Gobiosoma bosc (naked goby), to investigate local and regional scale population structure and gene flow along a salinity gradient (∼3 ppt to ∼18 ppt) in two North Carolina estuaries. G. bosc is an abundant and geographically widespread species that requires complex but patchy microhabitat  for reproduction and refuge. We sequenced 155 fish from 10 sites, using a common barcoding gene (COI). We also included recent sequence data from GenBank to determine how North Carolina populations fit into the larger biogeographic understanding of this species. In North Carolina, we found a significant amount of gene flow within and between estuaries. Our analysis also showed high predicted genetic diversity based upon a large number of rare haplotypes found within many of our sampled populations. Moreover, we detected a number of new haplotypes in North Carolina that had not yet been observed in prior work. Sampling along a salinity gradient did not reveal any significant positive or negative correlations between salinity and genetic diversity, nor the proportion of singleton haplotypes, with the exception of a positive correlation between salinity standard deviation and genetic diversity. We also found evidence that an introduced European population of naked gobies may have originated from an Atlantic source population. Altogether, this system offers a compelling way to evaluate whether factors other than dispersal per se mediate recruitment in an estuarine-dependent species of fish with a larval dispersal phase. It also demonstrates the importance of exploring both smaller and larger scale population structure in marine organisms to better understand local and regional patterns of population connectivity and gene flow.Many species of fish produce larvae that undergo a prolonged dispersal phase. However, evidence from a number of recent studies on demersal fishes suggests that the dispersal of propagules may not be strongly correlated with gene flow. Instead, other factors like larval behavior and the availability of preferred settlement habitat may be more important to maintaining population structure. We used an ecologically important benthic fish species,  Gobiosoma, are also found in temperate latitudes in the western Atlantic. Although common across a broad range of estuarine habitats and salinity gradients, the Gobiosoma remain relatively understudied , is a geographically widespread species—ranging from Connecticut to Campeche, Mexico—and the most commonly encountered gobioid fish in estuaries of the southeastern United States , due to biogeographic breaks that inhibit gene flow. The G. bosc in North America. To date, however, there have been no studies investigating genetic diversity at smaller scales . This is particularly relevant given the importance of suitable habitat in structuring populations of naked gobies, which are otherwise isolated from one another as adults within a broader habitat matrix.To date, few studies have attempted to quantify population connectivity in temperate fishes e.g.,  like G. d gobies  has provG. bosc along a salinity gradient from two North Carolina estuaries in order to quantify population connectivity within and between estuaries, and also to better understand the role of habitat and salinity in mediating gene flow and local adaptation. While naked gobies have a broad salinity tolerance (<1.0 ppt–32 ppt), they have been noted as most abundant in salinities below 24 ppt , or other conserved habitats that are spatially segregated but connected by gene flow.To quantify population structure in these estuaries, we used the common mitochondrial barcoding gene Cytochrome Oxidase I (COI), which has been used as a tool for population genetics studies across multiple diverse taxa over the past 20+ years , and spe the USA . Our stuGobiosoma bosc fish were sampled along a salient gradient spanning the Pamlico and Neuse River estuaries in the North Carolina coastal plain  from nine locations along the Pamlico and Neuse River estuaries, in addition to the site at Hoop Pole Creek  to sample specifically for naked gobies.From February to July 2017, naked gobies were sampled  to provide an average and standard deviation salinity value for each site that could be regressed against genetic (haplotype) diversity at each sample location.Two replicate crates were deployed at each sample location, making for a total of ten collecting units on the Neuse River and eight on the Pamlico River. Crates were zip-tied to 0.75 m wooden stakes secured in the nearshore subtidal zone, or deployed from fixed or floating docks using rope. Crates on both rivers were checked every 6–8 weeks, and the contents sorted using a large sieve (55.9 × 55.9 × 12.7 cm) with 2 mm mesh. A maximum of ten naked gobies were collected from each sample site during each sampling event. In order to minimize selection bias, fish from both crates were pooled together, and ten individuals were randomly selected from a grid divided into four quadrants. Only sexually mature adults were used in this study. Therefore, all fish less than 20 mm SL i.e.,  were relNaked gobies were dissected as part of an unrelated study assessing parasite diversity in these fish, and thus sampled fish were not released following capture. Once dissected, white muscle tissue was saved from each individual and immediately preserved at −20 °C for later DNA extraction. Genomic DNA was isolated from tissue samples using proteinase K/SDS digestion, chloroform extraction, and ethanol precipitation . CytochrKM077829.1) using Geneious10.1.2 . This resulted in a 530 base-pair fragment of the COI gene across all samples  with 100% coverage of the 530 base-pair COI fragment. These included 57 sequences  from a recent and comprehensive population genetics investigation of G. bosc in several North American populations, including New York, Virginia, South Carolina, Atlantic Florida, Gulf Florida, Louisiana, Mississippi, and Texas .Sequences were manually cleaned, inspected for ambiguities, and aligned without gaps to a reference sequence in GenBank  to graphically create haplotype networks.For our first analysis focused on North Carolina, we estimated the hierarchical analysis of molecular variance (AMOVA) using ARLEQUIN311 . ResultiARLEQUIN  and visun = 9 sites: four in the Pamlico River and five in the Neuse River). We used JMP Pro 13  to regress salinity with (a) genetic diversity and (b) the proportion of singleton haplotypes . This latter approach was used to determine whether there was any influence of salinity on the proportion of rare haplotypes in a population. Additionally, given the variability in salinity within these systems, we also explored whether there was any relationship between the standard deviation of salinity and genetic diversity.We also used ARLEQUIN to obtain genetic diversity values for each population to investigate whether there was any effect of salinity on haplotype diversity in the North Carolina populations. For this salinity analysis, we included sites that were sampled from the two rivers . Nonparametric estimators have been found useful in a number of studies for predicting the eventual asymptote in richness of a particular population  and do sFor our second analysis focused on goby biogeography, we performed an AMOVA to explore differences at the subregional level and also at the larger regional level, specifically between the Atlantic and Gulf of Mexico regions. We again used PopArt to graphically create haplotype networks, using incidence-based data from n = 88, and Neuse, n = 59), this haplotype (HAP5) was slightly more frequent in the Pamlico (78%) versus the Neuse (68%). At the haplotype level, most haplotypes were singleton occurrences: in the Pamlico, 60% of the haplotypes were singletons, and in the Neuse, 74% were singletons. When comparing between the Neuse and Pamlico sites, just 4 haplotypes (14%) were shared between the estuaries; thus at the haplotype level, there was much less overlap between them. However, at the individual level, 86% of the Neuse individuals shared haplotypes with the Pamlico, and 76% of the Pamlico individuals shared haplotypes with the Neuse. This was supported by non-significant differentiation in the AMOVA comparing these two estuaries . It is important to note, however, that most of the sharing between estuaries and among populations occurred with the dominant haplotype, HAP5. In addition to the dominant haplotype (HAP5), the second most frequent haplotype (HAP27) was also comprised of individuals from both estuaries, as well as Bogue Sound.In our North Carolina dataset ; Table 1ϕST analyses after accounting for multiple pairwise comparisons : MLC and CQC (p < 0.001); MLC and HPC (p = 0.009); and NCL and HPC (p = 0.009). In addition, n = 160) in the extrapolation curve than were actually detected (n = 20), and for the Pamlico ∼5 times more haplotypes were predicted (n = 80) than were detected (n = 15). Comparing between the estuaries, the Neuse was ∼2.5 times greater in predicted diversity than the Pamlico. Such diversity differences between the estuaries were also supported by a Shannon diversity test, finding H′= 1.55 for the Neuse and H′= 1.06 for the Pamlico.At the population level , the folR2 = 0.004; p = 0.873; R2 = 0.070; p = 0.490; R2 = 0.187; p = 0.245; ϕSTs), CDI and NCL, had salinities that were separated on average by 6 ppt, and these sites were also found in different estuaries. However, there was a significant positive correlation between the standard deviation of salinity and genetic diversity   .G. bosc sequences from the public sequence repository, GenBank, with our own North Carolina estuary samples. For this analysis, we explored regional differentiation across North America, including the mid-Atlantic (New York and Virginia), North Carolina , South Carolina, Atlantic Florida, Florida Gulf, Florida panhandle, and other Gulf states . In addition, we included five sequences found in a non-native population in Germany (Weser estuary). Except for North Carolina, these samples came from two studies: (p < 0.001), with North Carolina falling in with the southeast and mid-Atlantic samples. When comparing Atlantic versus Gulf of Mexico sites, there was significant differentiation between the two major regions (p < 0.001)  .n = 5) representative sequences from this region  must be taken with caution, as there are just a few , even though reports in the literature find naked gobies to be most abundant in moderate salinity habitats. In the sections that follow, we expand upon these findings and discuss their implications.obiosoma  and larg detected in the haplotype network of the protist Plasmodium falcipram (which infects African mosquitos) demonstrated clear population expansions for the parasite  in South Africa, suggesting a recent bottleneck and/or population expansion , our evidence for a possible population expansion could be a response to one or more of the 35 tropical cyclones to affect coastal North Carolina over the past two decades (In addition to demonstrating high diversity and a large number of singleton haplotypes (just a couple mutation steps away from the dominant haplotype), the star-like pattern of the haplotype network is also a well-known signature of populations that have undergone recent expansion e.g., . For exaparasite . In a maxpansion . Specifistuaries , larval  decades , or perh decades . A greatϕSTs  . Althougts e.g., . In our ts e.g.,  revealedts e.g., , wherebyts e.g., . Such ants e.g., . Alternats e.g., . Thus, dG. bosc, but have also advocated for the major synergistic role that salinity plays for this fish species. Larval G. bosc approaching competence-to-settle are known to congregate near the downstream edges of oyster reefs, rubble, or artificial structures . Altogether, the evidence from prior studies and our own suggests that gene flow in this species is mediated by multiple biotic and abiotic factors—principally among them the type of epibenthic substrate available as habitat, how the distribution of this habitat changes with salinity, and the location of suitable habitat relative to wind-forced circulation patterns.Further, previous studies have recognized the importance of habitat in structuring populations of ructures . Adults ructures . Shenker regalis  and red cellatus . Howeverded cans . Much liG. bosc collected from an offshore scallop bed, and there are occasional reports of juveniles collected off Beaufort, N.C., located close to the Atlantic Ocean . For example, in the Gulf, geographic differentiation was much more apparent with a considerable break at Apalachicola Bay, sub-dividing the Florida panhandle in two . While adult G. bosc are relatively cryptic and do not appear to stray far from complex habitat, this remains an untested assumption that could potentially inform our understanding of population connectivity in this species at the estuary level. Further resolution of the genetic connectivity among populations should also include genome-level markers , as it can be difficult to develop a detailed understanding of the magnitude of gene flow at smaller scales using only frequency-based approaches . Columns 2–10 represent newly collected raw data from populations in North Carolina. These include the abundance of a particular haplotype per site. Columns 11–12 represent data extracted from Genbank that were part of Click here for additional data file.10.7717/peerj.5380/supp-2Table S2Click here for additional data file.10.7717/peerj.5380/supp-3Table S3Click here for additional data file.10.7717/peerj.5380/supp-4Supplemental Information 1Sequence data for North Carolina Populations, Atlantic and Gulf of Mexico Populations , and GerClick here for additional data file.


