Chlamydotis macqueenii) breeding populations . Adults from the eastern population migrated twice as far (mean = 1184 km ± 44 s.e.) as the western population (656 km ± 183 s.e.) and showed significantly less variation in migration distance than the central population (1030 km ± 127 s.e.). The western and central populations wintered significantly further north  and the central population further west (−3.47° E ± 1.46 s.e.) than individuals from the eastern population. These differences could arise from a differing innate drive, or through learnt facultative responses to topography, filtered by survival. Translocated birds from the eastern population  migrated further than adults from either western or central recipient populations, particularly in their second migration year. Translocated birds continued migrating south past suitable wintering grounds used by the recipient populations despite having to negotiate mountain obstacles. Together, this suggests a considerable conserved heritable migratory component with local adaptation at a fine geographic scale. Surviving translocated individuals returned to their release site, suggesting that continued translocations would lead to introgression of the heritable component and risk altering recipient migration patterns. Conservation biologists considering translocation interventions for migratory populations should evaluate potential genetic components of migratory behaviour.Maintaining appropriate migratory strategies is important in conservation; however, translocations of migratory animals may alter locally evolved migration behaviours of recipient populations if these are different and heritable. We used satellite telemetry and experimental translocation to quantify differences and assess heritability in migration behaviours between three migratory Asian houbara ( Conseex situ management and release [Migratory species from all vertebrate groups are threatened ,17, with release ,7,22, bu release ,23. Nove release ,25; part release  or produ release ) relativ release  and pote release . ConservChlamydotis macqueenii) as a model system, examining populations along a longitudinal gradient within the Central Asian deserts. The species undertakes long-distance migrations and is subject to large-scale captive breeding and release programmes to reinforce threatened migratory populations throughout its range [To explore the importance of genetic origin for reinforcement initiatives involving migratory species, we used the migratory Asian houbara , which initially migrate south over the Ustyurt Plateau, then southwest to west crossing the Kopet Dag mountains, which do not appear to act as a barrier to their migration [Within Uzbekistan we examined a west–east longitudinal range: from the ‘western’ population in the Ustyurt Plateau  located towards the species' southwestern range limit; a ‘central’ population separated by the Aral Sea basin  and lyinigration ,33, to w2.2.Wild breeding adults were captured during the breeding season and fitted with back-mounted solar-powered satellite transmitters (PTTs) programmed to record 5 (30 g PTT) or 12 (45 g PTT) GPS locations per day . Transmitters weighing less than 3% of bird body mass are considered to have no detrimental effect on houbara  and do nFor head-starting and translocation, 11 wild clutches were collected from the eastern population  in spring 2017, artificially incubated and hand-reared in captivity . Twelve individuals  were randomly assigned to the central and western populations (six each): three mothers each contributed two chicks, of which one sibling was allocated to each treatment; the remaining individuals were each from different mothers. Translocated birds were released at six months old in mid-September  and wouMigration strategy can be age-related in birds  and a co2.3.We focused analyses on migration traits considered likely to be under genetic control (and hence conserved): initial orientation during the first migration step (hereafter ‘first-step bearing’); departure date from the post-breeding grounds; bearing from post-breeding area to wintering-site; wintering-site latitude and longitude; migratory distance (the straight-line displacement from post-breeding to wintering-site); wintering-site fidelity; and fidelity after return migration to breeding/release site ,32,37. WMigration metrics were compared between the three populations using generalized linear mixed models (GLMMs), incorporating individual identity as a random effect. We considered the effect of population identity to be supported if incorporating that term reduced the Akaike's information criterion adjusted for small sample size (AICc) value by ≥2 units relative to the null model , and subF-tests , controlling for experiment-wide error by a Bonferroni procedure. In all tests, p < 0.05 was interpreted as a significant difference, and p < 0.1 as marginally different . Translocated groups were qualitatively compared to data for wild groups owing to small sample sizes.The variance of each migration metric was compared between populations using pairwise Analyses considered both males and females from the eastern population, but only males from the central and western populations as it was not possible to trap females in these areas. Previous analysis found no difference between male and female adult houbara for first-step bearing, departure date, migration distance, wintering latitude, or breeding-site fidelity ,33. Howe3.F-test results can be found in electronic supplementary material, appendix S2.Model selection tables and 3.1.a,b), in terms of both first-step bearing  and wintering-site bearing . Variance in first-step and wintering-site bearings was also similar between populations . Departure day from the post-breeding areas did not differ between populations  and variance in departure date was similar across populations . However, populations differed in wintering latitude , with individuals from the eastern population wintering further south (mean latitude = 30.17° ± 0.41 s.e.) than those from the central  and western  populations, and western individuals marginally  further north of those from the central population (figures 2e). Overall migration distance also differed between populations . Adults from the eastern population migrated nearly twice as far  as those from the western population  but had similar variance . Adults from the central population migrated an intermediate distance (1030 km ± 127 s.e.) that did not differ significantly from either the western  or eastern  populations but with significantly greater variance than eastern individuals . Populations also differed in wintering longitude , with individuals from the central population (mean longitude = 56.40° ± 1.42 s.e.) wintering significantly further west  and the small sample of western birds (55.45° ± 2.08 s.e.) marginally further west  than those from the eastern population (59.87° ± 0.50 s.e.). The variance in wintering latitude (figure 2e) of individuals from the central population was marginally greater than those from the eastern population , but other pairwise comparisons of wintering latitude variance did not differ  and the variance in wintering longitudes was similar across the populations . One male from the larger sample of eastern individuals undertook an anomalous migration, moving northwest to winter in Kazakhstan on the Caspian Sea  and was fine-grained compared to both the scale of habitat extent within wintering ranges and the distances travelled during outward migration . Within-population variance in wintering-site fidelity  was also similar between populations . Breeding-site fidelity was similar across populations . Across all three populations, the 20 wild adult males returned to their display areas, but two of the 33 eastern females changed breeding site between years by greater than 200 km (figure 2h). The variance in breeding-site fidelity was similar across populations . Results were unchanged when the eastern sample was restricted to males.Wintering-site fidelity, the mean distance between successive annual wintering sites, was similar across individuals from all three populations . Of the five individuals that initiated migration, four survived to reach a wintering location (according to criteria of stop-over duration), and two (one from each recipient population) completed return migration in spring 2018 and migrated again the following winter  but subsd,e). Their first-winter outward routes showed an apparent mix of conserved orientation and facultative response to the Kopet Dag. One individual encountered the mountains but did not cross and turned back north to remain and winter in Turkmenistan  than wild adults from the recipient population d,e. TheiOf the two eastern birds translocated into the central population that survived to migrate, one  wintered in Turkmenistan and survived to the following March. The second reached a site in Iran further south (29.72° N) than the central population mean (34.36° N), again showing an initial deflection by the mountains, but on its second autumn migration it followed a more direct route (similar to its previous return path) that avoided the Kopet Dag and brought it to the southern coast of Iran , before it turned north and died.Both surviving translocated birds  showed fidelity to their release areas, initially returning to within 11.9 and 38.8 km, respectively ; after i4.n = 5), migratory behaviour of experimentally translocated birds indicated a potentially considerable heritable component to the differing migration strategies. This would signify finer-scale adaptation than suggested for Asian houbara by neutral genetic markers [Three wild breeding populations across a longitudinal gradient spanning only 640 km (14% of the 4460 km breeding range of migratory Asian houbara) had similar timing and orientation but differed in migratory distance and wintering latitude. Such differences in adult strategy could result from innate differences, learnt facultative responses to region-specific topography and environment along potential routes, or differential survival filtering out first year birds following sampling . However markers  or broad markers ,33.Translocated birds showed a clear drive to continue migrating south similar to their source population and migrated further than individuals from their recipient populations, which is strongly indicative of an inherited and innate migration trait. The heritability of migration distance is also supported given that translocated birds continued to fly south despite (i) passing suitable wintering sites used by the recipient population, (ii) the time and energy required to negotiate the Kopet Dag mountain barriers, and (iii) the expected weaker physical condition of captive-bred juveniles relative to wild adults . FurtherThe most probable mechanisms for innate control of migration distance are the duration of migratory activity and/or an innate latitudinal cue to settle . It is nTranslocated birds showed strong fidelity to release sites, allowing them to integrate with and reinforce the recipient population. Consequently, genotypes of translocated individuals are likely to introgress into recipient populations. Where released genotypes are even slightly less fit, supplementation can reduce population sizes and genetic diversity over the long term . Large-sCurrently, there is no agreement in the Convention on Migratory Species or between range states on sustainable management and translocation strategies for this heavily hunted migratory species, with multiple stakeholders releasing birds throughout its range . There aWhere migratory behaviour is known or suspected to be heritable, translocations should respect the fine-scale geographical structure of source and recipient populations. When this is not feasible , trial releases should be undertaken to assess both the potential differences between source and recipient populations and the effectiveness of further releases. The evidence presented here indicates the vital importance of experimental studies to evaluate the migratory behaviour of translocated individuals before scaling up interventions to a conservation reinforcement.


