Dicentrarchus labrax), the genomic regions involved in RI between Atlantic and Mediterranean lineages are enriched for anciently diverged alleles of unknown origin. Here, we used haplotype‐resolved whole‐genome sequences to test whether divergent haplotypes could have originated from a closely related species, the spotted sea bass (Dicentrarchus punctatus). We found that an ancient admixture event between D. labrax and D. punctatus is responsible for the presence of shared derived alleles that segregate at low frequencies in both lineages of D. labrax. An exception to this was found within regions involved in RI between the two D. labrax lineages. In those regions, archaic tracts originating from D. punctatus locally reached high frequencies or even fixation in Atlantic genomes but were almost absent in the Mediterranean. We showed that the ancient admixture event most likely occurred between D. punctatus and the D. labrax Atlantic lineage, while Atlantic and Mediterranean D. labrax lineages were experiencing allopatric isolation. Our results suggest that local adaptive introgression and/or the resolution of genomic conflicts provoked by ancient admixture have probably contributed to the establishment of RI between the two D. labrax lineages.Understanding how new species arise through the progressive establishment of reproductive isolation (RI) barriers between diverging populations is a major goal in Evolutionary Biology. An important result of speciation genomics studies is that genomic regions involved in RI frequently harbor anciently diverged haplotypes that predate the reconstructed history of species divergence. The possible origins of these old alleles remain much debated, as they relate to contrasting mechanisms of speciation that are not yet fully understood. In the European sea bass ( Speciation is often viewed as a progressive accumulation of reproductive isolation (RI) barriers between two diverging lineages through time. However, because it is a progressive process, speciation can once initiated take different pathways, sometimes leading to the erosion of an established species barrier or the acquisition of new speciation genes transferred from another species boundary. Here, we describe such a case in the European sea bass. This marine fish species split 300,000 years ago into an Atlantic and a Mediterranean lineage, which remained partially reproductively isolated after experiencing postglacial secondary contact. For unknown reasons, genomic regions involved in RI between lineages started to diverge well before the split. We here show that diverged alleles were acquired by the Atlantic lineage from an ancient event of admixture with a parapatric sister species about 80,000 years ago. Introgressed foreign alleles that were locally driven to high frequencies in the Atlantic have subsequently experienced reduced gene flow between the Atlantic and Mediterranean populations during the postglacial secondary contact, thus contributing to increased RI between two sea bass lineages. These results support the view that RI barriers can evolve via reticulate gene flow across multiple species boundaries.Drosophila pseudoobscura and Drosophila persimilis, which show higher divergence than collinear regions of the genome  barriers among diverging populations  is a marine fish species subdivided into two glacial lineages, which correspond to current Atlantic and Mediterranean populations . It is generally assumed that increased dXY indicates the presence of haplotypes that started to diverge earlier than the rest of the genome. However, regions of increased divergence may simply have resisted gene flow during secondary contact, whereas haplotypes in the remainder of the genome got rejuvenated due to recombination. This later hypothesis has however been rejected in the European sea bass based on simulations accounting for both background selection and selection against introgressed tracts . Our results show that gene flow occurred between D. punctatus and the Atlantic lineage of D. labrax about 80,000 years ago, resulting in a low background ancestry from D. punctatus in contemporary D. labrax genomes. By contrast, genomic regions involved in RI between the two D. labrax lineages generally display high frequencies of haplotypes derived from D. punctatus in the Atlantic, whereas these archaic tracts remain rare in the Mediterranean. This suggests that ancient admixture has played an important role in the evolution of RI between Atlantic and Mediterranean Sea bass lineages, consistently with predictions from models of local adaptive introgression and selection against genetic incompatibilities.The European sea bass  and 59 new D. labrax individual genomes. Fifty‐two of them were wild individuals captured from the Atlantic Ocean , the western Mediterranean Sea , and the eastern Mediterranean Sea . Some of these specimens were experimentally crossed to generate first generation hybrids, which were used to phase the genome of their parents using a phasing‐by‐transmission approach. To this end, seven F1 hybrids obtained from seven different biparental families (pedigree ♂AT x ♀WME) were also submitted to whole‐genome sequencing. All captive breeding procedures were performed at Ifremer's experimental aquaculture facility . Fish were reared in normal aquaculture conditions in agreement with the French decree no. 2013–118 (1 February 2013 NOR:AGRG1231951D).We sequenced the whole genome of one Whole genome sequencing libraries were prepared separately for each individual using either the Illumina TruSeq DNA PCR‐Free  or the TruSeq DNA Nano protocol , depending on DNA concentration (Table S1), and following Illumina standard recommendations. Pools of five individually barcoded libraries were then sequenced on 12 separate lanes of an Illumina HiSeq3000 using 2 × 150 bp PE reads at the GeT‐PlaGe Genomics platform . Thirty‐three individuals were sequenced twice due to insufficient amounts of sequence reads obtained in the first run (Table S1). For each individual, the alignment of PE reads to the sea bass reference genome  , containing 5,074,249 phased SNPs without missing data. The genetic relationships of the newly sequenced genomes with respect to the 16 already available were evaluated with a Principal Component Analysis . Although we detected a slight genetic differentiation between North and South eastern Mediterranean samples on the PCA , D. punctatus (PUNC), and the Atlantic (AT) and Mediterranean (MEDE) D. labrax lineages. We choose to use only the MEDE population because the western Mediterranean population (WME) is deeply introgressed by Atlantic alleles , D. punctatus as the potential donor species (P3), and the two D. labrax lineages as potential recipient populations (P1 and P2). We used the dataset containing 14,579,961 SNPs from D. punctatus and unphased D. labrax samples, and only kept sites that were available for both M. saxatilis and D. punctatus in genome alignments, representing a total of 9,606,462 SNPs. This allowed testing for different amounts of gene flow between P3 and P2, and P3 and P1, by comparing the number of genealogies of type ,O)  and ,O) . An excess of shared derived alleles between the donor and one of the two recipient populations  indicates gene flow from D. punctatus to D. labrax population P2 or P1, respectively. Although the ABBA‐BABA test is adequate to detect introgression, the Patterson's D statistic that measures the imbalance between the two types of genealogies (D=sum(ABBA)−sum(BABA)sum(ABBA)+sum(BABA)) is not appropriate to quantify introgression over small genomic windows s) to estimate admixture proportion between P2 and P3, where s = sum(ABBA‐BABA) and PD corresponds to the most likely donor population . To test for admixture between D. punctatus and different populations of D. labrax, we made different tests using successively the Atlantic (AT), eastern , western (WME), or the whole Mediterranean (MED) populations of D. labrax populations as P2 or P1. We used scripts from Martin et al. fD statistics in nonoverlapping 50‐kb windows along the genome, keeping only windows containing at least 500 SNPs.We tested for admixture between D. labrax lineage, we identified variants that were not shared with the eastern Mediterranean population, and conversely to test for introgression in the Mediterranean D. labrax lineage. We only analyzed the eastern Mediterranean population because the western Mediterranean is more strongly impacted by gene flow from the Atlantic , as the fraction of haplotypes for which a window was identified as introgressed. The inferred fraction of introgressed archaic tracts was finally averaged in nonoverlapping 50‐kb windows along the genome.Second, we used a method that allows archaic introgressed tracts to be identified without using an archaic reference genome for the donor species  over the average divergence of those populations to an outgroup species (dout). If gene flow has occurred genome‐wide, then locally elevated RNDmin values indicate regions where introgression has been limited or absent. We used MVFTools version 5.1.2 . For this analysis, we used 4,943,488 polymorphic sites that were phased within D. labrax and nonmissing in D. punctatus. On one hand, this dataset excludes a large number of variants that are differentially fixed between D. punctatus and D. labrax, and therefore underestimates the real level of divergence between D. punctatus and D. labrax. On the other hand, excluding diagnostic SNPs rendered the test more sensitive to the detection of ancient introgression, because the accumulation of divergence after introgression only adds noise to chromosomal variations in RNDmin. We estimated dout by averaging the divergence measures between M. saxatilis and the two Dicentrarchus species. All values were averaged in nonoverlapping 50‐kb windows along the genome.Finally, we used the RNDD. labrax lineages, we mapped Atlantic tracts introgressed into Mediterranean genomes and vice versa. Local ancestry inference was performed with Chromopainter version 0.04  were then combined to estimate the fraction of introgressed tracts (Fintro) for each position along the genome, which was finally averaged in nonoverlapping 50‐kb windows. For every variable position along the genome, Fintro is thus estimated as the fraction of individuals for which this position is located on an introgressed tract.To test whether ancient introgression has influenced genomic patterns of postglacial gene flow between Atlantic and Mediterranean D. labrax lineages. Genomic regions involved in RI between European sea bass lineages are characterized by elevated genetic differentiation and increased resistance to gene flow . Our rationale was that these regions should be associated with both high FST  and low Fintro values  . We used the HMM approach to map RI at two different scales, a SNP‐by‐SNP  and a 50‐kb window scale, which was more suitable to delineate regions . We used VCFtools version 0.1.15 , intermediate , and high FST/Fintro ratio values . The most likely state of each SNP/window was inferred by running the HMM algorithm chromosome‐by‐chromosome. Finally, we controlled for false discovery rate and retained only SNPs/windows with an FDR‐corrected P‐value inferior to 0.001  and fD values (see results) using D. punctatus as a donor species, we used the length of archaic haplotypes that were identified with the method of Skov et al. D. labrax lineages were considered, corresponding to 1310 windows