internode sequences16  in phylogeographic analyses can help infer historical range shifts and recolonization routes of a species18. Biparentally inherited nuclear simple sequence repeat variations (SSR) are more powerful for understanding ongoing demographic processes such as contemporary gene exchange24.How did this variation and its distribution come about? Although both dispersal and vicariance have been suggested as significant in shaping the evolution and biogeography of bamboosD. sinicus, to infer its evolutionary history, and to assess the main genetic characteristics that could help inform woody bamboo geographic speciation, i.e. dispersal or vicariance speciation.In the present paper we assemble molecular methods (using cpDNA and SSR markers) and migration patterns between populations in order to reveal the contemporary population structure of Dendrocalamus sinicus populations is shown in Fig. A total of 1947 bp combined cpDNA sequences were aligned which resulted in 10 polymorphic sites and 11 haplotypes Tables  and S2. D. sinicus and the outgroup D. latiflorus resulted in three most parsimonious trees, each with a length of 26 steps, a consistency index (CI) of 0.500, and a retention index (RI) of 0.683. The Bayesian (BI) tree agreed with the MP tree at nearly all nodes. The topology of the strict consensus tree , they did show high posterior probability values. Haplotypes H2, 4, 6, 7, 9, and 10 formed a clade with 0.95 posterior probability; the other five haplotypes formed another clade with 0.87 posterior probability. Five populations  have haplotypes from both lineages, and all of them were distributed in the central region except for 16 (southern region). The network analysis  were the best grouping option with the highest Flue Fig. . One grolue Fig.  was assi were theS was 0.106 (±0.047), and HT was estimated as 0.497 (±0.0843). At the group level, the WQ group exhibited higher genetic diversity  compared with the TZ group . We also detected highly significantly (P ≤ 0.01) larger NST values (0.875) compared to GST (0.787), indicating there is a strong phylogeographic structure across the distribution range of D. sinicus  and genetic diversity parameters are given in Tables .106 ±0.07, and HTD. sinicus. At the group level, populations from the WQ group also stayed stable, revealed by a clearly multimodal pattern in the mismatch distribution analysis  ranged from 18 to 37, effective numbers of alleles (NE) from 1.88 to 2.97, observed heterozygosity (HO) from 0.375 to 0.567 and expected heterozygosity (HE) from 0.356 to 0.629. Allelic richness (AR) estimates among all populations ranged from 2.25 to 4.40. Inbreeding index values ranged from −0.378 to 0.449, which indicate considerable variation in the intensity of inbreeding among populations  were a little higher than for the WQ group . Coefficients of gene differentiation (GST and G’ST) were also calculated in Table At the species level, total genetic diversity HThe STRUCTURE analysis showed that Log-likelihood values of the data increased considerably when raising K = 2 Fig.  and begaDendrocalamus sinicus , with 13.29% of the variation among groups, 17.35% of the variation among populations within groups, and the rest of the variation (69.36%) within populations  suggested no significant genetic barriers were detected through the distribution area Fig. .Bottleneck analysis detected seven population having experienced recent bottleneck effects in both groups Table . Five ofDendrocalamus sinicus can exchange alleles through migration, although it is not to the same extent among different regions. As a whole, migration rates from the Intermediate populations into the Northern or Southern populations were higher than that in the reverse directions.The result of the MIGRATE-N analysis indicated that based on cpDNA data, migration rates (with 95% confidence) between the Northern, or Southern, and the Intermediate populations were largely asymmetrical, with migration from the Intermediate populations into the Northern (m = 0.681) or the Southern populations (m = 0.695) typically greater than in the reverse direction  among Dendrocalamus sinicus shows high total genetic diversity represented by HT = 0.497 (cpDNA) and 0.743 (SSR), and the mean genetic diversity among populations is much higher than that within populations 30, implying lack of seed transmission among D. sinicus populations. With biparentally inherited markers, the detected genetic differentiation (GST = 0.237) of D. sinicus was slightly less than D. membranaceus (GST = 0.252)31, and far less than D. giganteus (GST = 0.847) and D. brandisii (GST = 0.842)32. The different results from plastid and nuclear DNA imply that the pollen transmission may far exceed seed dispersal in the sexual reproduction of D. sinicus17.On the other hand, the genetic differentiation of D. sinicus (r = 9.89) was much less than the average among Angiosperms and Conifers assessed (mean = 17)30. The contemporary probability of hybrids between the TZ and WQ groups in the wild would appear to be minimal. During the last c. 30 years, sporadic flowering and seed set in TZ populations of D. sinicus have been observed in natural populations in southern Yunnan, whereas sporadic flowering was rare with almost no seed set among WQ populations33. Our own observations of several flowering clumps of D. sinicus in the wild showed that their flowering times were not synchronous, which could explain a lack of pollination and seed set29. What is more important is that, based on cpDNA and SSR data, both groups of D. sinicus showed significant genetic differentiation which was consistent with geographic isolation.Moreover, the pollen-to-seed migration ratio (r = mp/ms) estimated among populations of 20. The SAMOVA analysis  possessed at least one exclusive haplotype or allele  of 18 populations covering the entire geographic range of 41. Three cpDNA intergenic spacer regions with rich information, i.e., rpl32-trnL, rbcL-psaI and trnG-trnT, were chosen for sequencing based on Zhang et al.42. The 20 µl PCR mix contained 10 µl 2× PCR buffer including KCl2 (100 mM), MgCl2 (3 mM), dNTP mixture (0.5 mM), Taq polymerase (0.1 Uµl−1), TrisCl  , as well as 1 µl each primer (5 µM), 1 µl template DNA (c. 30–50 ng genomic DNA), and finally 7 µl distilled deionized water. Polymerase Chain Reactions (PCR) were performed on a Veriti 96 WellThermal Cycler . The cycling conditions were template denaturation at 97 °C for 3 min followed by 32 cycles of 94 °C for 40 s, 52 °C for 40 s, 72 °C for 1 min, and a final step of 72 °C for 7 min.We extracted genomic DNA using a modified 4x cetyltrimethyl ammonium bromide (CTAB) extraction protocolPCR products were visualized on 1% TAE agarose gels and then purified using a Sangon Purification Kit . The purified products were used for bi-directional sequencing using the PCR primers and the PRISM Dye Terminator Cycle Sequencing Ready Reaction Kit . The products were run on an ABI 3730 xl DNA Sequencer. All sequences were deposited in GenBank under accession numbers KP213841- KP213854, and KP289037- KP289039 Table .43, were selected to detect the genetic divergence among 18 populations of Dendrocalamus sinicus. Loci selected for this study have only one or two alleles among all the genotyped individuals. PCRs for the microsatellites were performed separately for each locus in 20 µl volumes with 8.8 µl ddH2O, 0.6 µl of DNA extract, 0.3 µl of each fluorescently labelled primer and 10 µl 2× Taq PCR MasterMix , which comprised of 0.5 mM dNTPs, 100 mM KCl, 3 mM MgCl2 and 1 U HotStar Taq. PCR thermal cycling conditions were 3 min denaturation at 94 °C, 35 cycles of 30 s denaturation at 94 °C, 40 s annealing at 48 °C (Den058), 50 °C (Den033 and Den036), 52 °C  or 61 °C (Den006 and Den007), 50 s extension at 72 °C and a single 7 min extension step at 72 °C. PCR products were scanned with QIAxcel Capillary Gel Electrophoresis . Fragment sizes were determined using QIAxcel BioCaculator and analyzed with the software GenALEx version 6.444.Eight pairs of nSSR markers with higher genetic information, i.e., Den005, Den007, Den033, Den034, Den036, Den058, Den075 and Den09645. The inversions were treated as indels according to Simmons & Ochoterena46. The matrix of combined cpDNA sequences was constructed for the following analysis since the cpDNA in plants generally do not recombine47.We assembled and edited sequences in Sequencher version 4.1.4 . Multiple alignments of sequences and subsequent manual adjustments were obtained using Geneious Pro version 4.8.548, and relatedness between haplotypes were constructed using TCS program version 1.2125 with 95% statistical parsimony criteria. We investigated the distribution of the number of pairwise nucleotide differences for cpDNA sequence data according to the method of Rogers & Harpending49.All the combined cpDNA sequences were assigned to different haplotypes using DNASP version 5.10Dendrocalamus sinicus were analyzed using Maximum Parsimony (MP) in PAUP* version 4.0 beta 1050 with D. latiflorus as outgroup. We initially use a Modeltest version 3.751 based on hierarchical Likelihood Ratio Tests (hLRTs) to find a best-fitting model applied to Bayesian Inference analysis. We performed full heuristic tree searches with 1000 random stepwise addition, using the TBR branch swapping, ‘MulTrees’ options. To assess the bootstrap supports, we used 1000 replicates. We also calculated Bayesian posterior probabilities using the software program MrBayes version 3.1.252 with a Monte Carlo Markov Chain (MCMC) length of 2 × 106 generations.Phylogenetic relationships between haplotypes of 53 using K = 2–9, and chose the number of groups that gave the highest FCT, or the number of groups for which FCT began to plateau54. We excluded configurations with one or more single-population groups, because this indicates that the group structure is disappearing55. To partition variations within and among defined groups and populations, we performed analysis of molecular variance (AMOVA) using ARLEQUIN version 3.056.To identify clusters of genetically similar populations, we ran a spatial analysis of molecular variance (SAMOVA) in SAMOVA 1.057. Mean genetic diversity within populations (HS), total genetic diversity (HT), genetic differentiation (GST), and genetic differentiation considered as genetic distance between haplotypes (NST), were obtained using PERMUT version 1.0 (http://www.pierroton.inra.fr/genetics/labo/Software/). A permutation approach was used to test the significance of the differences between GST and NST27 with the same program.Molecular diversity indices, including the number of haplotypes, haplotype diversity (Hd) and nucleotide diversity (π), were estimated using DNASP version 5.10. The existence of phylogeographic structure was tested following Pons & Petit48 and Harpending’s raggedness index58 (HRag), using a parametric bootstrap approach59 with 1000 replicates in Arlequin. We constructed the mismatch distributions of pairwise genetic differences in each group using Dnasp. For the expanding population group identified, we used the formula t = τ/2 u to estimate the time since expansion began. Values for u were calculated as u = μkg, where μ is the number of substitutions per site per year (s/s/y), k is the average sequence length of the cpDNA region under study, and g is the generation time in years. The paleotropical bamboos diversified from an estimated ca. 15 Mya and followed by rapid radiation within the lineages11. We adopted the overall synonymous substitution rate of cpDNA in palaeotropical woody bamboos, 9.03 × 10−10 s/s/y, as the value of μ60. The value for k was 1947 bp, and 76 years was used as an approximation for generation time according to Janzen’s record of Dendrocalamus giganteus61. We also used Fu’s FS62 and Tajima’s D63 test of selective neutrality to infer demographic history of all populations as well as each group. We estimate the statistical significance by performing 1000 random permutations in Arlequin.To investigate evidence of recent population expansion, we tested the null hypothesis of spatial expansion using mismatch distribution analysis. The goodness-of-fit was tested with the sum of squared deviations (SSD) between observed and expected mismatch distributions64. We calculated the number of alleles (NA), private alleles (NP), effective number of alleles (NE), expected heterozygosity (HE), and observed heterozygosity (HO), for each population and group in GenALEx. FSTAT was used to estimate Allelic richness (AR), inbreeding index (FIS), total genetic diversity (HT), genetic differentiation based on the allelic frequencies (GST), and the standardized measure of genetic differentiation (G’ST).The Hardy-Weinberg equilibrium (HWE) for each population and each locus was tested in FASTAT version 2.9.3.265, based on Nei’s genetic distance66 (D) among all pairs of populations estimated in the procedure MSA version 4.0567. A further analysis of population genetic admixture was taken in STRUCTURE version 2.368 to conduct a Bayesian analysis at eight SSR loci. For K = 1 to 10, we performed 20 independent runs for 105 iterations after a burn-in period of 105 with no prior information on the origin of individuals. The combination of ‘admixture’ and ‘allele frequencies correlated’ model was used for the analysis. To determine the most probable value of K, we chose the corrected DeltaK method described by Evanno et al.69, corrected posterior probability method68, the MedMeaK and the MaxMeaK methods described by Puechmaille70. All the analyses were completed using Kestimator V.1.1270. For each K, ΔK was computed based on absolute value of the second-order rate of change of the likelihood distribution. STRUCTURE results were displayed with the software Distruct version 1.171. To gain a clearer view of genetic clusters, we conducted a principal coordinate (PCO) analysis among all 232 individuals in the program GenAlEx44.To reveal the phylogenetic relationships among populations, we generated a neighbour-joining (NJ) tree with bootstrap values inferred from 1000 replicates using the program PHYLIP version 3.656. To detect isolation by distance and evaluate the relative influences of gene flow and drift on the population structure at both the species and group levels, we conducted a Mantel test between matrices of pairwise genetic distance  and geographic distance obtained  with 999 random permutations in GenAlEx. We used the BARRIER program version 2.272 to identify geographical locations where major genetic barriers among populations occurred based on 1000 Nei’s genetic distance matrices. The input files for the BARRIER analysis were from two parts— the X/Y coordinates of the original points (locations of the sampled populations) and genetic distance matrix with 100 replications calculated by MSA 4.05.Analysis of molecular variance (AMOVA) was performed to assess the genetic differentiation among groups and between populations within groups  using the program Arlequin 3.073 to examine the deviation from mutation-drift equilibrium. We chose the two-phase model (TPM) and Wilcoxon test based on the type of molecular marker and the number of loci.Finally, to test if the populations had experienced recent historical population declines, we used the program Bottleneck 1.2.02D. sinicus, we divided its 18 extant populations into three regions: the Intermediate , Northern  M = m/μ, where m is the immigration rate per generation among populations and μ is the mutation rate per generation per locus, was evaluated with this program. The model comparison was done using Bayes factors that need the accurate calculation of marginal likelihoods. These likelihoods were calculated using thermodynamic integration in MIGRATE-N 3.6.11. We also used Migrate-N to test the relative support for different migration models to address specific dispersal hypotheses. The probability of four models were evaluated using marginal likelihoods and Bayes factors74: (1) a full model with two population sizes and two migration rates (from population A to population B and from B to A), (2) a model with two population sizes and one migration rate to A, (3) a model with two population sizes and one migration rate to B, (4) a model where A and B are part of the same panmictic population. All other settings were at default values except the increment between samples placed at 1,000; samples per replicate was set at 10,000; and burn-ins per replicate were set at 50,000,000, and 1,000 replicates.To detect the bidirectional migration rates between different extant distributions of p/ms) was calculated following the formula according to Petit et al.30.The pollen-to-seed migration ratio (r = mDataset 1


Neotricula aperta is the snail-intermediate host of the parasitic blood-fluke Schistosoma mekongi which causes Mekong schistosomiasis in Cambodia and the Lao PDR. Despite numerous phylogenetic studies only one DNA-sequence based population-genetic study of N. aperta had been published, and the origin, structure and persistence of N. aperta were poorly understood. Consequently, a phylogenetic and population genetic study was performed, with addition of new data to pre-existing DNA-sequences for N. aperta from remote and inaccessible habitats, including one new taxon from Laos and 505 bp of additional DNA-sequence for all sampled taxa,.a priori defined ecogeographical regions. Spring-dwelling taxa were found to form an ecological isolate relative to other N. aperta. The poor dispersal capabilities suggested by spatial-genetic analyses were confirmed by Bayesian inference of migration rates. Population divergence time estimation implied a mid-Miocene colonisation of the present range, with immediate and rapid radiation in each ecogeographical region. Estimated effective population sizes were large (120–310 thousand).Spatial Principal Component Analysis revealed the presence of significant spatial-genetic clustering. Genetic-distance-based clustering indicated four populations with near perfect match to N. aperta—suggesting human-mediated reintroduction of disease to controlled areas as the primary reason for control failure. The isolation of the spring-dwelling taxa and ecogeographical structure suggests adaptation of sub-populations to different habitats; the epidemiological significance of this needs investigation. The large effective population sizes indicate that the high population densities observed in surveyed habitats are also present in inaccessible areas; affording great potential for recrudescence driven by animal-reservoir transmission in remote streams. Mid-Miocene colonisation implies heterochronous evolution of these snails