Toona ciliata Roem subsequently develop into functionally unisexual flowers and their relative positions in the same inflorescence could enhance the outcrossing system in this species. Here we investigated the mating system of this species. We used eight nuclear microsatellite markers and investigated the progeny of 125 mother trees from six populations naturally distributed in South China, with sample sizes ranging from 64 to 300 seeds. The multilocus outcrossing rate was 0.970 ± 0.063, and the single locus outcrossing rate was 0.859 ± 0.106, indicating the pattern of predominant outcrossing. Selfing was present in one population, but biparental inbreeding occurred in five populations. Inbreeding was absent in maternal parents, and correlations of selfing among families or among loci were generally insignificant. Positive correlation of paternity at multiple loci was significant in four populations, but was not consistent with the results at single loci. Population substructure occurred in male similarity between outcrosses only in one population. Population genetic differentaitaion was significant (Fst = 34.5%) and the effects of isolation-by-distance at the eight loci were significant among the six populations. These results provide evidence that self-comptability and inbreeding naturally occur in T. ciliata and indicate that inbreeding avoidance is necessary during genetic improvement and breeding of this endangered tree species.Most initially perfect flowers of  Toona ciliata Roem (Meliaceae) is characterized by flowers of about 5 mm long. There are short pedicels of 1–2 mm long, five short calyxes, five white and oblong petals each 4–5 mm long, five stamens that are about as long as the petals, filaments that are sparsely pilose, elliptic anthers, an ovary that is densely covered with long hard hairs and contains 8–10 ovules per locule, a glabrous style, and discoid stigmas with five fine lines1. The flowers in the bud stage are perfect and hermaphrodite in the family of Meliaceae. Owing to the effects of unknown genetic or environmental factors, most floral development exhibits functionally male or female floewers although both anthers and pistils are present in each flower3. Sterile ovaries in functionally male flowers are formed and would not develop further. Stamens with anthers in functionally female flowers seem not to produce fertile pollen. This is an alternative to those patterns that avoid selfing and inbreeding by forming sexually diecious plants or employing self-incompatible genes. However, it is not clear whether such floral development is ubiquitous or not in genus Toona and other genera  of the Meliaceae2, and the flowers that remain perfect cannot be excluded. The functionally male and female flowers are disproportionally mixed and distributed in different positions in the same inflorescence. The central flower in a cymule is female while the lateral flowers are male3. Most individuals are sexually monoecious rather than dioecious. Thus, it is of interest to clarify the uncertainty of the mating system that T. ciliata possesses.The flower structure of 4. Based on the provenance populations of mixed seeds from multiple indidvisuals, the estimate of inbreeding coefficients was generally negative (Fis < 0), implying an outcrossing system under an equilibrium between selfing and outcrossing where the outcrossing rate is 5. However, more accurate estimate of the outcrossing rate or the selfing rate (α = 1 − t) remains lacking based on the pedigree of famility structure, where the maximum likelihood estimate of outcrossing rate can be derived under disequilibrium between selfing and outcrossing6.Preliminary inferences on the outcrossing rate of this species could be inferred from a recent study on population structureT. ciliata is of particular significance to its genetic conservation or sustainable management. This species is classified as an endangered species in China7 although it is not in the”Red lists” of the species at risk by the International Union for Conservation of Nature and and Natural Resources (IUCN). The importance of this timber tree species is due to its straight stem form and quality red wood for furniture in China. However, the low natural regeneration and over-cutting enhanced a substantial decline in population density9. This subsequently leads to the influences on mating system due to population demography and changes genetic variation within and between populations. So far, several programs have been set up to promote artificial plantations and genetic breeding, including provenance trials10 and the ongoing breeding program for insect-resistance. The critical issue is that the initial breeding programs were based on open-pollinated seeds derived from natural populations with unknown mating systems11, which could yield biased estimates of genetic parameters and evaluation of progeny performance12.Scoring mating system of 13. The range-wide distribution of T. ciliata was grouped into two clusters, the western and eastern parts. To assess variation of mating system in different regions, six samples were collected from populations in both western and eastern parts of the species distribution  and nuclear microsatellites  indicated that substantial genetic variation (about 79.26% with SRAP versus 32.4% with SSR) occurred among populationsEight pairs of SSR primers were screened according to the most sequence variability observed in six populations Table . Genotyp16, but with Micro-Checker (Oosterhout’s method) for the loci with null alleles for each population  and the logarithmic geographical distance were present at all eight loci (Table Fst/(1 − Fst) and the logarithmic geographical distance   3) was s18, null alleles at relevant loci in different populations were counted in estimating the outcrossing rate (or the selfing rate). Results showed that all populations exhibited a predominant outcrossing system  to 0.992 (Baoshan), with the mean of 0.859 (0.106). From the relation of selfing and outcrossing rates, α = 1 − t and their equal variances between α and t, significant selfing rates were present in Nanping  but not in the remaining five populations for the multilocus estimates. However, significant selfing rates at single loci were present in all populations except Baoshan. Significant differences between tm and ts occurred in Nanping and Simao, indicating that biparental inbreeding in addition to the occurrence of selfing in these populations6. Inbreeding coefficient of maternal parents (F) was not significant from zero in Yongren and Guanshan but were significantly negative in the remaining four populations, indicating no inbreeding in female parents.According to the instruction provided in MLTRem Table . Estimatrp(m) = 0.109, Se = 0.037), Tianlin (rp(m) = 0.208, Se = 0.055), Guanshan (rp(m) = 0.304, Se = 0.120), and Nanping (rp(m) = 0.312, Se = 0.06), indicating that the same fathers in pollination were partially shared in these populations but not in Yongren (rp(m) = 0.080, Se = 0.109) and Simao (rp(m) = − 0.133, Se = 0.274). The results were different from single-locus estimates where a significant correlation of paternity was found only in Nanping (rp(s) = 0.452, Se = 0.087). Single locus estimates of paternity were significantly greater than multilocus estimate only in Nanping (rp(s)-rp(m) = 0.140, Se = 0.043), indicating that population substructure occurred in male similarity between outcrosses in Nanping but not in other populations. Significant correlation of selfing among loci (rloci) was not found in all populations, indicating the independence among the eight SSR loci in paternity correlation.The correlation of selfing among families was not significant in all populations, indicating independence among families in selfing. The positive correlation of paternity at multiple loci was significant in Baoshan  > rp(m)). This strongly suggests the occurrence of limited pollen dispersal both within and among populations in different regions of the species distribution. Although maternal parents showed lack of inbreeding (F = 0), the number of paternal parents was limited in four out of six populations investigated. This could be partially attributed to the limited numbers of pollen donors within or between populations or to the over exploitation that led to low population density. Reports of low natural regeneration was probably associated with the low quality of seeds due to inbreeding depression9.Estimates of paternity correlations indicated that a certain proportion of full-sibship in the same half-sib progeny occurred in four populations except Simao and Yongren that possessed multiple paternity for pollination. Further, Nanping and Guanshan populations exhibited population substructure in male similarity among outcrosses ) that ranged from 3 to 12 individuals19.Biparental inbreeding inferred from a comparison of T. ciliata is essentially different from T. sinensis, one genetically related species in monophyly genus Toona in Meliaceae20. The differences between T. ciliata and T. sinensis are subtle in flower morphological traits. The flower structure of T. sinensis is characterized by flowers of 4–5 mm long, short pedicels, 5-dentate or shallowly undulate calyxes, five white, oblong and glabrous petals each 4–5 mm long and 2-3 mm wide, ten stamens (five fertile and five degenerate), eight ovules per locule, the style longer than the ovary, and the discoid stigmas with five fine lines. T. sinensis is sexually diecious and has the system of complete outcrossing. T. ciliata retains perfect flowers, and its mating system is evidently predominant outcrossing from this study. Their qualitative difference in mating system is likely related to the speciation time between T. ciliata and T. sinensis22, and distinct evolutionary history modulates each species .The mating system of 23, resulting in different sizes of progeny populations available for analysis. Although the sample sizes per progeny (4–10 seeds per family) were relatively small in comparison with some reports in the literature, these samples were appropriate for scoring this predominant outcrossing system. These are based on two reasons. One is that microsatellite markers are highly polymorphic and the number of eight loci is sufficient to identify cross individuals. The maternal genotypes can be directly observed  or in the field24. This range of sample sizes provides