of 50 kb. This choice was justified because archaic tract detection relies on a signal of differential introgression between two populations. Therefore, archaic tracts can be correctly identified and delimited only if they are present in one lineage  but absent in the other , which was only the case in RI islands between Atlantic and Mediterranean D. labrax lineages (see Results).We used two different approaches to estimate the time since foreign introgression within d Fisher . Because(L¯) as a function of the number of generations since introgression (t), the local recombination rate (r in Morgans per bp), and the proportion of admixture (f), which takes the form L¯=[(1−f)r(t−1)]−1 , as well as between the two lineages of D. labrax (tAtlantic – Mediterranean). For each estimation, we used the average value of the retained windows. Hence, for tlabrax – punctatus: f = 0.096, r = 3.693×10−8 M/bp . Parameter p was estimated separately for each chromosome by averaging over the values estimated per individual haplome. We finally estimated Tadmix chromosome‐by‐chromosome using the average recombination rate and the fraction of archaic introgressed tracts of each chromosome (Table S2). The time in generations was converted into years using a generation time of 5 years  should be positively correlated to fD. Moreover, if the abundance of archaic tracts within Atlantic D. labrax explains the presence of anciently diverged alleles between Atlantic and Mediterranean Sea bass lineages, dXY should increase with the amount of ancient admixture. Finally, if regions involved in RI between Atlantic and Mediterranean Sea bass lineages harbor reduced frequencies of D. punctatus‐derived tracts in the Mediterranean, a positive correlation is expected between RNDmin measured between D. punctatus and Mediterranean D. labrax and ancient admixture from D. punctatus within the Atlantic.We used Spearman's correlation test to evaluate relationships among D. punctatus within D. labrax genomes, separately in the Atlantic and Mediterranean lineages. Because anciently introgressed alleles most likely originated from D. punctatus (see Results), we used D. labrax polymorphic sites for which M. saxatilis harbors the ancestral and D. punctatus the derived state  to characterize ancient introgression. For each of these SNPs, we measured the frequency of the D. punctatus‐derived allele separately in the Atlantic and Mediterranean D. labrax populations using VCFtools. We then separated SNPs associated to RI islands from those that were not associated to RI islands in the SNP‐based HMM analysis to represent the site frequency spectrum of each D. labrax lineage, conditioned on D. punctatus being derived (CSFS). Finally, two conditioned joint site frequency spectra (CJSFS) were generated  to represent the bi‐dimensional SFS between Atlantic and Mediterranean D. labrax lineages, conditioning on sites that have the derived allele in D. punctatus. These analyses aimed at distinguishing two hypotheses with respect to the mechanisms underlying differential introgression of D. punctatus‐derived mutations in RI islands between Atlantic and Mediterranean D. labrax. Our first hypothesis was that anciently introgressed alleles are not directly involved in RI but simply maintained at different frequencies because genetic barriers between D. labrax lineages  have impeded their postglacial rehomogenization. In this case, we expected no excess of high‐frequency D. punctatus‐derived mutations in RI islands compared to non‐RI regions. Alternatively, under the hypothesis that anciently introgressed alleles are associated with RI in sea bass, an excess of D. punctatus‐derived mutations almost fixed within RI islands in the Atlantic but nearly absent in the Mediterranean was expected compared to the alternate configuration .We then focused on SNP‐level statistics to specifically address the frequency distributions of derived mutations from M. saxatilis), the spotted sea bass (D. punctatus), and the European sea bass (D. labrax), which is further subdivided into two partially reproductively isolated populations: the Atlantic and Mediterranean Sea bass lineages. The most represented topology found genome‐wide across most of the 50‐kb windows corresponds to the expected species tree  was more than five times higher than divergence between Atlantic and Mediterranean D. labrax lineages (0.1%), consistent with previous estimates  compared to the Atlantic D. labrax lineage (0.53%). Within D. labrax, divergence to the Atlantic population was higher for the eastern (0.1%) compared to the western Mediterranean population (0.09%) , as expected due to gene flow between Atlantic and Mediterranean D. labrax lineages  between the Atlantic and Mediterranean lineages of D. labrax  was found along the genome in both Atlantic (4.85% in non‐RI islands) and Mediterranean (2.73% in non‐RI islands) D. labrax individuals  compared to the Mediterranean lineage. Interestingly, those regions also presented the highest fD values . These results thus support the hypothesis that the detected archaic segments that locally reach high frequencies in some regions of Atlantic D. labrax genomes have been inherited from D. punctatus at some time in the past. Furthermore, regions of particularly increased D. punctatus ancestry also showed the highest absolute divergence values between Atlantic and Mediterranean D. labrax lineages, with positive genome‐wide correlations being found with dXY for both fD  and Farchaic .We also searched for the presence of archaic introgressed tracts in ls Figs.  and S3C.min statistic to detect chromosomal variations in ancient introgression. Values of RNDmin measured between D. punctatus and the Atlantic D. labrax lineage were low and relatively constant along chromosomes  and fD  in Atlantic genomes, along with increased dXY between Atlantic and Mediterranean D. labrax lineages . These results thus indicate the existence of outlying patterns of D. punctatus ancestry in the most divergent genomic regions between D. labrax lineages, due to increased and decreased frequencies of anciently introgressed tracts in the Atlantic and Mediterranean lineages, respectively, compared to the background level. Interestingly, the relative proportions of the two discordant topologies were similar along most of the genome, except for regions with locally increased values of dXY, Df (for the AT population), Farchaic (for the AT population), and RNDmin (for the Mediterranean populations). In these regions, we found an excess of discordant genealogies grouping D. punctatus with the Atlantic D. labrax lineage , thus strengthening the association of RI‐islands to differential rates of archaic ancestry.Finally, our HMM approach allowed 70,738 SNPs to be categorized as being likely associated with RI islands between the two es Figs.  and S3G.ean Fig. . They alD. punctatus and D. labrax by first comparing the length distribution of D. punctatus tracts introgressed into Atlantic D. labrax genomes to that of Atlantic D. labrax tracts introgressed into western Mediterranean D. labrax genomes  than Atlantic D. labrax tracts ). Dicentrarchus punctatus tracts were also less abundant in almost all length classes except for the shortest tracts ·3.693e−8·5513)+1andtAtlantic−Mediterranean=1((1−0.341)·3.23e−8·52026)+1, which placed the timing of admixture between D. punctatus and D. labrax approximately six times earlier than the secondary contact between the two D. labrax lineages. Using the age of secondary contact previously estimated between Atlantic and Mediterranean Sea bass lineages  of the HMM model used to detect archaic introgressed tracts to estimate one value of Tadmix for each chromosome (Table S2). From the obtained time distribution  years.We estimated the timing of past gene flow between mes Fig. . The twocts Fig. . We estiion Fig. , we estiD. punctatus alleles segregate in D. labrax. For SNPs that were not associated to RI‐islands by the HMM approach, the one‐dimensional distribution of allele frequencies (CSFS) was highly similar between Atlantic and Mediterranean D. labrax lineages, showing a bimodal shape with few intermediate frequency variants , partially overlapping range distributions, and interfertility in artificial crosses , which is only slightly higher than the estimated persistence of archaic ancestry in humans and brown bears  of anciently introgressed tracts along Atlantic D. labrax genomes. By contrast, regions of elevated RNDmin that coincided with the location of RI‐islands revealed local resistance to introgression in Mediterranean D. labrax genomes. These results tend to be confirmed by the excess of genealogies grouping D. punctatus with the Atlantic compared to those grouping it with the Mediterranean lineage of D. labrax within RI‐islands. Therefore, both lineages contain D. punctatus introgressed tracts at relatively similar levels outside RI islands, which contrasts with strong archaic ancestry differences found within RI‐islands.Another potential issue with the tests performed to detect ancient admixture is that they often rely on differential introgression patterns between two candidate recipient populations  and southern Mediterranean Sea . It is thus likely that the latitudinal range shifts that occurred during quaternary ice ages  and a hybrid zone, as it exists between Atlantic and Mediterranean Sea bass lineages.Reproductive isolation may also have evolved through the resolution of genetic conflicts resulting from the contact between two diverged populations (Schumer et al. D. punctatus about 80,000 year ago have contributed to the strengthening of nascent RI between Atlantic and Mediterranean D. labrax lineages. The resulting genomic architecture of RI between contemporary D. labrax lineages is thus constituted by a mosaic of fixed blocks of different ancestries, that is, a mixture of genetic barriers inherited from the divergence history particular to D. labrax and the contribution of ancient admixture. Although additional analyses will be needed to fully understand which process has driven the fixation of D. punctatus alleles within Atlantic genomes, the resolution of genetic conflicts between D. punctatus and D. labrax seems the most parsimonious hypothesis (Schumer et al. To conclude, our results show that divergent haplotypes that were introgressed from Associate Editor: Dr. Z. GompertSupplementary Table 1. Summary statistics of sequencing and mapping data for each individual.Supplementary Figure 1. Depth of coverage per individual.Supplementary Figure 2. Principal Component Analysis of the European sea bass population genetic structure.Supplementary Figure 3. Statistics measured in non‐overlapping 50 kb windows along the genome.Supplementary Figure 4. Genome‐wide correlations between pairs of statistics measured in non‐overlapping 50 kb windows.Supplementary Figure 5. Introgressed tract length distributions.Supplementary Figure 6. Data and results for the SNPs and 50 kb window based HMM approach to identify regions involved in reproductive isolation between the two lineages of D. labrax along chromosome 7.Supplementary Figure 7. Distributions and joint allele‐frequency spectrums of derived D. punctatus alleles present in D. labrax.Supplementary Figure 8. Distributions of the fraction of archaic tracts for Atlantic and Mediterranean genomes inside and outside regions involved in RI.Supplementary Table 2. Values used to estimate Tadmix for each chromosome.Click here for additional data file.


