Vigna marina, using 308 individuals collected from the entire Indo‐West Pacific (IWP) region. Chloroplast DNA variation showed strong genetic structure that separated populations into three groups: North Pacific (NP), South Pacific (SP) and Indian Ocean (IN) (F′CT among groups = 0.954–1.000). According to the Approximate Bayesian computation inference, splitting time between NP and SP was approximately 20,200 years  before present. Moreover, a signal of recent population expansion was detected in the NP group. This study clearly showed the presence of a cryptic barrier in the West Pacific region of the distributional range of V. marina. The locations of the cryptic barrier observed in V. marina corresponded to the genetic breaks found in other plants, suggesting the presence of a common cryptic barrier for sea‐dispersed plants. Demographic inference suggested that genetic structure related to this cryptic barrier has been present since the last glacial maximum and may reflect patterns of past population expansion from refugia.Ocean currents are an important driver of evolution for sea‐dispersed plants, enabling them to maintain reciprocal gene flow via sea‐dispersed diaspores and obtain wide distribution ranges. Although geographic barriers are known to be the primary factors shaping present genetic structure of sea‐dispersed plants, cryptic barriers which form clear genetic structure within oceanic regions are poorly understood. To test the presence of a cryptic barrier, we conducted a phylogeographic study together with past demographic inference for a widespread sea‐dispersed plant,  Alternatively, it has been suggested that LDD of sea‐dispersed plants is more limited than initially expected due to land and water barriers as well as the mobility and survival of diaspores during dispersal  specifically adapted to long distance dispersal  Merr. that grows in tropical and subtropical sandy beaches throughout the tropics  in the IWP region. Therefore, this species can be a model species to test the presence of cryptic barriers across the IWP region. Vigna marina has a subspecies, V. marina ssp. oblonga (Benth.) Padulosi, but we did not use it in this study as it is only distributed in West Africa and has been suggested to be not so closely related  to V. marina  to evaluate the genetic diversity and population genetic structure throughout the species distributional range using chloroplast DNA (cpDNA) and show if clear genetic structure caused by a cryptic barrier exists within the west Pacific region, and (b) to infer the past demographic history of V. marina in this region using the ABC approach to assess the processes of formation of the cryptic barrier that shaped the genetic structure.The aim of this study was to reveal the presence and process of formation of a cryptic barrier in 22.1Vigna marina in thirty‐four localities and the sample size at each location ranged from one to 31 individuals, with a total sample size of 308 individuals  and Mighty AmpTM DNA Polymerase (TaKaRa Bio) were used for PCR. After purifying the PCR products using illustra ExoProStar , the PCR products were sequenced directly using an ABI 3500 Genetic Analyzer (Applied Biosystems), an ABI 3130 xl Genetic Analyzer (Applied Biosystems) or a DNA sequence service supplied by Eurofins MWG operon company . The DNA sequences were aligned using MUSCLE as implemented in MEGA ver. 6.0 . For the following analyses, we removed all sequence gaps by using TRIMAI ver. 1.3 , nucleotide diversity (π), Tajima's D  following the median‐joining method , and to define groups of populations that are geographically homogeneous and maximally differentiated from each other. Here, the algorithm was performed by SAMOVA software   and “Infer population size change in the North Pacific group” (ABC2). To simplify the scenarios in the ABC analysis, we defined three populations based on the result of SAMOVA: North Pacific group (NP), South Pacific group (SP) and Indian Ocean group (IN)  and maximum values of time scales (Supporting Information Table 2.4.2To examine the past transition of the effective population size of the North Pacific group (NP), which had enough haplotype diversity for within group demographic analysis, we tested three simple population demographic scenarios Figure .Scenario 1—Constant model: effective population size of NP was constant at N1 from the present to the past. (Na = N1)Scenario 2—Expansion model: effective population size of NP changed from Na to N1 at t. (Na < N1)Scenario 3—Bottleneck model: effective population size of NP changed from Na to N1 at t. (Na > N1)The scenarios were as follows:D, the number of private segregating sites and the mean of numbers of the rarest nucleotide at segregating sites were used as summary statistics for each of the three populations. The number of haplotypes, the number of segregating sites, the mean of pairwise differences and FST were used as the summary statistics for each of the population pairs. One million simulations were run for each scenario in both ABC1 and 2. After all the simulations had been run, the most‐likely scenario was determined by comparing the posterior probabilities using the logistic regression method. The goodness of fit of the scenario was assessed by the option ‘“model checking”’ with principal component analysis (PCA) in DIYABC, which measures the discrepancy between model and real data.We changed the priors of the maximum population size and the maximum values of time scale from 10,000  to 100,000 to obtain better posterior distributions based on the results from the pilot runs  were observed throughout the species distributional range  indicate recent population expansion in this region. In contrast, significantly positive values were observed in the Ryukyu population suggesting a recent bottleneck, possibly due to this population being located near to northern margin of the species distributional range. For the NP and SP groups, although no significant signal of population expansion or contraction was detected based on Tajima's D, and Li and Fu's D and F indexes, the ABC2 inference showed significant signal of population expansion in the NP group (see below).In total, 29 haplotypes were detected and high levels of genetic diversity  when the 21 populations were divided into K = 3 groups, composed of the North Pacific group (NP), South Pacific group (SP) and the Indian Ocean region (IN)  Figure . The pai3.2V. marina of three years according to our field observations. The median values of the mean mutation rate of cpDNA and the median values of mean coefficient k C/T were estimated as 2.92 × 10−8 (95%CI: 1.51 × 10−8–5.50 × 10−8) and 11.50 (95%CI: 8.15 × 10−1–2.00 × 101), respectively  and the 95%HPD did not overlap with those of the other scenarios. For scenario 2, the median values of effective population size of N1 (North Pacific), N2 (South Pacific), N3 (Indian Ocean) and Na  were 81,400 , 23,400 , 6,010 , and 37,400 , respectively. The median value of t1, the divergence time when SP split from NP was 9,170  generations ago and that of t2, the divergence time when IN split from NP and SP was 38,200  generations ago. These time scales of t1 and t2 converted into absolute time as 20,200 and 114,600 years ago assuming a generation time for k C/T were estimated as 4.96 × 10−8 (95%CI: 2.32 × 10−8–9.39 × 10−8) and 11.40 (95%CI: 7.81 × 10−1–1.99 × 101), respectively  and its posterior probability did not overlap and was much higher than that for scenario 1  and scenario 3   showed clear genetic structure that divides the distributional range of V. marina into three regional clusters: North Pacific (NP), South Pacific (SP) and Indian Ocean (IN) , suggesting very limited gene flow among regions. In addition, potential patterns of admixture between the NP and SP regions were found only in the populations located near to the boundary of the two genetic clusters. Finally, the median‐joining network showed that the two major groups of haplotypes, CP1 (NP) and CP2 (SP), were phylogenetically differentiated from each other. On the other hand, most of the major haplotypes were highly shared among populations within each of the NP or SP clusters, suggesting substantial gene flow among populations within each genetic cluster. In addition, the AMOVA suggested only a low proportion of variation was due to differences among populations within clusters  and subsequent landmass formation over large areas have been reported in South East Asia (Sunda shelf) and the Oceania region (Sahul shelf)  before present (BP), corresponding to the period of the Last Glacial Maximum . This suggests that a cryptic barrier for ) Voris, . These lD and Fu and Li's D and F, suggesting past population expansion of V. marina from glacial refugia after the LGM. Cannon, Morley, and Bush  in the South Pacific based on Tajima's and Bush  recentlyand Bush . Indeed,Xylocarpus granatum , suggesting highly restricted gene flow among them. Thus, as far as the demographic history among the three regional groups is concerned, the bias in this study is likely limited. In addition, as gene flow after divergence wasn't considered, divergence times might have been underestimated (Tsuda et al., In this study, ABC analyses explored the population demographic history in relation to refugia during LGM or the past ice age previous to the LGM. Although statistical uncertainty remains (e.g., time scale, generation time, broad 95% CI range and assumed model, reviewed in detail see Tsuda, Nakao, Ide, & Tsumura, 5V. marina, was clearly detected. The locations of the cryptic barrier observed in V. marina corresponded to the genetic breaks found in other plants, suggesting the presence of a common cryptic barrier for sea‐dispersed plants in the West Pacific region. Demographic inferences using the ABC approach suggested that genetic structure related to the cryptic barrier has been present since the last glacial period and may reflect patterns of past population expansion from refugia. These results suggest that despite high LDD ability that can homogenize genetic structure, present phylogeographic patterns of sea‐dispersed plants have been strongly affected by glacial climate changes, as reported in other land plants.In this study, the presence of a cryptic barrier in the West Pacific distributional range of a widespread sea‐dispersed plant, None declared.T.Y., Y.Tsuda, K.T. and T.K. designed the study. T.Y., K.T., R.N., Y.Tateishi and T.K. carried out field collection. T.Y. and R.N. carried out the molecular work. T.Y., Y.Tsuda and R.N. analyzed the data. All authors contributed to the writing of the paper and all have approved of the final version. Click here for additional data file. Click here for additional data file.