Short tandem repeats (STRs) located on the Y chromosome with the properties of male-specific inheritance and haploidy are widely used in forensics to analyze paternal genealogies and match male trace donors to evidence. Besides, Y-chromosomal haplotypes play an important role in providing breathtaking insights into population genetic history. However, the genetic diversity and forensic characteristics of Y-STRs in Guizhou main ethnic groups  remain uncharacterized. Here, we obtained Y-chromosomal 23-marker haplotypes in three Guizhou populations and submitted the first batch of Y-STR haplotype data to the YHRD. The HD in the aforementioned three populations are 0.99990, 0.99983, and 0.99979, respectively, and DC values are 0.9902, 0.9908, and 0.97959, respectively. Subsequently, genetic differentiation between our newly studied populations and reference groups along ethnic/administrative divisions, as well as national/continental boundaries were investigated via AMOVA, MDS, and phylogenetic relationship reconstruction. Significant genetic differentiations from our subjects and other groups are identified in ethnically, linguistically and geographically diverse populations, including most prominently Tibetans and Uyghurs among 30 mainland Chinese populations, Taiwanese groups and others among 58 Asian populations, as well as African groups and others among 89 worldwide populations. Qiannan Bouyei has a close genetic relationship with Guangxi Zhuang, and Zunyi Han and Qiandongnan Miao have close genetic affinity with Hunan Han and Guizhou Shui, respectively. Collectively, this new-generation Y-STR amplification system can be used as a supplementary tool in forensic identification and male parentage testing and even pedigree search. Human Y chromosome variations, with the properties of male specificity, haploidy and escaping from crossing-over, play an important role in the studies of anthropology, genealogy, as well as population and forensic genetics. Poznik et al. found over 65,000 Y-chromosomal genetic variants  via massive parallel sequencing 1244 individuals from 26 diverse populations7. The better understanding of the human Y-chromosome variations has driven its unprecedented process in the forensic applications9. Y-STRs, also known as microsatellites located on the human Y chromosome, are tandemly repeated short (2–6 bp) DNA sequences5. Thomas Willems et al. have investigated the mutation rates, forensic characteristics and potential applications of 4,500 Y-STRs on the basis of population sequence data1. Ballantyne et al. found 13 most mutable Y-STRs extracting from 186 markers after analyzing the mutation rates covering 352,999 meiotic transfers in forensic male lineage identification10. These previous contributions have prompted the widespread use of the non-recombining Y-chromosomal microsatellites in the forensic science: inferring biological sex of perpetrators, inferring paternal bio-geographic ancestry, characterizing paternal lineages of unknown crime scene male trace donors, predicting a man’s surname, paternal and complex kinship identification, as well as familial searching17. The PowerPlex® Y23 System, developed and released in 2013 by the Promega and co-amplifying 23 Y-STRs , plays an important role in the research of population genetic, forensic genetics, human evolution and molecular anthropology20.Recently, advances of the whole Y chromosome high-coverage sequencing have facilitated the clear understanding of the genetic variations of this unilinearly transmitted genome segment and revolutionized the insights and prospects of interdisciplinary researches23. While massive researches have concentrated on the genetic polymorphisms based on autosomal-STRs27, X-Chromosomal-STRs30 and mitochondrial genome genetic markers31 in distinct Chinese populations. Guizhou province, located in the southwestern part of China with a population over 34 million, is one of China’s most demographically diverse province. The first three largest populations are Han (62%), Miao (12%) and Bouyei (8%). Han ethnic group, with a population over 1.2 billion, is the world’s largest ethnic group and widely distributed in the East Asia, Southeast Asia  and others. According to the historical materials, Han Chinese population was believed to be decedents of confederation of Huaxia tribes which residing along the Yellow River in the north of China32. Previous studies hold the opinion that a significant difference has existed between the northern Hans and southern Hans, but, others found just continuous genetic North–South gradient in the Chinese Han population34. Besides, as we all known that, the observed population substructure could be complicated by many factors, such as the number and kinds of genetic markers, the geographic origins or coverage of studied populations and reference populations34. Miao has a population of approximately 12 million and lives primarily in the southern Chinese mountains, whose language family belongs to the Hmong–Mien language family. The Bouyei, as the eleventh largest ethnicity with approximately 2.5 million population, live in semi-tropical, high-altitude forests of the southwest China. Previous historical evidence suggested that Bouyei is the decedents of the oldest Tai people and Bouyei language is very close to the Zhuang language and belongs to Tai-Kadai the language family.China, as a multi-ethnic country which consists of Han Chinese populations and 55 officially recognized minorities, has been the research hotspot in the genetic study to explore and elucidate the population substructures and the origin of these ethnic groups12. As yet, Y chromosome variation data in Guizhou populations, especially for Chinese Bouyei and Guizhou Miao, remains blank.However, little is known about the diversity of the aforementioned Y-STRs in Guizhou populations. Y chromosome haplotype reference database (YHRD) is contributed to provide a large and high quality Y-STR haplotype data from distinct genetic populations across the world for forensic and population genetic applications and researches37, we investigated the Y-chromosomal STR haplotype distributions in three Guizhou ethnicities in the southwestern China using the PowerPlex Y23 amplification system 20 and submitted the first batch of Y-STR haplotype data of Zunyi Han (YA004233), Qiandongnan Miao (YA004235) and Qiannan Bouyei (YA004236) for forensic, genealogical, and ethnic evolutionary researches. Additionally, we combined our new datasets with previously published reference populations44 defined by ethnic and administrative boundaries, as well as national and continental geographic divisions . With this unprecedented dataset, we aimed to comprehensively characterize genetic relationships and reconstruct phylogenetic history.In the continuation of our previous studiesWe genotyped a total of 308 Guizhou individuals successfully and provided the first Y-chromosome haplotype data of three studied populations, as showed in Supplementary Tables 1–3 Forensic parameters, including allele frequencies and gene diversity (GD), are listed in Supplementary Tables 4–6 For the Bouyei population, 96 different haplotypes are observed from 98 individuals. Among them, 94 are unique and 2 are duplicates  and one haplotype shared by two individuals (0.99%)  via analysis of molecular variance (AMOVA), Multidimensional scaling plots (MDS) and phylogenetic relationship reconstruction. Supplementary Table 47. However, this study based on 23 Y-STR haplotype data fails to reveal this genetic phenomenon which is explicable by the few populations from north China.3589 Y-STR haplotypes consisting of 23 markers from 11 Chinese populations41, 4620 Y-STR haplotypes from 22 populations are employed to calculate the pairwise Rst values. As shown in Supplementary Table To explore the genetic homogeneity and heterogeneity among newly investigated populations and Chinese minority ethnic groups23, obvious substructures with other reference ethnicities are identified at Qinghai Hui, Ordos-Western Mongolian, Cangzhou Hui, Minnan Han, Yunnan Bai, Fujian She, Meizhou Hakka Han, Southern Han, Inner Mongolia Mongolian, Qiandongnan Miao, Guangxi Zhuang, Yunnan Dai, Xinjiang Uyghur, Guizhou Shui, and Tibet Tibetan. Figure 42 are visualized using the Neighbor-Joining tree . The average Rst values reflecting individual population genetic differences range from 0.0302 at Zunyi Han to 0.1616 at Tibet Tibetan  to 0.4026 (Taiwan Tsou) in Zunyi Han, from 0.0079 (Northern Thai) to 0.4683 (Taiwan Tsou) in Qiandongnan Miao, from −0.0054 (Thailand Shan) to 0.4485 (Taiwan Tsou) in Qiannan Bouyei  further reveal the partial population substructure between large-scale geographic divisions. As shown in Supplementary Table 48 combined with our data are used to investigate the genetic divergence and similarities. The average of pairwise Rst values focused on Zunyi Han, Qiandongnan Miao and Qiannan Bouyei are 0.1445, 0.1922, and 0.1660, respectively. Five clear genetic affinity clusters can be identified: East Asian cluster, American cluster, European cluster, South Asian cluster, and African cluster . Our results, as expected, demonstrated that our targeted studied populations keep the furthest genetic relationship with Africans.Calculation of Rst values between our studied subjects and seven meta-populations−2 per locus per generation and slowly mutating (SM) Y-STRs with the low to midrange mutation rates (approximately∼10−3)49. SM Y-STRs have the advantages in the phylogenetic studies and providing investigative leads in the family searches50, however, RM Y-STRs are more suitable for forensic paternal lineage identification or other complex kinship identification51. PowerPlex® Y23 system included all markers included in the previously developed systems  and other four SM Y-STRs  and two RM Y-STRs (DYS570 and DYS576) included in the recently selected 13 rapidly mutation systems51. To accurately estimate the match probability of the Y-chromosomal haplotype from the crime scene to the perpetrator or infer the male biological ancestry of Chinese minority populations, more haplotype data and detailed genetic diversity form different populations are important. Besides, all forensic analysts, researchers focused on the historical and family genetics have commonly recognized that the appropriate grouping of haplotypes based on ethnically/geographically/linguistically different populations are necessary for the sensitivity of male-specific STRs to population differentiation53.Y-STRs can be categorized into two main kinds on the basis of Y-STR mutation rates: Rapidly Mutating (RM) Y-STRs with mutation rates approximately 1036 and Yi37, demonstrated that 23 Y-STRs are highly informative and polymorphic and could be served as a useful and interesting tool in forensic practical applications. Additionally, this study enriches the Y-STR database of the southwest Chinese ethnic populations and provides the first batch of Y-chromosome STR profiling data of these three underrepresented Chinese populations to the Y Chromosome Haplotype Reference Database (YHRD), which is essential to assist the calculation and interpretation of match probabilities in forensic male lineage identification, as well as characterizing population male genetic history53.Thus, in the present study, we investigated the genetic polymorphisms/haplotype diversity and forensic characteristics of 23 Y-chromosomal STRs (21 single-copy Y-STR loci and one multi-copy locus. 