appropriate estimates of variances. The sampling errors are calculated from the binomial distribution by 18. Our estimates of standard errors for the outcrossing rate or the selfing rate were less than 10% except Guanshan for the estimate of multilocus outcrossing rate  among the six populations, and detected significant IBD effects among the six populations. Zhan et al.4 showed that IBD effects were absent among populations in the western part but present in the eastern part. IBD effects among populations could likely affect mating system since mating systems differed in different regions under significant IBD effects29.Mating system of a natural plant population can be shaped by many factors, including local population density, pollen dispersal within and between populations, plant height, phenological period, and global changes 31. From Zhang et al.31, an analytical relationship among IBD effects, gene flow and mating system can be roughly inferred by synthesizing the results of Rousset32 (Fst/(1 − Fst) = a + b ln), Caballero and Hill33 , and Hu and Ennos34 under classical island model35, i.e.N is the population size, α is the selfing rate, and mS and mP are the migration rates of seeds and pollen, respectively; a is the intercept of regression analysis, and b is the regression coefficient. A positive correlation is possible between selfing rate (α) and geographical distance under significant IBD (b > 0) effects.The relationship between IBD between populations and mating system could be complicatedN (1 − α/2). This change comes from alternation of gene flow within rather than between populations. IBD at the population level reinforces this process by increasing the chance of interbreeding of relatives, which indirectly decreases genetic diversity within populations . Reduction in effective population size was reported in an isolated population of Myracrodruon urundeuva although pollen dispersal of this species is mediated by wind and bees36. The second process is that IBD impedes both seed and pollen flow between rather than within populations, mS + (1 − α) mP/2. Selfing only interacts with pollen flow that is restricted by IBD through decreasing population connectivity or increasing physical distances due to clear-cutting. Empirical studies support the impedement to gene flow by habitat fragmentation37 or IBD at the population level, with a few exceptions of case studies39. Taken together, the interaction of the two processes could reinforce the effects of IBD on mating system.Thus, two processes could relate IBD effects to mating system. One is the demographic change owing to the reduction of effective population size by selfing/inbreeding, αm > 0 and tm − ts > 0) and Guanshan (tm − ts > 0) could be associated with Wuyi (2158 m above sea level at the highest peak) and Xuefeng (a part of Yunnan-Guizhou Plateau) Mountains that naturally impeded seed and pollen flow between western and eastern parts of the species distribution  of pollen from outside populations but increased pollen or seed dispersal distance within the population. They also showed that selective logging reduced the reproductive population size, and increased bottleneck effects (related to Ne) and the rate of selfing or inbreeding among relatives. Conclusions similar to Carneiro et al.14 were also drawn in Baillonella toxisperma42 and other species41. Thus, population genetic structure could be affected by selective logging in natural forests of T. ciliata9.Practices of forest management frequently affect population genetic structure within and/or between populations. For instance, selective logging, such as removal of individuals in adults or in the reproductive stage, results in low population densityT. ciliata could produce substantial population genetic differentiation. Management , such as selective logging and clear-cutting followed by natural ecological restoration could yield interbreeding among relatives43. These practices of conventional forest management erode genetic diversity and destroy habitats. Barriers to the inter-population gene flow enhance population genetic differentiation and reduce genetic variation within populations, leading to high homozygosity in local habitats. This may temporally improve adaptation of subdivided populations to local habitats (high frequency of adaptive homozygotes), but reduce the potential for long-term evolutionary response to globally changing environments. Further, when locally adapted populations hybridize, progeny so produced becomes less fit to local habits, analogous to the outbreeding depression. Therefore, silvicultural management, such as assisted migration of seeds from distinct provenances45 and maintenance of non-isolated populations in multiple preserved areas, is the key to the viability of T. ciliata in China. Since T. ciliata is evidently self-compatible, practices that promote extensive pollen dispersal within and between populations, such as improving population density by planting seedlings in logging gaps46 and/or plantation with genotypes differing from neighborhood trees, can enhance outcrossing and reduce inbreeding depression.The existence of self-ferilization and inbreeding in T. ciliata is an important timber species that has been over exploited owing to its high quality of wood for furniture in China. Scoring its mating system helps to understand the reproductive ecology of this species and hence to imply its natural regeneration. This study investigated mating system of six natural populations in different regions and showed occurrence of selfing or inbreeding in different geographical regions. T. ciliata exhibited a predominant outcrossing, but allowed selfing and inbreeding. Analysis of population genetic structure showed that substantial genetic variation existed among the six populations. Isolation-by-distance effects were significant among the six populations but insignificant among the four populations in the western part of the distribution of this species. The results suggest that one practice of management is to remove barriers to gene flow in this species, including assisted migration and planting seedlings in logging gaps. The results also indicate the needs of avoiding inbreeding in tree breeding programmes.4 where seed samples were mixed and the pedigree information was not recorded.Six natural populations were selected in 2017 and 2018  to 300 seeds in Nanping (30 open-pollinated families), and an average of 140 seedlings per population (4–10 seeds per family) were germinated for mating system analysis. Note that the sample sizes were appropriate when highly polymorphic markers were employed −1. Quantified DNA samples were stored at − 20 °C for PCR amplification.DNA extraction was conducted by using 100 mg fresh leaves and following manufacturer’s instructions of the DNAsecure Plant Kit . Agarose gel electrophoresis (1.0% w/v) was applied to check the quality of DNA extraction. The DNA concentration was checked with a Thermo Scientific NanoDrop 1000 spectrophotometer , and adjusted to 50 ng μLT. ciliata4. Eight pairs of SSR primers were screened according to the most sequence variability observed in six populations. These SSR markers are nuclear genomes-based, and the resultant amplicons follow biparental Mendelian inheritance. Table a), and the observed allele sizes for each SSR locus.Selection of SSR markers was based on a previous study of Machilus pauhoi47 was employed. The PCR amplification was carried out in a 25 μL reaction volume containing 1U Taq DNA polymerase (TaKaRa), 1 μL 20 ng μL−1 template DNA, 2 μL 25 mmol L−1MgCl2, 0.5 μL 10 mmol L−1dNTP, 0.5 μL 10 mmol L−1 of each forward and reverse fluorescent primer pair, 2.5 μL 10× PCR buffer . PCR amplification was conducted using following cycle procedure: an initial 3 min of denaturing at 95 °C, followed by ten cycles of three steps . The next 20 cycles were then used with the same steps . A final elongation step was at 72 °C for 6 min. The PCR products were detected by capillary electrophoresis using an ABI 3730XL DNA analyzer after confirmation of PCR amplification on a 2% agarose gel. Genemapper 4.0 software (Applied Biosystems) was used to estimate molecular sizes of SSR-PCR amplifications.The same procedure as our previous study on 17 to discriminate errors arising from short allele dominance , stuttering and null alleles. A pooled population consisting of all families was used to check genotyping errors. In this program, presence of null alleles was suggested when homozygotes were overall excess and evenly distributed across the homozygote-classes. Mis-scoring of stutters was suggested when heterozygotes were deficit with alleles differing in size by a single repeat and large homozygotes were in excess. Short allele dominance was suggested when homozygotes were biased towards either extreme of the allele size-distribution. Null allele frequencies were estimated using the method of Oosterhout et al.17.To check genotyping errors, we applied Micro-Checkerk of locus j at population i. The expected heterozygosity (He) at a locus in a population was calculated by 35 and Weir48, population genetic differentiation at a single locus was calaulated byk at locus j over r popuations, and 0: df = r − 148. For multilocus estimate,Let entclass1pt{minima49.A program in R was provided to calculate population genetic differentiation based on allele frequencies “”. Since 24 where each allele status at each locus  was indicated in preparing dataset. Estimates (expectation–maximization method) of mating system parameters included the multilocus population outcrossing rate (tm), the average single-locus population outcrossing rate (ts), the inbreeding coefficient of maternal parents (F), the correlation of paternity at multilocus (rp(m)) and single locus (rp(s)), the correlated selfing rate (rs), the difference between tm and ts, and the difference between rp(s) and rp(m). Because estimates of allele frequencies between pollen and ovules were heterogenous in some half-sib families, their inequality was set in running the program (not pooled), which yielded greater maximum likelihoods with our datasets. Standard errors of population estimates were calculated using 1000 bootstraps that were based on resampling of progeny array.MLTR was used to handle the presence of null alleles with SSR markersSupplementary Information 1.Supplementary Information 2.Supplementary Table 1.