Amaranthus tuberculatus reveals the answer to be, “it depends,” as we surprisingly find examples for both modes of evolution.While evolution has been thought of as playing out over millions of years, adaptation to new environments can occur very rapidly, presenting us with key opportunities to understand evolutionary dynamics. One of the most amazing examples of real-time evolution comes from agriculture, where due to the intense use of a few herbicides, many plant species have evolved herbicide resistance to become aggressive weeds. An important question has been whether herbicide resistance arises only rarely and then spreads quickly, or whether herbicide resistance arises all the time de novo. Our work with glyphosate resistance in US Midwestern and Canadian populations of  Amaranthus tuberculatus poses one of the most significant threats to crop yields in the Midwestern United States, with both agricultural populations and herbicide resistance only recently emerging in Canada. To understand the evolutionary mechanisms driving the spread of resistance, we sequenced and assembled the A. tuberculatus genome and investigated the origins and population genomics of 163 resequenced glyphosate-resistant and susceptible individuals from Canada and the United States. In Canada, we discovered multiple modes of convergent evolution: in one locality, resistance appears to have evolved through introductions of preadapted US genotypes, while in another, there is evidence for the independent evolution of resistance on genomic backgrounds that are historically nonagricultural. Moreover, resistance on these local, nonagricultural backgrounds appears to have occurred predominantly through the partial sweep of a single haplotype. In contrast, resistant haplotypes arising from the Midwestern United States show multiple amplification haplotypes segregating both between and within populations. Therefore, while the remarkable species-wide diversity of A. tuberculatus has facilitated geographic parallel adaptation of glyphosate resistance, more recently established agricultural populations are limited to adaptation in a more mutation-limited framework.The selection pressure exerted by herbicides has led to the repeated evolution of herbicide resistance in weeds. The evolution of herbicide resistance on contemporary timescales in turn provides an outstanding opportunity to investigate key questions about the genetics of adaptation, in particular the relative importance of adaptation from new mutations, standing genetic variation, or geographic spread of adaptive alleles through gene flow. Glyphosate-resistant  Amaranthus tuberculatus was first reported in Missouri in 2005 but has since been reported in 19 US states  long-read data collected on the Pacific Biosciences Sequel platform using 15 SMRT cells. After assembly, polishing, and haplotype merging, the reference genome consisted of 2,514 contigs with a total size of 663 Mb and an N50 of 1.7 Mb . Our final genome size is consistent with recent cytometric estimates of 676 Mb (SE = 27 Mb) for A. tuberculatus ] = 0.1342 , using Missouri as a reference (ST) between individuals with ancestry homogenous for different lineages at K = 2 was 0.212, on par with or greater than that between other congeners , with PC1 separating var. rudis and var. tuberculatus ancestry, and PC2 separating Canadian and American accessions . Furthermore, while Essex grouped with Walpole and Natural populations on PC2, it was found at the other end on PC1, more different from Canadian populations than even the most geographically distant Missouri population , while treemix indicated that Walpole may be a hot spot for gene flow, with 9 of 10 total migration events across the tree involving Walpole   C. Thus, rudis introgression into Walpole, these populations were similarly differentiated from nearby natural populations homogenous for var. tuberculatus ancestry as they were from comparably admixed populations in Illinois . This, along with the tight clustering of Walpole and Natural populations in the PCA and structure analyses, implies that Walpole populations experienced strong and rapid local adaptation to agricultural environments upon its conversion from wetland, which may have been facilitated by introgression from var. rudis. We therefore sought to find genes that were highly differentiated between Walpole and Natural populations, putatively involved in agricultural adaptation. A Gene Ontology (GO) enrichment test for the top 1% of genes with excess differentiation between Walpole and natural populations identified genes with monooxygenase and oxidoreductase molecular function, with histone methylation biological function, and several protein classes involved in transport and amino acid/protein modification . Apart from errors in phenotyping or copy number estimation, this implies that intermediate copy number amplification alone may not always be sufficient for resistance, e.g., if amplified copies are not properly expressed. While EPSPS amplification was most frequent in the Midwest , copy number in resistant individuals was on average almost twice as high in Walpole . Previous estimates of EPSPS copy number in resistant A. tuberculatus were up to 17.5 copies relative to diploid susceptibles , explaining 48% of the variation in resistance in Walpole, but only 23% and 27% in Essex and the Midwest. In these latter 2 regions, however, an additional 10% of variation was explained by a nonsynonymous substitution at codon 106, the most common and well-characterized genetic mechanism of glyphosate resistance across species outside of the genus Amaranthus , encompassing 108 genes .Our chromosome-scale genome assembly provided a unique opportunity to determine the structure and genomic footprint of selection around the amplified SI Appendix, Fig. S3). Nonetheless, to control for the possibility of residual SNP differences that exist among gene copies and/or for allelic dropout, we created a consensus haploid sequence by random downsampling to 1 allele per heterozygous site. Because we downsampled SNP by SNP, we do not expect our downsampling to be biased toward any particular haplotype.Characterizing signals of selection for a high copy number region can be challenging. First, typical population genetic statistics ignore potential variation among gene copies that are collapsed into a single haplotype. Ideally, phasing of a multicopy region would allow for full resolution of the single-nucleotide polymorphism (SNP) differences within and between haplotypes. However, very recent gene amplification is expected to limit SNP variation among amplified copies, and will also hinder phasing approaches from short read data. Second, variation may not be recognized because of allelic dropout of low-copy variants. Analysis of the relationship between EPSPS copy number and homozygosity in our dataset suggested that higher-copy haplotypes did not feature more SNP variation than lower-copy haplotypes, implying that generally few new mutations distinguish among amplified copies . Moreover, there was a marked reduction in genetic diversity (mean pairwise differences) around EPSPS, as well as elevated differentiation (Fst) and extended haplotype homozygosity . A custdefault)  taking os genome  using redefault) . The 16 freebayes .We used reebayes  to call reebayes , 51 adapA. hypochondriacus-finished pseudoassembly using the MAKER pipeline , using expressed sequence tag evidence from an A. tuberculatus transcriptome assembly  medium supplemented with 13-13-13 Osmocote in a greenhouse that was maintained at 28/22 °C day/night temperatures for a 16:8-h photoperiod. Plants were sprayed at the 5 to 7 leaf stage with 1,260 g of glyphosate  per hectare. Fourteen days after treatment, plants were rated visually on a scale of 0 (highly sensitive) to 5 (no injury). Plants rated 2 or higher were classified as resistant. Prior to herbicide treatment, single leaf samples were taken from each plant and stored at −80 °C until ready for genomic DNA extraction. Tissue from plants rated as highly glyphosate resistant or susceptible were selected from each population for genomic DNA extraction using a modified cetrimonium bromide method .EPSPS was estimated by dividing the coverage at each site across the focal region by the mode of genome-wide coverage after excluding centromeric regions  and regions of low coverage , which should represent the coverage of single-copy genes.Scaled coverage and copy number at https://github.com/tvkent/Degeneracy) to score 0-fold and 4-fold degenerate sites across the genome. This procedure estimated 17,454,116 0-fold and 4,316,850 4-fold sites across the genome, and after intersecting with our final high-quality freebayes-called SNP set, resulted in 345,543 0-fold SNPs and 326,459 4-fold SNPs. The latter was used as input for demographic modeling.To model neutral demographic history and estimate neutral diversity, we used a Python script  (https://github.com/dportik/dadi_pipeline (easySFS (https://github.com/isaacovercast/easySFS), and samples were projected downward to maximize the number of loci without missing data vs. number of individuals retained. We ensured that the log-likelihood of our parameter set had optimized by iterating the analysis over 4 rounds of increasing reps, from 10 to 40. We tested a set of 20 diversification models, with variation in split times, symmetry of migration, constancy of migration, population sizes, and size changes. The most likely inferred demography followed a model of secondary contact, where initially populations split without gene flow, followed by population size change with asymmetrical gene flow, and included 8 parameters: size of population 1 after split (nu1a), size of population 2 after split (nu2a), the scaled time between the split and the secondary contact (in units of 2*Na generations) (T1), the scaled time between the secondary contact and present (T2), size of population 1 after time interval (nu1b), size of population 2 after time interval (nu2b), migration from population 2 to population 1 (2*Na*m12), and migration from population 1 to population 2 (m21). Ne was calculated by substituting the per-site thaliana mutation rate (7 × 10−9) (Our 2-population demographic model of (V1.7.0)  using thpipeline . 