Use of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools . The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted.Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity  and differentiation . Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data.Here we used microsatellite and SNP data generated from Gunnison sage-grouse (We demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms. Accurate estimation of population genetic parameters has become an important part of wildlife conservation . GeneticA single nucleotide polymorphism (SNP) is a location in the DNA sequence where individuals vary at a single nucleotide. Technological advancements have allowed creation of much larger SNP genotype datasets, greatly increasing the number of loci sampled with less effort and lower cost in comparison to microsatellite development and genotyping . BecauseIn addition to the potential improvement in precision of population parameter estimates from the increased number of loci, the explosion of genomic techniques and their application to non-model organisms has also led to the ability to ask new questions about conservation , 36. SNPTechnological advancements in genomic approaches for non-model organisms has resulted in use of reduced representation sequencing methods to generate large SNP datasets for many wildlife species; datasets that are often archived and available for potential future use. Understanding how SNP data compare to inferences made from the more traditional microsatellite data is important for long-term genetic monitoring given the increasing trend of using SNP data for conservation objectives. Previous studies have compared the relative abilities of SNP and microsatellite loci to evaluate levels of relatedness –49, probCentrocercus minimus) is a sagebrush obligate avian species listed as threatened under the Endangered Species Act in 2014. The species exists as a network of seven populations predominantly occurring in Colorado and a small portion of the range extending into Utah HO had the lowest correlation across marker type   while values from SNPs were lower, ~ 0.200 . Values of HE showed high correlation , and relative consistency in ranking populations across marker types . The values for HE were within similar ranges as HO, microsatellite estimates at ~ 0.500 (range: 0.413–0.578) and SNP estimates at ~ 0.200 , and consistent ranking of populations by levels of genetic diversity  across marker type , however, ranking of populations was not as consistent  across marker types and the magnitude of the values for each marker type resulted in different inferences in some cases . All differentiation metrics had a high correlation across marker types and datasets , 5 groups with all SNPs (BIC = 454.768), and putatively adaptive SNPs (BIC = 298.376), and 4 with putatively neutral SNPs (BIC = 449.803). The optimal number of PCs to include in the DAPC analysis as determined by the a-score method was 22 for microsatellites, 6 for all SNPs, 5 for putatively neutral SNPs, and 6 for putatively adaptive SNPs. Clustering of individuals in DAPC with microsatellites identified Piñon Mesa as the only population that clearly separates from the other populations along discriminant function 1  for three populations. SNPs, however, would have an obvious advantage if conservation actions required an understanding of the relative levels or ranking of most measures of genetic diversity.Of the four diversity metrics evaluated here, see Fig. . HO, howmoderate , 59, 64. of SNPs , or whet of SNPs , 75; twos Table S. Howeverr > 0.9, p ≤ 0.05 for all comparisons). Some argue reliance on a single measure of differentiation for conservation purposes risks inaccurate characterization of populations [p ≤ 0.05 in all comparisons). Different metrics of population differentiation showed a consistent pattern of which populations were most similar, though the magnitude of a metric was sometimes very different. If the magnitude of the differentiation metric is of conservation relevance, then the marker types are not equivalent.In general agreement with multiple studies –60, 64 aulations –78. Our ulations , 60, butDJost is considered a relative degree of allelic differentiation, while FST and GST are fixation indices [DJost tended to produce values higher in magnitude with microsatellites than with SNPs [DJost [GST estimates with microsatellites , versus the theoretical maximum heterozygosity for SNP loci (HE = 0.5), will also result in higher magnitudes of GST when calculated from microsatellite data. Importantly, FST has proven to be more robust to per locus allelic diversity and heterozygosity . Frfixation . FixatioFST proving more robust [DJost will be much smaller in magnitude, and to a lesser degree, so will GST. Relatively low levels of mutation, migration, and small populations typically correspond to lower allelic diversity. Gunnison sage-grouse is composed of seven isolated populations, with very low migration rates among populations, though not as low as SNP mutation rates. Our comparison of FST values across marker types demonstrates relatively consistent agreement between both magnitude and ranking of pair-wise comparisons , and ha samples , 54, 88.Blood samples were collected near breeding grounds within six of the populations as part of a 2005 study . The datFrom the same 254 previously collected blood samples that were genotyped at microsatellite loci, a subset were previously chosen for RAD-Seq  based onHO), expected heterozygosity (HE), allelic richness per locus (AR), and inbreeding coefficient (FIS) using the ‘diveRsity’ [For each putatively neutral dataset, we estimated observed heterozygosity . We retained all of the PCs, ran the algorithm for 100,000 iterations, and used 10 starting centroids per run. The number of genetic clusters (K) with the lowest BIC was selected, as recommended by Jombart et al. [K for each dataset, we used the a-score method to identify the optimal number of PCs to retain in DAPC while constructing linear functions to describe genetic differentiation among K groups. Second, we created dendrograms from an individual-based genetic distance matrix calculated as the proportion of differing nucleotide sites [hclust in R and the “ward. D2” method [We compared the identification of distinct units using microsatellites, all SNPs, putatively neutral SNPs, and putatively adaptive SNPs. First, we performed discriminnant analysis of principal components (DAPC) with microsatellites, putatively neutral SNPs, all SNPs, and candidate adaptive loci with the ‘adegenet’ package in R . DAPC sut et al. . After wde sites , excludi” method . The “waAdditional file 1: Table S1. Diversity statistics. Table S2. Differentiation statistics. Fig. S1. Dendrograms created using the “single” (based on closest pair) method. Fig. S2. Dendrograms created using the “complete” (based on furthest pair) method. Fig. S3. Dendrograms created using microsatellite loci from the 60 individuals included in the SNP dataset. Fig. S4. Discriminant analysis of principle components (DAPC) for microsatellite from the 60 individuals sampled for SNPs.


Cryptozona siamensis, one of the most widespread land snails, is native to Thailand, and plays a key role as an agricultural pest and intermediate host for Angiostrongylus spp. However, its genetic diversity and population structure has not yet been investigated, and are poorly understood. Therefore, a genetic analysis of the C. siamensis population in Thailand was conducted, based mitochondrial 16S rRNA (402 bp) and COI (602 bp) gene fragment sequences. Cryptozona siamensis randomly collected from 17 locations in four populations across Thailand, between May 2017 and July 2018. Fifty-eight snails were used to examine the phylogeny, genetic diversity, and genetic structure. The maximum likelihood tree based on the 16S rRNA and COI fragment sequences revealed two main clades. A total of 14 haplotypes with 44 nucleotide variable sites were found in the 16S rRNA sequences, while 14 haplotypes with 57 nucleotide variable sites were found in the COI sequences. The genetic diversity of C. siamensis in term of the number of haplotypes and haplotype diversity, was found to be high but the nucleotide diversity showed low levels of genetic differentiation for the COI sequence as also noted with the 16S rRNA sequence. The population genetic structure of C. siamensis revealed genetic difference in most populations in Thailand. However, low genetic difference in some populations may be due to high gene flow. This study provides novel insights into the basic molecular genetics of C. siamensis. Cryptozona siamensis, a terrestrial pulmonate gastropod, belongs to the family Ariophantidae [Cryptozona siamensis have been reported as the intermediate host of Angiostrongylus that cause eosinophilic meningitis in human worldwide especially China, Taiwan, and Thailand [Cryptozona siamensis are important as intermediate hosts that promote the endemicity and transmission of Angiostrongylus cantonensis and A. malaysiensis [A. cantonensis [A. cantonensis in human [Cryptozona siamensis is native to Thailand, and is regarded as a cosmopolitan species, being one of the most widespread land snails in Southeast Asia [C. siamensis from areas adjacent to Thailand, such as Malaysia, Singapore, and Laos [Cryptozona siamensis has gained attention as an important agricultural and horticultural pest, in India, the United States of America, and Thailand [The land snail hantidae , 2. CrypThailand , 4. Crypysiensis , 5, 6. Ttonensis , 8. Ingein human . Cryptozast Asia , with reand Laos , 12. CryThailand , 14.ST matrices revealed the substantial geographic genetic structuring and complex dispersal patterns of the land snail Succinea caduca [Camaena cicatricosa from 20 locations using mitochondrial gene (COI and 16S rRNA) and internal transcribed spacer (ITS2) sequences. This showed significant fixation indices of genetic differentiation and high gene flow among most populations [Achatina fulica was found to be low [Cryptozona siamensis and Sarika resplendens) and Dyakiiaea (Quantula striata) was also noted by using 16S rRNA gene [In the last few years, DNA sequencing data has been used to study and clarify the evolution of morphological characteristics of ambiguous organisms –18 whilea caduca . In Chinulations . In Thaio be low . In LangRNA gene .C. siamensis is currently poorly understood, as it has been the focus of only a limited number of studies. The genetic structure of C. siamensis from 3 populations of Thailand and additional one population from Malaysia was studied on allozyme variation on horizontal starch gel electrophoresis [C. siamensis was examined in previous study, no nucleotide sequencing of this land snail is available in the country. Therefore, the objective of this research was to investigate the genetic diversity and genetic structure of C. siamensis from Thailand, based on mitochondrial DNA-sequence variation at the COI and 16S rRNA loci.Molecular population phylogeographic studies can offer information on specific genetic variations, population formations, and genetic structure . Moreovephoresis . AlthougThe experimental protocol for the use of animals (snail intermediate host) in this study was approved by the Center for Animal Research of Naresuan University . The biosafety protocol was approved by the Naresuan University Institutional Biosafety Committee .A. cantonensis, which uses snails as an intermediate