Meles meles) have found conflicting microsatellite and mitochondrial DNA evidence in Irish populations, suggesting Irish badgers have arisen from admixture between human imported British and Scandinavian animals. The extent and history of contact between British and Irish badger populations remains unclear. We use comprehensive genetic data from Great Britain and Ireland to demonstrate that badgers in Ireland's northeastern and southeastern counties are genetically similar to contemporary British populations. Simulation analyses suggest this admixed population arose in Ireland 600–700 (CI 100–2600) years before present most likely through introduction of British badgers by people. These findings add to our knowledge of the complex colonization history of Ireland by mammals and the central role of humans in facilitating it.The colonization of Ireland by mammals has been the subject of extensive study using genetic methods and forms a central problem in understanding the phylogeography of European mammals after the Last Glacial Maximum. Ireland exhibits a depauperate mammal fauna relative to Great Britain and continental Europe, and a range of natural and anthropogenic processes have given rise to its modern fauna. Previous Europe-wide surveys of the European badger ( Howevertimidus) , suggesttimidus) , with ge martes)  and pygmminutus) , linkingMeles meles) exemplifies the challenges in understanding the biogeography of Ireland [The European badger . These were collected from the Republic of Ireland (RoI), Northern Ireland (NI) and GB. One hundred and seventy six badger carcasses from an ongoing road traffic accident (RTA) survey were collected by the Department of Agriculture, Environment and Rural Affairs Northern Ireland (DAERA-NI) across all six counties of NI during the period from September 2011 to March 2013. GPS locations of carcasses were logged and a tissue sample was stored for DNA extraction. 278 badger carcasses from ongoing bovine TB control-related culling operations in the RoI were collected by the Department of Agriculture, Food and the Marine (DAFM) during 2014. These badger carcasses were collected from sites distributed across 23 of the 26 counties of RoI. The three counties excluded were Donegal, Dublin and Louth. GPS coordinates of locations of culled animals were collected and a tissue sample stored for DNA extraction. A map of Ireland containing county names and boundaries is shown in electronic supplementary material, figure S1. For 21 samples across both territories, no geo-location data were available. Geo-locations for Irish animals are found in electronic supplementary material, data S1. The map in figure 1Ninety-one additional badger hair samples were made available from five regions of GB––Gloucestershire, Oxfordshire, Pembrokeshire, Powys and Northumberland. No geo-location data were supplied for these animals.2.2.et al. [DNA extraction and microsatellite genotyping with a 14 loci panel derived from the work of Carpenter et al. .Meles meles using the NCBI Basic Local Alignment Search Tool BLAST (http://blast.ncbi.nlm.nih.gov/). Haplotype identities were those defined by O'Meara et al. [All badgers were Sanger sequenced for a 214 bp section of the mitochondrial D loop. Specifically, a 214 bp section of the mtDNA control region was amplified using the primers LRCB1 5′-TGG TCT TGT AAA CCA AAA ATG – 3′ and H16498 5′ – CCT GAA GTA AGA ACC AGA – 3′. PCR conditions consisted of 1 cycle of 96°C for 15 min, followed by 40 cycles of 96°C/60 sec, 50°C/60 sec, 72°C/60 sec, followed by a final elongation at 72°C for 10 min [All genetic data were mapped using ArcGIS ArcMAP 10 using Latitude and Longitude coordinates based on the Irish Grid .2.3.O) and expected (HE) heterozygosity and the inbreeding/fixation co-efficient (FIS). We performed this for the combined GB samples, the combined Irish samples, each GB region and the two STRUCTURE inferred Irish sub-populations (See Results).In GENEPOP , we asseBadgers from NI were sampled after road traffic accidents whereas their RoI contemporaries were sampled after sett side trapping, we wanted to rule out any possibility that behavioural differences potentially related to ranging could make direct genetic comparison inappropriate. We therefore compared allele frequency data between the County Down RTA population and another County Down population sampled sett side (data not shown).2.4.a priori unknown and may result from the ancient or recent divergence of all sub-populations from a common ancestral population or human-aided introductions [K. Both models were run without location prior. To infer best fitting number of K, we used the ΔK method of Evanno et al. [K = 1 to K = 10 with a burn in of 50 000 and Markov chain length of 100 000, for 20 iterations per K value. The convergence of key statistics along the burn in chain was assessed as per the STRUCTURE manual. We then analysed the data using STRUCTURE Harvester [K value (n = 20) were processed using the program CLUMPP [We analysed microsatellite data from all badgers using STRUCTURE 2.3.4 to determine population sub-structure across both islands . Since aductions ,12, we ro et al.  over conm CLUMPP , with fim CLUMPP .ST values using FSTAT 2.9.3.2 [We quantified genetic differentiation between GB regional populations and the two Irish sub-populations inferred by STRUCTURE by calculating pairwise F 2.9.3.2 . Statist 2.9.3.2  calculat 2.9.3.2  in the R 2.9.3.2 .2.5.find.clusters function was used first to assign individual samples to proposed sub-populations. We retained all 80 principal components for this initial step. We then applied the DAPC analysis function to the number of clusters exhibiting the lowest Bayesian Information Criterion (BIC) to produce a scatterplot, retaining 40 principal components which accounted for 90% of the observed variance, and all linear discriminants.We also assessed sub-structure using the multivariate Discriminant Analysis of Principal Components (DAPC) method , which d2.6.n = 414 & n = 40). Mutation rates were retained at the default setting as per the DIYABC manual. After initial exploratory analyses, the following parameters were set. Effective population sizes for the two Irish sub-populations were allowed to vary between 10 and 10 000 individuals, and 10 and 15 000 for the GB population. Two historical scenarios were considered. Both are visually represented in Fst and δμ2 distance. One million datasets were simulated per scenario. Summary statistics calculated for the mtDNA data were number of haplotypes, number of segregating sites, mean of pairwise differences, variance of pairwise differences and pairwise Fst. We assessed the reliability of the simulated data in comparison to observed prior and posterior data by PCA. DIYABC produced posterior probabilities of both scenarios and posterior distributions of historical parameters by logistic regression using the closest 1% of simulated datasets to the observed data.To determine the timing of the contact between Irish and British badgers, we implemented an Approximate Bayesian Computation (ABC) on microsatellite alone and combined microsatellite and mtDNA data in the software package do it yourself approximate Bayesian computation (DIYABC)  for a su3.3.1.Z tests of allele frequencies compared between RTA animals and sett side capture badgers from County Down, when corrected for multiple comparisons indicated there were no significant allele frequency differences, suggesting there is no representative bias in the NI RTA dataset compared to RoI animals.a and b) exhibit similar average numbers of alleles per locus. Irish badgers exhibited lower genetic diversity (expected (He) and observed (Ho) heterozygosity, 0.56 and 0.48, respectively) and fixation indices (Fis 0.14) than their British contemporaries , owing to higher relative frequencies of multiple alleles in GB animals (data not shown). As a result, GB sub-populations exhibited greater sub-population genotype differentiation compared to that of Ireland.Standard population genetic indices of badgers across Britain and Ireland are shown in table 13.2.K plot exhibited a peak at K = 2 and a smaller one at K = 6 , with a higher mean log likelihood than the independent allele frequencies model . The K = 2 data indicated that Irish badgers in Counties Down, Antrim, Armagh, Laois, Wicklow, Carlow, Wexford and Tipperary exhibited a British-like genetic heritage . The K = 6 analysis output also indicated that while there was a significant admixture apparent between the four badger sub-populations, the signal of GB genetic heritage was still apparent in the northeastern County Down and southeastern Counties of Wicklow and Carlow . Given that both hierarchical STRUCTURE models supported the GB genetic heritage in these regions, in