1D and  × 10−9)  into thePLINK  (treemix (V3) , we used scripts from the genomics general pipeline available at https://github.com/simonhmartin/genomics_general, binning SNPs into 100-kb windows with a step size of 10 kb. To estimate the proportion of introgression of var. rudis ancestry into Walpole agricultural populations in these genomic windows, we used the f statistic (but with nonoverlapping windows) (tuberculatus into var. rudis), we used Missouri as the reference ingroup. For investigation of introgression of Essex populations into Walpole (var. tuberculatus into var. rudis), we used Natural populations as the reference ingroup. Last, for investigation of introgression of Natural populations into Essex (var. tuberculatus into var. rudis), we used Missouri as the reference ingroup. To get CIs for the f statistic estimates, we performed jackknifing by calculating pseudovalues by removing one 250-kb block at a time.We used (V2.3.4)  to estimmix (V3)  to inferwindows) . For invst) in 10-kb windows, and classified windows as outliers when they were in the top 1% for extreme differentiation. A GO enrichment test was then performed for these outlier regions, after finding their intersecting annotated A. tuberculatus genes, and their orthologs in A. thaliana using orthofinder , we used the interval function in LDhat (https://github.com/QuentinRougemont/LDhat_workflow.To detect differences in the strength and breadth of sweep signal associated with selection from glyphosate across geographic regions, we used SNPs called from the pseudoassembly of our in LDhat  to estimXP-EHH scan (selscan (https://github.com/simonhmartin/genomics_general were used for calculating differentiation and the difference in diversity. Pseudohaploid haplotypes were also used to calculate a maximum-likelihood tree for the 235 SNPs in EPSPS. For each tree, we realigned sequences before bootstrapping 1,000 replicates of our haplotree with clustal omega (Sweepfinder2 (To account for the fact that high-copy number loci may allow for increased diversity relative to single-copy regions, we randomly sampled 1 allele per locus along the length of chromosome 5 to create pseudohaploid haplotypes for our sweep scans. This ensures that any increased differentiation is due to differences among individuals, rather than among haplotypes within individuals. The EHH scan , calcula(selscan . Scriptsal omega . In contpfinder2 , 34, a pSupplementary File


A unique population structure using principal component analysis illustrated clear distinctions between Duroc, Yorkshire, Hampshire, breeds of Chinese origin, and feral Pacific Island populations were identified. Five Y chromosome haplotypes were evaluated and demonstrated migration patterns from European, central Asia, and potentially Polynesian waves of gene flow. Quantifying diversity and potential origin of Pacific populations provides insight for future uses, and the need for preservation. Viewing gene bank holdings in context of diversity measures we found a lack of inbreeding within breeds, suggesting the collection represents a wide sampling of individual breeds.Human migration and trade facilitated domesticated livestock movement, gene flow and development of diverse populations upon which agriculture is based. In addition, varying USA ecological conditions has led to a diverse set of livestock populations to utilize. Quantifying genetic diversity of these populations is incomplete. This paper quantifies genetic diversity captured by the National Animal Germplasm Program and explores genetic structure and differences among 19 pig populations  using 70,231 SNP from 500 animal samples. Among continental US breeds F Specifically the assessment provides insights to the genetic variability captured in the USDA’s swine germplasm collection6. The study evaluated major breeds, often termed international commercial breeds, rare breeds, Chinese breeds imported into the U.S. during the late 1980’s, and feral populations from the Pacific islands of Hawaii, Kauai, and Guam. It has been hypothesized that such feral populations may be harbingers of genetic diversity not found in other US populations given the potential for either Asian or Polynesian ancestry7.The objective of this study was to quantify the genetic diversity of a substantial number of pig breeds found in the United States (US) as previous assessments tend to be focused on Europe and Asia8 and additional domestic pigs gone feral upon the chain of Hawaiian Islands. McCann et al.8 suggested animals sampled in the Hawaiian Islands originated from Europe, China, Papua-New Guinea, Vanuatu, and shared haplotypes with other domestic-feral pigs and S. verrucosus (from Java). Larson et al.9 suggest Hawaiian Islands pigs as members of the Pacific clade. No analysis has been performed on Guam’s feral population. But as part of the Mariana island chain, feral pigs might belong to an East Asia clade9.Current feral pig populations on the Hawaii and Kauai are the product of a migration wave associated with Polynesian settlers followed by European explorers during the 1700’s10: England, China, and the U.S. Obviously, U.S. breeds were imported or derived from other parts of the world at varying points in time; however, the imports have been used to maintain the original breed or construct new breeds like Duroc, Hereford, Ossabaw Island, Spots/Poland China, and Chester White. The Duroc in particular is an interesting example as its foundation breeds have not been shown to have strong genetic linkages with other European breeds3. These authors have suggested that the breed may have been comprised, in part, of Guinea Hog from Africa (among other breeds) due to its red color.Breed development occurred in three geographic areasA better understanding of the genetic diversity among these U.S. populations has a number of uses, including: general management of genetic diversity by public and private sectors, targeting future germplasm collections, and providing input into policies concerning feral pig populations on Pacific islands.Basic marker statistics of the GGP Porcine HD v1  have shown that more than half of the markers were polymorphic for feral and rare breeds/genetic groups Table  suggestiThe calculated genetic diversity parameters Table  were perin-situ population captured in the repository by the germplasm conservation program. The feral population on HI had the highest inbreeding level (0.081) which is higher than the inbreeding levels for KI (−0.017) and GI (0.011), which are geographically smaller islands.Overall, the levels of inbreeding in most of the populations evaluated were low indicating the high genetic diversity levels among the ST, was non-significant for only three comparisons MA vs LB, MA vs OI, and MA vs GH  accounted for 39.6% of the variation Fig. . The pri11. However, the YK subpopulations are likely due to imported animals during the 1980’s which were widely used within that breed.ADMIXTURE was run with K = 2 to 21 and those results were in agreement with PCA. Cross validation error was used to assess which K provided insights into population structure. That said from K = 7 to K = 21 the cross validation curve was asymptotic with an approximate 1.5% change per K. Therefore we selected K of 2, 3, 7, 8, and 10 for evaluation. At K = 2 the breeds were partitioned between Meishan (ME), originating in China, and those from the continental US. Admixed were the populations from GI, HI, KI, MI, and FE  within breed/population were low suggesting boars sampled for the germplasm collection were lowly related and a broad range of genetic variability has been captured in the gene bank. Furthermore, FIS values were lower than the pedigree based inbreeding levels previously computed20 and Canadian values15.Based upon the population parameters evaluated US breeds, as represented by germplasm samples in the repository, are genetically robust with regard to heterozygosity levels. Genetic diversity of repository samples were similar to European, Asian and previous US valuesST suggested the breeds evaluated are distinct; similar to21, using microsatellite markers (FST = 0.10 between DU and YK). As reported in the literature15, the estimates of FST within European and within Asian origin populations are smaller than among Asian and European breeds and are in agreement with ADMIXTURE analysis. Paired combinations of Fst between feral populations of the Pacific and breeds originating in China were similar and confirm the PC analysis.Among populations, pairwise F22. On the other hand, the low number of markers should not be an issue since these markers did not suggest the presence of bottlenecks (data not shown); conversely, they highlight the high genetic diversity of these populations (high Ho and low FIS).The number of polymorphic SNP in the larger panel Table  and with23. Typical of PCA analysis a relatively small proportion of genetic variance was accounted for, however previous reports for pigs display similar proportions24. Our results underscore the divergence of Duroc which usually appears as a main and separate cluster from other breeds26.The PCA provides a unique view of the relationship among the 19 populations evaluated, in terms of the placement of US mainland breeds (and selection efforts which have differentiated these populations), Pacific islands, and breeds from China  pair-wise FST values were similar to the DU – HS value. The three maternal white breeds had significant but smaller pair-wise FST values, the PC analysis indicated the YK was distinct from the LA and CW  and HI (H1 and H2) were present among continental US populations, suggesting admixture with later importation of European derived pigs. The PCA and ADMIXTURE results appear to support the haplotype analysis among the Pacific island populations. In