host, C. siamensis specimens were randomly collected from 17 locations across Thailand, between May 2017 and July 2018  pepsin solution, as previously described [C. siamensis samples in this study were found to be negative for Angiostrongylus larvae.During a survey for uly 2018 . The snauly 2018 . The snaiamensis . These iiamensis . The bodescribed . FortunaC. siamensis was extracted using a Tissue & Cell Genomic DNA Purification Kit , according to the manufacturer’s instructions. An aliquot of the DNA solution was checked by running it on a 0.8% (w/v) agarose gel, in a 1 × TBE buffer, at 100 V. The gel was stained with ethidium bromide, followed by a destaining with distilled water, and photographed under UV light. The rest of the DNA solution was kept at -20°C for later use as the PCR template.Genomic DNA from each individual 5′-CGCCTGTTTATCAAAAACAT-3′) and 16Sbr (5′-CCGGTCTGAACTCAGATCACGT-3′) primer [® PLUS 2 × Master mix , 1.5 μl of 5 μM of each primer (0.25 μM), 9 μl of distilled water, and 3 μl of the DNA template (20–200 ng). Thermal cycling for the 16S rRNA PCR amplification was performed at 96°C for 2 min, followed by 35 cycles of 94°C for 30 s, 45°C for 1 min, and 72°C for 2 min, and then a final 72°C for 5 min [5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO2198 (5′-TAAACTTCAG GGTGACCAAAAAATCA-3′) primer [® Gel and a PCR Clean-up kit , according to the manufacturer’s instructions. An aliquot of the purified PCR product was checked by 1.2% (w/v) agarose gel electrophoresis as above, while the rest was used as the template for commercial sequencing  in both the forward and reverse directions using the same primers as in the PCR.The DNA fragment (500 bp) of the 16S rRNA gene was amplified by PCR using the 16Sar  primer . The PCRor 5 min . The 710) primer  as descrCryptozona was performed by BLASTn searching the NCBI database (http://blast.ncbi.nlm.nih.gov/Blast.cgi) an aligning the obtained homologous nucleotide sequences using ClustalW. Phylogenies were estimated using maximum likelihood (ML) with the general time reversible model, neighbor joining (NJ) with Kimura two-parameter (K2), and maximum parsimony (MP) with the subtree-pruning-regrafting (SPR) and node support values, based on 1000 bootstrap replicates, in the MEGA Version 7.0 program [The nucleotide sequences were edited by viewing the peaks of the chromatogram in the SeqMan II software . Phylogenetic analysis, including species identification  of the  program . In addi program , where t program . AlthougHaplotype diversity and nucleotide diversity were calculated in ARLEQUIN, version 3.5.1.2 . The relFST. Analysis of molecular variance (AMOVA) performed in ARLEQUIN was used to test the genetic difference among groups. Although the data were generated for 16S rRNA and COI gene fragments, for most of the populations from the different regions, the substitution rate was higher for the COI, making it the more appropriate and informative population level marker. Thus, the COI data were the focus of the population genetic structure analyses.The genetic differentiation among the populations from each region, was calculated in ARLEQUIN, based on pairwise Cryptozona species, 58 individual land snails  were randomly selected for genetic studies. PCR-based analysis and sequencing of their 16S rRNA and COI regions, was performed, together with a BLASTN search of the edited sequences. Based on the 402 bp of the 16S rRNA gene, all 58 sequences (GenBank accession nos. MK858467-MK858524) in this study showed high identity (96 to 99%) with those of GenBank accession no. JQ728565, which is in agreement with the identification of the taxa in the present study as C. siamensis.To identify the C. siamensis from Malaysia with 97% of Bayesian posterior probability. Clade 2 contained 3 sequences from the Chon Buri Province , revealed 2 main clades , for the 58 n clades . Clade 1n clades .C. siamensis in Thailand and 7 sequences from Malaysia in 4 populations . Fourteen haplotypes (16S1-16S14) were identified with 44 nucleotide variation sites  was obtained from 58 sequences of on sites . Of theson sites . The geo02 bp wason sites ..Fourteen haplotypes CO1-CO14), from the 58 sequences of the 4 populations  in Thailand, were identified, based on the COI genes (602 bp) with nucleotide variations at 57 sites . Of thes-CO14, frFST values for the 16S rRNA sequences of the C. siamensis, revealed statistically significant differentiation (P < 0.05), whereas between the populations C and D no genetic differences were identified . The 65 16S rRNA gene sequences, were classified into 14 haplotypes, 9 that were unique, and 5 that were shared between the different populations. The 58 COI sequences were classified into 14 haplotypes, 9 that were unique and 5 that were shared between the different populations. High haplotype diversity  was also reported from Camaena cicatricose in China [A. fulica in Thailand [C. siamensis, were different. These results were similar to those from a previous report on the genetic diversity of the 16S rRNA and COI genes of the land snail Cyclophorus fulguratus [C. siamensis. Many previous reports in land snails have established that the COI gene is a reliable molecular marker for phylogenetic analysis [C. siamensis in the present study could be due to small sample sizes. This was consistent with the previous research on the Succinea cadusa snail [Camaena cicatricosa and Succinea caduca [Collisella subrugosa snail in Brazil showed variation due to environmental conditions and differing selection pressures [We have analyzed the genetics of the land snail in China . In contThailand . The genlguratus ; as the lguratus . In termlguratus , and thuanalysis –46. In csa snail . The patsa snail . The gena caduca , 29. In ressures .C. siamensis from all populations. Previous research has suggested that when the pairwise FST is greater than 0.15, it implies a high level of genetic differentiation among the population. Whereas, if the pairwise FST is between 0 and 0.05, it implies a low level of genetic differentiation between the populations [FST values showed a significant genetic differentiation between the most populations, based on the analysis of the 16S rRNA and COI genes. Moreover, the phylogenetic analysis and haplotype network construction showed the lack of clear population genetic structures. This suggests that the gene flow within the C. siamensis population in Thailand might bring about genetic homogeneity [FST values, based on the 16S rRNA and COI sequences between the populations, were over 0.15. In contrast, the pairwise FST based values on the 16S rRNA sequences, showed different results in some populations compared to the COI sequences. This suggested that the 16S rRNA gene had a relatively slow of evolution rate, and a low variability, compared to the COI gene [C. siamensis population may be affected by the ecological environment, climate barriers, and geographic barrier factors [Camaena cicatricose [Cyclophorus fulguratus [Euhadra quaesita [C. siamensis.The population genetic structure was examined using the COI and 16S sequence data from 4 populations of Thailand. The substitution rate for the COI gene was high in the ulations . In thisogeneity . In thisCOI gene , 50. Thi factors , 29. Thilguratus , 51. In quaesita . It may C. siamensis in Thailand based on 16S rRNA and COI genes was found among some populations. The results suggested that extensive gene-flow was a possibility. In support of this, considerable levels of gene-flow have been reported among C. siamensis populations in Thailand. Populations of C. siamensis in the areas with a low level of genetic differentiation, exhibit higher levels of gene flow than the populations with a high genetic differentiation [C. siamensis from the three regions of Thailand, and one region in Malaysia. The population of C. siamensis among the 3 geographic regions  of Thailand as well as the population in Malaysia, showed a high degree of gene flow. This was consistent with the research that the haplotype network of C. siamensis in Thailand was shared and linked to the haplotype from Malaysia with mutation steps. In the present study, gene flow within the C. siamensis population in Thailand could be possible for several reasons. Cryptozona siamensis often occurred in habitats associated with human activities, such as vegetable gardens, in flower pots, and in wall crevices of houses. In particular, the transportation of potted plants or vegetables contaminated with snails across provinces may have promoted the movement of snails. Therefore, the possibility of dispersal of C. siamensis among populations in each area by humans could be plausible. Similarly, the African land snail in China, A. fulica, could be spread through shipments of plants especially pot plants [C. cicatricosa in China could be spread through cargo transportation [C. siamensis between populations in each region may arise by human activities [C. siamensis from Thailand may be explained using several possibilities. In addition, transportation by human activities may promote the spread of A. cantonensis which is hosted by this land snail. Similarly, Lv et al. (2009) reported the distribution of A. cantonensis in China associated with invasive land snail, A. fulica [C. siamensis infected with A. cantonensis was found in the present study, previous reports found that C. siamensis was infected with A. cantonensis. In Thailand, C. siamensis infected with A. cantonensis was found in Phetchabun, Kalasin, Phitsanulok, and Kamphaeng Phet provinces [C. siamensis are uncommon dish for people in Thailand. Human may get infection with A. cantonensis by consumption of vegetable contaminated with A. cantonensis larvae [C. siamensis is important to maintain the life cycle of A. cantonensis and may transmit to human.The genetic homogeneity of ntiation . Althougntiation . Recentlt plants , as wellortation . Therefotivities . The postivities , 56. In tivities . The mov. fulica . Althougs larvae . TherefoC. siamensis samples taken in Thailand. The maximum likelihood tree based on the 16S rRNA and COI fragment sequences of C. siamensis revealed two main clades. Most of the sequences fell in clade 1 and 3 samples from Chon Buri Province (population A) was placed in clade 2. The genetic diversity of C. siamensis in term of the number of haplotypes and haplotype diversity, was found to be high but the nucleotide diversity among the different populations of Thailand showed low levels of genetic differentiation for the COI sequence as also noted with the 16S rRNA sequences. Population genetic structure of C. siamensis based on FST value in 16S rRNA and COI genes was genetically different among most of population exception of some populations. Genetic differentiation in the populations of the C. siamensis may result from the effects of the ecological environment, climate barriers, and geographic barriers. However, low genetic difference in some populations may be due to high gene flow which may occur from the transportation by human activities. In addition, transportation by human may lead to spread of A. cantonensis which is hosted by C. siamensis. This study shows the genetic diversity of the C. siamensis populations across several regions of Thailand, and their interrelatedness.We have reported on the genetic diversity of the 16S rRNA and the COI genes, from the S1 Table(XLS)Click here for additional data file.S2 Table(XLS)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.