and associated schistosomes and suggests against coevolution of snail and parasite. Heterochronicity favours ecological factors as shapers of host-parasite specificity and greater potential for escape from schistosomiasis control through host-switching.The strong spatial-genetic structure confirmed the poor dispersal capabilities of  Neotricula aperta live. Control of the snails is an effective approach to control of the parasite; however, because many suitable habitats for N. aperta occur in remote and inaccessible areas, knowledge of N. aperta population sizes and interconnectivity is insufficient for the design of effective snail control interventions. Although much of the region is difficult to survey by conventional means, population genetics can be used to estimate population structure and total size from small samples of accessible populations. The study added to existing data-sets, to give more population samples and longer DNA-sequences, together with improved analytical approaches to provide a better overview of N. aperta. The findings suggest that N. aperta in different kinds of habitats are also genetically different, with very low levels of migration between them; this genetic clustering is greater than expected from spatial distance alone. Further work is needed to determine if these different clusters vary in ability to transmit the parasite. The overall population size estimates were very large; thus suggesting that high snail population densities observed in accessible habitats are also characteristic of inaccessible populations—parasites are therefore more likely to return after disease control by immigration from remote areas. Finally, the timing of evolutionary events for snails and parasites was found to differ; this implies that the parasite may not be as strongly restricted to one species of snail as originally thought, which has implications for avoidance of parasite control by host-switching.The disease Mekong schistosomiasis poses a threat to the health of about 1.5 million people living near the Mekong river and its tributaries in Cambodia and Laos. It is a water-borne parasite transmitted by direct contact with water in which freshwater snails of the species  Schistosoma mekongi Voge, Bruckner & Bruce 1978  aBayesian ). The prBayesian . The 200Bayesian , which aN. aperta; however, they focused on sampling in the lower Mekong river around Kratié, used a short sequence from the cox1 gene (342 bp) and a phylogeny estimated by Neighbour-Joining (NJ), which is a distance based method and therefore decouples estimation of genetic distance from estimation of the tree. Consequently, such a phylogenetic method is greatly inferior to ML (or other tree+model based estimators), unlikely to work well with short sequences, and is now reserved mainly for very big data (as it is fast). Wang et al. (2014) [N. aperta or even an independent species’. The finding of such disjunction in the pattern of genetic variation in these snails further supports the need for judicious population genetic study of this snail. In addition, to the issues described above, none of the previous studies incorporated geospatial data into the analysis—the present study was the first to incorporate such data.Wang et al. (2014)  also rep. (2014)  reportedS. mekongi from most of Laos; this implied that a spread of Mekong schistosomiasis into central and northern Laos (and even into Thailand) was possible. Unfortunately, the computing power and analytical approaches (e.g. a network based clustering approach) available to the 2008 study were far inferior to those available today. In addition, more realistic modelling of the cox1 data is now possible, enabling their use in such a study. Further, the dating techniques used in the 2008 study were rather simplistic. Consequently, the present study was performed to apply modern analytical approaches to the full data-set, i.e. including both cox1 and rrnL, plus one additional taxon, representing a previously unsampled river. Unlike Attwood et al. (2008) [N. γ-aperta, as low gene-flow between the strains may violate assumptions of the analyses. The samples of the Nong Kai population newly reported in 2015 [For reasons of clarity, from here on this account will, when referring to elements of the present study, reserve the term ‘(sub-)population’ for those clusterings found to be genetically distinguishable, validated, (sub-)populations, and use ‘taxon’ for all other samples/collection sites or suspected but unevaluated populations. The term clade will be used for populations or clusters thereof in a phylogeny. The findings of Attwood et al. (2008)  suggeste. (2008) , the preS. mekongi. Of particular significance to public health is to confirm the South to North migration of the snails, the extent of gene-flow between snails in transmission foci on the Mekong river and tributaries draining into the Mekong from Laos and eastern Cambodia, and the extent of divergence between spring-dwelling and river-dwelling snail taxa. Such questions relate to the potential for expansion of the range of N. aperta (and thereby of S. mekongi) northwards into Laos unrestricted by lack of potential habitat, the role of source populations in tributaries as sources in restoration of Mekong river snail populations involved in transmission following the annual flood (and in reintroduction of S. mekongi from elsewhere), and the potential for spring-dwelling snails to act as intermediate hosts for S. mekongi and support transmission in habitats currently assumed to be free of schistosomiasis. The findings of the study are therefore of considerable value in the design and planning of future schistosomiasis control and for risk-mapping in the Mekong region.The aim was to evaluate the findings of Attwood et al. (2008)  and to cde novo. N. aperta collected, and sample codes used. Sampling procedures were as previously reported [cox1) and the large ribosomal-RNA gene (rrnL) were obtained, both loci being situated in the mitochondrial genome. In addition to those properties of mitochondrial loci  that make them suited to population genetic studies, the use of these two loci allowed incorporation of a large pre-existing data-set covering almost all of the known range of N. γ-aperta. Full details of sequencing procedures, primers and justification for choice of loci have been published elsewhere [The snails involved in the study were collected in Cambodia, Laos and Thailand, as reported earlier , with threported . Brieflylsewhere . Sites wDNA-sequence data used in the analyses have been deposited in the GenBank as follows:rrnL EU306175–EU306335 (excluding Xe Noy taxon), deposited with earlier publication [lication .cox1 KU999382-KU999795 (excluding Xe Noy taxon)rrnL Xe Noy MF663267-MF663277cox1 Xe Noy MF663256-MF663266Robertsiella silvicola was chosen, as phylogenies for the Pomatiopsidae indicate that it lies at the root of the clade containing all Mekong river Neotricula [cox1 and rrnL, respectively).For those analyses requiring an outgroup, the snail otricula . The corcox1+rrnL ‘both loci’ alignment was created using pyfasta 0.5.2 [cox1 sequences for which there was a corresponding rrnL sequence. The reading frame of the protein coding locus was determined using ExPASy Translate [Using SeqTrace 0.9.0 , DNA Seqta 0.5.2  to selecranslate . The appranslate , under aN. aperta) were then expanded . A break was introduced into the Nam Theun river to simulate the barrier now posed by the Nam Theun 2 dam, which was not then incorporated into the OpenStreetMap data-set. The image was next desaturated and brightness minimised. The negated image was then imported to R as a raster array, the grey-scale information extracted and rasterised, coordinates were then reassigned to the image, which was finally pre-projected  to create a cost-surface that was used to express resistance to dispersal in subsequent analyses. To account for the fact that downstream migration is more likely than upstream, a NW to SE (decreasing) cost gradient was applied to the array (mirroring the predominant flow direction and current of the rivers in the region). In effect, this resistance surface was telling the analyses that dispersal between rivers was highly unlikely unless the rivers were very close together (within 3 km), and dispersal upstream  was less likely than downstream.The generation of a resistance surface is a requisite for spatial analysis of these data. Consequently, the CRAN R 3.2.3  OpenStreST values were estimated using the R package hierfstat 0.04–22 [Before attempting a detailed analysis of migration patterns and phylogeography, the data were interrogated for population genetic structure. First, inter-taxon F 0.04–22 . The dat 0.04–22 , with sl 0.04–22  and ape  0.04–22 . A Mante 0.04–22 , was the 0.04–22  and ‘riv 0.04–22 . To avoi 0.04–22  and adeg 0.04–22 .N. γ-aperta; the use of multivariate analysis provides a rapid and flexible (i.e. independent of population genetic models) approach to determining if significant deviations from panmixis occur across the range of this snail, before attempting a more involved phylogeographical analysis. In particular, the use of linked loci  violates the assumptions of model based population genetic clustering approaches such as those used in STRUCTURE [A simple assessment of geographical distribution