23 Y-STRs) in 101 unrelated southwest Han Chinese individuals, 98 Bouyei individuals and 109 Miao individuals residing in Guizhou Province using the PowerPlex Y23 PCR amplification kit. DYS385a/b locus is the most diverse and polymorphic marker (GD > 0.9468) in three populations. The forensic diversity measures of RMP, DC, and HD in three newly genotyped Chinese populations, combined with the previously investigated Gelaoet al. recently revisited the Chinese male genetic landscape on the basis of 38,000 17-Y-STR haplotypes and found Han Chinese populations are homogeneity and genetic differentiation exists among Minorities (Tibetans and Kazakhs) and Han Chinese23. However, there are a large number of population migration and genetic admixture  after anatomically modern human migrated out of Africa. Besides, Abundant evolutionary forces  also has shaped the genetic landscapes nowadays55. Y-chromosomal STRs are important and indispensable to explore the origin of modern humans, tracing the migration trajectories and timing of ancient human, and inferring the male genetic genealogy evolution, as well as dissecting the population stratification for constructing regional-effective forensic reference database and reasonably designing case-control studies in the whole genome association studies to avoid false positive results. Thus, we conducted a more comprehensive population genetic comparisons based on more Y-STRs (23) to dissect the genetic relationships of worldwide populations and Chinese nationwide populations. In this study, we conducted the population comparisons to investigate the detailed genetic background of our focuses  as well as explore the genetic relationships among 30 mainland Chinese populations (Han Chinese and minority populations)43, 58 Asian populations43 and 89 worldwide populations44. Our results demonstrated that Qiannan Bouyei has a close genetic affinity with Guangxi Zhuang, as well as Zunyi Han with Hunan Han, and Qiandongnan Miao with Guizhou Shui. Additionally, significant genetic distinctions have existed among Hans, Uyghurs, Tibetan and Taiwanese populations. Population structure analysis revealed a strong association between genetic distance and geographical or ethnic affinity.Nothnagel et al. have investigated the genetic diversity of the 23 Y-STRs and population structure among 12 worldwide populations with sample sizes varying from 9 to 9238 and Purps et al. analyzed the Y-chromosomal haplotype diversity of 19,630 individuals from 129 different populations in 51 countries19. In this study, we conducted genetic studies on the basis of 308 individuals from 3 populations. Considering the relatively small sample size, more attention should be paid in the forensic practices and population genetic applications. Inter- and intra-populations structure between the three focuses  and other reference populations along different geographical/ethnically divisions revealed that the Zunyi Han is genetically close to other geographically adjacent Han Chinese populations and keeps the remote genetic relationships with Miao and Bouyei populations. Bouyei population has a stronger genetic homogeneity with Zhuang population, both of them belong to the Tai-Kadai-speaking populations. We identified the genetic stratification among Han populations within the Sino-Tibetan-speaking populations, and Bouyeis and Zhuang populations within the Tai-Kadai-speaking populations. However, genetic affinities among different language-family-speaking populations are also observed, such as Hmong-Miens-speaking population of Miao and Tai-Kadai-speaking population of Shui. Significant genetic differences along continental boundaries based on the Y-chromosome generations is also identified. Worldwide population relationship patterns are consistent with the geographical categories. The present results emphasize the common paternal ancestry of same language family populations, and geographical isolation and paternal residence play a pivotal role in population structure reconstruction. To better disentangle the genetic structure and population history of Han, Miao and Bouyei in the natural processes  and elucidating genetic perspectives with other linguistically and geographically related populations, further studies based on the maternal mitochondrial DNA and whole genome sequence data or high-density chips data should be considered.Gao This study investigated the Y-chromosomal STR haplotype distributions in three Guizhou ethnicities in the southwestern China and submitted the first batch of Y-STR haplotype data of Zunyi Han (YA004233), Qiandongnan Miao (YA004235) and Qiannan Bouyei (YA004236) for forensic, genealogical, and ethnic evolutionary researches. The HD in the aforementioned three populations are 0.99990, 0.99983, and 0.99979, respectively, and DC values are 0.9902, 0.9908, and 0.97959, respectively. Comprehensive population comparisons along with ethnic divisions, administrative divisions, and national/continental boundaries were performed using AMOVA, MDS, and Neighbor-Joining phylogenetic relationship reconstructions. Overall, Qiannan Bouyei has a genetic relationship with Guangxi Zhuang. And Zunyi Han and Qiandongnan Miao respectively have the genetic affinity with Hunan Han and Guizhou Shui. Genetic structures of our studied three populations are significantly different from Chinese minority ethnicities  and Taiwanese populations in the East Asian. Worldwide population structure demonstrated that five population sub-structures can be dissected based on the Y-STR haplotype data in accordance with continental divisions.All of the experimental procedures in this study were strictly followed the humane and ethical research principles. All participants signed the written informed consent before sample collection. Our study design was approved by the Medical Ethics Committee of Zunyi medical university and Sichuan University.Peripheral blood samples were collected from 308 unrelated healthy Chinese individuals from three Chinese major population groups in Guizhou Province, southwest China, including: 98 Bouyei individuals residing in Qiannan District, 101 Han individuals recruited from Zunyi District, 109 Miao individuals residing in Qiandongnan District. One milliliter of blood was obtained in tubes with EDTA. The ancestors of all subjects must live in the present region at least three generations. The QIAamp DNA Blood Mini Kit  was used to extract the genomic DNA based on the manufacturer’s recommendations. A 7500 Real-time PCR system (Thermo Fisher Scientific) was employed to determine the DNA concentration using Quantifiler Human DNA Quantification Kit. The DNA was diluted to 1 ng/μL and stored at −20 °C until amplification.56.Twenty-three Y-STR loci  included in the PowerPlex Y23 System were co-amplified in one multiplex PCR reaction on a ProFlex PCR System (Thermo Fisher Scientific) according to the manufacturer’s instructions. In brief, 25 μL PCR reaction volume, consisting of 0.5 μL of template DNA, 5 μL of master mix and 2.5 μL of primer pair mix was employed. PCR cycling conditions were 96 °C for 1 min, followed by 28 cycles of 94 °C for 10 sec, 61 °C for 1 min, 72 °C for 30 sec, and a final extension at 60 °C for 20 min. Separation and detection of PCR amplified products were conducted using capillary electrophoresis on a 3500 Genetic Analyzers  with 36 cm capillary array and POP-4 polymer. 1 μL amplified product was added to deionized Hi-Di formamide (10 μL) with 1 μL CC5 ILS 500 Y23 size standard (Thermo Fisher Scientific). Capillary electrophoresis was conducted with the injection voltage of 1.2 kV and injection time of 15 sec. Allele designation was conducted using the software of GeneMapper ID-X v.1.4 by comparison with the allele ladder provided by the corresponding kit, which was followed by the DNA Commission of the International Society of Forensic Genetics (ISFG)57. The positive of control DNA 2800 M and negative control of ddH2O in each batch of genotyping were conducted. The genotype data of three Chinese ethnic groups were submitted to the Y chromosome haplotype reference database (YHRD)53 (http://www.yhrd.org) and received the following accession number YA004233 (Zunyi Han), YA004235 (Qiandongnan Miao) and YA004236 (Qiannan Bouyei).We carried out all of our experimental procedures in forensic genetic laboratory in the Department of Forensic Biology, West China School of Basic Science and Forensic Medicine, Sichuan University, which is accredited with the China National Accreditation Service for Conformity Assessment (CNAS) and ISO 17025. The recommendations published by the DNA Commission of the International Society for Forensic Genetics (ISFG) were followed in the overall experimental procedure59:Na and Nh respectively denote the total number of the tested samples and haplotypes, and Pai and Phi respectively mean the allele frequency of the ith allele of corresponding locus and ith haplotype. The discrimination capacity (DC) was assessed as using the following formula:A and Nh respectively means the number of distinct haplotypes in one population and total observed haplotypes. The random match probability (RMP) was determined as:Phi denotes the ith haplotype frequency. Comprehensive populations comparisons at different scales based on Y-chromosomal STR haplotype data are performed to investigate genetic similarities and differences between our studied populations and eight Han Chinese populations, nineteen Chinese minority ethnicities, fifty-eight Asian populations, seven Meta-populations, and eighty-nine worldwide populations48, respectively. Pairwise Rst genetic distances are calculated via the online tool in the YHRD using the analysis of molecular variance (AMOVA), and Multidimensional Scaling plots (MDS) based on different Rst genetic matrixes are also performed using the online tool in the YHRD53. According to the constraints in the process of AMOVA and MDS calculation, all haplotypes with unspecified alleles, intermediate alleles, null-alleles, triplicated or duplicated alleles were removed, and DYS389I were substracted from DYS389II for the Multi copy locus. Finally, phylogenetic relationships are reconstructed on the basis of Rst genetic matrix using the Molecular Evolutionary Genetics Analysis 7.0 (MEGA 7.0) software60.Allele frequencies of 23 Y-STR loci and haplotype frequencies were calculated using the direct counting method. Forensic statistical parameters of gene diversity (GD) and haplotype diversity (HD) were calculated using the Nei’s formulaSupplementary Tables S1–S11.