Fig. Y-chromosome results provide insights into the migration of these swine populations. Interestingly GI’s population had haplotypes from China (H4) and an unknown origin (H5). We hypothesize that H5 may be part of the Pacific clade as reported earlier and HI H and H2 wth century. However, because of its presence in the Chinese MI breed H2 could have originated during the domestication of pigs in China and imported into Europe during the 18th century.Haplotypes H1 and H2 are common in the continental US and the Hawaiian Islands. Haplotype-2 was the most cosmopolitan of haplotypes appearing in China, Hawaiian Islands and US. Additionally its internal position in the network analysis Fig.  suggests27.Haplotype H3 was observed in 11 of the 19 populations but it was only found in the continental US. Also, it was the only haplotype among the prominent breeds: DU, HS and YK; and minor breeds: TA, Hereford and GH. Given that the Chinese and Pacific populations lack the H3 haplotype suggests a European origin, and may have as an original source wild boars found west of the Caucus Mountains14 assessing Canadian DU, YK, and LA using LD. This study’s results are also in agreement with the Ne computed with pedigree information19 for DU, YK, LA, HS, and BE. In all instances Ne was >50 exceeding the minimum Ne suggested by FAO28. By pooling study populations we noted substantial variation, as suggested by an Ne = 236 which resides in the gene bank and can be used to advance breeding goals, similar to that reported with sheep29.A major aspect of this study was to provide a first assessment of the within and among breed genetic diversity captured in the national gene bank collection. Effective population sizes for commercial breeds were in agreement with work28. Results for breeds with less than 15 animals’ are viewed as preliminary. That said, genetic parameters for SP, HE and TA were similar to breeds with larger sample size. Up to K = 10 in the ADMIXTURE analysis the SP and TA were admixed, at K = 10 the HF were placed in a unique cluster, but TA was not. Those early admixture patterns for low-medium K values reflect clusters of breeds that share recent admixture events, higher genetic diversity and/or were not undergoing selection nor experienced a recent bottleneck15.For breeds with more than 20 animals genotyped the results tended to be homogeneous, in that, levels of heterozygosity and inbreeding were similar and at levels that suggest sufficient genetic variability exists among the populations captured in the repositoryThe samples from Guam, Kauai, Hawaii, and US/Chinese ME provide interesting models for evaluating small isolated populations. The ME included randomly bred lines; while the island populations are all feral but confined to the island sampled. Genetic parameters Table  for GI aLarge and substantial genetic differences in pig populations dispersed across the continental US, Pacific Islands and Chinese breeds were found. Results suggest that feral populations from Pacific islands have a combination of European, East Asian and potentially South East Asian origin. Identifying the diverse origins of feral pigs on the Pacific islands contributes to the policy dialog about the control/eradication and/or conservation of these populations. While there may be environmental issues, the populations in question are unique and may have cultural significance for persons of Polynesian ancestry. Exploring feral genomes further may reveal other genetic attributes of interest for the research community and industry.in-situ populations, our results suggest no lack of genetic variability. Some rare breeds showed a lack of genetic distinction in PC analysis and were admixed which was likely due to limited sample size. But, HE and TA were distinct  and were shown to have measures of genetic variation in the same ranges as the commercial breeds. As the collection of swine genetic resources in the gene bank continues to grow it will be a resource to further explore various aspects of genetic diversity or gene function.This study’s evaluation of commercial breeds acquired for gene banking purposes is encouraging. Samples from commercial breeds suggest a range of genetic variability has been captured by the gene bank. As an indicator of genetic variability among No samples were collected for this study; rather they were collected as part of other studies or program activities not associated with this study. Semen samples were acquired from swine artificial insemination centers by the National Animal Germplasm Program as part of efforts to conserve genetic resources. Blood samples from Pacific island populations were collected by USDA Wildlife Services in their routine efforts to manage feral populations and then provided to the National Animal Germplasm Program.http://genomics.neogen.com/en/). All samples and genotypes are deposited with the USDA ARS National Animal Germplasm Program (https://nrrc.ars.usda.gov/A-GRIN/database_collaboration_page_dev).This study focused on assessing populations found upon the continental US and its Pacific islands. We were particularly interested in evaluating feral Pacific populations’ origin and relationship to rare and commercial breeds. Samples and data originated from 19 pig breeds , Meishan – U (randomly mated control herd maintained at Iowa State University) and Meishan – MARC (randomly mated control herd maintained by USDA-ARS).The Meishan was composed of three subpopulations2; Kauai, 1,440 km2; and Hawaii, 10,432 km2. Guam’s samples were from the same area of that island.Substantial distances exist between the geographic areas sampled. From continental U.S. to the Hawaiian Islands is approximately 3,900 km and Hawaiian Islands to Guam is approximately 6,000 km. The distance between the Hawaiian Islands of Hawaii and Kauai is approximately 500 km. Island size varies greatly: Guam, 544 km. Due to the use of feral and rare breeds we first evaluated the polymorphism content of the BeadChip transferable to these breeds. SNP with call rate <0.95 and located at sexual chromosomes were pruned from the initial dataset, leading to 57,668 SNP. Basic marker statistics as number of polymorphic SNP, average call rate and average number of alleles were calculated for each breed , using GGP Porcine HD v1 . Final Reports generated with Genome Studio Software  were imported into SNP & Variation Suite v8.6 ed Table .2 > 0.3. The final data set had 8,764 SNP used in all autosomal analysis.The next step was remove markers not mapped in the Sscrofa10.2 assembly . The 54,994 remaining SNP were filtered using the following genetic parameters: Hardy-Weinberg Equilibrium (HWE) p < 0.0001, and Linkage Disequilibrium (LD) r30. Principal Component Analysis (PCA) using SNP & Variation Suite v8.6 (SVS)  was performed to evaluate population stratification. The SVS software implements the EIGENSTRAT algorithm31. The results were represented in a 3D scatterplot of the first three principal components using SigmaPlot 13 (https://systatsoftware.com/products/sigmaplot/).Within breeds genetic diversity parameters were estimated with 8,764 SNP using Arlequin 3.5.1.331 which is based on maximum likelihood. The inference of number of populations or clusters (K) present in the analysis was estimated by the cross-validation procedure., where the smallest cross-validation error rate indicates the most probable K value for the data set33. The default termination criteria for the ADMIXTURE analysis was assumed when the log-likelihood increases by less than ϵ = 10−4 between interactions. The termination criteria of is ϵ = 10−5 between interactions was also tested, without any difference on the cross-validation error values. The routine analysis was carried out for 22 clusters (Ks) with 10 replicates for each one. A second ADMIXTURE analysis with nine populations consisting of minor and rare breeds, and feral populations (12 clusters tested with 10 replicates each) was performed. The graphic representations of the proportions of assignment of each individual within population were visualized using CLUMPAK (http://clumpak.tau.ac.il/)34.Population structure analysis was carried out using ADMIXTURE 1.2.230 and the relationship between haplotypes was investigated by constructing median networks using Network 5 (http://www.fluxus-engineering.com/).The GGP Porcine HD v1 contains 14 SNP within the Chromosome Y. The analysis of the Y chromosome in mammals reflects the paternal history of migration and evolution of breeds and populations. For this analysis all female samples were eliminated, therefore 475 male samples were used. The 14 markers were pruned using a call rate <0.95. Of the remaining 11 SNP, two were monomorphic, and three more presented heterozygosity ≠ 0. Ultimately, six SNP were used to estimate the number of different haplotypes, haplotypes frequencies and to reconstruct a network among populations. The haplotype estimates and frequencies were calculated by the software Arlequin 3.5.1.334 was used with default conditions. Prior to using SNeP, SNP filtering was redone dropping the LD aspects. As a result 16,021 SNP were used in this analysis. Due to small sample sizes for some breeds the LD analysis was performed on 10 groups indicated by the population structure identified when ADMIXTURE analysis used K = 10. The 10 populations were: BE, CW, DU, a Chinese group , a Pacific island group , a minor breed group , HS, HE, LA, and YK35.Effective Population Size: To establish baselines and trends of Ne the SNeP softwareUSDA, Agricultural Research Service, is an equal opportunity/affirmative action employer. Mention of companies or commercial products does not imply recommendation or endorsement by the USDA over others not mentioned. USDA neither guarantees nor warrants the standard of any product mentioned. Product names mentioned solely to report factually on available data and provide specific information.Table S1 – Overall characteristics of the 18 populations genotyped with the SNP Beadchip after initial quality filter with a total of 57,668 SNPs.