followed by multivariate methods was used to establish the presence of distinct populations in TRUCTURE  and BAPsTRUCTURE . SimilarA table of  standardised allele frequencies was subjected to Principal Component Analysis (PCA), as implemented in adegenet. Here PCA eigenvalues represented the amount of genetic diversity accounted for by each Principal Component (PC), and a sudden decrease in eigenvalues may correspond to the point where true structure in the data gives way to noise . In the The above PCA-based tests, restrict the analyses to few out of the many PCs, and therefore fail to utilise the data fully. Spatial structures in the whole data can be detected using a Mantel permutation test  for corrR2 is obtained for each MEM (the highest R2 is taken as the test statistic and compared to a reference distribution obtained by Monte-Carlo resampling of randomly permuted frequency matrices). The global test involves decomposition of the matrix into global MEMs, and the local test into local MEMS [Two randomisation tests are available in adegenet to determine which scale of structures are interpretable for the data . In thescal MEMS . Here 99cal MEMS . The colcal MEMS . The cluN. γ-aperta by multivariate approaches, the amount and direction of gene-flow, and thereby inferred rates of migration, among these sub-populations can be estimated. To enable this, the R package phangorn 1.99.14 [N. aperta has been described as a metapopulation, and the analysis should therefore avoid methods such as those implemented by Migrate-N that assume stable sub-population structure over time. Nevertheless, Migrate-N 3.2.8 [Having obtained an estimate of population structure within  1.99.14  was used-N 3.2.8  was usedversus static chain heating schemes, random or UPGMA starting trees, etc) and prior distributions (e.g. on starting theta and migration rates (mis), being uniform or random uniform or exponential) for the Migrate-N analyses. Initially, starting values for thetas and mis were based on Fst, with later runs started using estimates of theta and mi from the output of the currently best performing test-run. The relative performance of each run was assessed through Bayes-Factor (BF) tests comparing MArginal Likelihoods (MALs) determined by thermodynamic integration coupled with the use of Bezier-curves to improve approximation where a low number of heated chains is used (i.e. four here) [ST starting values and uniform priors on theta and mi, UPGMA starting-tree, a static heating scheme , and posterior generation by SLICE sampling. Runs with the above settings, and BFs, were then used to test alternative hypotheses regarding the number of distinct sub-populations (panmictic units) present in N. aperta.Several series of test runs were performed in order to select starting parameter values, settings  . Naturalur here) , in the N. aperta populations between northern and southern Laos [The Migrate-N based analyses were complemented by interrogation of the data using IMa2p . IMa2p mern Laos ).Test runs, with different starting parameter values, were used to determine appropriate values to initialise the main runs. At the same time trendline plots were check for persistence of obvious trends and multiple runs, that differed only in random-number seed, were performed with the expectation that parameter estimates (and posterior probabilities) should be similar; these measures provided an indication that the Markov chains had converged in distribution. ESS values among the parameters >>50 were considered a sign of adequate mixing among parallel chains. Plots of posterior density were used to assess influence of priors , together with runs sampling from the prior distribution alone. The full range of IMa2p’s appropriate run options see  were evaBEAST was used to estimate a phylogeny for the individual snails sampled, and to estimate divergence times for major clades through a Bayesian approach. Bayesian phylogenetics does not assume approximate normality or large sample sizes as would general ML methods , and is cf. next best run). A plot of MAL against generation number (from 6 to 1450 million generations), for runs with all other settings as in cf. worst and next best run respectively, 19.4583 and 9.6710). Subsequently, three such runs were performed with different random number seeds in order to confirm further convergence. No outgroup taxon was required, as the use of a relaxed clock model provided an estimate of the position of the root of the tree.Initially a dated phylogeny was estimated with calibration priors on key cladogenic events. BEAST allows specification of a large number and variety of priors, starting-values and models. BFs enabled comparisons for a series of short (48 million generations) test runs used to determine optimum settings. For each test run a MAL was recorded; this MAL was the log marginal likelihood (using stepping stone sampling) obtained from pathLikelihood.delta. In brief, the tests examined the effect of changing or removing priors on substitution rates (ucld.stdev and meanRate), population size history (tree priors), offset on tree height, and date calibrations (TMRCAs and root). The purpose of such tests was to ensure that no prior was overly determinant (i.e. shaping) of the posterior distribution; this was further established by running the final analyses without the data (i.e. using the priors only), which can also reveal unpredicted problematic interactions between priors. The posterior distributions were examined using Tracer 1.5 . and theN. aperta as dominated by cladogenesis following diastrophic events, changes in river courses and orogenies [The BF based model testing suggested that substitution rates were best represented by an Uncorrelated relaxed Clock with branch-specific rates drawn from an Exponential Distribution (UCED). An exponential distribution implies that most of the branches have rates at the lower end of the range, with a few branches showing high rates. The choice of an uncorrelated model implies an episodic mode of evolution , which irogenies . In addirogenies , a featuN. aperta [N. aperta. The correspondence of these clades to sub-populations used in the migration studies of the present investigation  taken from an earlier population phylogenetic study of . aperta . The pri. aperta  as majorThe phylogeny is presented as a 50% majority rule consensus tree representing the Maximum Clade Credibility (MCC) trees of three replicate estimates, and produced using sumtrees Version 4.1.0 . The MCCcox1 and sites 546–1050 to the rrnL locus. The first character represented a third codon position. A single partition, with a HKY+I+G, model was found, by PartitionFinder, to be the simplest scenario that appeared to be least inadequate in representing the evolution of the data (BIC 17053.344).The data-set, after editing for quality control and removal of taxa lacking quality sequence data for both loci, comprised 1050 characters (nucleotide sites or base-pairs) and 260 individuals (excluding the outgroup), representing 27 taxa of the Mekong river and nine of its tributaries in Cambodia, Laos and Thailand . Within ST values ranged from 0.024 to 0.946 (mean 0.579). The extreme FST values corresponded to DIL versus OHG and KRK versus TOT; these corresponded to almost, but not exactly, the most extreme river distances. Similarly, the Mantel test suggested high levels of IBD (P < 2x10-7) FThe PCA for genetic structure (genetic diversity among genotypes) indicated a number of discernible potential populations . A corre1). Consequently, the data contained interpretable variability and spatial structure, and only the first PC should be retained in subsequent analyses. Now that interpretable spatial-genetic structure had been detected, data regression onto MEMs was used to determine if global or local spatial structures should be interpreted. The results indicated that, whilst the test for interpretable local structure was not significant , that for global structure was highly significant .The Mantel test for population structure was highly significant . ConsequN. γ-aperta, with a clade containing all spring-dwelling taxa plus those of the upper reaches of the rivers sampled in Khammouane, and a second, larger, clade comprising all other taxa. The larger clade is divided into a sub-clade including all taxa of the rivers of northeastern Cambodia and a sub-clade containing all Mekong river taxa (including taxa of the lower reaches of the rivers in Khammouane). Finally, an interpolation map, using lagged principal scores from the sPCA, was produced (using the R package akima 0.5–12 [N. γ-aperta—the North to South cline mentioned above is seen clearly therein (i.e. the blue to red transition).Plotting lagged scores onto the geographical space  revealeda 0.5–12 ) and is Ward’s clustering with a maximum limit of five taxa indicated four ecogeographical populations , could be partly due to further (cryptic) population structure and cross-population sampling. Greatly unequal sample sizes, e.g. TOT→WBR, would lead to unequal underestimation of θ, with θTOT being most underestimated in the example given. The observation of a very high migration rate TOT→WBR, with a relatively very low rate WBR→TOT might be due to the greater probability of dispersal, during floods, from TOT into the Nam Yom and onward