line with the objective in this study to investigate links between British badgers and Irish contemporaries, we focused our efforts on the K = 2 analysis output data, which exhibited the strongest statistical support . Using a previously described population assignment Q score threshold of 85% for this Irish badger dataset [a). The remaining 40 badgers, having at least 15% British heritage, were designated as Irish sub-population 2. The sub-populations currently inhabit distinct geographic locations, with sub-population 2 found primarily in the northeastern and southeastern counties of Ireland (a). Both Irish sub-populations and all British regional sub-populations exhibited significant pairwise genetic differentiation from one another, as measured by Fst . British regional sub-populations were least differentiated from Irish sub-population 2 . Specifically, badgers from Gloucestershire and Northumberland were the British populations most similar to Irish sub-population 2 (Fst = 0.15). For the DAPC cluster analysis, the find.clusters function, executed in adegenet returned a curve which indicated that K = 14 had the lowest BIC . The resulting K = 14 DAPC scatterplot is shown in STRUCTURE analysis indicated that a sub-set of Irish badgers exhibited the evidence of historical admixture with British badgers . The corheritage . The cor dataset , we defi Ireland a. Both Iet al. [et al. on account of our sequencing of a shorter region of the mitochondrial control region. However, as with O'Meara et al. [Seven mtDNA haplotypes were identified in the Irish badger population. Haplotypes H2, H9, H14, H15 and H20 accounted for 96.0% of all haplotypes in Ireland. Five haplotypes, H2, H9, H14 and H15 had previously been reported by O'Meara et al. . Previouet al. . H2, theet al. , while Het al. . H20 . Similar lack of support for simulated historical models has been observed before when using combined mtDNA and microsatellite data to address the effects of admixture in forming extant badger populations in Europe . AdditioMicrosatellite data alone did exhibit greater support for historical scenarios, so from here-on, we refer to the results derived from that dataset. A higher posterior probability for DIYABC scenario 2 (0.65 CI 0.63–0.66) versus scenario 1 (0.35 CI 0.34–0.37). PCA evaluation of the DIYABC analysis for scenario 2 indicated the chosen historical model explains the observed data . In keeping with the DIYABC manual guidelines, observed data are seen to cluster in the centre of simulated posterior datasets, which are themselves nested within simulated prior datasets. Historical parameter estimates from DIYABC are shown in Genotype and mtDNA sequence type data are available in electronic supplementary material, Data S1 along with additional detail. The genetic contribution from British badgers in founding Irish sub-population 2 was estimated to be 23%, with admixture from Irish sub-population 1 accounting for the remaining 77%.4.We have shown that a sub-set of Irish badgers, primarily located in the northeast and southeast of the island, share genetic ties, both nuclear and mitochondrial, with British contemporaries, most likely as a result of colonization from GB in the recent past, involving a small number of animals which admixed with already resident Irish animals. This finding expands upon prior evidence for badger colonization of Ireland, highlighting added complexity by showing how the extant Irish badger population has been formed by separate, region specific, colonization processes, from multiple sources and subsequent admixture.K = 2 appearing in analyses of these types. K = 2 findings can be a spurious finding, therefore, with artefacts in admixture analyses introduced by coercion, leading to inaccurate assumptions of genetic heritage. However, we believe this is unlikely to be the case in this instance. When one considers the full range of evidence we present, we believe that the chances such an artefact has arisen are low. At both hierarchical levels identified (K = 2 and K = 6), the STRUCTURE data is congruent, suggesting GB like genetic heritage in badgers from southeastern and northeastern counties. If an artefact driven by some stochastic effect of the STRUCTURE algorithm was the reason for our data, why would its effects only be limited to Irish animals from the northeastern and southeastern counties, the very regions Frantz et al.'s [There has been justified recent criticism of an over reliance on the outputs from STRUCTURE for inferring population admixture and sub-structure , with thet al.'s  independOur data are congruent with the role of human-aided animal introductions to Ireland  given thet al. [et al. [et al. [et al. [Our data also help to further understand the findings of Frantz et al. , who rep [et al. , whose a [et al.  observed [et al.  have sugVulpes vulpes) and pine martens were introduced during the Bronze (2500–500 BC) and Iron Ages (500 BC – 400 AD) [Erinaceus europaeus), rabbits (Oryctolagus cuniculus), red squirrels (Sciurus vulgaris) and fallow deer (Dama dama) to the island [A significant caveat to our hypothesis as detailed above is that the period of time identified by DIYABC exhibits a wide confidence interval, suggesting this translocation took place at some point between the late Bronze Age and the early twentieth century. There is considerable evidence for human-aided movement of animals into Ireland during this period. Red foxes ( 400 AD) , presuma 400 AD) . The Vik 400 AD) , with wi 400 AD) . Norman e island , likely et al. (1760 CI 525–6390) for the occurrence of the admixture event between Iberian and Balkan refugial badgers that founded the modern day Scandinavian population [In addition, our DIYABC data suggest that the two European sub-populations that went on to found the modern populations of Britain and Ireland post LGM , diverged around 11 000 ybp. This timing predates the transition of Britain from being a European peninsula to becoming an island around 8500 ybp . Also, tpulation . We suggIn summary, these data further advance our knowledge of the history of colonization of Ireland by mammals. They also help to deepen our understanding of the extant Irish badger population structure and the forces that shaped it, providing general lessons about the interaction of environmental and anthropogenic factors in determining the phylogeography of European mammals. Future work to undertake microsatellite comparison of the whole Irish population to the wider European population would be beneficial in further elucidating the finer details of how and when Ireland was colonized by this important species. Comparison to Scandinavian badgers would perhaps be most useful given how common the Atlantic fringe haplotypes are in Ireland; however, our finding that the second most common mtDNA haplotype (H2 – 18.5%) is one commonly seen in Central Europe  suggests


The genetic backgrounds of these two populations were explicitly characterized by the analysis of molecular variance (AMOVA) and multi-dimensional scaling (MDS) plots based on 27 Y-STRs. Then, population comparisons were conducted by observing Y-SNP allelic frequencies and Y-SNP haplogroups distribution, estimating forensic parameters, and depicting distribution spectrums of Y-STR alleles in sub-haplogroups. The Y-STR variants, including null alleles, intermedia alleles, and copy number variations (CNVs), were co-listed, and a strong correlation between Y-STR allele variants  and the Y-SNP haplogroup QR-M45 was observed. A network was reconstructed to illustrate the evolutionary pathway and to figure out the ancestral mutation event. Also, a phylogenetic tree on the individual level was constructed to observe the relevance of the Y-STR haplotypes to the Y-SNP haplogroups. This study provides the evidence that basic genetic backgrounds, which were revealed by both Y-STR and Y-SNP loci, would be useful for uncovering detailed population differences and, more importantly, demonstrates the contributing role of Y-SNPs in population differentiation and male pedigree discrimination.Y chromosomal short tandem repeats (Y-STRs) have been widely harnessed for forensic applications, such as pedigree source searching from public security databases and male identification from male–female mixed samples. For various populations, databases composed of Y-STR haplotypes have been built to provide investigating leads for solving difficult or cold cases. Recently, the supplementary application of Y chromosomal haplogroup-determining single-nucleotide polymorphisms (SNPs) for forensic purposes was under heated debate. This study provides Y-STR haplotypes for 27 markers typed by the Yfiler Primarily, they are used in practical work for forensic purposes, such as paternity tests , criminaeration) ,6,7. ForAmong