At least eight local duck breeds have been recognized and documented as national germplasm of Indonesia so far. It is necessary to genetically characterize the local duck breeds for aiding conservation and future improvement strategies. Thus, this study was carried out to assess genetic diversity and phylogenetic relationship of eight local duck populations of Indonesia using microsatellite markers.In total, 240 individuals  from Alabio (AL), Bayang (BY), Magelang (MG), Mojosari (MJ), Pegagan (PG), Pitalah (PT), Rambon (RM), and Turi (TR) duck populations were genotyped using 22 microsatellite markers.FIT = 0.237), was partly due to the heterozygote deficiency within populations (FIS = 0.114) and moderate level of genetic differentiation among populations (FST = 0.137). The most diverse population was MG (He = 0.545) and the least diverse population was AL (He = 0.368). The majority of populations were relatively in heterozygote deficiency (except AL), due to inbreeding. The genetic distances, phylogenetic trees, and principal coordinates analysis concluded that the populations can be grouped into two major clusters, resulting AL, MG, and MJ in one cluster separated from the remaining populations.The results showed a moderate level of genetic diversity among populations, with a total of 153 alleles detected over all loci and populations, ranging from 3 to 22 alleles per locus. Observed (Ho) and expected heterozygosity (He), as well as polymorphism information content over all loci and populations were 0.440, 0.566, and 0.513, respectively. Heterozygote deficiency in the overall populations (The present study revealed a considerable genetic diversity of studied populations and thus, proper management strategies should be applied to preserve genetic diversity and prevent loss of alleles. Attention and awareness to genetic conservation of locally developed livestock breeds have increased in recent years, evidenced by many studies concerning genetic diversity of the breeds. Conservation of genetic diversity plays an important role in sustaining the livestock breeds. Genetic diversity within a species similarly increases the probability of survival in a range of environments  and provIn Indonesia, a number of local duck breeds, namely Alabio (AL), Bayang (BY), Magelang (MG), Mojosari (MJ), Pegagan (PG), Pitalah (PT), Rambon (RM), and Turi (TR) were included as important assets by the Indonesian Ministry of Agriculture, and play an important role in a socio-economic aspect as they provide livelihood to smallholders as well as food for humans. Ducks are reared by breeders for egg production and the culled ducks used for meat production. These local ducks are known for their high fitness levels under harsh conditions and ability to survive with coarse and alternative fodder. Because of these important roles, to evaluating and monitoring the genetic diversity status and phylogenetic relationship of these local breeds is highly recommended. Comprehensive knowledge of the existing genetic variability is the first step for the conservation and utilization of domestic animal biodiversity ,4. ConseRecent advances in molecular technology allow us to assess genetic diversity of livestock breeds at DNA level. Microsatellites or simple sequence repeats are recently the most favoured molecular markers for population analysis, owing to the high variability, ease, and accuracy of assaying microsatellites . They maIn Indonesia, the use of molecular markers for assessing genetic diversity in several local duck breeds has been previously reported, including AL using 7 microsatellites , BY usinIn total, 240 animals representing eight local duck populations in Indonesia  were sampled from six provinces . The eigTwenty-two microsatellite markers distributed in 6 linkage groups and chromosomes  were choF-statistics, including inbreeding coefficient of an individual relative to the subpopulations (FIS), inbreeding coefficient of an individual relative to the total population (FIT), and genetic differentiation index between population (FST) which were calculated using GenAlex ver. 6.501 [FIS). For phylogenetic relationship analysis, GenAlex software was used to perform pairwise population matrices based on either FST or Nei’s genetic distance and to construct principal coordinates analysis (PcoA). The resulted pairwise population matrices were then used to construct phylogenetic trees using MEGA software ver. 7.0.14 [The genetic diversity among populations was determined by these indicators: number of alleles (Na), observed heterozygosity (Ho), expected heterozygosity (He), and polymorphism information content (PIC) which were estimated using Cervus ver.3.0 program , and F-sr. 6.501 . The sof. 7.0.14 .Genetic diversity indicators are summarized in F-statistics were estimated in a fixation index as genetic differentiation (FST), global deficit among eight duck populations (FIT), and the heterozygote deficit within duck populations (FIS), with an average value of 0.137, 0.237, and 0.114, respectively  trees (The pairwise J) trees .The resulted NJ trees revealed relatively similar results using both matrices. Two main clusters were formed, with AL, MJ, and MG duck populations in one cluster, whereas others joined together in a different cluster. Such clustering of the duck populations into two main clusters clearly indicated that some populations originated from different provinces and or islands. A PcoA is also presented using allele frequencies of 22 loci to summarize population relationships . The firIn this study, all microsatellite loci were found to be polymorphic. The average number of alleles in this study (Na = 6.96) were lower than the findings of the other studies using same microsatellite markers in Asian duck populations, with number of alleles of 9.38  and 11.5To test the informativeness of observed loci, we measured PIC, with the resulting average value of 0.513. For animal traceability, PIC>0.5 and He>0.6 are the most reasonable informative loci for application of genetics . From 22FIS. Such phenomenon can be explained by various factors such as non-random mating, unamplified alleles  and subdivision in populations studied (Wahlund’s effects). The studied populations revealed a moderate genetic differentiation among eight populations (FST = 0.137). The results showed that genetic diversity maintained within duck populations was higher than the one preserved among duck populations. This genetic diversity could be a valuable tool for implementing future genetic improvement and conservation of duck populations in Indonesia.Based on the average value of expected heterozygosity (0.566), a moderate level of genetic diversity among populations studied was obtained. In addition, heterozygote deficiency was detected, which was depicted by the lower average value of observed compared to expected heterozygosity, as well as the positive average value of FIS in the seven populations, showing a departure from Hardy-Weinberg equilibrium. The disequilibrium was mainly caused by heterozygote deficiencies, as a result from the existence of inbreeding and or Wahlund effect (population substructure). Since the blood samples were collected from the same flock for each population, the existence of Wahlund effect may be ruled out. The reasonable cause of heterozygote deficiency is the presence of inbreeding. AL and MJ duck populations were reared under a intensive production system, established by livestock breeding center, while the remaining populations were reared under semi-intensive production systems by breeders in villages. Furthermore, after interviewing these breeders, it appears that often there is no pedigree record kept of the animals in semi-intensive production systems and mating between genetically related animals can occur. Unplanned and unsystematic breeding strategies may lead to the lack of sufficient number of breeding males in the breeding population. Mating between animals with similiar phenotypes also occured as the villagers believed mating between ducks with a certain feather colour produced offspring with higher egg production and thus, a panmixic population is unlikely to occur.The genetic diversity indicators within eight duck populations are also summarized in FST values and Nei’s [FST values or Nei’s genetic distance. PT duck population was sampled from a highland-isolated area, while the two AL and MJ duck populations were sampled from same livestock breeding center (BPTU-HPT Pelaihari) with a controlled breeding system. Projection of population relationships by constructing NJ trees based on the two indicators clearly separated the analyzed populations into two clusters. The clustering pattern was further supported by PcoA analysis. MG and MJ duck populations were consistently grouped in one cluster that was closer to the AL duck population compared to the remaining populations. One interesting result was that RM and TR duck populations (originated from Java island) also tended to join together and clustered with BY, PG, and PT duck populations (originated from Sumatera island) in both NJ trees. In the past, many migrants from Java island moved to Sumatera island and other larger islands in Indonesia to get more land for agriculture. Therefore, it is possible for BY, PG, PT, RM, and TR duck populations to share common ancestors when the migrants brought the ducks with them to the new region. The study highlighted that geograhic distance is not always a predictor of phylogenetic relationship. However, to get better understanding of phylogenetic among populations, it is important to combine information on the basis of phenotypic and molecular genetic characterization, as well as geographic and historical information of the analyzed populations.Genetic distance indicators of nd Nei’s  genetic In conclusion, the results of this study demonstrate moderate level of genetic diversity and differentiation among populations, but low to moderate level of genetic diversity within populations. Preventing loss of further alleles with low genetic diversity in populations studied should be considered by implementing effective breeding strategies to reduce inbreeding and increase heterozygosity. Also, the two major phylogenetic clusters clearly showed the genetic relationship of the duck populations. Finally, we highlighted the usefulness of these microsatellite markers to evaluate genetic diversity and phylogenetic relationship in local duck populations of Indonesia. The results indicate the risk status and threats to the duck populations and are useful for designing conservation plans and developing future genetic improvement.