downstream to MEK; however, the spring population is a phylogentically distinct ecotype, biogeographically isolated, and inflation of the θWBR/θTOT ratio is an alternative explanation. Unusually high migration is also seen TOT→BOL despite these populations being isolated by highland and considerable distance . Overall it is likely that migration levels among all populations are between zero and ten snails per generation.MigrateN starting parameters were as detailed in Methods: ‘Inference of migration rates’ above. Despite a Gelman’s R < 1.2, high acceptance ratios and ESS values ranging from around 70k to 1 million, replicate runs did not give consistent migration rate estimates. Consequently, the CKR and MEK populations were combined into a single population covering the karst rivers of Khammouanne immediately to the North (e.g. Xe Bang Fai drainage) and the Mekong river of Laos and Cambodia, into the northern part of which the rivers of CKR drain. The results of three replicate runs of 50 million generations each are given in Although perhaps unable to reliably estimate all parameters of these gene-flow models, Migrate-N was used in model testing with respect to number of distinct sub-populations present. eμ from Migrate-N  taxon had to be excluded because runs with all three taxa  failed to converge within 48x(12x3.4GHz) hxCPUs during test runs or crashed after the burnin. Again this was possibly a consequence of the smaller sample and effective-population size of TOT relative to the lotic populations. TOT was not simply merged with WBR because TOT had appeared as a highly discrete population throughout the population structural analyses. Its merger with any other data partition was therefore unjustified and its exclusion saved computational time. No significant autocorrelation was found among any of the parameters estimated (suggesting that the data were sufficient to distinguish each of them), and ESS values for all exceeded 150. igrate-N  are muchIn contrast to population size, the migration rate estimates were less consistent  and the Uninformative data can appear to describe an island model if a high upper bound is set as a prior on the splitting time of the ancestral population, as such analyses tend to infer a splitting time at that upper bound. To exclude this possibility, runs were performed with -t set to 25% of the value indicated by the test runs. Despite the reduction in the prior, the same high estimate of splitting time was returned; this suggested that the data were consistent with an island model.The MEK-1, ), CKR-2 clades form a basal polytomy. Within the CKR-1 clade, a trichotomy describes a monotypic clade (MOP), trifurcate clade (YOM), and a polytomic clade (six branches), within which CKS (TOT) forms a monophyletic clade and KLR and TKN appear respectively monophyletic on a bifurcate clade. The remaining four branches comprise of MXL and YOM. The two CKR clades differ in that CKR-1 includes CKS and TKN, and CKR-2 includes BKV taxa. The main clade of CKR-2 comprises a ) clade, an ) clade, three monotypic MXL clades, with two monotypic BKL clades basal to this main clade.The standard deviation on the mean branch rate estimate for the uncorrelated relaxed exponential clock used was low (0.0019); this suggested that meaningful divergence times may be obtained by sampling the posterior. The marginal probability densities of the divergence time estimates showed HDIs (95% highest posterior probability densities) of around 4 Ma; their means are given in N. aperta is not panmictic and that there is limited gene-flow among these regions. PCA indicated a marked clinal disjunction between the North and South of the range, with perhaps two, less well defined, sub-populations in the South  appear far more panmictic. Such panmixis is most likely the result of mixing among sub-populations during the annual flood, and the ready interconnection of the rivers involved. Nevertheless, these populations still showed significantly positive spatial auto-correlation, which implies that each snail is more likely to be surrounded by individuals more closely related to it than would be expected if the distribution were random . Snails of the most southeasterly populations (i.e. the rivers of northeastern Cambodia) appeared to be surrounded by individuals less closely related to them than expected in the absence of population structure. This may be due to a lack of migration among the rivers of this region despite their geographical proximity, which leads to the existence of spatially close but genetically distant individuals.The study found that population genetic variation corresponded with snail ecology or habitat. The fact that Ward’s clustering almost exactly recovered the eco-geographical structure of the samples, strongly suggests that he South . The dissPCA and data regression onto MEMs indicated highly significant global population structure, but much less local structure. The North-South divide suggested by PCA was reinforced by plotting of lagged principal scores onto geographical space. The existence of a third sub-population comprising the sampling sites of Northeast Cambodia and the Xe Kong drainage of Laos  was supported by the second PC of the sPCA, and to a lesser extent by the minimum variance clustering dendogram for the first PC (of the sPCA), where it appears as a sub-clade of the major southern clade .N. aperta and that some degree of ecological, as well as physical, isolation might be present. The sub-populations inferred by sPCA were also consistent with these ecogeographical clusters  events).In contrast to Ward’s clustering, phylogenetic estimation using BEAST, found only CKS to be monophyletic (and only as a sub-clade of one of two CKR clades). It should be noted, however, that whilst PCA and related methods are based solely on genetic differences, BEAST attempts to recover history and could give a better estimate of the ancestral relationships of the sub-populations. The BEAST phylogeny  suggestse [Confidence intervals for divergence time estimates (from BEAST) were wide, such that it is not possible to order the times of the MRCAs of all three major clades in e  (here thrrnL data only and fewer sampling sites), the order of divergence events appears to be near simultaneous divergence of the spring-dwelling Cammon karst and Cammon karst stream clades (NSP), and of MEK-2, followed by that of BOL. In contrast, Attwood et al. (2008) [As in the 2008 study (based on the . (2008)  dated th. (2008) . The fou. (2008) , and majN. aperta exists as a single panmictic population. Nevertheless, unexpectedly high levels of migration were observed between CKS (TOT) and BOL and WBR (i.e. MEK+CKR); these were attributed to systematic error caused by the relatively small sample size and underestimated θ of CKS. In support of this, Attwood et al. (2008) [eM ranging from 0.000 to 0.005 between CKS+CKR and BOL+MEK1 or BOL+MEK2. Exclusion of CKS, allowed estimation of NeM between BOL and WBR which was found to be close to zero (0.001) WBR→BOL and almost ten times higher BOL→WBR; this is expected as N. aperta is thought to show very poor survival out of water. Even dispersal downstream (BOL→WBR) is likely to occur at low rates because habitats suitable for this snail are highly discontinuous [Values of the population migration rate  were muc. (2008) , who alsntinuous . The hige between 81084 and 313281 are very high. Even for dense stands of gregarious molluscs such as Ostrea edulis (the European flat oyster) Ne is reportedly only around 23000 [N. aperta is much smaller than the aforementioned oyster, and lithic substrata provide a vast surface area along their ridges and crevices; therefore N. aperta populations may be very large. Although there is often no linear relationship between snail population density (or even density of infective snails) and prevalence of schistosomiasis in humans, the existence of very large numbers of snails around human settlements, each snail shedding few cercariae, is likely to favour transmission of S. mekongi. It is worth noting in this context, that in comparison with Biomphalaria glabrata (Say 1818) transmitting Schistosoma mansoni Sambon 1907, where one snail may shed over 2000 cercariae per day [N. aperta is much lower , the ceof 0.22% ). Most ong river  . Consequently, the results imply that the present distribution of N. aperta is more a result of history than of ecology, and that this snail is not currently necessarily currently limited by the distribution of suitable habitats. Nevertheless, dispersal capabilities appear to be very low  and expansion of the range is likely to occur at very low rates, even with human activity. Hydropower expansion, with 133 dams completed or proposed for the lower Mekong basin [S. japonicum, that ecological factors (e.g. schistosomes evolve to avoid snails that would release their cercariae in habitats that do not favour transmission) are perhaps more important than phylogenetics, and that host switches are more likely than previously thought [S. mekongi and other Asian species, relates to the chance of the parasite escaping the effects of snail control efforts and requires further investigation.The findings of the present study were not inconsistent with a colonisation of Laos and Cambodia via southern Vietnam and into the Bolovens region; however, an