Eunicea flexuosa. Previous analyses based on a handful of markers could not distinguish between models of genetic exchange after a period of isolation (consistent with secondary contact) and divergence with gene flow (consistent with primary divergence). Analyses of the history of isolation, genetic exchange and population size based on 15,640 new SNP markers derived from RNAseq data best support models where divergence began 800K BP and include epochs of divergence with gene flow, but with an intermediate period of transient isolation. Results also supported the previous conclusion that recent exchange between the ecotypes occurs asymmetrically from the Shallow lineage to the Deep. Parallel analyses of data from two other corals with depth‐segregated populations (Agaricia fragilis and Pocillopora damicornis) suggest divergence leading to depth‐segregated populations may begin with a period of symmetric exchange, but that an epoch of population isolation precedes more complete isolation marked by asymmetric introgression. Thus, while divergence‐with‐gene flow may account for much of the differentiation that separates closely related, depth‐segregated species, it remains to be seen whether any critical steps in the speciation process only occur when populations are isolated.The distributions of many sister species in the sea overlap geographically but are partitioned along depth gradients. The genetic changes leading to depth segregation may evolve in geographic isolation as a prerequisite to coexistence or may emerge during primary divergence leading to new species. These alternatives can now be distinguished via the power endowed by the thousands of scorable loci provided by second‐generation sequence data. Here, we revisit the case of two depth‐segregated, genetically isolated ecotypes of the nominal Caribbean candelabrum coral  Eunicea flexuosa co‐occur across the Caribbean, with high levels of gene flow among populations. Demographic analyses based on SNPs derived from RNA‐seq data suggest a long history of genetic exchange during this pairs' divergence, but also 100K years of transient isolation that may have played a key role in finalizing speciation.Two depth‐segregated, genetically isolated ecotypes of the sea fan  Such plEchinometra, Landry et al., The geographic distributions of close relatives, however, do not all fit a model of strict allopatric speciation. Examining the geographic ranges of over 1,000 species of New World seaweeds, Pielou  found thHow then to explain the formation of new marine species with pelagic larval development without deep geographic divides? One way is to recognize that the geographic ranges of species are dynamic, such that the degree of overlap between sister species that we see today reveals little about their ranges during steps leading towards genetic isolation. Distant colonization events, geological change or the alternation of sea level or prevailing currents may produce transiently isolated populations. Divergence between these populations and their ancestral source could initiate reproductive isolation that was either continued or completed upon secondary contact. The genetic imprint of such diverge and reconnection may be well preserved in coastal species with limited dispersal . The two ecotypes, Shallow and Deep, differ in several aspects of colony and spindle morphology   and the Deep ecotypes (27) from both their native depth and an intermediate depth in Parguera (Media Luna Reef), Puerto Rico. To confirm the Shallow and Deep ecotypes, we sequenced the 5′ end of the diagnostic mitochondrial ) Bayer, . We presE. flexuosa. Transcriptomic data provided the best option. Second, these RNAseq data come from a larger reciprocal transplant experiment aimed at testing changes in gene expression.We chose to use RNAseq to generate SNPs for our demographic analysis for two reasons. First, corals host many microbial symbionts, including single‐celled algae that can number >30,000 per cell. DNA from these symbionts must be filtered out or they can confound demographic analyses of their host. Algal symbionts can be screened if bleached or naturally symbiont‐free colonies are available to create a reference + RNA by hybridizing it with oligo (d)25 magnetic beads. We then coupled the extraction kit with the NEBNext® RNA Library Preparation Kit following the manufacturer's recommendations (except we used ½ reactions) with a final PCR enrichment step. Libraries were examined for quality with a Bioanalyzer 2100 (Agilent Technologies) and quantified with a fluorescent plate reader (Sinergy HTX). To avoid lane effects, we barcoded all samples with unique codes, pooled them and sequenced across six HiSeq 2000 (100 PE) lanes. Sequencing was done at the Vincent J. Coates Genomics Sequencing Laboratory (GSL) at UC Berkeley.To isolate high‐quality mRNA, we dissected ~25 mg of tissue and used the NEB2.2http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Before assembling the transcriptome, we removed bacterial RNA and Symbiodinium contamination with Deconseq‐graph_0.1 . We retained the unmatched reads for downstream analysis.We cleaned and trimmed raw reads as necessary (often six bases at the 5′ end) using Trimmomatic‐0.33 , avoiding linked SNPs.To call SNPs, we used 2.3moments . Using the P. homomalla's transcriptome as an outgroup, we then generated the unfolded SFS using moments  and projected the SFS to 48 (Deep) and 58  alleles. To account for variability in the SFS estimation, we used a nonparametric bootstrapping by resampling the SNP file generated from vcf2dadi.pl five times using dadiBoot.pl (available: https://groups.google.com/forum/#!searchin/dadi‐user/vcf2dadi.pl/dadi‐user/kvzhF4XSyng/idVM5lLUpt0J).To transform the filtered VCF file to https://github.com/z0on/AFS‐analysis‐with‐moments/) in moments. Briefly, the models for two diverging populations can include up to three historical epochs, during which effective population size can vary from other epochs. Parameters for genetic exchange can also vary among epochs and may be symmetrical or asymmetrical. SNPs can be partitioned into two classes: those belonging to genomic islands that experience enhanced differentiation or limited exchange and the rest of the genome. Critically, multiple models not only allow for divergence with gene flow  and various forms of secondary contact (genetic exchange subsequent to an epoch of isolation) but can account for changes in population size in ancestral and post‐split populations. Simulations  scores, differences between each model against the best model, the relative likelihood of each model given the data, the model probability and the evidence ratio in favour of each model. We used the evidence ratio to rank each model and followed Anderson  in adeneget v. 2. 1.1 for a dataset of 15,640 SNPs. We plotted samples using PC1 and PC2. To better understand the structure of the populations across depth gradients, we performed a discriminant analysis of principal components (DAPC) in Adegenet v. 2.1.1, partitioning the variance into that between‐ and within‐groups to maximize discrimination. The number of clusters inferred was estimated by 1,000 iterations of the K‐means clustering between K = 1 and 3 after retaining all PCs, and selecting the optimal number of PCs by 1,000 replicates of the a‐score. We also inferred neighbour‐joining trees using the R package phangorn v2.5.5  shallow and deep populations of what has been a single nominal species are genetically differentiated and (b) genomic data  were available.Agaricia fragilis system in Bermuda  or deep (D) except individuals AFMPX6982H and AFMPD6982H, as we were unable to tell their sampling location or whether it was a mismatched individual, respectively. Our final data set consisted of nextRAD‐derived 8,898 SNPs across 93 individuals .The first is the Pocillopora damicornis collected from the shallow reef flat (F) and deeper reef slope (S) areas on Heron Island in the southern Great Barrier Reef .The second data set is from 39 100‐bp PE raw reads were generated from the 59 individuals of E. flexuosa  than any alternative , divergence with gene flow is estimated to have begun 561 Kya, leading into a 500+ Ky epoch of asymmetrical gene flow, primarily from Shallow to Deep ‐gene‐flow, as more complicated histories of transient genetic isolation may still have occurred  that allows for more complex patterns and with over 3,000 times as many genetic markers as before. This large number of markers provides a robust estimate of the site frequency spectrum, the basis for demographic analyses (like moments) that perform best at recent time scales  using moments all supported divergence‐with‐gene‐flow  population expansion for both ecotypes. Such a pattern is common to many Caribbean reef‐associated species  selection. If so, genetic diversity would be lower than for truly neutral markers .The best‐fit model for E. flexuosa  in isolation? As of yet, we do not know the genetic basis of the ecological and reproductive traits that segregate the two ecotypes. Outlier analyses for candidate genes associated with phenotypic divergence may help identify them. Given that information, and a genomic sampling of multiple individuals, new approaches could help to map and date selective sweeps driving divergence . Together, these suggest that multiple components of the coral holobiont play a role in adaptation with depth and potentially to giving rise to depth‐segregated reef species.Finally, a full understanding of divergence with depth may require knowledge of the interactions between the coral host and its consortium of symbionts. In All authors declare no conflict of interest.C. P. and M. E. H. designed the study and wrote the manuscript; C. P. performed the field and laboratory research and analysed the data.https://publons.com/publon/10.1111/jeb.13731.The peer review history for this article is available at Supplementary MaterialClick here for additional data file.