Chinese Han populations, huge efforts have been made to dig into population genetic backgrounds via genome-wide markers. Gao et al. developed a population genome database called “PGG.Han”, which enrolls over 114,000 Han individuals . Previouhttp://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm), the population size of Shandong is about 89 million, and Shandong population is mainly composed of the Han nationality (98.02%). As for Yunnan province, it is the most southwestern region in China and possesses the highest ethnic diversity in China . In addition to the Han nationality, there exist 25 diverse ethnic minorities with the population size greater than 6000, including Yi, Hani, Bai, Dai, Zhuang, and others. Among these, 15 are unique to Yunnan. Individuals belonging to minority groups account for 33.4%. Years of cultural exchanges and gene flows have resulted in mixed ethnic components in Yunnan Han population.Located in the middle and lower reaches of the Yellow River, Shandong province is on the northeastern coast of China mainland. It is the birthplaces of Chinese culture and is of great importance to Taoism, Buddhism, and Confucianism in China. Shandong is the second most populous province in China. According to the 2010 China census  for experiments involving humans. The conception and implementation of this study were approved by the Ethics Committee of Fudan University .n = 305) lived in Zibo City, Shandong Province, and the male ancestors of all donors had been living in the sampling sites for three generations. As A total of 870 male unrelated samples of Chinese Han ancestry were collected with appropriate informed consent, consisting of blood samples provided on Flinders Technology Associates (FTA) cards . Among them, 565 lived in Zhaotong City, Yunnan Province, while the rest (https://isogg.org/), Phylotree [We considered the following 24 binary Y-SNP markers within the Y-SNP Pedigree Tagging System  : E-M96, hylotree , and Y Chylotree ,21. We ahylotree ): DYS438® PCR System 9700  in accordance with the manufacturer’s instructions. For this, 1 mm2 of blood stain on an FTA card was cut using a Harris micro-punch  and then added into each reaction mix. In addition, 1 ng of male 9948 control DNA  was amplified as the positive control in each batch. The amplification products were separated by capillary electrophoresis (CE) performed by a 3500xL Genetic Analyzer (Thermo Fisher Scientific). The typing result was determined by means of GeneMapper® ID-X Software v1.4 (Thermo Fisher Scientific). For each sample, PCR–CE analysis was performed in two replicates to check that the genotyping was accurate. In addition, the variants detected in this study were confirmed by replicates of PCR–CE analysis.Direct amplification (aka DNA extraction-free method) was performed using the GeneAmphttps://yhrd.org). The assigned accession numbers of Shandong and Yunnan Han populations were YA004617 and YA004618, respectively.The Y-SNP data in concert with the Y-STR data obtained were validated and submitted to the release R62 of the Y-chromosomal haplotype reference database . The allele frequency of each Y-STR locus was generated by direct counting. The estimation method of gene diversity (GD) was analogous to that used for HD, where pi represents the frequency of the ith allele. To calculate these parameters, the “Basic.stats” function included in the “heirfstat” package developed by Thierry et al. [https://www.r-project.org/).The allele of the locus DYS389II was defined by subtracting that of DYS389I. Forensic parameters regarding haplotype information were calculated for the 27 Y-STR loci included in the AmpFLSTR™ Yfiler™ Plus Kit . Haplotyaplotype . Match ptruction . In othey et al.  was utilhttp://www.fluxus-engineering.com/sharenet.htm) [A median-joining (MJ) network based on 27 Y-STR haplotypes was constructed using Network 5.0.0.3 software (net.htm) , in ordenet.htm) . n = 2314) [n = 282) [n = 161), Xinjiang Kazak (n = 130) [n = 66) [n = 172), Tibet Shigatse Tibetan populations (n = 230) [n = 247) [n = 136) [n = 473) [n = 843) [n = 1550) [n = 877) [ST) were then used to perform multidimensional scaling  of RST were evaluated with 10,000 permutations.As reported, Nothnagel et al. analyzed genetic phylogeny based on 17 Y-STR haplotypic data from almost 38,000 Chinese male samples . Till no = 2314) , Hulun Bn = 282) , Xinjian[n = 66) , Tibet Cn = 230) , and Hann = 247) , Shenzhen = 136) , Hainan n = 843) , Changzhn = 877) . Softwarn = 877)  was utiln = 877) ). In ordng  by “MASn denoted the number of Y-STR loci, and i was the ith locus, while mi, ai, and bi represented the mutation rate of the ith Y-STR loci and the genotyping information of two different individuals. As for the 24 Y-SNPs, all samples were covered. The calculation of genetic distance  using Y-SNP loci was adopted according to Neikij equals 0 or 1 depending on whether their SNP alleles are identical or not [Haplotypes with intermediate alleles, copy number variations, and null alleles were removed from the individual-level phylogenetic reconstruction. Pairwise genetic distance  of 27 Y-STR loci was calculated using y theory . In the l or not . Phylogel or not  of R lanWith the aim to verify the sampling representativeness of Shandong and Yunnan Han populations and to reveal the genetic backgrounds of the two populations located in southern and northern parts of China, population data of other 13 representative Chinese populations  were selp-values above 0.0005 which are not indicated in bold in After Bonferroni correction, the significant difference was set to 0.05/105 ≈ 0.0005. Insignificant differences, referred to In Specific to the Chinese Han populations cluster, another MDS plot focused on the construction of the inner structure of Han population to dissect subtle population relationships. The pattern matched the substructure of Han Chinese described in a previous study . The eigFor both populations, 24 Y-SNPs were analyzed, and 18 Y chromosome haplogroups were defined . The distribution of haplogroups within the Shandong and Yunnan Han populations are displayed in p = 0.05/20 = 0.0025) were discovered. In detail, the Yunnan Han population showed much higher frequencies in O1a-M119 and O1b-M268, but lower frequencies in O2-M112, O2a2-P201, and O2a2b-P164, which was also reflected by the disparity in haplogroup distribution  might be related to nomad incursions into the Central Plain in history . The difFour haplogroups—O1a, O1b, O2a1, and O2a2b, were characterized by dominant but different distributions in the two populations. The O1a haplogroup is mainly distributed in southern China, Malaysia, Vietnam, and Indonesia males. The O1b haplogroup is unique to modern Eastern Eurasian populations. Previous findings indicated that the proportion of the O1 haplogroup is significantly higher in southern China compared with northern China , which wIn total, 55 null alleles were observed at 14 different loci . Furthermore, 71 micro-variants were found in 69 samples, including 8 single-copy loci, i.e., DYS518 , DYS627 , DYS448 , DYS438 (10.1), DYS458 (14.1 and 15.1), DYS570 (19.2), DYS449 (30.1 and 30.2), and DYS481 (23.2), and two multi-copy loci, i.e., DYF387S1a/b  and DYS385a/b . We found 10 copy number variations (CNVs): DYS518 (37/38), DYS390 (23/24), DYS437 (15/16), DYS389 I (12/13), DYS576 (19/21), DYS456 (15/16 and 17/18), DYS385 (13/19/20), and DYF387S1 34/35/36) in other 10 samples. After searching in the YHRD database and other referenced publications /35/36 in,62,63,64Interestingly, among the 69 samples with micro-variants, 29 carried “.2” mutation at DYS518, which were all found to be descents of QR haplogroup ancestors, accounting for 64.4% of individuals assigned to the QR-M45 haplogroup. Albeit it has been concluded that the QR haplogroup is not a major haplogroup of the East Asian population , 92.2% oTo uncover the varying patterns of Y-STRs within haplogroups from different populations, three major haplogroups, i.e., C2, O1, and O2 were selected, to which the majority of the Shandong and Yunnan Han samples belonged .Significant differences of allelic frequencies were observed at DYS627 within all three haplogroups, which was also the only difference observed in both O2 and C2. In O1, however, significant differences could also be observed in single-copy loci DYS481, DYS389I, DYS389II, and DYS570 and in the multi-copy locus DYS385a/b. Albeit the varying patterns of most Y-STR loci showed close correlation with Y haplogroups instead of populations, significant differences at some Y-STR loci within the identical major Y haplogroups may reflect their different ancestral sources. In general, the regularity of a varying pattern demonstrated that the Y-STR gene pool remained stable, regardless of