earlier date (Miocene) was estimated relative to that reported by Attwood et al. (2008) . In thisng basin , is likeng basin . The resng basin . In this thought . The likN. aperta of the Cammon plateau in Laos are distinct ecotype, and that there is a marked lack of gene-flow between the northern and southern halves of the snail’s range. Consequently, further investigation is required to assess the potential for spring-dwelling snails to act as intermediate hosts for S. mekongi and to support transmission in habitats currently assumed to be free of schistosomiasis. The remarkable correspondence between ecogeographical area and snail population genetic structure suggests that some degree of ecological adaptation, in addition to physical barriers, inhibits introgression between these regions. In turn this suggests that persistence of snail populations in the Mekong river through spate periods is not achieved primarily by colonisation from seeder populations in tributary highland streams that experience a less severe flood cycle, which has been proposed as an explanation for snail persistence [The present study supports view that the spring-dwelling sistence . The finN. aperta exists as a metapopulation at multiple scales, including down to a micro-population-level granularity; this has implications for the design of schistosomiasis control interventions. Similarly, the lack of gene-flow between tributary populations (except perhaps those of Bolovens) and those of the Mekong implies that the effects of Mekong river and highland stream interventions will be independent. Interpretation of phylogenetic reconstructions implies that history shapes the current distribution of N. aperta and some expansion of the range is possible, especially after hydropower development alters the regional hydrology. The study has confirmed limited gene-flow between Cammon plateau populations in the North of the range and other populations, and that spring-dwelling snails are probably a distinct ecotype. Further work is needed to assess the epidemiological significance of the spring-dwelling taxa. The extent of the analyses was limited by the number of characters sampled and future studies should use more extensive sampling of the genome, which is now becoming more practical as technology improves. The present work used pre-existing data that included some very remote and/or now extinct sub-populations, as well as newly published data. The work therefore provides a record of the population-genetics of N. aperta prior to the impact of extensive hydropower development in the region, as well as an indication of the potential for range expansion as well as predictions of responses to schistosomiasis control.In summary, correspondence between ecogeographical sub-populations and clades identified phylogenetically, and by genetic distance based clustering, in the present study, illustrates the value of improved sampling . The study has shown that Field Research: Material from Laos was collected with the permission of the Ministry of Public Health Lao PDR. Material from Cambodia, with the permission of the Cambodia National Malaria Center. Material from Thailand, with the permission of Mahidol University (Faculty of Science).S1 TableExponential distributions are described as mean, offset.(CSV)Click here for additional data file.S2 TableThe estimates are mean ± SE (Standard Error of the mean). ESS, Effective Sample Size ; HDI, the 95% highest posterior probability density. The meanRate is the average rate for the branches on the tree weighted by branch length and expressed in substitutions/site/Ma.(CSV)Click here for additional data file.S1 Fig(PNG)Click here for additional data file.S2 FigThe observed value is indicated by the black diamond symbol.(PNG)Click here for additional data file.S3 Fig(PNG)Click here for additional data file.S4 FigA, Parzen scatterplot for distribution of genotypes along the first two PCs. B, a loading plot for the PCA.(PNG)Click here for additional data file.S5 FigNeotricula γ-aperta.Plots are shown for the first (A) and second (B) PCs in a PCA of standardised allele frequency data for (PNG)Click here for additional data file.S6 FigThe observed value is indicated by the black diamond symbol.(PNG)Click here for additional data file.S7 FigA, scree-plot of composite eigenvalues, with first two PCs in red. B, Decomposition of sPCA into Moran’s I against variance for each PC.(PNG)Click here for additional data file.


Local adaptation is a dynamic process by which different allele combinations are selected in different populations at different times, and whose genetic signature can be inferred by genome‐wide outlier analyses. We combined gene flow estimates with two methods of outlier detection, one of them independent of population coancestry (CIOA) and the other one not (ROA), to identify genetic variants favored when ecology promotes phenotypic convergence. We analyzed genotyping‐by‐sequencing data from five populations of a lizard distributed over an environmentally heterogeneous range that has been changing since the split of eastern and western lineages ca. 3 mya. Overall, western lizards inhabit forest habitat and are unstriped, whereas eastern ones inhabit shrublands and are striped. However, one population (Lerma) has unstriped phenotype despite its eastern ancestry. The analysis of 73,291 SNPs confirmed the east–west division and identified nonoverlapping sets of outliers (12 identified by ROA and 9 by CIOA). ROA revealed ancestral adaptive variation in the uncovered outliers that were subject to divergent selection and differently fixed for eastern and western populations at the extremes of the environmental gradient. Interestingly, such variation was maintained in Lerma, where we found high levels of heterozygosity for ROA outliers, whereas CIOA uncovered innovative variants that were selected only there. Overall, it seems that both the maintenance of ancestral variation and asymmetric migration have counterbalanced adaptive lineage splitting in our model species. This scenario, which is likely promoted by a changing and heterogeneous environment, could hamper ecological speciation of locally adapted populations despite strong genetic structure between lineages. We combined gene flow estimates with different methods of outlier detection, to identify different sources of genetic variability in a lizard with deep genetic structure in the Iberian Peninsula. We found evidence of the maintenance of ancestral genetic variation and genetic innovations being favored when ecology demands adaptive convergence. It is tIt is possible to screen genome‐wide patterns of DNA polymorphism to detect locus‐specific signals of divergent selection by using theoretical predictions about the effects of positive natural selection on allele frequencies  and a well‐developed layer of Cistus shrubs .We sampled lizards in the focal population (Lerma) and in two pairs of populations that replicated either its eastern genetic lineage  toward the posterior end of the animal. We measured the size of the striped surface with the “magic wand” tool (at 10% tolerance) after clicking at the middle of the stripe. We subsequently used the “similar” option of the “magic wand” tool (at 10% tolerance) to select pigmented scales and used the percentage of colored pixels in the analyzed surface as a measure of the size of the stripe. We measured the darkness of the stripe using the inverse of brightness of the colored layer. Note that we did not use a color standard to reduce the error in the measurement of brightness, but the fact that all lizards were photographed under the same conditions of illumination and exposure made our images directly comparable.During the breeding season of 2012, we took tissue samples from 18 adult lizards (>1 year old) noosed or captured by hand in Lerma. During the breeding season of 2015, we captured and sampled with the same methods another 77 lizards . These 95 lizards were used for genomic analyses. In 2016, we captured 18 lizards in Lerma that were used for the analysis of phenotypes along with the 77 lizards captured in the other populations during 2015. Therefore, different individuals from Lerma were used for genetic and phenotypic analyses. In order to characterize lizards' phenotype, we brought them to the laboratory to record their snout‐vent length (SVL) and body mass and to measure their dorsal coloration from images  with a cell lysis step of 24 hr and resuspension in DNase‐free water at 60°C.Pst1 for GBS library preparation. Sequencing was done in an Illumina HiSeq2500 sequencer. The pipeline used for SNPs discovery was UNEAK, implemented in TASSEL v.3.0  for which the model had highest predictive accuracy. However, we also explored higher K values to detect patterns of genetic structure among the five populations. To complement such clustering analysis, we performed a multidimensional scaling analysis (MDS) on TASSEL 5.2. . Although grouping will make the estimates of local population size not interpretable for pooled populations, this strategy does provide robust estimates of gene flow , or loci that could not be successfully sequenced from at least 75% of individuals in each population. The resulting SNP dataset included 6,421 loci.FST coefficients into a population‐specific term (β) and a locus‐specific