Tetraena mongolica Maxim (Zygophyllaceae) is an endangered species endemic to western Inner Mongolia and China, and is currently threatened by habitat loss and human over-exploitation. We explored the genetic background, its genetic diversity, population structure, and demographic history, based on 12 polymorphic nuclear microsatellite loci. Our results indicated high genetic diversity in extant populations, but no distinguishable gene cluster corresponding with a specific biogeography. Population demography analysis using a MSVAR indicated a strong, recent population decline approximately 5,455 years ago. These results suggest that the Yellow River and Zhuozi Mountain range may not prevent pollination between populations. Finally, we surmised that the population demography of T. mongolica was likely to have been affected by early mankind activities. Understanding population history and genetic structure is a key aspect of ecological research . EndemicPrevious studies revealed that natural landscape features such as mountains and rivers can act as genetic boundaries and shape the structure of populations . HoweverTetraena mongolica Maxim is a member of the broader genus Tetraena in the subfamily Zygophyllaceae  genotyped onto an extensive dataset to evaluate the current genetic diversity in T. mongolica populations, and to assess the effect of natural landscape barriers (Yellow River and Zhuozi Mountains) in shaping population structure. Lastly, we modeled the demographic history of T. mongolica to assess the effects of historic events on population demography. Our findings may be useful for the conservation and management of T. mongolica and other species endemic to the Yellow River basin.Evolutionary, demographic and genetic analyses all contribute to conservation and management of species . We geneT. mongolica. This investigation project and the sample collection were approved by the West Ordos National Nature Reserve, Inner Mongolia Province, China. Field experiments were also approved by the West Ordos National Nature Reserve, Inner Mongolia Province, China.The collection of samples was performed within an investigation project on plants of T. mongolica were collected from eight populations along the G6 Road: Shizuishan ; Dishan ; Hainan ; Dongalashan ; Wuda ; Qianlishan ; Wujiamiao  and Taositu   . Leaves T. mongolica  and sufficient water. The amplification program was conducted with following conditions: 5 min denaturing at 95 °C; followed by 35 cycles of 30 s at 95 °C, 20 s at the annealing temperature (55/60 °C), 30 s at 72 °C; and 5 min at 72 °C. PCR products were genotyped on an ABI 3730 semi-automated sequencer  utilizing the GS500 marker, followed by analysis under GeneMarker 1.85   .HO), expected heterozygosities (HE) and inbreeding coefficients (FIS). In addition, allelic richness (AR) was also calculated to estimate the allelic diversity that compensates for unequal sample size by FSTAT and averaged across loci (FST) between populations was estimated using ARLEQUIN 3.0  was run for a total of 1 million generations discarding the first 100,000 as burn-in. The most likely K explaining the variation in the data was selected estimating the maximal value of the log likelihood [Ln Pr(X/K)] of the posterior probability of the data for a given K  passed through a demographic change (a bottleneck or an expansion) at time T in the past, which changed its size from N1 to N0 following an exponential model. Five independent simulations were run to estimate the distributions of these three parameters. For T. mongolica, the average generation time is four years  of the posterior distributions were calculated from five runs data. Finally, we plotted the marginal posterior distributions of the three parameters by the LOCFIT package  was 0.840 (0.810–0.873), while the overall expected heterozygosity (HE) was 0.868 (0.832–0.882)  . Allelic2–0.882) . Inbreed2–0.882) . For the2–0.882) .K statistics output showed a clear maximum at K = 2 (Delta K = 4.98) (P(K) =  − 19,881.82)  (P(K) =  − 19,596.44) . Furthermore, no separate groups were identified in the FCA analysis  , but no ,881.82) . The ΔK  = 3.69) , with an,596.44) . These d,596.44) . Accordioss them . Besidesanalysis . Specifianalysis . The popanalysis . OverallN0 and N1 did not overlap under exponential models, which indicates that the whole population passed through a significant reduction in effective population size  was approximately 923, while the ancestral effective population size (N1) was approximately 62,214, showing an approximately 67-fold population decrease. Furthermore, the medians of the posterior distribution log T = 3.7368 , and the HO ranged from 0.213 to 0.305, with an average of 0.263 at the population level  indicates a 67-fold population decline, starting approximately 5,455 years ago, and is mirrored in similar declines for animals. For example, in Northeastern Malaysia, human-induced deforestation and habitat fragmentation resulted in a recent population collapse in orangutans, Pongo pygmaeus, approximately 210 years ago  and evolutionarily significant units (ESUs) for conservation . In thisT. mongolica populations still harbor a surprisingly rich gene pool. Furthermore, neither distinguishable genetic clusters nor population differentiation were detected among extant T. mongolica populations. Finally, a strong and recent population decline event was discovered, which was likely to have been brought about by recent human activities, and emphasizes the need for urgent conservation measures to ensure its ongoing survival.In this study, 339 individuals from eight populations were successfully genotyped at 12 nuclear loci, successfully. Based on microsatellite data, high levels of genetic diversity were revealed in this endangered species. This study implies that the wild 10.7717/peerj.5645/supp-1Supplemental Information 1Click here for additional data file.


Anadara tuberculosa , an emblematic species of the East Pacific mangrove ecosystem declined in South American countries  mainly due to overharvesting and habitat loss or degradation. Understanding the genetic aspects of geographic variations and population structure of A. tuberculosa, currently unknown, appears as a priority to fishery authorities in order to elaborate integrated and collaborative conservation policies for fishery management, aquaculture, and stock enhancement programs. We used mtDNA sequence data to investigate haplotype diversity, genetic structure, and demography of A. tuberculosa. Results indicate genetic homogeneity of populations distributed north and south of the equator, respectively. However, statistically significant differentiation emerged between northern and southern populations with pairwise фST values ranging between 0.036 and 0.092. The oceanic current system acting in the area (Panama Current and Humboldt Current) might play a role in limiting the larval dispersal of the species, still poorly understood. Demography reconstruction supported recent population expansion, possibly started after last glacial maximum. Our results would suggest separate and independent management of populations north and south of the equator.Wild populations of the pustulose ark,  Samples were collected from two sampling sites north of the equator (Colombia and Ecuador) and three south of the equator (Ecuador and Peru).At present, genetic studies of 22.1A. tuberculosa were collected in Peru: National Sanctuary Mangrove of Tumbes  in 2011; Ecuador: El Oro , Guayas , Esmeraldas  in 2015; Colombia: Tumaco  in 2016. Two hundred forty‐two individuals were sampled in total. Sample size for each sampled locality is reported in Table Samples of 2.2Total genomic DNA was individually extracted from approximately 100 mg of tissue that could be spats, gill, and mantle, using a standard CTAB protocol  index  and within‐group heterogeneity minimized . In this case, the analysis was restricted to adjacent groupings, under the implicit assumption of possible IBD. Further support was also sought by comparing pairwise FST and фST estimates.Following a different approach, different demographic models  were also investigated using Beast 2.4.5  rate (μ), usually expressed in units of percent change per million years (%/Myr). We here consider two COI lineage mutation rates (1/2 divergence rate) for marine invertebrates as proposed by Crandall et al.  who esti2.4https://earth.nullschool.net/about.html, copyright 2018 Cameron Beccario) which uses data from the program Ocean Surface Current Analyses Real‐time   ranged between 0.874  and 0.986 . Nucleotide diversity (π) ranged between 0.005  and 0.008 . The number of haplotypes and private haplotypes appeared positively and linearly correlated to sample size . Given the combined evidence provided by the two analyses, we considered assemblage B for subsequent demographic analyses.The pairwise is Table  also indr(фST) = 0.718, p(r rand >= r obs) = 0.097 and r(FST) = 0.639, p(r rand >= r obs) = 0.092.The correlation coefficients resulted from Mantel test were 3.2Genealogical relationships between haplotypes are reported in Figure 3.3фST analysis, demographic histories were investigated by considering two groups of populations: Group 1 that included Tumaco and Esmeralda, and Group 2 that comprised Guayas, El Oro, and Tumbes. In all tests, D*, F*, Fs, and D were negative, but statistical significance was observed only for D*, F*, and D for Group 2  and for Fs for both Groups 1 and 2 . For both groups, the observed mismatch distribution was more similar to the mismatch distribution expected under the population expansion model than under the constant size model . A clearer evidence of demographic expansion was shown by Group 2 (b). Bayes factors indicated the BSP as the best representation of the demographic history of Group 1, whereas the exponential model was preferred for Group 2  and nucleotide diversity (π) were comparable to or higher than values observed in other natural populations of bivalves  was more marked in Group 2 than in Group 1. Thus, although both Groups 1 and 2 showed population growth, the degree of the demographic event was more pronounced in Group 2.None of the demographic analyses performed supported constant size populations, although they depicted different scenarios for Groups 1 and 2. In fact, all class I estimated statistics showed negative values, but they were statistically significant only for Group 2. This could depend on the fact that D*, F*, and D have low power to reject the constant size model and the power of such statistics rapidly decreases with increasing of the elapsed time since the expansion event, whereas Fs, which was statistically significant for both Groups 1 and 2, performs better  and 9.4Kya (higher rate), both estimates suggesting that the event was recent. If the appropriate mutation rate is comprised between 5.3%/Myr and 0.65%/Myr, it is very likely that the demographic process may have started at the end of the Last Glacial Maximum (LGM), which is dated approximately between 19 and 20 Kya in the northern hemisphere and 14–15 Kya in the West Antarctic (Clark et al., 5A. tuberculosa. Despite the potential long‐range larval dispersal, such variation is geographically structured with populations at north and south of the equator not being completely connected. As in other bivalves, a combination of life history traits and oceanic prevalent currents may explain the pattern observed. Climatic changes occurred at the end of the LGM may be responsible for the documented demographic expansions. While awaiting for more data becomes available from other locations, we suggest separate management of populations at north and south of the equator.In conclusion, we showed a high level of genetic variation in equatorial The authors declare no competing interest.BD and VC designed the work; BD, KP, RA, and CC collected samples and contributed genetic data; GG and BD contributed