Chrysodeixis includens. First, we sequenced mitochondrial markers to conduct a phylogeographic investigation of C. includens historical processes. Then, we combined a de novo genotyping‐by‐sequencing approach with a study of agricultural landscapes to uncover recent processes of adaptation. Primarily, we found low genetic diversity across all markers and clear indications of a recent demographic expansion. We also found a lack of significant isolation by distance (IBD), and weak or absent genetic structure considering geographic locations. However, we did find initial signs of population differentiation that were associated with host plant types . Agricultural landscape attributes, including soybean crops, were significantly associated with putative markers under positive selection. Moreover, positive selection associated with host differentiation was putatively linked to digestive enzymes. This study showed how landscape composition and host plants can affect the evolutionary process of agricultural pest insects such as C. includens.Evolutionary studies of insect pests improve our ability to anticipate problems in agricultural ecosystems, such as pest outbreaks, control failures, or expansions of the host range. Here, we investigated the mechanisms underlying the evolutionary processes behind the recent census size expansion and local adaptation of  However, there is no clear connection between population dynamics  and the underlying adaptive process, mainly because of differences in the time scales on which ecological and evolutionary dynamics operate  (Lepidoptera: Noctuidae: Plusiinae), a native to the Americas, has emerged as a serious pest of soybean and cotton  to measure the levels of population genetic structure in important agricultural areas in Brazil, and (c) to test whether positive selection is taking place in different geographic regions and cultivated crops; and if confirmed, then to investigate which environmental features are associated with the ongoing adaptive processes. In a broader context, our goal was to shed more light on the adaptive processes that allow previously unimportant insects to become significant pests.Recent studies using inter‐simple sequence repeat (ISSR) markers in Brazilian populations of 22.1C. includens were collected from 15 of the principal common bean, soybean, and cotton‐producing regions in Brazil between January and May 2017, by actively collecting larvae or with pheromone traps. Approximately 800 larvae of C. includens were collected per sample site in the field. After they matured, 30 insects were transferred to individual 1.5‐ml Eppendorf tubes containing 99% EtOH and stored at –80°C until further sample processing. Considering the geographic range of soybean and cotton cultivation, we directed our sampling efforts to cover the most ecologically or climatically diverse combination of natural areas  and crop types that could provide a realistic view of the Brazilian agriculture mosaic (Table Specimens of ic Table .DNA was extracted from the insects by using an adapted CTAB (2%) extraction protocol and resuspended in 70 µl of Milli‐Q water  and the United States Geological Survey EarthExplorer (USGS EarthExplorer) repositories, respectively. A buffer of a 25‐km radius from the sampled point was used to delimit the size of the classified landscapes used. Landscapes were classified in the software ArcGIS 10.2.2, using the “create signature” option that uses different spectral responses that can be associated with the presence of a class . Supervised classification was performed using a maximum‐likelihood classification and was manually inspected for errors and misclassifications. At two geographic locations (BACO and MTCV), two sample collections were performed (soybean versus predominantly cotton areas) in overlapping landscapes. We only performed the analyses on the soybean landscape at those two locations, to ensure a minimum difference in the time frame between sample collections, avoiding the effect of migration between the landscapes. Soybean and cotton landscapes were contrasted later in separate analyses.2) *10,000], number of patches, and mean patch area were collected to describe landscape structure and composition. For the “landscape‐level metrics,” the Shannon diversity index (SHDI) and Shannon evenness index (SHEI) were estimated  had their dimensional space reduced by PCA transformation. This approach allowed us to assess the position of each putative population in environmental space (climate + hosts). We used the coordinates of the projections on the first PC axis as our independent variables. The importance of each variable in the PCA was presented as the variable contribution to the first PC axis, which was given by squaring the product of the loadings by the component standard deviation and dividing it by the square of the total PCA loadings multiplied by the component standard deviation  was used to reduce the dimensionality and to simplify pattern recognition of the landscape and climate variables. We selected land cover as our patch‐based metric to study the response to the landscape composition at the genomic level. The 14 land‐cover attributes were transformed with PCA to reduce the dimensionality, and the first PCA coordinate was used as a predictor. We selected land cover as our primary landscape variable based on our a priori knowledge that 2.3Two mitochondrial fragments from the COI and COII genes were amplified in PCR for 61 individuals from 15 sample sites Appendix  Monteir. Raw mit2.4PstI, CTGCAG) was used during the genome digestion step to reduce genome complexity. After library preparation, DNA samples were quantified by qPCR, and the size distribution checked using an Agilent BioAnalyzer. Libraries were sequenced on an Illumina HiSeq 2500 (100‐bp single‐end reads) at the Animal Genome Centre at USP/ESALQ , from 12 sample sites Table . Samples2.5C. includens COI haplotype relationship and genetic diversity throughout the Americas. Details of the method are shown in Appendix For COI‐COII concatenated sequences, we calculated the haplotype diversity and nucleotide diversity parameters using DnaSP ver. 5  and the number of mismatches allowed between stacks to merge them into a single allele (M = 4). Setting m to 3 has shown good performance for a broad range of data and represents a good trade‐off between coverage and polymorphs . We used the general criteria of M = n. In the following step, STACKS matches loci found in each individual against the catalog, using default settings. Using this approach, STACKS genotyped a total of 340,089 loci with mean effective per‐sample coverage of 97.7× (stdev = 27.9×), minimum coverage 10.1×, and maximum coverage 164.8×.Raw sequences were demultiplexed, trimmed to 90 bp, and filtered according to the population module to filter missing data, retaining only loci present in 80% or more individuals within a sampling location (r = .8) and ~80% or more across sampling locations (p = 8). Minor allele frequency cutoff was set at 0.05, and maximum observed heterozygosity limited to 50%. The resulting dataset was saved as VCF, genepop, and structure files and converted to other formats using PGDSPIDER 2.0 when necessary  implemented in BEAST version 1.8.2  from a simple pooled population to perform the demographic reconstruction analysis  interactions, using 10 replications for each K value without prior population information. The analyses were run from K = 1 to K = 10, allowing allele correlation and an admixture model. The most likely number of clusters was determined using the Evanno method implemented in STRUCTURE HARVESTER 0.6.93   under neutrality  of 0.05. To assure more stringent detection parameters, we selected the “force mean FST” and “neutral mean FST” options. We also used a Bayesian approach that estimated the posterior probability of a given locus to be under selection, contrasting this assumption with the neutral model. A second analysis was implemented in BayeScan v2.1  detected by both Lositan and BayeScan, and landscape and climate variables. The partial Mantel test accounts for the nonindependence of points by creating a random distribution to use as a null distribution and test for significance  based on “snmf.” Again, for this analysis, individuals collected from cotton landscapes were removed, as were individuals with more than 10% missing data. The two variables were used to test the associations with climate and landscape. To test the association, we used the coordinates of the first PC of WorldClim variables and the landscape composition (percentage of each component of the landscape) described in the previous section . The Gibbs sampler algorithm was run for 10,000 cycles, following a burn‐in of 5,000 cycles. To control for false‐positive detection, we used the Benjamin–Hochberg algorithm, adjusting the false discovery rate (FDR) q = 10%. Putative loci under selection detected by more than one method were used as queries in a BLASTx search against the NCBI database, using Blast2GO  was also tested using a latent factor mixed‐effect model (LFMM) implemented in R package 33.1C. includens revealed a star‐like topology of the haplotype relationships, with a central haplotype (haplotype H1) that is widely distributed and in a high frequency, and additional haplotypes at low frequencies , connected to the central haplotype by a single mutation step  of Brazilian p Figure . The ubiC. includens in Brazil seems to be evenly distributed through the species’ range and is moderate to low. The haplotype and nucleotide diversities across the locations sampled were Hd = 0.455 and π = 0.00048, respectively. Haplotype and nucleotide diversities were highest in the Cerrado  and Atlantic Forest biomes (Hd = 0.505 and π = 0.00059) and lowest in the Caatinga biome, where each sample site had only a single haplotype   and Fu's Fs . In addition, the model of a sudden expansion did not reject the hypothesis of a spatial expansion for C. includens . Similarly, the EBSP analysis based on 50 nuclear sequences showed a signature of recent demographic expansion in the C. includens populations. Based on the assumed molecular clock calibration (2.9 × 10−9 mutations/site/generation), the expansion started ~300 years before the present   Figure . Soybean) Figure . The sec) Figure . Based sThe PCA of the agricultural landscapes, based on the land‐cover attributes, revealed similarities and dissimilarities between the landscapes and was highly useful for pattern recognition Figure . The firThe PCA of the WorldClim data defined a climate space of reduced dimensionality where the agricultural landscapes are located. The first two components were significant and together explained 80.1% of the overall variance Figure . The fir3.4HO = 0.005 ± 0.000), and inbreeding coefficient (FIS = 0.004–0.007) were found across the 12 sites where samples collected in the same regions were more similar , but a consistent separation of collecting sites according to broad regions, where samples collected in the same regions were more similar according to FST values . The STRUCTURE analysis confirmed a low degree of differentiation among the sampling locations. However, a higher value of K (K = 4) was detected by the Evanno method , observed heterozygosity  among population pairs, independently of the method used , but not in MTCV  Figure . When co4C. includens population is undergoing demographic expansion. The results of the analysis  are consistent with the history of diversification and demographic expansion observed in the Americas . The demographic reconstruction traces the beginning of the C. includens population expansion back to the year 1,700, coinciding with the period of colonization of the Americas. However, the demographic reconstruction  must be cautiously interpreted, given that the genome‐wide mutation rate for this particular species is not known   and by host  can be identified and indicate a process of differentiation driven by both genetic drift and positive selection. In our study, soybean fields were the predominant agricultural type in all landscapes, covering up to 50% of the total area in some cases . The existing extensive soybean fields might be reducing genetic diversity in C. includens. If this is the case, then the levels of genetic diversity of C. includens may be affected by genetic drift, promoted by continuous processes of (re)colonization of soybean crops and rapid increases in population density within a short period. In a recent study, the number of moths captured by light traps in farmland in the Brazilian Cerrado was positively correlated with the presence and phenological stage of local soybean crops, where the period of high moth density in the area lasted only 60 days , along with the continuing adoption of Bt soybeans in Brazil  has been detected (Kaplanoglu, Chapman, Scott, & Donly, Inevitably, extensive monoculture areas will not only favor the performance of certain herbivores but impose strong selection pressures on the populations of pest insects Via, . In addi4.2C. includens when cotton plants were the main driver. Further studies are needed to reinforce the evidence of host‐related race formation and the functional importance of the candidate genes listed here.Understanding how genetic diversity is distributed over the range of a species is essential to study patterns of gene flow and to assess adaptive trends. Knowledge of the genetic structure of populations will enable us to more reliably infer which biotic and abiotic factors may be responsible for gene‐pool isolation or the lack of it Avise, . Habitat5C. includens in Brazil. This pattern could be attributed to recurrent evolutionary processes such as gene flow, or to a historical process associated with demographic expansion and host‐related adaptations. Analyses of the landscape composition suggested that the increase in the soybean crop area is likely important for the process of local adaptation, in particular in relation to host‐specific adaptations. Landscape composition and configuration may explain the still‐incipient differentiation between the hosts; and no effect of climate variables was detected. Our results reinforced the general recommendation for polyculture and for more diverse agroecosystems as strategies to prevent the rapid evolution of undesirable traits. Polyculture including one or more nonhost plants often limits the total number of pest insects relative to the numbers in monoculture systems, by reducing food resources and offering more opportunities for antagonistic ecological interactions with natural enemies, for instance (Risch Both the mitochondrial and SNP markers revealed a pattern of low genetic diversity and a weak or absent genetic structure in ce Risch .Bt and pesticide resistance could affect C. includens. Understanding how adaptive processes shape the evolutionary trajectory of pest populations will not prevent the ongoing transformation of natural populations, but can guide us in a search for better resistance monitoring and crop‐succession management over time.The present data increase our understanding of how the host range and future problems of None declared.ASC, CSS, EMGC, GH, PMD, and RAC conceived and designed the study. CSS collected the data. ASC, CSS, and EMGC analyzed the data. ASC, PMD, and RAC provided reagents, analytical tools, and financial support. ASC, CSS, and EMGC wrote the manuscript. All authors read, corrected, and approved the manuscript.Appendix S1‐S7Click here for additional data file.