Plantago lanceolata to test the contributions of natural selection versus neutral evolution to population divergence in temperature‐sensitive phenotypic plasticity of floral reflectance. In P. lanceolata, reflectance plasticity is positively correlated with latitude/altitude. We used population pairwise comparisons between neutral genetic differentiation (FST and Jost's D) and phenotypic differentiation (PST) to assess the contributions of geographic distance and environmental parameters of the reproductive season in driving population divergence. Data are consistent with selection having shaped large‐scale geographic patterns in thermal plasticity. The aggregate pattern of PST versus FST was consistent with divergent selection. FST explained thermal plasticity differences only when geographic distance was not included in the model. Differences in the extent of cool reproductive season temperatures, and not overall temperature variation, explained plasticity differences independent of distance. Results are consistent with the hypothesis that thermal plasticity is adaptive where growing seasons are shorter and cooler, that is, at high latitude/altitude.A long‐standing debate in evolutionary biology concerns the relative importance of different evolutionary forces in explaining phenotypic diversification at large geographic scales. For example, natural selection is typically assumed to underlie divergence along environmental gradients. However, neutral evolutionary processes can produce similar patterns. We collected molecular genetic data from 14 European populations of  FST versus QST or PST comparisons are an important tool for inferring the relative importance of neutral evolution versus natural selection  of variation in floral reflectance plasticity in FST) for 14 populations of P. lanceolata in their native European environment, (b) infer patterns of migration and admixture potentially shaping population differentiation, (c) test whether isolation by distance explained a significant proportion of the variance in neutral AFLP markers, (d) compare FST and PST to test for a signature of natural selection, and (e) assess whether phenotypic divergence in thermal plasticity between populations is best explained by distance between populations, neutral evolution, and/or specific environmental properties of the reproductive season that might drive population divergence. The environmental variables we examined allowed us to evaluate potential drivers of selection. We used Mantel tests to examine whether geographic distance and neutral genetic differentiation (FST or Jost's D) were correlated, and whether geographic distance and population differences in each environmental variable were correlated. We used multiple regression of distance matrices (MRM) analyses to determine whether variation in PST could be explained by FST and Jost's D, geographic distance, and/or environmental properties of the reproductive season. We used linear regression models to examine how phenotypic and genetic differentiation varied along axes of geographic distance and environmental differences.The goals for our study were to collect and analyze molecular genetic AFLP data in order to (a) estimate neutral genetic population diversity and differentiation  is a temperate perennial herb native to Eurasia. A weedy species, it is an obligate outcrosser that is primarily wind‐pollinated. Reflectance  and the color of a spike  are thermally plastic and are determined by the ambient temperature experienced during flower development  and marginally with altitude  of the source population  in thermal plasticity was calculated as a conservative proxy for quantitative genetic differentiation (QST) associated with floral reflectance plasticity asPhenotypic differentiation  using a modified CTAB method  and MseI (M) primers and selective preamplification using standard AFLP EcoRI (E) and MseI (M) primers containing selective nucleotides E + AC and M + CC . We quantified AFLP reaction products with MegaBACE ET550‐R size standards on a MegaBACETM Fragment Profiler and scored them in GeneMarker . Using the criteria described above, we developed a consensus score for individuals for which we had data from multiple runs.2.5www.ipcc-data.org). Monthly means were used because daily data were not available. The period 1961–1990 was selected to reflect the environmental conditions under which the populations we sampled had evolved. Variables were estimated by interpolation of the nearest neighboring weather stations to each population  The "cool proportion" of the season was calculated as the proportion of the flowering season spent at temperatures below 15°C, based on monthly means. The physiological rationale for this value is described in Lacey et al. . (b) Theprcomp function, R Development Core Team, To simultaneously estimate the combined effect of multiple variables, we created three composite reproductive environment variables using principal components analyses (PCA) . Jost's D on the other hand is specific to the loci being measured and is more strongly affected by mutation than migration. Thus, Jost's D is not legitimately equivalent to QST or PST  between neutral genetic differentiation (FST and Jost's D) and geographic distance between populations in the ecodist package  on genetic differentiation (FST and Jost's D) and geographic distance with 106 permutations in ecodist  of phenotypic differentiation (2.9PST) and neutral genetic (FST) differentiation by examining whether 95% confidence intervals for PST and for FST among population pairs overlapped the value where FST = PST. When 95% confidence intervals failed to overlap the value where FST = PST, we concluded FST and PST differed. We could not utilize more advanced methods developed for predicting the distribution of neutral PST values based on FST values  on genetic differentiation (FST and Jost's D) and each environmental variable independently with 106 permutations in ecodist  phenotypic and genetic differentiation increased with increasing geographic distance and along environmental clines, and (b) slopes and y‐intercepts of phenotypic and genetic differentiation differed along these axes. In cases where the slope of phenotypic differentiation was significantly greater than that of neutral genetic differentiation, there was no need to test for equality of y‐intercepts. Data in each linear regression were tested for linearity using a runs test. We regressed phenotypic differentiation (PST) and genetic differentiation (FST and Jost's D) against axes of geographic distance between populations, and pairwise‐population differences in environmental properties of the reproductive season  using GraphPad Prism version 6.07 for Windows, GraphPad Software, La Jolla California USA, www.graphpad.com.To examine the patterns of between‐population differences in PST should (a) increase more sharply than FST and Jost's D as environments increasingly differ between populations and/or (b) have a higher y‐intercept value  at 33.1P. lanceolata. At the AFLP markers we sampled, mean population heterozygosity did not vary with latitude  or altitude . The northern Italian population IB, which displayed the greatest overall heterozygosity, was genetically more similar to populations in Germany, southern Italy, and Spain than to other populations . Despite the admixture, southern Italian populations  consistently remained different from other populations . In MRM analyses that excluded geographic distance, neutral genetic differentiation (FST and Jost's D) was always a statistically or marginally significant predictor of the variation in PST  and the 95% confidence intervals did not include values where PST = FST  population pairwise comparisons, we found that T Figure . We did PST could be explained by the cool proportion of the season and Thermal_PC (the composite variable for cool proportion and duration), independent of the contributions of geographic distance and FST  failed to improve the model's explanatory power when compared to the model with Thermal_PC alone Table I–L. AssoST differed substantially from FST and Jost's D when the statistics were regressed on geographic distance between populations and on population differences for two environmental variables characterizing the reproductive season  increased more sharply than did neutral genetic differentiation (FST or Jost's D) with increasing differentiation in the relative proportion of reproductive time at cool temperatures. Additionally, combining the effect of the cool proportion and reproductive season duration variables into a single principal components axis, Thermal_PC, strengthened this effect, that is, increased the slope of PST. In contrast, analyses showed no significant effect of the magnitude of thermal variation or precipitation.The results of MRM and linear regression analyses produced equivalent conclusions and were consistent with the prediction of the Frequency Hypothesis but not with that of the Magnitude Hypothesis (consistent with Lacey et al., Thermal plasticity was first proposed to be more adaptive at higher latitudes and altitudes because the magnitude of thermal variation is greater in these regions (Ghalambor et al., Our geographic study differs from many others in terms of geographic scale. Earlier studies have typically examined thermal plasticity of a group of related species over a large geographic range, for example, tropical to temperate regions (e.g., Angilletta, PST values are likely conservative underestimates of QST because we conservatively used a heritability value of 1.0 in our calculations, and reflectance data were collected from clones of the same individuals grown at the same controlled temperatures. Additionally, parental environmental effects had been reduced by passing parents of our experimental plants through one generation in a similar environment, and all individuals were grown in the same environment. Therefore, between‐population differences are due exclusively to genetic factors (see Lacey et al., We expect selection on thermal plasticity in nature to be greater than our data suggest. Our P. lanceolata (Abu‐Asab, Peterson, Shetler, & Orli, P. lanceolata is better adapted to environments with short and cool reproductive seasons, our data suggest that the advantage of thermal plasticity will generally decrease in extant populations of other species as well, as warmer weather becomes more prevalent. On the other hand, warming should transform areas beyond today's high latitudinal and altitudinal range limits into suitable habitats. In P. lanceolata, floral reflectance plasticity should help facilitate the colonization of new populations toward the poles and higher elevations. Recent ecological niche models are consistent with these predictions (Valladares et al., Temperature increases associated with contemporary climate change and local land‐use change, for example, urbanization, are widespread and are already having a strong influence on species distributions IPCC, . For exaIn closing, we emphasize that plastic responses are specific to the traits, environments, and organisms considered and, thus, are as diverse as life itself. As a result, determining whether plasticity, or the evolution of plasticity, can ameliorate the effects of climate change depends on several factors (Munday, Warner, Monro, Pandolfi, & Marshall, The authors have no conflict of interest to declare.L.C.B., D.L.R., and E.P.L conceived the sampling design; L.C.B. conducted laboratory work; and M.M.M, D.L.R., and E.P.L performed analyses and wrote the manuscript.FigS1Click here for additional data file.FigS2Click here for additional data file.FigS3Click here for additional data file. Click here for additional data file.