data analysis; GG, BD, and VC drafted the manuscript. All authors critically revised and approved the final manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Breeding of fruit trees is hindered by their large size and long juvenile period. Genome-wide association study (GWAS) and genomic selection (GS) are promising methods for circumventing this hindrance, but preparing new large datasets for these methods may not always be practical. Here, we evaluated the potential of breeding populations evaluated routinely in breeding programs for GWAS and GS. We used a pear parental population of 86 varieties and breeding populations of 765 trees from 16 full-sib families, which were phenotyped for 18 traits and genotyped for 1,506 single nucleotide polymorphisms (SNPs). The power of GWAS and accuracy of genomic prediction were improved when we combined data from the breeding populations and the parental population. The accuracy of genomic prediction was improved further when full-sib data of the target family were available. The results suggest that phenotype data collected in breeding programs can be beneficial for GWAS and GS when they are combined with genome-wide marker data. The potential of GWAS and GS will be further extended if we can build a system for routine collection of the phenotype and marker genotype data for breeding populations. Pears, which are important fruit tree species2 in the genus Pyrus , have a juvenile period of 6–12 years1. ‘Kosui’ and ‘Hosui’, major cultivars of Japanese pear (Pyrus pyrifolia Nakai) were released 18 years after the parental cultivars were crossed3. Marker-assisted selection (MAS), especially at an early seedling stage, is a promising strategy for improving the efficiency of selection in fruit tree breeding, because it enables the selection of a large number of individuals, accelerates selection and crossing, and reduces cultivation cost. However, MAS has not been widely used in fruit tree breeding, especially in the improvement of fruit yield and quality traits, because of some technical limitations5. Bi-parental quantitative trait locus (QTL) mapping for detecting QTL-linked markers is time- and cost-consuming, especially in the preparation of an experimental population, and an expected marker effect may not be attained in a different genetic background6. An intrinsic problem of MAS is that it is not suitable for the improvement of complex traits controlled by a number of genes7.Breeding of fruit trees is a long-term process because of their long juvenile period8. GWAS enables the detection of QTLs or causal genes for a target trait without using a bi-parental segregating population9. GS enables the selection of superior individuals based on genomic estimated breeding values, which take into account the effects of multiple genes controlling a target trait10. Combining GWAS and GS with MAS will accelerate breeding cycles11 and rationalize the design of breeding programs13.High-throughput genotyping technologies have greatly reduced the cost and time of genotyping and have made a large number of markers routinely available, which enables us to use genome-wide association study (GWAS) and genomic selection (GS) to overcome the limitations of MAS14 and the accuracy of GS15 are generally improved by large datasets, preparation of such datasets is sometimes not practical because of the characteristics of fruit trees mentioned above. Routinely collected breeding population data could be useful in GWAS and GS of fruit trees and beneficial for functional plant genomics17. A previous study that used GWAS and GS for parental varieties of Japanese pear revealed the potential of these approaches12. However, the statistical power of GWAS was rather low because the phenotypic values of the varieties were characterized as ordinal categorical scores12. The full potential of GWAS and GS needs to be assessed using not only parental populations, but also continuously evaluated practical breeding populations.Although the power and resolution of GWASIn the present study, we evaluated the power of GWAS and accuracy of genomic prediction using a parental population of 86 varieties and breeding populations of 765 trees from 16 full-sib families that have been evaluated in routine breeding. Our objective was to use GWAS to find the candidate genomic regions for the fruit quality traits and to validate the optimal model for GS in the breeding populations. Finally, we discuss the potential of using breeding populations evaluated routinely in breeding programs for GWAS and GS in fruit tree breeding.r2 values and linkage map distances  than in the parental population (0.33). In contrast, the 95th percentile of r2 values between unlinked SNPs ) was higher in the parental population (0.11) than in the combined population (0.05). The patterns of LD decay were almost identical in all LGs except for LG 16  1 family, were observed in the combined population  values and/or more significant SNPs  <0.05) were detected for all the fruit quality traits in the single-locus GWAS using the combined population than in the parental population. More significant SNPs  score ≥3) were also detected in the combined population than in the parental population in the multi-locus GWAS methods. The number of significant SNPs detected in the multi-locus GWAS methods was larger than in the single-locus GWAS, and ISIS EM-BLASSO detected the largest number of the significant SNPs among the three multi-locus GWAS approaches. Significant SNPs in the single-locus GWAS were detected for five traits , and BSR2) in the parental population (Supplementary Table r) = 0.93; Supplementary Table r = −0.67). The corresponding SNP for FruC and Rust was significantly detected for both traits in the multi-locus GWAS (FASTmrEMMA). Single common significant SNPs were detected for HarT, FruW, and HeaR  and for FruC and FruD  in the single-locus GWAS using the combined population. Common significant SNPs for HarT, FruW, and HeaR, and FruC and FruD were also significantly detected in two (FASTmrEMMA and ISIS EM-BLASSO) or one (FASTmrEMMA) multi-locus GWASs, respectively , intermediate for SugC and HeaR (0.5 ≤ r < 0.7), and low for FruD and WatC (r < 0.5)  was attained even in type (i) validation.To evaluate the accuracy of genomic prediction for families in the breeding population, five types of validation were used. For eight traits except HeaR, higher prediction accuracy was attained in the combined population as a training set (type iii) than in the parental population (type i) or breeding populations as training sets (type ii) Fig. . When pr.5) Fig. . For FruAccuracy of genomic prediction was compared among 12 methods for the breeding populations. The accuracy of Random Forest exhibited large differences depending on the trait, whereas other methods exhibited smaller differences or were relatively stable among the methods Figs  and S6. r > 0.65) was observed even in MLR. The accuracy tended to be higher for MLR based on GWAS in the combined population than for MLR based on GWAS in the parental population for traits in which the power of GWAS was higher in the combined population than in the parental population. For Rust, BSR1, and BSR2, the MLR model showed high accuracy in CV using the parental population  with all SNPs outperformed multiple linear regression (MLR), with significant SNPs detected by single-locus GWAS in the combined population for all nine traits in type (v) validation Fig. . For FruFor all nine traits in type (v) validation, the prediction accuracy of the multi-kernel model, which considered both dominance and additive genetic effects, was almost the same as that of the single-kernel model, which considered only additive effects Fig. . Additivr > 0.05) than the single-trait model in CV using the parental population  validation for eight of the nine traits, the exception being FruC where the single-trait model outperformed the multi-trait model Fig. . For fru19. The resolution of GWAS and accuracy of GS depend on the pattern of LD14. In the present study, the wide range of LD in the parental population  and combined (0.34) populations were higher than the r2 value (0.2) that is necessary for accurate genomic prediction20, and were slightly higher than in other rosaceous species, apple (0.32)21 and strawberry (0.26)22.LD reflects population genetic processes, such as mutation, recombination, the mating system, and the breeding system14 and influences the accuracy of genomic prediction23. The structure in the parental population was ambiguous, which may reflect the narrow genetic background of Japanese pear cultivars24. The LD between unlinked markers was lower in the combined population than in the parental population, suggesting that adding multiple segregating families to the parental population made subpopulation structure more ambiguous. Weak subpopulation structure in the parental and combined populations may improve the resolution of GWAS and accuracy of genomic prediction.Subpopulation structure in a target population causes spurious association in GWAS25 and dairy cattle26. Meta-analysis of GWAS revealed the efficiency of combining multiple populations for pig27. The higher degree and shorter range of LD in combined populations may reduce false positives in GWAS28. Many QTLs are shared between closely related populations26 and may also increase the power of GWAS.In single- and multi-locus GWASs, more significant SNPs (FDR <0.05 or LOD score ≥3) were detected for all nine fruit quality traits in the combined population than in the parental population, thus indicating that combining data from multiple families with the data of the parental population increases GWAS power. Combining multiple populations increased GWAS power in citrus12. On LGs 3 and 15, QTLs for harvest time were detected using a bi-parental segregating population derived from ‘Akiakari’ × ‘Taihaku’29. Chen et al.30 revealed that most of the common markers for Japanese pear and Chinese pear were mapped on corresponding LGs in the same order and at similar distances. However, the associations detected in this study are inconsistent with the fruit maturity date QTL detected in a population derived from two Chinese pear varieties, ‘Bayuehong’ and ‘Dangshansuli’31. In apple, harvest time QTLs were identified on LGs 3, 9, 10, and 16 in a segregating population derived from ‘Telamon’ and ‘Braeburn’6 and on LGs 3, 10, 15, and 16 in a population derived from ‘Orin’ and ‘Akane’32. Because the level of collinearity between chromosomes of pear and apple is high33, the results in apple and in the present study strongly suggest the presence of a harvest time QTL on LG 10 of Japanese pear.SNPs detected in GWASs may be useful as markers for MAS. For HarT, significant associations in single- and multi-locus (FASTmrEMMA) GWASs were detected on LGs 3, 10, and 15, and LGs 3 and 15 of them were consistent with associations detected previouslyPPACS2) in Japanese pear29 and two ACC synthase genes (MdACS1 and MdACS3) in apple32 have been mapped previously. ACC synthase catalyses the synthesis of the ethylene precursor ACC from S-adenosyl methionine. In Japanese pear34 and apple35, ripening and fruit storage potential are closely related to the amount of ethylene produced. The QTL for HarT on LG 15 is tightly linked to the preharvest fruit drop in apple32, and a significant association for FruD was observed on LG 15 in the multi-locus GWAS (mrMLM) of this study. The significant association on LG 10 for HarT was consistent with that for FruW and HeaR, suggesting pleiotropy or close linkage among QTLs for these traits, which resulted in the high phenotypic correlation between HarT and FruW. A high genetic correlation (r > 0.7) between ripening time and fruit weight was described by Abe et al.36. In a population derived from the Chinese pear varieties ‘Bayuehong’ and ‘Dangshansuli’, one of the four QTLs for fruit weight was located on LG 