Pampusminor) is an economically important fish, and its numbers are declining because of overfishing and environmental pollution. In addition, owing to the similarities of its external morphological characteristics to other species in the genus Pampus, it is often mistaken for grey pomfret (P.cinereus) or silver pomfret (P.argenteus) juveniles. In this study, the genetic diversity and structure of 264 P.minor individuals from 11 populations in China and Malaysia coastal waters were evaluated for the first time, to the best of our knowledge, using mitochondrial cytochrome b fragments. The results showed that P.minor had moderate haplotype diversity and low nucleotide diversity. Furthermore, two divergent lineages were detected within the populations, but the phylogenetic structure corresponded imperfectly with geographical location; thus, the populations may have diverged in different glacial refugia during the Pleistocene low sea levels. Analysis of molecular variation (AMOVA) showed that genetic variation originated primarily from individuals within the population. Pairwise FST results showed significant differentiation between the Chinese and Malaysian populations. Except for the Xiamen population, which was classified as a marginal population, the genetic differentiation among the other Chinese populations was not significant. During the Late Pleistocene, P.minor experienced a population expansion event starting from the South China Sea refugium that expanded outward, and derivative populations quickly occupied and adapted to the new habitat. The results of this study will provide genetic information for the scientific conservation and management of P.minor resources.The southern lesser pomfret ( Because of the rise in fishing pressure, habitat destruction, and global climate change, understanding the level of marine biological variation and its genetic structure is of crucial significance to the protection of marine biological resources and genetic diversity . CurrentPampusminor Liu & Li, 1998 is an offshore warm-water pelagic fish classified under the class Actinopterygii, order Perciformes and family Stromateidae. It is a newly discovered species, distributed primarily south of the mid-southern East China Sea and along the coast of Southeast Asian countries , this species was consistently mistaken for grey pomfret (P.cinereus) or silver pomfret (P.argenteus) juveniles in early studies , P.minor was also strongly affected by the Pleistocene glacial period. Thus, under the harsh environmental conditions of the glacial period, most of the individuals within its distribution range went extinct, and only a handful of isolated populations in glacial refugia (such as the South China Sea) survived. As the climate warmed during interglacial periods, sea levels rose, which led to population expansion; hence, the corresponding phylogeographic patterns and population genetic structure may be detected.The region in which nal seas , which tP.minor thus far, which have only focused on morphology  were used to study the genetic diversity, genetic structure, and historical demography of 11 P.minor populations in China and Malaysia coastal waters. In addition, the effects of paleoclimatic, paleo-geological, marine geological, environmental and other factors on population formation, distribution and expansion routes, as well as genetic exchange, were revealed. This enabled us to investigate the mechanisms underlying the current phylogeographic patterns of this species, which can serve as a scientific reference for fishery management.In this study, mitochondrial DNA sequences  and Malaysia  were collected  was amplified with the primers L14734: 5’-AACCACCGTTGTTATTCAACT-3’ .Genomic DNA of CAACT-3’  and H151CAACT-3’ . All PCRCytb sequences were aligned using the DNASTAR  software and manually edited. Haplotypes were defined based on sequence data without considering sites with gaps using DnaSP ver. 5.00 (AMOVA) in ARLEQUIN software was employed to investigate the genetic variation and test population structure. The MEGA 5.0 (NJ) tree based on the genetic distance among haplotypes, and implemented with 1000 replicates. The relationships of haplotypes by unrooted minimum spanning tree (MST) was evaluated via the MINSPNET algorithm in ARLEQUIN software , and τ   . The rea–7/site/year  was significantly higher than G+C content, thus showing an AT bias.A total of 264 sequences were obtained from the 11 Cytb haplotypes were defined in the 264 individuals. The number of haplotypes in each population ranged from three to seven. The number of haplotypes shared by two or more populations was eight (36.4%). There were 14 unique haplotypes (63.6%), and seven populations had unique haplotypes, with the number ranging from one  to four (SK)  and low nucleotide diversity (0.0035 ± 0.0023). This phenomenon is usually due to bottleneck effects, resulting in population expansion or rapid population growth in small populations, accompanied by the generation of a large number of new mutations .Based on the TrN+G model, the net genetic distance between the two haplotype lineages was 0.006. Based on a mitochondrial FST between populations were relatively large. The FST values between the Chinese and Malaysian populations were all above 0.25, and statistical tests indicated significance, thus showing very great differentiation FST betweulations .AMOVA was used to detect the genetic structure of the populations , accounting for 52.26% of the variation, whereas genetic differentiation among populations accounted for only 47.74% of the variation.ns Table . First, P.minor populations, the 11 populations were grouped into two, four, and six gene pools based on their geographic distribution. The results of all groupings showed that the genetic differentiation among groups was relatively large with statistical significance (p < 0.05), whereas genetic differentiation originating primarily within populations was highly significant (p < 0.01), and genetic differentiation among populations within groups was also significant (p < 0.01).To further confirm the genetic structure of the P.minor sequences was unimodal, and similar results were found in both lineages . Tajima’s D test for each lineage and the overall population yielded negative values, and were all statistically significant, except for lineage 2. In addition, the SSD and HRI test indices were not significant (p > 0.05)  also indicated the same result  Table , indicatult Fig. .–7/site/year and τ, the population expansion time points of lineages 1 and 2 were estimated to be 101 and 218 Kya, respectively, which was during the Late Pleistocene. The ratio of 1θ after expansion to 0θ before expansion is infinite, indicating a sharp increase in the size of the effective maternal population of P.minor after population expansion. BSPs for lineage 1 and lineage 2 showed that both lineages have undergone the Late Pleistocene demographic expansion , which was larger than that of lineage 1   (P.argenteus (h = 0.775 ± 0.041) (Anguillamossambica (0.691 ± 0.043)  , P.arge± 0.041) , Anguill± 0.043)  and otheutations .P.minor compared to other economic fishes have helped maintain its moderate level of genetic diversity. In addition, P.minor is a widely distributed species and has a wide dietary preference. Its spawning grounds exhibit different characteristics according to the different marine regions in which it is distributed, and its habitat conditions are heterogeneous . The discontinuity of habitats and the instability of population changes can result in differentiation between species populations . Both thrganisms .P.minor. With the arrival of the fourth glacial period, the sea level fell by about 120~140 m, and P.minor populations may have become isolated in the South China Sea refugium. After the glacial period, as sea levels rose, P.minor populations in the refugium expanded toward the coasts of China and Malaysia. The NJ tree and haplotype network tree show that Hap_1 was the only shared haplotype between the Chinese and Malaysian populations, and accounted for a relatively large number of individuals. This indicated that it was the ancestral haplotype, thus further demonstrating that the P.minor populations originated from the same refugium.In the Late Quaternary, the global climate experienced a series of glacial-interglacial cycles. In the last 800 Kya, climate fluctuations mainly occurred at intervals of ~100 Kya . The fouCytb gene acts as a subunit in complex V of the oxidative phosphorylation pathway , small yellow croaker (Larimichthyspolyactis), and hairtail (Trichiurushaumela), will been avoided.Based on these results, we speculate that the time during which P.minor in China and Malaysia coastal waters were evaluated. The results showed that all P.minor had moderate haplotype diversity and two divergent lineages. The phylogenetic structure of P.minor corresponded imperfectly with geographical location at the Cytb gene level, but significant divergence between Chinese and Malaysian populations was detected. To get precise phylogeographic structure, more sensitive DNA markers such as SLAF, RAD and WGS will be employed and reveal the adaptive evolution mechanism of this species. Lower haplotype diversity is detected in China, which further indicated that Chinese fishery resources are facing greater fishing pressure and more focus is needed on fishery protection and management.Genetic signature of