Cardisoma guanhumi is widely distributed throughout tropical and subtropical estuarine regions in the Western Central Atlantic (WCA). Patterns of population genetic structure and historical demographics of the species were assessed by mtDNA control region sequence analysis to examine the connectivity among five populations (n = 97) within the region for future conservation strategies and decision-making of fishery management. A total of 234 polymorphic nucleotides were revealed within the sequence region, which have defined 93 distinct haplotypes. No dominant mtDNA haplotypes were found but instead a distribution of a few low-frequency recurrent haplotypes with a large number of singletons. A NJ-tree and a median-joining haplotype network revealed two distinct clusters, corresponding to individuals from estuaries located along the Caribbean Sea and Brazilian waters, respectively. AMOVA and FST statistics supported the hypothesis that two main geographic regions exists. Phylogeographical discontinuity was further demonstrated by the Bayesian assignment analysis and a significant pattern of isolation-by-distance. Additionally, tests of neutral evolution and analysis of mismatch distribution indicate a complex demographic history in the WCA, which corresponds to bottleneck and subsequent population growth. Overall, a sharp genetic break between Caribbean and Brazilian populations raised concerns over the conservation status of the blue land crab.The blue land crab  Cardisoma guanhumi Latreille 1825 (Decapoda: Brachyura: Gecarcinidae) is a nearly terrestrial species widely distributed throughout tropical and subtropical estuarine regions in the Western Central Atlantic, ranging from southeast Florida, Central America and the Bermudas, through the Gulf of Mexico and parts of the Caribbean Islands, to Brazil (from Ceará to São Paulo) [The blue land crab o Paulo) ,4,5. Aloo Paulo) .i.e., overexploitation) and ongoing habitat degradation. Therefore, the species is currently listed as “threatened, over-exploited, or threatened with overexploitation” in Brazil [The species is intensively exploited as a food resource in many countries along the Atlantic coast of Central and South America, particularly Puerto Rico, the Bahamas, Honduras, Columbia, Venezuela, and Northeast Brazil ,8,9,10, n Brazil  and as “n Brazil  in USA. C. guanhumi distribution not only would help to obtain a deeper understanding of evolutionary process, but also is of paramount importance for management and conservation of the species. An understanding of its population genetic structure is critical in order to establish sustainable fishery policy priorities and management plans, as well as for defining effective conservation measures to maintain wild crab stocks at high levels of productivity [The knowledge of geographic patterns of population structure within the uctivity ,17,18.Genetic structure of benthic organisms with a planktonic larval stage is dominantly determined by the probability of larval exchange among populations, and therefore, influenced by the dispersal ability of individuals and their larvae. Potential larval flows (gene exchange) between two putative populations, in turn, may be driven by biological  and ecological factors  ,20,21,22C. guanhumi females from the estuaries migrate to the shore and release eggs into saltwater. Once hatched, free swimming larvae molts through five larval stages that may last at least 42 days under laboratory conditions [C. guanhumi larvae dispersal/retention. This, in turn, would respond to regional endemism patterns existing in this ocean region, as seen for many other species [nditions ,3,23, whnditions , along w species ,27,28,29mtDNA) control region (CR), the most rapidly evolving and highly variable non-coding region in mitochondrial genome. The CR of the mtDNA has proved to be a useful tool to address evolutionary questions, e.g. the intra-specific population structure of many crab species [These possibly occurring evolutionary processes may be detected by the sequencing of the mitochondrial DNA  were assessed by contiguous mtDNA sequences (a 112-bp 12S rRNA fragment and 598-bp of the 5′-end control region) to examine the connectivity among these populations within the WCA for future conservation strategies and decision-making of fishery management.In this investigation, patterns of population genetic structure and historical demographics of the blue land crab C. guanhumi samples captured off the Western Central Atlantic (mtDNA haplotypes were found but instead a distribution of low-frequency recurrent haplotypes with a large number of singletons. Similar haplotypes were only detected in Brazilian mangroves (Sergipe and Bahia).The analysis of mitochondrial DNA control region of Atlantic  producedAtlantic . DNA seqfA = 0.443, fT = 0.313, fC = 0.161, and fG = 0.083. Genetic diversity indices (average ± standard deviation), haplotype diversity (Hd), and nucleotide diversity (π) are presented in ISS (0.09) much smaller than the critical ISS value (CISS = 0.80), indicating that sequences are highly useful in phylogenetic reconstruction [The transversion/transition ratio was 0.1648, and base frequencies were truction .The neighbour-joining tree was constructed based on Kimura 2-Parameter distances of 93 individuals. In the tree, two very distinct clusters were observed, corresponding to the Caribbean Sea and the Brazilian coast . Only fimtDNA sequences for C. guanhumi showed the genealogical relationships among 93 haplotypes based on the least number of substitutions. The network consisted of two consecutively connected sub-networks corresponding to the two studied regions with most haplotypes connected by many mutation steps  departed significantly from zero, which indicated genetic structure was existed in C.guanhumi populations.The AMOVA of ulations . The aveFST analysis .Further evidence of population genetic structuring within the five localities was revealed by analysis . Accordip < 0.01).Furthermore, all possible pairwise Da comparisons were high between Caribbean and Brazilian localities, and statistically significant. The largest genetic differences were found between the FLO and SER . It is worth observing that the number of detected haplogroups (3) corresponded to the number of clades depicted in the NJ-tree and the median-joining network  detected three mitochondrial DNA haplotype clusters, hereafter referred to as haplogroups, across the five populations sampled, one of which was restricted o the Brazilian waters (HG1), with minor presence in Puerto Rico (Caribbean Sea), and two haplogroups (HG2 e HG3) restricted to the Caribbean exclusively . Within  network .FST values and the geographic distances between localities . The Fu’s SF-test, which is devised specifically to detect population expansion and is more sensitive to the presence of singletons in the samples, showed significant values in four populations , but with a mean not significant negative value .Results from Tajima’s D and Fu’s C. guanhumi individuals sampled from all five localities were constructed respectively  control region as marker [C. guanhumi is also in agreement with data from other marine organisms, particularly from other marine crustacean species with planktonic larvae using the same mitochondrial markers [C. guanhumi population distribution in the Western Central Atlantic [The analysis of the contiguous observed , which is marker . The hig markers ,39. The Atlantic  with deeAtlantic ,42. ThisAtlantic , and on Atlantic ,44).P. argus) in a study carried out using the same mtDNA fragment [C. guanhumi and P. argus, share similar geographical ranges, from southern USA to southern Brazil. Both species do seem to experience obstacles for gene flow in the region encompassed by their studies . The dispersal capacity of their larvae is probably diminished by the Amazon and Orinoco River plumes and North Brazil Current (NBC) rings, which may be acting as a geographical barrier.The patterns observed in this species are particularly comparable to those obtained for other crustacean  was restricted to the estuaries along the Brazilian coastline, which were closely related and did cluster together, and the other two haplogroups (HG2 + HG3) were restricted to the Caribbean. This evidenced sharp genetic separation between two geographical regions might be attributed to differences in sequence divergences between haplotypes. The analysis of mtDNA sequence data also revealed that population samples within the Brazilian coast are nearly homogenous. The MJ network of the observed 93 haplotypes did reveal a possible geographic pattern within the Caribbean . Moreovulations , which mulations  from therassipes  and Call sapidus ), it is i.e., off the Brazilian coast) seem to be responsible to a near-homogeneous diversity in the Brazilian coast  the mixan coast . The pelThe presence of this phylogeographical discontinuity was further demonstrated by the results of the Bayesian assignment analysis , accordiC. guanhumi larval dispersal mechanisms, and more studies on the species biology, as well as on the local currents, are needed. At the present, based on our results, a simple model of isolation by distance can also explain the population genetic structure of C. guanhumi within the tropical Western Central Atlantic region since population genetic differentiation (estimated as FST) does appear to be related to geographic distances separating populations ; Florida ; Alagoas ; Bahia ; Sergipe   . Muscle C. guanhumimt genome was amplified by a pair of primers, DLUSSAF (5′-GTA TAA CCG CGA ATG CTG GCA C-3′) and ILEUCAR . The PCR consisted of 30 cycles of 95 °C for 30 s, 50 °C for 30 s, and 68 °C for 60 s, with an initial denaturation of 95 °C for 30 s and a final extension of 68 °C for 5 min using a Veriti 96-well Thermal Cycler . All amplifications were run against a negative control in which all components, except DNA template