1031, consistent with the presence of a QTL for FruW on LG 10 in Japanese pear.On LG 15, one 1-aminocyclopropane-1-carboxylate (ACC) synthase gene  transporters have been implicated in this trait in both pear39 and apple38. The major components of russet skin are lignin, cellulose, and hemicellulose40, and ABC transporters are involved in lignin, cutin, and suberin transport42. In Japanese pear, some ABC transporters displayed differences among russet- and green-pericarp genotypes in RNA-seq analysis39. The significant association on LG 8 for FruC was consistent with that for FruD in the single- and a multi-locus (FASTmrEMMA) GWASs using the combined population and with that for Rust in the multi-locus GWAS (FASTmrEMMA) using the parental population. The common association on LG 8 for these traits could imply pleiotropy of close linkage among QTLs controlling these traits, resulting in the high or moderate phenotypic correlations among the traits.One large significant association for FruC on LG 8 both in single- and multi-locus (FASTmrEMMA) GWASs was consistent with an association mapping study of skin russet coverage in 29. For Aci, a QTL on LG 14 detected in Japanese pear29 was consistent with the significant SNP detected in a multi-locus GWAS (ISIS EM-BLASSO), but not with the significant association on LG 6 detected in both single- and multi-locus (FASTmrEMMA and ISIS EM-BLASSO) GWASs.The largest  peak SNP detected on LG 8 was for SugC, which was significant in a multi-locus GWAS (FASTmrEMMA), and was consistent with one of the QTLs detected in Japanese pear44. Many common significant SNPs were detected in both approaches, whereas some of the significant SNPs were not consistent between the one single-locus and three multi-locus GWAS methods, as mentioned above. This suggests that a combination of single- and multi-locus GWAS methods could increase the chances of identifying of genes or QTLs that control the traits.A larger number of significant SNPs were detected in the multi-locus GWASs than in the single-locus GWAS. This implies that the multi-locus GWAS methods have larger power than the single-locus GWAS for the fruit quality traits evaluated in this study, because the traits are quantitative and are controlled by multiple, sometimes numerous, genes or QTLs. The advantage of multi-locus GWAS methods for complex traits controlled by multiple loci has been reported45. However, higher accuracies have been obtained across a population based on combining multiple populations in a training dataset than within a population when multiple populations were closely related and marker effects were the same across both populations47. Because the collection of phenotypic data is not easy in fruit trees, genomic prediction using data from multiple breeding populations will be beneficial. The validity of using multiple breeding populations for genomic prediction has been described in citrus25. In the present study, genomic prediction was most accurate when models were trained with the data from the family targeted by GS because of a close relation between training and test sets and accurate estimation of marker effects.In genomic prediction for the breeding population, training with the combined population attained higher prediction accuracy than training with the parental population or the breeding populations only. The result may imply that the parental and breeding populations are closely related to each other and that marker effects are almost the same across populations. In general, genomic prediction across populations that are of low relevance has lower accuracy than genomic prediction within a population, as discussed in an apple studyet al.48. Random Forest is a machine learning method that can be effective in capturing large-effect QTLs49 and their interactions48. In rice, Random Forest was the best-performing model among GS methods for flowering time, in which a single large-effect QTL on Chr. 3 was identified by GWAS50. In our present study, GWAS detected a highly significant association on LG 8. As in a study by Spindel et al.49, the highly significant association may cause the superiority of Random Forest for FruC. On the other hand, Random Forest was not the best model for FruC in seven individual families, in which phenotypic variance was biased toward smooth green or red russet skin, and/or no polymorphism was observed in the most significant SNP. The result implies that the most significant SNP for FruC mainly explained the difference between green and red skin, but not variation within each colour. MLR with the most significant SNP also showed high prediction accuracy for FruC in the breeding populations, suggesting that traditional MAS with a marker for the significant SNP is useful in this trait. Because MLR with the most significant SNP was also accurate for Rust, BSR1, BSR2, and FruC in the parental population, traditional MAS may also be useful for these traits, especially for selection of parents.Among the 12 methods for single-trait genomic prediction, Random Forest performed best for FruC in evaluation based on all families, whereas the accuracy of other methods showed small differences or were relatively stable among the methods. The mean of 11 methods always exhibited an upper-middle level of accuracy among the methods for all traits. This suggests that Random Forest is an appropriate method for FruC, whereas the mean of the methods exhibiting stable accuracy would be more suitable for the other traits, although the best method varies depending on the traits. The stability of the mean of all methods compared was also shown by Onogi Eucalyptus breeding51, inclusion of dominance effects improved the prediction of the total genotypic values in specific situations where the dominance-to-additive variance ratio (≥0.5) and broad-sense heritability (0.6) were high. As suggested by Zhao et al.52 and Denis and Bouvet51, a small population size might also reduce the benefit from a model considering dominance effects. Moreover, additive variance in the additive model tends to capture non-additive variation53, as experimentally confirmed54. This could also be a reason why the dominance model did not increase the accuracy of genomic prediction. In contrast, for Appear the multi-kernel model was more accurate than the single-kernel model. Dominance variance in Appear was predominant in the parental population. The result suggests that the dominance effect should be taken into account in the selection for Appear.For all nine traits, little difference was observed between the multi-kernel model considering dominance and additive genetic effects and the single-kernel model considering only additive effects. The result implies that the additive model was sufficient to explain genetic variation in the population, or the model that considers dominance and additive genetic effects could not be beneficial because of small dominance variation. In a study simulating 56. A few missing values of phenotypes in a combined population can result in almost the same performance of these two models. In CV using the parental population, the prediction accuracy of multi-trait models was higher than that of the single-trait models for FruS and SpuN. The rate of missing values for FruS was comparatively high , which included 33 modern, 19 old, and 16 indigenous cultivars, and 16 breeding lines, of which 74 varieties were identical to those used in our previous study12, and 2 indigenous cultivars of Chinese pear (P. ×bretschneideri Rehd.)  were evaluated , and 768 SNPs in the remaining nine families. SNPs were genotyped by using a custom-designed SNP array for Illumina GoldenGate Genotyping Assay (Illumina Inc.)  between pairs of 563 SNPs that were mapped on the genetic linkage map . The r2 values between pairs of unlinked markers were also calculated.Squared correlation coefficients  scores of the breeding populations were calculated based on the eigen vectors obtained in the PCA of the parental population to locate the breeding populations in the PCA space of the parental population.The genetic structure in the parental population was estimated using hierarchical clustering and PCA. Hierarchical clustering based on Ward’s method63 implemented in the “GWA” function of the R package rrBLUP ver. 4.064. To avoid spurious associations due to population structure, a kinship matrix and the scores of the first four PCs were included in the MLM as random and fixed effects, respectively. The kinship matrix was computed using the “A.mat” function of the R package rrBLUP. The optimal number of PCs was determined by estimating the variances of PC scores. The variance of PC score decreased rapidly until PC4 and only gradually thereafter  were also conducted using the R package mrMLM ver. 3.044. The kinship matrix used in the single-locus GWAS was also used in the three multi-locus GWAS methods. The significant associated SNPs were determined by the critical threshold of LOD score ≥3 as described in Tamba et al.66, Wang et al.44, and Wen et al.65.Single-locus GWAS was conducted using an MLMet al.25. The prediction accuracy of the models was cross-validated as described below.To evaluate the accuracy of genomic prediction on a single-trait basis, we used 12 methods: genomic best linear unbiased prediction (GBLUP) with ridge kernel regression (RR) or Gaussian kernel regression (GAUSS), Random Forest, Ridge Regression, Lasso, Elastic Net, Bayesian Ridge Regression, Bayesian Lasso, BayesA, BayesB, BayesC, and the mean prediction of all the above methods. Prediction models based on the 12 methods were built as described by Minamikawa 10(p) values for each trait were entered in single-trait-targeted MLR of the R function “lm”68 unless the squared correlation coefficient between the SNPs was ≥0.6 (to prevent multicollinearity). In general, one or few markers are used for MAS to improve traits controlled by a small number of major genes and/or large QTLs. The prediction accuracies of the models were compared to that of GBLUP (RR), which treats all SNPs.To evaluate the potential of MAS based on SNPs detected in GWAS with the parental or combined population without genotypes targeted by genomic prediction, the top one, two, or three peak SNPs with high −loget al.25. Both are single-trait models and are implemented in the R package of BGLR ver. 1.0.369. The additive (h2) of each trait was computed as the ratio of To evaluate the importance of dominance effects on genomic prediction, a multi-kernel model (considering both additive and dominance effects) was compared with a single-kernel model (considering only additive effects), as described by Minamikawa 70. We also used the R package glmnet ver. 2.0–10 for three different linear regression-based multi-response Gaussian family methods: Ridge Regression , Lasso , and Elastic Net 71.To evaluate the accuracy of genomic prediction on a multi-trait basis, we employed four methods, which took genetic correlations among traits into account, and compared their accuracy with that of the methods based on a single trait. A Bayesian multivariate mixed model fitted via variational Bayes named PHENIX was tested by using the R package phenix ver. 1.01 genotypes), and (v) 10-fold CV with the combined data from (iii) and (iv). The CVs in types (iv) and (v) were repeated 3 times, and the identical pattern of folds  was adapted to all prediction models in each CV. The 10-fold CV repeated 5 times was also conducted to evaluate the accuracy of genomic prediction in the parental population, because nine traits were evaluated only in that population  between observed and predicted genotypic values. When estimated r was less than 0, it was regarded as 0. The prediction accuracy for each family and for the combination of all families was calculated. Root-mean squared errors between the observed and predicted values were also calculated for comparing the prediction accuracy among the families, because the magnitude of segregated variation differed considerably among the families  training with the parental population, (ii) training with the breeding populations excluding the target family, (iii) training with the combined population  excluding the target family, (iv) 10-fold cross-validation (CV) with the target family (only for family 540; leave-one-out CV was performed because of a few FSupplementary informationSupplementary data