the different haplotypes in Yunnan and Shandong Han populations or the big differences in geographic and cultural definitions. Further, the different patterns for different major haplogroups revealed the primary superiority of Y-SNP haplogroups in classifying male groups, dissecting population structure, and exploring population migration. In forensic practices, especially for the Chinese Y-STR haplotype database which includes tens of millions of Y-STR haplotypes, Y-SNP could play a critical role for pedigree discrimination, as well as biogeographic inference.The GDs of all 27 Y-STR markers were calculated both for the three major haplogroups  of the two populations separately and for the total population . For then) in one population are different from each other, the forensic parameters HD, MP, and DC would be equal to 1, 1⁄n, and 1, respectively, and it would not be worth comparing them.Moreover, all Y-STR markers were used to analyze the classic forensic parameters in the two populations. Among all 870 samples, 864 haplotypes were unique . There w™ Plus kit helped to significantly increase the haplotype diversity and discrimination capacity but decreased the match probability in populations at various scales. For the sub-population composed of samples assigned to higher resolution haplogroups, MP was higher, which conformed to the common knowledge that one Y-STR haplotype would be liable to match those from the same Y-SNP haplogroups. Thus, for samples assigned to the identical high-resolution haplogroup, more Y-STRs are required to identify unrelated males.The HD and DC values of Yunnan Han population were comparatively greater than those of Shandong Han population, though they were high for both populations. The MP value of Yunnan Han was smaller. The varying patterns of the forensic parameters indicated that the 10 new Y-STR loci incorporated within the YfilerIn Significantly, the structures observed in the MDS plots were different. In summary, Shandong and Yunnan Han populations, the representatives of northern and southern Chinese Han, were focused on to investigate their genetic backgrounds via 27 commonly used Y-STRs and 24 East-Asian-haplogroup-determining Y-SNPs. Among the 870 samples, 864 haplotypes were unique. The observed Y-STR allele variants including null alleles, intermediate alleles, and CNVs were summarized. Of these, “DYS518~.2” alleles were all found within QR haplogroup individuals, and a network was constructed to characterize the evolutionary pathway of this kind of variant. Primarily, the forensic parameters  within different Y chromosomal haplogroups furnished the evidence that the co-application of Y-STR and Y-SNP analysis would provide more informative characteristics of various populations. A phylogenetic reconstruction on the individual level further explained that Y-STRs combined with Y-SNPs would help increase the discriminability of male pedigrees using a Y chromosome database. This study sheds light on basic genetic backgrounds utilizing both Y-STR and Y-SNP loci, showing their usefulness for uncovering detailed population differences. More importantly, this tentative study will likely help to build a Y-SNP databank to promote Chinese male pedigree discriminability.


Cooking time of the common bean is an important trait for consumer preference, with implications for nutrition, health, and environment. For efficient germplasm improvement, breeders need more information on the genetics to identify fast cooking sources with good agronomic properties and molecular breeding tools. In this study, we investigated a broad genetic variation among tropical germplasm from both Andean and Mesoamerican genepools. Four populations were evaluated for cooking time (CKT), water absorption capacity (WAC), and seed weight (SdW): a bi-parental RIL population (DxG), an eight-parental Mesoamerican MAGIC population, an Andean (VEF), and a Mesoamerican (MIP) breeding line panel. A total of 922 lines were evaluated in this study. Significant genetic variation was found in all populations with high heritabilities, ranging from 0.64 to 0.89 for CKT. CKT was related to the color of the seed coat, with the white colored seeds being the ones that cooked the fastest. Marker trait associations were investigated by QTL analysis and GWAS, resulting in the identification of 10 QTL. In populations with Andean germplasm, an inverse correlation of CKT and WAC, and also a QTL on Pv03 that inversely controls CKT and WAC (CKT3.2/WAC3.1) were observed. WAC7.1 was found in both Mesoamerican populations. QTL only explained a small part of the variance, and phenotypic distributions support a more quantitative mode of inheritance. For this reason, we evaluated how genomic prediction (GP) models can capture the genetic variation. GP accuracies for CKT varied, ranging from good results for the MAGIC population (0.55) to lower accuracies in the MIP panel (0.22). The phenotypic characterization of parental material will allow for the cooking time trait to be implemented in the active germplasm improvement programs. Molecular breeding tools can be developed to employ marker-assisted selection or genomic selection, which looks to be a promising tool in some populations to increase the efficiency of breeding activities. Phaseolus vulgaris L.) is one of the most important cultivated grain legumes and is consumed by millions of people worldwide, particularly in developing countries in the tropics  to F9:11 generation. (2) A multiparent advanced-generation intercross (MAGIC) population previously described by 4:6 RILs generated by the SSD method. (3) The “Vivero Equipo Frijol” (VEF) panel, previously described by Phaseolus  have been introduced by the Mesoamerican breeding program over recent decades. Therefore, the panel consists of recent breeding lines as well as available ancestors and initial interspecific introgression pre-breeding lines.In this study we used four different populations of common bean to elucidate the genetic architecture of cooking time: (1) A bi-parental population (DxG) previously described by 2 laid out for each replicate of each line. The DxG population and its parental lines were established in the field following a randomized complete block design with three replicates for each RIL in 2011. The MAGIC population and its eight founders were planted in 2013 in an alpha-lattice incomplete-block design with three replicates as described by The field trials of all four populations were planted at the CIAT Palmira experimental field station . The experimental unit in these trials were row plots of 2.22 mThe water absorption capacity (WAC) was measured using the method described by Modified at CIAT—more information below). Each soaked seed was placed in a well of the plate. On top of each seed a 90-g piercing pin was set down, and the Mattson device was placed in boiling distilled water (> 98°C). For each seed, the time (expressed in minutes) that it took to be completely pierced by the pin was recorded . The time between harvest to the evaluation moment was more than 2 years for the DxG and the MAGIC population, and less than 6 months for the VEF panel and MIP panel.Cooking time (CKT) was measured on 24 seeds with the Mattson pindrop cooker .The Mattson cooker was modified to become partially automated using an embedded system for taking data from each seed individually. The system uses a custom-made printed circuit board assembly with 24 installed micro-switches that detect if any of the 90-g stainless steel piercing pins pierce the bean. A ribbon cable connects the plate to a Udoo micro computer system harboring a router for Wi-Fi communication. Furthermore, a PT100 sensor was added to allow monitoring of the temperature throughout the experiment. Finally, a web application was developed to monitor and control wirelessly the process on any computer or mobile device . A Grubbs test  was usedy is a vector with the phenotypic responses, μ is the overall intercept, Gm is the effect of the mth genotype, Miis the effect of the ith machine, Rj is the effect of the jth replicate, (RB)jk is the effect of the kth block nested within the jth replicate , and εmijk is the error term corresponding to ymijk. In this model, the terms Mi, Rj, and (RB)jk were treated as random effects. The Gm term effects were treated either as fixed  or random . We assumed that every random term u and the residual ε adjusts to a normal distribution with mean 0 and independent variances where 2) estimates were calculated using the method proposed by 2 estimates were computed using the equation below:To determine the proportion of the genetic variance controlling CKT and WAC for each population, broad-sense heritability  protocol (1 and the Institute of Biotechnology of Cornell University2. Each 96-well