were added. Amplicons were checked for correct size and quality by gel electrophoresis with SyberSafe™ staining.The largest portion of the control region and a 112-bp short fragment of the 12S gene within T ATA-3′ ). Amplif® PCR Purification columns in order to remove the excess primers and nucleotides, and concentrate the amplified PCR fragments. The purified double-stranded amplification products were used as template DNA in sequencing reactions. Cycle sequencing was performed using the ABI Prism BigDye™ Ready Mix (Applied Biosystems) and primers DLUSSAF and ILEUCAR, separately, on a Veriti 96-well Thermal Cycler. Then, sequencing products were purified using isopropanol to remove unreacted fluorescent BigDye Terminators. The PCR products were sequenced on the ABI 3500 Genetic Analyzer (Applied Biosystems) in both forward and reverse directions. All new distinct nucleotide sequences were submitted to the GenBank database .PCR products were purified with InvitekForward and reverse DNA sequences for each individual were inspected with sequence editor CHROMAS version 2.23  and corrected when necessary. Homologous nucleotide sequences from all samples were aligned using the program CLUSTALX version 1.81  on the sISS.c, critical value) with the observed saturation index (ISS) [The occurrence of substitution saturation, which could create a bias in phylogenetic reconstruction, was investigated by comparing half of the theoretical saturation index expected when assuming full saturation (ex (ISS) . Indicesex (ISS) , were caex (ISS) .Unique haplotypes were identified using DNASP version 5.10 . GeneticC. guanhumimtDNA sequences were also imported into MEGA version 6.0 [The aligned sion 6.0  for estision 6.0 . Sites wsion 6.0 .A network was generated to infer the genealogical relationships among haplotypes using the median-joining algorithm , implememtDNA variation was examined by a hierarchical analysis of molecular variance  and popion 3.51  using thion 3.51 . Fixatioion 3.51 .A) between populations was also calculated asiXY is the average of pairwise differences between populations X and Y, and PiX/PiY are the averages of pairwise differences among individuals within population X and Y, respectively. Post-hoc Bonferroni’s correction for multiple comparisons were used when appropriate.A corrected average pairwise difference (Dk (k is the maximum number of clusters) up to k = 10, and the results were averaged according to the resultant likelihood scores.Additionally, a Bayesian Analysis of Population Structure (BAPS ) was empThe isolation-by-distance hypothesis was examined by a Mantel’s test ,72. Geogsp by, firstly, testing selective neutrality for each population and for all individuals using Tajima’s D [SF [Demographic patterns of populations were assessed in DNAjima’s D  and Fu’s’s D [FS  statisti’s D [FS ,76. The ’s D [FS ) was use’s D [FS .mtDNA CR gene sequences, identified high genetic diversity and significant genetic differentiation in C. guanhumi within the Western Central Atlantic. A sharp genetic break between Caribbean and Brazilian populations, which appears to be associated with a marine biogeographic boundary to gene flow, raised concerns over the conservation status of the blue land crab. The population structure implied that a clear subdivision exists in C. guanhumi regional populations, and should be considered as different management units for further effective conservation and management purposes [mt genome in this study. The use of multiple genetic marker systems could increase the resolving power of this genetic study and the inclusion of crabs from different estuaries and larger numbers of individuals at each site should confirm the pattern of genetic population structure revealed in this study. Further studies including nuclear markers  are nee


To determine allele frequencies and forensic statistics of 22 autosomal short tandem repeat loci in Chinese Mongolian population.Blood specimens were collected from 134 unrelated healthy Mongolian individuals, and 22 short tandem repeat loci were co-amplified and genotyped. Allele frequencies and forensic parameters were calculated, and population genetic differences were analyzed among Mongolian population and other eight Chinese populations: Northern Han, Guangdong Han, Chengdu Han, Xinjiang Hui, Xinjiang Uygur, Hainan Li, Qinghai Tibetan, and Hainan Han.P < 0.05).All the loci were in the Hardy-Weinberg equilibrium, and after Bonferroni correction there was no linkage disequilibrium between them. The allele frequencies of these 22 loci were between 0.0037 and 0.3657. This panel had high discriminating power and genetic polymorphism in the Mongolian population, with combined power of discrimination of 0.999999999999999999999999998399 and combined probability of exclusion of 0.9999999999566925. Structure analysis showed no evidence that these nine Chinese populations had different component distribution. However, genetic distance analysis showed significant differences among them  than from the populations in Hainan province (Hainan Han and Hainan Li populations). Xinjiang province is an ethnic autonomous region in the northwest of China, bordering Russia, Pakistan, India, Kazakhstan, Tajikistan, Kyrgyzstan, Afghanistan, and Mongolia. Historically, the province was home to an important route on the Silk Road, functioning as China’s gateway to the west. It is inhabited by 47 ethnic groups, including Mongolians, which mainly inhabit the Bayingol Mongol Autonomous Prefecture, Hoboksar Mongol Autonomous County, and Bortala Mongol Autonomous Prefecture. Besides these Chinese regions, Mongolians also inhabit Mongolia and parts of Russia. They are predominantly shamanist and speak a language from the Mongolian group of Altaic family.A short tandem repeat (STR) is a train of repetitive base sequences on the DNA strand. STR genetic polymorphisms can be analyzed by measuring the exact number of repeating units on the DNA. The novel panel used in this study is a STR genotyping system based on capillary electrophoresis analysis with 5-color fluorescence labeling, which encompasses Amelogenin gene and 22 autosomal STR loci: D1S1656, D2S1338, D3S3045, D4S2366, D5S2500, D6S477, D7S3048, D8S1132, D9S925, D10S1435, D11S2368, D12S391, D13S325, D14S608, D15S659, D16S539, D17S1290, D18S535, D19S253, D20S470, D21S1270, and D22-GATA198B05. The 22 loci are distributed in 22 pairs of autosomes, and their amplified fragments are less than 450 bp.This panel was validated by a previous study , which aThis observational population genetics study was conducted in June 2017 at the Xi’an Jiaotong University. A total of 134 peripheral blood samples of volunteer unrelated healthy Mongolian individuals (90 women and 44 men) were collected from Chinese Xinjiang Uygur Autonomous Region and saved in the form of a paper blood collection card. Individuals were considered eligible if they met the following criteria: (i) there were no blood relationships between them, (ii) they all lived in Xinjiang Uygur Autonomous Region for over three generations, (iii) and there was no migration in their family history. Informed consent for study participation and data presentation was obtained from all volunteers before sampling. The study was approved by the Ethics Committee of the Institute for Xi’an Jiaotong University .After the extraction of genomic DNA using the Chelex-100 method , Ameloge1)(1–DP2)(1–DP3)…(1-DPk); CPE=1–(1–PE1) (1–PE2) (1–PE3)…(1–PEk). In these two formulas, indicates the number of loci. The allele frequencies of 22 loci were compared between the Mongolian and other reference populations by Arlequin software v. 3.5 (A) and fixation index (Fst) values in Mongolian and other populations were calculated with DISPAN   of the 2e v. 3.5 . The STRe v. 3.5 . Genetich DISPAN  and Geneh DISPAN , respecth DISPAN  based one v. 6.0  and Phyle v. 6.0 -21. PrinP values of 22 loci were all greater than 0.05, which meant that none of these loci deviated from the HWE  to 0.1016 D19S253). In contrast, the PD values of all loci were greater than 0.9, except for D19S253 (0.8984); with a CPD value of 0.999999999999999999999999998399. The Ho values ranged from 0.7463 (D10S1435) to 0.9179 (D20S470) and He values from 0.7634 (D10S1435) to 0.8810 (D2S1338). The heterozygosity of all the loci was greater than 0.7. These results indicate that these loci have high discrimination power in Xinjiang Mongolian population ,25. The 3. In conWe assessed the differences between Xinjiang Mongolian population and six reference populations in the allele frequencies of these 22 loci by using the analysis of molecular variance . There wA between the populations were calculated based on allele frequencies of 16 overlapping loci. Fst values (a measure of genetic differentiation) between any two of seven populations (except for Chengdu Han and Qinghai Tibetan) were obtained to quantify the genetic relationships between different groups. DA values ranged from 0.0035 to 0.0379 and Fst values from 0.0002 to 0.0138 , Northern Han , and Xinjiang Uygur , and the greatest genetic distance from Hainan Li . Overall, the relationships among these populations were relatively close  offered no evidence that they had different component distribution. Next, we used a series of bioinformatics methods to analyze the genetic relationships between the populations. Do 0.0138 . Xinjianly close .A values and allele frequencies we constructed two phylogenetic trees  , which wpost hoc power analysis of HWE tests was performed by R version 3.6.0  was based on previous studies  was base. Given ton 3.6.0  , the genetic relationships have to be interpreted in light of certain limitations. In order to further conduct population research and explain the origin of Mongolians, the genetic characteristics of these 22 loci should be evaluated in other populations and genetic characteristics of Mongolians at other loci should be assessed.