Mustela erminea), a Holarctic mammalian carnivore, using whole-genome sequences. We identify two spatio-temporally distinct episodes of introgression coincident with large-scale climatic shifts: contemporary introgression in a mainland contact zone and ancient contact ~200 km south of the contemporary zone, in the archipelagos along North America’s North Pacific Coast. Repeated episodes of gene flow highlight the central role of cyclic climates in structuring high-latitude diversity, through refugial divergence and introgressive hybridization. When introgression is followed by allopatric isolation  it may ultimately expedite divergence.At high latitudes, climatic shifts hypothetically initiate recurrent episodes of divergence by isolating populations in glacial refugia—ice-free regions that enable terrestrial species persistence. Upon glacial recession, populations subsequently expand and often come into contact with other independently diverging populations, resulting in gene flow. To understand how recurrent periods of isolation and contact may have impacted evolution at high latitudes, we investigated introgression dynamics in the stoat ( Mustela erminea) from four regions of glacial refugia. They find evidence for two past introgressive events between lineages that coincide with interglacial periods, a pattern that may extend to other high–latitude species.Jocelyn Colella et al. report whole-genome sequences of 10 stoats ( Three primary macro-refugial locations are hypothesized to have enabled the persistence of temperate terrestrial North American species through Pleistocene glacial cycles . These include an expansive Northern Beringian refugium shared with Asia4 and two Southern refugia, separated into East and West by the Rocky Mountains or Great Plains/Mississippi drainage6. A fourth, smaller refugium (or series of refugia), hypothesized to exist on areas of exposed continental shelf during the last glacial maximum near contemporary North Pacific Coastal archipelagos10, may have provided another isolated sanctuary for long-term coastal persistence of terrestrial species. Although this refugium has received varying degrees of empirical support, its existence is critical to understanding dynamics of intercontinental biotic exchange and it may have played a primary role in the early peopling of the Americas11.Glacial refugia are fragmented pockets of unglaciated land where terrestrial species have persisted and diverged through ice ages, and which have significantly structured biological diversity at high latitudesMustela erminea, the stoat or ermine (Family: Mustelidae) delineates four genetically distinct mitochondrial lineages geographically corresponding to these four refugia12. Although glacial isolation appears to have impacted the long-term evolution of this mammalian meso-carnivore, the effects of glacial recession and subsequent secondary contact between refugial lineages remain unexplored. Therefore, we investigated the consequences of cyclic climates and pulsed introgression on genomic diversity in this circumboreal species complex. During inter-glacial warming, divergent lineages expanded from refugial centers until they reached environmental or biological barriers13. In some cases, admixture occurred upon secondary contact with other lineages. If M. erminea experienced serial bouts of climate-mediated introgression, a repeated signature of introgressive hybridization should be evident in the genomes of refugial descendants14.Phylogeography of high-latitude 15 now being explored on a genomic scale. We define introgressive hybridization as interbreeding and the movement of alleles between two genetically distinct lineages. Although often difficult to parse introgression from incomplete lineage sorting in closely related taxa or lineages16, investigations of divergent lineages, such as those within the M. erminea complex, provide insight into the genomic consequences of introgression. For example, genetic swamping or homogenization can prevent divergence between mixing lineages, while Bateson–Dobzhansky–Muller19 and mitonuclear20 incompatibilities can lead to hybrid breakdown, thereby promoting divergence through reinforcement22. Although our understanding of hybridization emerges largely from research on plants24, the genomic era has uncovered substantial reticulate evolution  in a growing number of animal species26, including humans27. As histories of divergence and speciation-with-gene flow continue to be discovered , the implications of hybridization for the conservation of evolutionarily distinct units appear profound30.Contact zones are windows into evolutionary processesTo test whether genomic structure in stoats reflects refugial origins and to explore the consequences of contact among lineages, we generated ten whole-genome sequences of representatives from each refugial clade. With expanded genomic coverage, we test for signatures of refugial divergence and introgression, characterize the timing of introgression events relative to climatic oscillations, and infer the impact of introgressive hybridization on divergence across the complex landscape of northwestern North America.M. erminea drawn from each refugial lineage and two spatially disjunct contact zones , and used ADMIXTURE33 analyses to define populations.To test our hypothesis that the four mitochondrial stoat lineages originated as the result of isolation and divergence in each of the four major North American refugia, we generated whole-genome sequences for ten 12 , calling into question whether this widespread mustelid is a single species (Supplementary Table 34 and black bears35). Additional structure within the East clade , which can indicate a history of genomic introgression or incomplete lineage sorting. ADMIXTURE identified the same two individuals as admixed between East  and Beringia  clades or as a single, but distinct population, consistent with shared source populations Fig. . Both Al12; therefore, we suspect they are derived from an ancient hybridization event that occurred during an earlier interglacial period, prior to the contemporary insularization of this clade. We found no evidence of admixture, however, in the Kupreanof Island sample.Surprisingly, NPC Island stoats also tested positive for admixture, with Beringia-East parentage Table  and b. TF4-statistics, similar to D-statistics44 and ABBA/BABA45, to highlight differential backcrossing histories among lineages and used admixture graph fitting46 to estimate the topological placement of admixed samples relative to their potential sources.Biased or asymmetric introgression may indicate a selective advantage, the existence of genetic incompatibilities, or a demographic imbalance. Alternatively, equal contributions from both parental source populations may suggest that there are minimal genetic incompatibilities between hybridizing stoat clades, as we would expect within a single species. For the NPC Island clade, biased allelic overlap with one source population may shed light on interglacial colonization dynamics, as the island may have been colonized by both Beringia and East ancestors who subsequently interbred. We used f4 results highlight the influence of repeated glaciation in North America as reflected in multiple episodes of gene flow between lineages originating in independent refugia. Allele sharing (f4) reflected phylogenetic relationships, with stepwise genetic distance from the ancestral Beringia clade increasing with greater geographic distance from Beringia , reflecting substantial intra-specific divergence within M. erminea. Biased allelic overlap suggested that YTAK shares more alleles with the East source, whereas SYT is more backcrossed with the Beringia source , drift, or demographic parameters. If gene flow is neutral, extended periods of contact may promote fusion between East and Beringian lineages. However, the contemporary persistence of both Old World Beringian and New World East lineages in North America suggests that gene flow during brief periods of interglacial contact through the Pleistocene were insufficient to homogenize refugial divergence.Admixture graph fitting identified SYT as the result of Beringia and East admixture, while YTAK was produced from an ancestral admixture event between East and a shared ancestor of all stoat lineages Fig. . The vasce Table . DiffereBiased allele sharing between NPC and Beringia Table  is consi49, the current geographic isolation of the NPC Island clade, and the limited dispersal abilities of insular M. erminea50, we suspect that hybridization is not ongoing on NPC islands. In contrast, based on the current distribution of mitochondrial diversity12 and our understanding of postglacial population expansion, we expect that stoats from East and Beringia clades are actively interbreeding along the Alaska-Yukon border. To approximate the timing of admixture events, we converted drift unit branch lengths (D), output from MixMapper51, to absolute time (years) using the formula D ≈ 1−e−t/2Ne(solved for t generations)52.Given the pattern of North American glaciation54) and Sangamonian interglacial (80–140kya54). The weaker NPC hybrid signal relative to contemporary Alaska-Yukon hybrids (f3Z-score), the insular isolation of this clade for at least the past 10,000 years55, and the short generation time of stoats (2 years56) suggest that NPC Island admixture is more ancient than that occurring in the mainland Alaska-Yukon zone. We hypothesize that the hybrid origin of the NPC clade predated a period of glaciation and refugial isolation, but this point requires further exploration with expanded sampling and tests of linkage disequilibrium. If NPC stoats continue to evolve in isolation, our results suggest that continued divergence in allopatry may ultimately lead to speciation.The estimated time of admixture for Alaska-Yukon hybrids did not differ from zero Table , suggest12 suggests that island founder effects or a bottleneck5 occurred among NPC stoats in the coastal refugium57. Drift may impact small populations and may have further accelerated NPC stoat differentiation.Based on our results, NPC islands were colonized either by admixed individuals or independent invasions of both parental lineages  that subsequently hybridized. Introgressive hybridization, preceding divergence in isolation, may have disproportionately elevated the evolutionary distance between NPC Island stoats and other lineages Figs. –4. IsolaNe), with a distribution most similar to that of their most-backcrossed source population . Last, we expected cladogenesis to coincide with refugial isolation during glacial periods and demographic troughs, while Ne is expected to rise during interglacials as a consequence of population expansion.We expected glacial cycling (periods of isolation/contact) to have impacted the historical demography of each refugial stoat clade differentially. Further, we hypothesized that individuals with a history of introgression will exhibit elevated effective population sizes  and felid61  genomes.Combined with diversity metrics  may be ephemeral64. The narrow Alaska-Yukon hybrid zone and strong East-Beringia genomic differentiation, however, suggests that such peripheral hybrid populations are ephemeral and minimally contribute to long-term evolution of high latitude diversity. If introgression events are temporary, genomic evidence of serial hybridization offers a model for detecting refugia and tracking colonization routes