Gasteracantha cancriformis circumscribes a species with profuse variation in size, color and body form. Distributed throughout the Neotropics, G. cancriformis is the only morphological species of Gasteracantha in the New World in this globally distributed genus.Modern molecular analyses are often inconsistent with pre-cladistic taxonomic hypotheses, frequently indicating higher richness than morphological taxonomy estimates. Among Caribbean spiders, widespread species are relatively few compared to the prevalence of single island endemics. The taxonomic hypothesis Gasteracantha using three target genes. Within the Caribbean, we estimated genetic diversity, population structure, and gene flow among island populations.We inferred phylogenetic relationships across Neotropical populations of Gasteracantha throughout the Caribbean, G. cancriformis, while suggesting two recently divergent mainland populations that may represent separate species, diverging linages, or geographically isolated demes. The concatenated and COI (Cytochrome c oxidase subunit 1) phylogeny supported a Caribbean clade nested within the New World. Genetic variability was high between island populations for our COI dataset; however, gene flow was also high, especially between large, adjacent islands. We found structured genetic and morphological variation within G. cancriformis island populations; however, this variation does not reflect genealogical relationships. Rather, isolation by distance and local morphological adaptation may explain the observed variation.Our findings revealed a single widespread species of  Tropical island archipelagos are some of the most biodiverse and species-rich ecosystems on the planet . As spatIslands have been used extensively as tools for studying dispersal patterns because oceans act as tough filters against taxa with low vagility . A lineaGasteracantha, the spiny-backed orb weaver, is a widespread spider genus . These spiders build remarkably conspicuous orb webs in open areas  use molecular data to reconstruct a novel phylogeny; (2) examine the genetic diversity, population structure, and geographic distribution within the Caribbean; (3) assess correspondences between genetics, morphology, and geology. To accomplish these goals, we present a novel molecular phylogeny based on the most extensive sampling and first molecular dataset within the Caribbean.Here we tested the taxonomic hypothesis and phylogeography of Gasteracantha were collected (2011–2016) from Cuba, Hispaniola, Jamaica, Mona, Puerto Rico, the Lesser Antilles, Turks and Caicos (TCI), Mexico, Costa Rica and the South Eastern United States (SEUS) using standard aerial searching and vegetation beating methods (Gasteracantha (data from  methods . The speCOI: Cytochrome c oxidase subunit I), (16S: 16SrRNA), and one nuclear loci , that have demonstrated successful amplification and informative variation in spiders at low taxonomic levels  under default settings. The final alignments were then aligned by eye, edited and maintained in Mesquite.We extracted DNA from 148 individuals with the QIAGEN DNeasy extraction kit. We amplified two mitochondrial loci  was set as a normal prior with mean = 0.0112 and SD = 0.001; these substitution rates have been estimated to be similar across spider lineages  in Arlequin v. 3.5  (FST) and absolute (dXY) differentiation between island populations. We calculated FST)/(1– FST)  in Arlequin to test partitioning of genetic variation by islands in G. cancriformis. Number of migrants (Nm) was calculated in Arlequin to estimate gene flow between populations. Haplotype networks were assessed using median-joining methods in PopART 1.7 (http://popart.otago.ac.nz) (G. cancriformis using the R-package RhierBAPS (We assessed population structure and estimated genetic differentiation between Caribbean island populations of n v. 3.5  to inferity (Hd) , pairwisity (Hd) , and aveo.ac.nz) . We implo.ac.nz) , a hierahierBAPS . We perfGasteracantha. Uncorrected p values among and between potential species groups were calculated in Mega 7 (http://www.abi.snv.jussieu.fr/public/abgd/) to identify shifts from low intraspecific distances to higher interspecific in the COI sequences. We set P (prior intraspecific divergence) from 0.01 to 0.1; steps set to 10; X (minimum relative gap width) set to 1.5; Nb bins (for distance distribution) set to 20; we selected the Kimura (K80) model and set TS/TV to 2.0.DNA barcoding and genetic distance were used to test for species boundaries within Neotropical n Mega 7 . We testn Mega 7  rather tn Mega 7 . The ABGecodist  distances. We ran a Mantel test for 10,000 permutations using the R-package ecodist  to assesctoMineR  to analyCOI, 546 – 16S and 506 – ITS2, for a concatenated matrix of 1581 base pairs. The models used in the MrBayes and BEAST analyses for each of the loci were HKY + I + G for COI, GTR + G for 16S, and GTR + I + G for ITS2. Phylogenetic inferences for both the single-gene (COI) and pruned  BEAST concatenated datasets indicated three clades (PP > 0.75) within the New World—two mainland clades and a predominantly island clade that included some individuals from SEUS  with gene flow reaching infinity. The highest pairwise genetic distances were between Mona and Cuba (FST = 0.78772) and lowest migration rates (Nm = 0.13475) (KXY) and average number of nucleotide substitutions per site (dXY) between island populations ranged from 2.1 to 0.00397 (Jamaica and TCI) to 7.6875 and 0.01453 (Jamaica and Mona) respectively  (K) was 5.14855 among island populations. The 16S dataset had fewer haplotypes (H = 8) and less haplotype diversity . Haplotype and nucleotide diversity were relatively lower for islands with smaller areas   . The nucectively . Within ctively) . The aveand TCI) .COI split Gasteracantha into three geographic, putative independently evolving groups, Caribbean islands, west of the Andes, and east of the Andes . Furthermore, there was a substantial amount of intermixed and shared haplotypes among islands  and abdominal color  and island. The Lesser Antilles, TCI and Puerto Rico clustered tightly around four spines  populations in the Caribbean and North and South America  clades-one primarily Caribbean clade   than the tiny (2–3 mm long) males  males . Furtherg) males . While wCOI distance p scores ranged from 4.1% to 6.7% between island and mainland populations; however, this was for a single gene and discordance among our phylogenetic analyses do not provide strong enough evidence for new species. Population level Next Generation Sequencing will clarify relationships and would help to recover a more robust species tree. Furthermore, future intra-specific studies on this lineage may consider more closely related outgroups based on recent Araneidae phylogenies (G. cancriformis (N. America and the Caribbean) additional species may be expected.Species delimitation analyses revealed genetically divergent populations, uncorrected logenies . Still, Gasteracantha characterize a good dispersing lineage of spiders that colonized the Caribbean over water and have continued exchange among islands. Gene flow is high among island populations of Gasteracantha ; however, it does not entirely obfuscate a geographic signal. The largest proportion of genetic variability (49.21%) is explained between islands for COI. While 16S did have genetic clustering between the two mainland populations and the islands, it did not did not have significant genetic variability (−0.39%) between the island populations  would have existed, we reject the land bridge hypothesis for this lineage. The intermediate dispersal model . Notably, one major pitfall associated with Mantel tests is that they are often subject to spatial autocorrelation and erroneously low p-values   . Within  studies . Birds  weakly geographically structured. Moreover, we did not find a correspondence between genetics and color morphs. For instance, identical r morphs , thus imr morphs . Selectir morphs . Environr morphs . The twor morphs , also shrom Cuba . This sujor loci , uncoverT. grallator, the Hawaiian happy-face spider, are a classic example of discrete color polymorphisms among spiders. G. cancriformis.Color polymorphisms are paradoxical in nature; typically, genetic drift and natural selection remove variation from populations . From thG. cancriformis includes a distinctive genetic group that is largely from the Caribbean islands, which suggest that the sea is a geographic barrier that promotes genetic differentiation between islands and mainland. However, little evidence of genetic divergence between Caribbean islands, and lack of Caribbean monophyly are indicative of gene flow between islands and continents, suggesting that this species’ high vagility facilitates dispersal across geographic barriers. Though we found the presence of unique phenotypes in some islands, the loci that we used did not elucidated an association between patterns of genetic diversity and phenotypic diversity. Gasteracantha cancriformis is an ideal model system for future studies to explore ecological, evolutionary, and behavioral questions. The striking polymorphic phenotypes within this species include characters that are closely associated with geography (spine number) and characters that are not (color), leaving much to learn about ecological and behavioral factors that influence the evolutionary maintenance of this color polymorphism. NGS and/or RADseq data would provide higher resolution for testing population level relationships as well as patterns of gene flow and migration between islands.We found that 10.7717/peerj.8976/supp-1Supplemental Information 1COI, (B) 16S, (C) ITS2, and (D) concatenated dataset. Error bars in blue (95% HPD), nodal support indicated.Tip data and posterior probability labeled at nodes for (A) Click here for additional data file.10.7717/peerj.8976/supp-2Supplemental Information 2Branch colors indicate geographic location, tips represent individual specimens, images represent polymorphs. (A) Polymorphism variation is high even within single islands. (B) Color is not specific to island, spines are highly specific to island regardless of phylogenetic placement. (C) Islands with small areas  Turks and Caicos have multiple colors morphs. (D and E) All specimens from the South Eastern United States are white with red spines.Click here for additional data file.10.7717/peerj.8976/supp-3Supplemental Information 3Further specimen details of tip labels can be found in Supplemental Table 1. Nodes are labeled by support (posterior probability)Click here for additional data file.10.7717/peerj.8976/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.8976/supp-5Supplemental Information 5All samples from Colombia and Brazil were acquired from GenBank and originally made accessible by Saldago-Roa et al. (2018).Click here for additional data file.10.7717/peerj.8976/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj.8976/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj.8976/supp-8Supplemental Information 8Click here for additional data file.10.7717/peerj.8976/supp-9Supplemental Information 9Click here for additional data file.10.7717/peerj.8976/supp-10Supplemental Information 10Click here for additional data file.10.7717/peerj.8976/supp-11Supplemental Information 11Click here for additional data file.10.7717/peerj.8976/supp-12Supplemental Information 12Click here for additional data file.