term (α). We selected loci with α > 0, suggesting positive selection and a conservative false discovery rate (corrected for multiple testing) of q ≤ 0.05. To obtain these parameters, we ran the reversible‐jump MCMC algorithm implemented in the program with a prior odd value of 10, and using 20 pilot runs of 5,000 iterations each, followed by 100,000 iterations with a burn‐in of 50,000. In order to search for outliers taking into account the variation in the degree of relatedness among populations, we performed a CIOA using the Bonhomme et al.  and CIOA (HCIOA), using ANCOVA with population as factor, heterozygosity of the relevant set of outliers as the dependent variable, and overall heterozygosity (HALL) as the covariate.We analyzed variation among populations in the heterozygosity of outlier SNPs detected by ROA  revealed similar patterns for all phenotypes, with Aranjuez at one end of the phenotypic gradient and Lerma grouping with the western populations at the opposite end. Consistently with its suggested adaptive value, the proportion of striped lizards in each population remained strikingly constant between years, as shown by its high repeatability (intraclass correlation coefficient of 0.997) when comparing the values obtained in 2015 at Aranjuez, Brihuega, El Pardo, and Navacerrada with those reported by Díaz et al. . The proportion of striped lizards in Lerma (44%) was higher than in western populations, but their stripes were so tenuous that their overall phenotype was clearly western‐like , Aranjuez was the first population to separate from the rest of its lineage , followed by Brihuega and Lerma . However, when we set K equal to the number of populations in our sample, we did not detect any genetic structure between the two western populations . The MDS using the same dataset produced an axis with eigenvalue = 0.463, which defined an east–west gradient that discriminated between both mitochondrial lineages with p = 1.0  than in Brihuega (49.1 ± 0.6) or Aranjuez (6.25 ± 0.07).Our maximum‐likelihood estimates of gene flow revealed highly asymmetrical patterns of migration among lizard populations (ANOVA for among‐group variation in the estimates of immigration: 3.3α > 0 (0.97 < α < 1.35) and q ≤ 0.05. The CIOA identified nine additional outlier loci with p < .001, none of which was detected by Bayescan. The MDS analysis performed with all 21 outliers yielded a single axis  representing a divergence gradient with western populations on one end and Aranjuez on the opposite end. This analysis placed Brihuega near Aranjuez, and Lerma close to the western populations, thus recovering the same pattern observed for lizard phenotypes , placing all individuals from Aranjuez and Brihuega into two clusters, and dividing individuals of Navacerrada and El Pardo into two clusters that did not match the western populations  or to one of the two western groups (probability of assignment of 0.547 ± 0.155). When we forced the model toward higher cv‐errors, the next result was for K = 2 . However, the correlation was not significant in Brihuega  or in Lerma .Aranjuez and the two western populations, located at opposite extremes of the genetic gradient identified by MDS and admixture analyses, scored high homozygosity  for the outliers detected by ROA. Lerma, and to a lesser extent also Brihuega, scored significantly higher heterozygosity of ROA outliers than expected from overall genome heterozygosity  have evolved in Lerma when this population already had the ancestral genetic variation (at ROA loci highly homozygous in the west) that could be selected to warrant local adaptation to western‐like habitat. This paradox may hide a more complex scenario in which environmental gradients are multidimensional, with other factors  affecting the dynamics of local adaptation besides the forest‐to‐open gradient driving the divergence between the two lineages , which could hamper speciation despite strong genetic structure. Complex systems like this one may thus exemplify how to shed light on a variety of important questions at the interface between local adaptation and the first steps toward speciation (or the lack of it; Rosenblum, None declared.AL‐G, JP‐T, and JAD initiated and designed the study; AL‐G and JAD undertook fieldwork; AL‐G conducted molecular work; AL‐G analyzed molecular data; AL‐G, JP‐T, and JAD analyzed nonmolecular data; AL‐G wrote the first draft, and JP‐T and JAD contributed substantially with the revisions that led to the final manuscript.


Genomic studies of parallel (or convergent) evolution often compare multiple populations diverged into two ecologically different habitats to search for loci repeatedly involved in adaptation. Because the shared ancestor of these populations is generally unavailable, the source of the alleles at adaptation loci, and the direction in which their frequencies were shifted during evolution, remain elusive. To shed light on these issues, we here use multiple populations of threespine stickleback fish adapted to two different types of derived freshwater habitats—basic and acidic lakes on the island of North Uist, Outer Hebrides, Scotland—and the present‐day proxy of their marine ancestor. In a first step, we combine genome‐wide pooled sequencing and targeted individual‐level sequencing to demonstrate that ecological and phenotypic parallelism in basic‐acidic divergence is reflected by genomic parallelism in dozens of genome regions. Exploiting data from the ancestor, we next show that the acidic populations, residing in ecologically more extreme derived habitats, have adapted by accumulating alleles rare in the ancestor, whereas the basic populations have retained alleles common in the ancestor. Genomic responses to selection are thus predictable from the ecological difference of each derived habitat type from the ancestral one. This asymmetric sorting of standing genetic variation at loci important to basic‐acidic divergence has further resulted in more numerous selective sweeps in the acidic populations. Finally, our data suggest that the maintenance in marine fish of standing variation important to adaptive basic‐acidic differentiation does not require extensive hybridization between the marine and freshwater populations. Overall, our study reveals striking genome‐wide determinism in both the loci involved in parallel divergence, and in the direction in which alleles at these loci have been selected. The repeated emergence of similar life forms within ecologically similar environment provides particularly convincing evidence of determinism in evolutionary diversification driven by natural selection. While well documented at the phenotypic  level, the genomic underpinnings of such parallel evolution remain elusive—to what extent is phenotypic parallelism reflected by genomic parallelism, and where do the genetic variants used for repeated adaptation originate? To examine these questions, we study young  populations of stickleback fish displaying striking phenotypic similarity within multiple basic and acidic lakes on the island of North Uist, Scotland. We first type high‐density genome‐wide single‐nucleotide polymorphisms (SNPs) five basic and five acidic populations, and in individuals from two marine sites, the latter providing a meaningful present‐day surrogate of the genomic make‐up of the marine ancestor of the lake populations. Based on these SNPs, we establish that the basic and acidic lake populations have adapted independently from one another. We then identify numerous genomic regions in which the populations show strong and consistent differentiation according to habitat, indicating widespread parallel genetic responses to divergent selection. Inspecting allele frequencies and allele associations in these regions reveals sharing of the same genetic variants within each habitat type. This adaptive genetic variation is also found in the marine ancestor, although variants selected in the ecologically relatively extreme acidic lakes tend to be uncommon in the sea. Nevertheless, these variants do not appear to be eliminated from the sea, likely because they are selectively (nearly) neutral when occurring at low frequency. Overall, our work highlights that phenotypic parallelism can be mirrored by parallel evolution at the genomic level; that the genome‐wide sorting of standing genetic variation can be predicted from the ecological difference between novel and ancestral habitats; and that considering the ancestor can greatly strengthen genomic investigations of parallel evolution.multiple populations adapted independently to each habitat type are available, as such “parallel”  and west coast  of the island. These fish, however, were not lagoon‐residents—which exist on North Uist but are phenotypically distinct  or the Pst1 enzyme  . The rationale of the parallel restriction of each subpool with a separate enzyme was to avoid DNA fragments too short for sequencing that would have resulted from the simultaneous restriction with Nsi1 and Pst1 at recognition sites located in close proximity. Our parallel‐restriction approach  and then combined, yielding two replicate pools per population. These pools were then subjected to the standard RAD library preparation steps  and barcoded individually, pooled PCR‐free into a single library, and whole‐genome (not RAD) paired‐end