among high latitude species. Here, we provide yet another example of introgressive hybridization in mammals, highlighting both the prevalence and varied role of introgression in mammalian evolution. Our results demonstrate that, for geographically widespread species, the long-term evolutionary role of introgression often may be inconsequential relative to larger biogeographical processes, such as island vicariance, refugial isolation, or rapid environmental change.When backcrossing occurs into both parental populations, as in the Alaska-Yukon hybrid zone, introgression may be stochastic or selectively neutral. Consequently, extended periods of contact may lead to homogenization65. Even a temporary reduction in fitness can enable traversal between fitness-landscape optima and promulgate alternative evolutionary trajectories, which can permanently impact the genomic structure of high latitude populations and potentially lead to speciation66. Genomic evidence of hybridization, followed by divergence in geographic isolation, is consistent with a hybrid origin for the NPC lineage. Though still incipient in this case, the process of introgression followed by allopatry may lead to hybrid speciation67. Hybridization can catalyze the evolution of reproductive barriers68 or expedite divergence through the rapid generation of novel genetic recombinants. Although the mechanisms underlying this special case of divergence with gene flow remain elusive, a plausible precondition for speciation is the separation of lineages into allopatric ranges, which may enhance the genetic divergence of a recombinant population, even if introgression is not directly implicated in speciation. Therefore, NPC stoats potentially highlight the integral role of post-hybridization allopatric divergence in the evolutionary histories of island and refugial taxa, but expanded insular sampling is required to fully test this mechanism of divergence.In some situations, however, a population bottleneck in a small refugium or in response to insularization can enable the temporary persistence of less fit recombinant genotypes20, although this idea is not without controversy. Under this scenario, hybridization between incipient species can result in unfit hybrids and natural selection might act against hybridization, reinforcing pre-zygotic isolation mechanisms, eventually leading to speciation and avoiding maladaptive hybridization69. In this fashion, continuing and progressive reinforcement of pre-zygotic mechanisms would ultimately result in speciation and complete isolation between lineages70, if hybridization and selective pressures on both lineages are symmetrical71. With an active and plausibly ongoing hybrid zone, along with more ancient island admixture, stoats provide a unique opportunity to investigate the impact of symmetrical versus asymmetrical introgression using genomics.It has long been argued that pre-zygotic isolation is reinforced when diverging groups return to parapatry and hybridize72. In this parallel system, the English Channel separating Britain from the European mainland has been serially exposed through Pleistocene glacial cycles73, effectively homogenizing populations across the Channel. On the other hand, the Irish Sea, nearly twice the depth of the English Channel, further separates Ireland from Britain, presenting a formidable barrier to gene flow that allowed only occasional influx of novel alleles from mainland or British immigrants during extreme glacial events. This mechanism of post-hybridization allopatric divergence is not restricted to land bridge or continental archipelagos. Oceanic island populations of Darwin’s storied finches on the Galapagos Islands also were impacted by climate-mediated pulsed hybridization that was coincident with changes in sea level due to glaciation74.With multiple waves of mainland colonizers corresponding to climatic cycles and potentially adding novel genetic elements to insular genomic architectures, the process of repeated, climate-mediated hybridization may have played a role in diversification across other land-bridge island systems. Irish stoats, for example, exhibit elevated genetic diversity compared to neighboring populations in Great Britain, despite persisting on a smaller island farther from a continental sourceM. e. haidarum) poses a particular challenge for the U.S. Endangered Species Act, which currently denies protection for hybrid taxa75. Mustela erminea haidarum is federally protected in Canada on the Haida Gwaii Islands of British Columbia56, but also occurs on Prince of Wales Island, Alaska, where it has no protection. This study is congruent with previous work noting that this island-restricted stoat subspecies is genetically76 and morphologically77 distinctive, but levels of management protection at the federal level differ profoundly between Canada and the United States.Admixture in this insular endemic  within a single species complex, highlighting the multifaceted role of introgression in mammalian evolution and the varied temporal and geographic scales at which this process unfolds. At high latitudes, where dramatic range shifts in response to glacial cycling afforded recurring opportunities for contact and isolation, ephemeral hybridization has repeatedly shaped biological diversity12. Ten whole-genome sequences for representatives from each refugial stoat clade, and with additional sampling in suspected contact zones ). Quality scales were compared across samples and rescaled to Illumina 1.8 + phred + 33 quality score, when necessary, to maintain consistency . Reads were mapped to the domestic ferret genome83 (Mustela putorius furo) using the Burrows-Wheeler aligner84 (BWA). An additional BWA iteration extracted mitochondrial genomes. Final depth of coverage ranged from 10 to 61× (Supplementary Table 85 (GATK) for all stoats and again against each of two outgroups (M. putorius and Martes americana) and filtered by minimum depth (minDP = 2), genotype quality (minGQ = 30), minimum minor allele frequency (MAF = 0.1), and scaffold size and location (1 Mb), and then private alleles and indels were removed using VCFtools86 (Supplementary Table f-statistics) to identify introgression and backcrossing histories, therefore singletons, since they are not shared, do not provide information about allelic overlap among populations. Our minDP (2) was set as one-third of the coverage of our lowest coverage samples  as recommended by the PSMC manual. Also, 2 is the minimum requirement for detecting heterozygotes. Format conversions  were conducted using PLINK87. Missing data were removed (--max-missing) based on analysis specifications. SNPs were spaced (1 per 50 bp window) to account for linkage disequilibrium  and sorted into 46 ‘pseudo-chromosomes’ to enable the application of human-specific analyses on a non-model system with 40 chromosomes.Contact zones and populations were defined based on expanded mitochondrial samplingnes Fig. . Liver s89 estimated the most appropriate model of evolution for mitochondrial genomes and autosomal SNPs, with and without outgroup sequences (M. putorius and Martes americana). We generated phylogenies for the entire mitochondrial genome  and autosomal nuclear SNPs  using RAxML90  and Beast291 . It should be noted that phylogeny inference using highly variable data  can induce acquisition bias resulting in longer branch lengths92, however, other divergence metrics  provide additional evidence of substantial divergence between refugial stoat clades. The oldest known M. erminea fossil93 (1.8 My) was used as a log-normal fossil calibration  to estimate divergence times in Beast2 . A log-normal distribution places the highest probability on ages that are somewhat older than the fossil date, with non-zero probability to infinity. Log-normal distributional priors were selected to place 1.8 Mya at the median and shape priors encompassed late Pliocene to early Pleistocene, similar to Harding and Smith94. Fossil-calibrated divergence estimates separate two pairs of stoat clades (Beringia-NPC and East–West) at 4.47 Mya , with the Beringia-NPC split dated within the early Pleistocene at 2.1 Mya (±0.6 My), over 1 million years before East–West cladogenesis .jModeltest95. To accommodate genetic exchange between populations of the same species, TreeMix uses genome-wide allele frequency data to infer historical relationships among populations to maximize the composite likelihood of the sample covariance matrix (What), while modeling both cladogenesis and migration. TreeMix iterates over a standard bifurcating topology to identify a series of migration edges that most increase the likelihood score. TreeMix was run without default sample size corrections (-noss), because multiple populations were comprised of a single individual. We limited the number of migration events (-m) to three, to examine only the most influential events among the few groups examined. TreeMix simulations with M. putorius as the outgroup identified ancient geneflow between Beringia stoat ancestors and M. putorius. Simulations were re-run with M. americana as an outgroup to assess whether long-branch attraction between distantly diverged M. erminea and M. americana (>11Mya96) impacts migration inference in TreeMix, but results were consistent, regardless of the outgroup used. After TreeMix identified gene flow between M. erminea and M. putorius  among populations97. Diversity statistics  score identified the most appropriate number of populations (K = 6) by iteratively leaving a sample out and reexamining the partitioning of genetic structure among the remaining samples.PCAs were generated in SNPrelateF-statistics were run in AdmixTools41 and MixMapper51 using M. americana as an outgroup after TreeMix identified ancient gene flow between M. erminea and M. putorius ] quantify drift through summary statistics , with larger values indicating greater divergence42 (Supplementary Table f2 statistics were generated from the compute_moment_stats and compute_most_additive_trees functions in MixMapper with 1000 bootstraps and SNP blocks of 50 (1 per 50 bp). f3-statistics explicitly test for admixture  and considered all permutations where Source1, Source2, and the Target samples came from different populations. Populations  were defined by phylogenetic relationships ). We also compared hybrid individuals (as identified by f3-statistics) against individuals from ‘pure’ populations ) and admixed populations ) to decipher the backcrossing histories of hybrid samples and characterize patterns of gene flow across populations. f4-statistics are negative (Z-score ≤−5) if there is more allelic overlap between X and Y than between X and Z since the evolutionary split between Y and Z, and positive (Z-score ≥5) if there has been more recent gene flow between X and Z than between X and Y. f4 results are in Table 12Ne Model 2 using multi-locus Approximate Bayesian Computation approximates mean clade Ne at: 250k for Beringia, 50k for NPC, 125k for East, and 75k for West; therefore, the combined Ne for NPC, East, and Beringia populations is 375k. D is tightly correlated with Ne and additional efforts to refine historical population sizes  should improve the resolution of our admixture date estimates. Generational output was converted to years using a M. erminea generation time of 2 years56.To parse the backcrossing history of each hybrid sample, 58 was used on consensus genomic sequence data (using both complete and down-sampled sequence data) to characterize historical demography  and stoat generation time, resulting in distributions of Ne through time ).PSMCphy Fig.  by examiime Fig. . One hunhttps://github.com/jpcolella/Ermine_WGS_2018.Our custom python spacing script is available on GitHub at Genomic reads are available in NCBI’s Sequence Read Archive, accession: SRP138989. Assembled FASTA files are available on Dryad (10.5061/dryad.bv2g720).Supplementary Information