sequenced to 151 base pairs on a single Illumina HiSeq2500 lane.http://www.novocraft.com/products/novoalign/; alignment settings provided on the Dryad repository, https://doi.org/10.5061/dryad.4ck2q0m). Resulting SAM files were converted to BAM format and accessed in R using Rsamtools , pooled over the two replicate libraries, and aligned to the third‐generation assembly , and by restricting the dataset to loner SNPs separated by at least 1 Mb (227 SNPs). Over this latter physical distance, linkage disequilibrium is minimal in this , and visualized the populations along the first two. Running a principal component analysis on the same data and visualizing the populations along the first two components produced almost identical results.In a second analysis, we explored the genetic similarity among our populations by ordination using nonmetric multidimensional scaling (NMDS) and the stringently filtered dataset described above . At each SNP, we first identified the major and minor allele across the global allele pool comprising all freshwater populations. Next, we randomly sampled a single allele from each population at each SNP, assigned these alleles the value of 1  or 0 , and derived a binary population similarity matrix from these values using the R function A major objective of our study was to assess if the repeated evolution of characteristic ecotypes within the basic and acidic lakes is mirrored by the consistent, parallel sorting of genetic variation between these habitats. Our key resource to address this question were genome‐wide scans for the magnitude of genetic differentiation performed for all 45 possible pairwise population comparisons within and across the freshwater habitat types. These included 25 basic‐acidic (B‐A), 10 basic‐basic (B‐B), and 10 acidic‐acidic (A‐A) population combinations. We here considered only SNPs displaying a total read coverage of at least 50× within each population, and a MAF across the global pool of all B and A populations superior to 0.2 to ensure adequate information content , was then integrated within each of the three freshwater habitat comparison categories. To do so, we calculated at each SNP the mean of the AFD values from all population pairs in a given comparison category, provided the SNP was represented by a sufficient number of individual comparisons . . The first approach was phylogenetic and involved deriving a single diploid multilocus genotype for each population by sampling two nucleotides at random from each population‐specific pool at each core SNP, and concatenating them as IUPAC characters. The resulting data were used to construct a maximum likelihood tree as described above. We then repeated this procedure for the same number of SNPs (N = 42) chosen at random from the genome‐wide SNP panel. To ensure that these latter “random SNPs” were minimally affected by divergent selection between the basic and acidic lakes, we here only considered SNPs exhibiting a magnitude of differentiation within 0.5% of the median value (AFD = 0.25) observed across all SNPs in the combined B‐A comparison. Our prediction in this phylogenetic analysis was that at the core SNPs, the basic populations should show a greater genetic similarity to the marine fish than the acidic populations, whereas in the genealogy for the random SNPs, no freshwater ecotype should appear systematically closer to the marine fish.Acidic lakes show a greater ecological difference from the sea than basic lakes, and acidic ecotypes display stronger phenotypic differentiation from their marine ancestor than basic ecotypes Fig. B and C. Our second approach to investigating if the acidic ecotypes are genetically more derived from their marine ancestor than the basic ones involved ordination using NMDS. We here followed the protocol described above, except that only a single ordination axis was extracted from both the core and random SNPs. Our prediction was that at the core SNPs only, the basic populations should display a greater genetic similarity, and hence greater proximity on the NMDS ordinate, to the marine fish than the acidic populations.The third approach, finally, was a locus‐specific analysis of allele frequencies at the core SNPs. We here first classified the two alleles at each SNP as “basic” or “acidic,” based on their average frequency over all populations within each lake type. That is, the allele exhibiting an average frequency >0.5 across the basic populations was considered the basic allele, and vice versa. Then we determined the frequency of the basic and acidic allele at each SNP in the marine population, which allowed us to evaluate the prediction that core SNP alleles characteristic of the acidic ecotypes occur at relatively low frequency in the marine ancestor. We here again used the random SNPs as a negative control, determining basic and acidic alleles as described for the core SNPs.As a robustness check, all analyses described in this section were repeated with an independent sample of random SNPs selected by controlling their magnitude of differentiation in the B‐A comparison less strictly. This produced very similar results supporting the same conclusions , we finally hypothesized that genetic diversity should be relatively reduced around the core SNPs in the acidic populations. The reason is that in these populations, the locally favorable variants must generally have experienced greater frequency changes reducing neutral variation in the physically linked chromosomal neighborhood particularly effectively   Fig. , and S11within each habitat type , 42 independent genomic regions satisfied our criteria for loci under highly parallel B‐A differentiation. These regions generally contained multiple SNPs nearly fixed for alternative alleles between most populations from the two lake types  in the marine fish at 32 of the 42 SNPs . The frequency distribution of the acidic alleles across the core SNPs was thus biased toward low values in marine stickleback and differed strikingly from uniformity expected for polymorphisms having segregated under selective neutrality for a long time —all core SNP alleles found in freshwater were also present in the sea. For the two core SNP regions scrutinized by targeted sequencing, the repeated use of standing variation during parallel evolution was confirmed directly by haplotype sharing among similar ecotypes from different lakes. Furthermore, adaptation to the ecologically relatively extreme acidic lakes has involved the accumulation of genetic variants relatively uncommon in marine fish, whereas the basic ecotypes have mostly retained the allele predominant in the sea. This B‐A asymmetry in marine core SNP allele frequencies provides a strong indication that these regions are truly involved in adaptation.in general.An intriguing question is why acidic core SNP alleles still occur at relatively appreciable frequencies in the sea Fig. C left—giAs a potential alternative explanation to migration‐selection balance, we consider that alleles selected to high frequency in acidic lakes may not be deleterious within the marine habitat when segregating at modest frequency—a prediction from models of local adaptation involving polygenic traits Latta —thus prepredominant one in the sea, strong allele frequency changes and associated selective sweeps tended to occur within the basic populations (negative B‐A difference in genetic diversity). These observations offer a further validation of the ecological importance of the genomic regions tagged by our core SNPs. In addition, this analysis indicates that allele frequencies observed in present‐day marine stickleback must be similar enough to those in the true marine ancestor of our freshwater populations to still allow detecting their association with patterns of genetic diversity shaped during adaptation.We have demonstrated that the differentiation between basic and acidic stickleback ecotypes on North Uist has generally involved the retention of alleles common in the ancestor in the basic lakes, and the selection of alleles uncommon in the ancestor in the acidic lakes. This implies that at loci important to B‐A differentiation, the basic populations must mostly have experienced relatively weak allele frequency changes, or no changes at all, whereas the acidic populations must have experienced stronger allele frequency changes and hence stronger associated reductions in genetic diversity , and the highest diversity occurred in the marine fish .Table S3. Pairwise comparisons per habitat (AFD and FST).Table S4. List of genes around the top core SNPs.Table S5. Characterization of the 42 core SNPs.Figure S1. Schematic description of the SNP generation protocol.Figure S2. Unrooted nuclear phylogeny .Figure S3. Marine‐freshwater differentiation by chromosome.Figure S4. Standardized basic‐acidic differentiation.Figure S5. BayPass analysis.Figure S6. Robustness check for random SNPs.Figure S7. Comparision SNP density vs. nucleotide diversity (π).Figure S8. Robustness check for selective sweeps.Figure S9. Unrooted nuclear phylogeny .Figure S10. Unrooted nuclear phylogeny .Figure S11. Unrooted nuclear phylogeny (SNP spacing at least 1Mb).Figure S12. Description of the top core SNPs.Figure S13. Genome‐wide basic‐acidic differentiation.Figure S14. Potential chromosomal inversions.Click here for additional data file.