plate was sequenced in one lane of an Illumina HiSeq platform device using single-end or paired-end reads ranging between 100 and 150 bp.Genotyping of the MAGIC population and its founders (629 RIL + 8 lines), the VEF panel (330 lines), the MIP panel (210 lines), and each founder genotype of the DxG population was obtained using the protocol , as prevprotocol . BrieflyP. vulgaris G19833 v2.1. .The construction of the genetic map of the MAGIC population was described in detail by pulation . Brieflypulation   procedure of the software IciMapping (v4.1)  with 10 p value was equal to or smaller than the Bonferroni-corrected threshold   , providiP panel) . ManhattP panel) .r) between the observed  and the predicted values  of the validation set. Different priors for parametric regressions on the SNP markers were tested, including the Bayesian ridge regression (BayesRR), BayesA, BayesB, BayesC, Bayesian Lasso (BLasso), and a GBLUP model. All these priors are based on additive effects models. In addition, Bayesian reproducing kernel Hilbert spaces regression (RKHS) was tested fitting a single Gaussian kernel model in the (average) squared-Euclidean distance between genotypes, as defined by h = 0.5. The RKHS model is a semi-parametric approach that incorporates additive and non-additive effects.A single-trait assessment of prediction ability was performed for each population individually using the R package BGLR (v1.0.8) , with 10A cross-prediction scenario was tested between and within populations and traits, using the RKHS model described above. Unlike the single-trait assessment of genomic prediction, different datasets were used for training and validation in this case. This scenario was divided in two separate cases. The first consisted in using the BLUEs of CKT, WAC, or SdW from a single population to predict every other trait in the same population. In total, 18 different combinations of training-validation datasets were obtained for this first case. For each combination, a similar cross validation process used 70% of the individuals from the training set of BLUEs to train the model. The remaining 30% of individuals from the validation set of BLUEs were used to calculate the PA between observed (TBVs) and predicted values (GEBVs). The random 70:30 assignment was repeated 100 times. The second case used the BLUEs from a given trait-population to train the model, and then it was used to predict every other trait in a different population, producing 54 different combinations of training-validation datasets. In this case, no cross validation was done, performing a single training and validation step. This second case of cross-prediction scenario resembles a more realistic breeding context.Cooking time, WAC, and SdW were evaluated in four different populations incorporating a large genetic variability: The DxG population , the MAGIC population , the VEF panel (Andean breeding lines), and the MIP panel (Mesoamerican breeding lines).Rj and (RB)jk terms in equation (1) were not significant for any trial. Since they were accounted for as random effects terms, the model presented in equation (1) automatically drops the zero variance terms and reduces itself.Significant phenotypic variability was observed in all populations for all traits . The DxGThe MAGIC population, VEF, and MIP panels presented similar phenotypic variability for CKT, with the lowest average values for the VEF (37.4 min), MAGIC (38.1 min), and MIP (51.6 min) . In the Correlations between the evaluated traits were somewhat inconsistent between populations . SignifiWe investigated the effect of seed color on CKT. In the VEF and MIP panels, light colored beans presented faster cooking time compared to darker beans, the white seeded being the fastest cooking group . HoweverThe top 5% of the fastest cooking lines for each population are listed in The sequencing data from the DxG parental lines, the MAGIC population, the VEF, and MIP panels were merged into a single matrix of 17,508 polymorphic markers that were used to assess the population structure . The firTo investigate the genetic basis of the CKT and WAC, QTL analyses were performed on the biparental DxG population and the multi-parental MAGIC population, and GWAS was carried out on the MAGIC, VEF, and MIP panels.For the QTL analyses, the genetic map previously reported for DxG was used  Supplem. Three QThe genetic map previously reported for the MAGIC population was used for QTL analyses . Five QTGWAS on the MAGIC population, VEF, and MIP panels revealed six QTL, three for CKT and three for WAC ,6. CKT3.2 value, explaining 34% of the phenotypic variation with an allelic effect of -1.98 min  for CKT ranged between 0.18 (MIP) and 0.52 (MAGIC), while the mean PA for WAC ranged between 0.05 (MAGIC) and 0.43 (DxG); the PA for SdW is higher than the other traits, ranging between 0.52 (MAGIC) and 0.64 (DxG) . In geneA cross prediction between CKT, WAC, and SdW was performed between and within the MAGIC, MIP, and VEF populations to assess prediction ability using different training-validation datasets. The cross-validation results between traits in the same population followed the behavior of the phenotypic correlations, with PAs ranging between -0.36  and 0.25  . The PA Taken together, these results show that the PA across populations for CKT, WAC, and SdW is mostly low suggesting different genetic bases. GPs within populations, on the other hand, show promise for breeding applications with acceptable predictive abilities, as long as it would be applied within these genetic groups.Several factors such as taste, nutrition, cost, and convenience influence the food choice of consumers . The conHigh genetic variability in all four populations was found, in line with a previous report . Also, hThe seed is a living organism that can be susceptible to the processing and manipulation that is carried out right after harvest. Long periods in non-optimal storage conditions have been reported to increase cooking time due to the hard-to-cook (HTC) phenomenon . The DxGThe populations with Andean contribution (DxG population and VEF panel) had a significant negative correlation between WAC and CKT, in parallel with previous reports . During In this study, we compared external characteristics of the seed such as weight and color with its cooking time. The correlation between CKT and SdW was not consistent within populations. Some studies have shown weak relationships between CKT and SdW. Recently, an increasing number of studies in common bean have investigated the genetics of cooking time; among them, several QTL studies  and studA QTL was found in populations with Andean contribution (DxG population and VEF panel) with opposite effects on CKT and WAC (CKT3.2/WAC3.1). The favorable allele in DxG is contributed by the Andean parent G19833. This locus likely causes the negative correlation that was observed between CKT and WAC in these populations. A similar QTL was previously described for WAC and CKT in chromosome Pv03 . WA3 andASP locus (0–1.5 Mb) associated with seed coat luster: Mature dry black bean seeds are either opaque (dull) or shiny (glossy) (The genetic control of WAC may be different in the Andean and Mesoamerican lines investigated here. WAC7.1 was identified in the populations with Mesoamerican origin (MAGIC and MIP panel). The phenotypic correlations between WAC and CKT were distinct, and accordingly, different QTL were identified in this study at chromosomes Pv03 for the Andean and Pv07 for Mesoamerican populations. WAC7.1 co-locates with the (glossy) . The Asp(glossy) .The QTL CKT2.1 and CKT3.1 were identified in the MIP panel and the MAGIC population, respectively. Both QTL were previously reported in the Andean panel ADP . In CKT3Several studies have tried to identify the genetic characteristics of CKT and WAC in an effort to unravel their genetic architecture. In all cases, they confirm a relatively high heritability. Some reports indicate that both traits can be controlled by a small number of genes , while oGiven that CKT and WAC appear to have a partially quantitative mode of inheritance, we evaluated to what extent genomic prediction models can capture its genetic variability. Prediction accuracies for CKT ranged from 0.18 to 0.52, suitable for breeding in the MAGIC population, but not so for the MIP panel. Higher accuracies were observed for SdW, ranging from 0.52 to 0.64, close to previously reported values for this trait . SimilarIn this work, we compared different population types, using constructed bi-parental and eight-parental RIL populations besides two different breeding panels. All population types appear basically suitable for identifying genetic variability, for genetic mapping, and GP. RIL populations performed somewhat better for predicting CKT and WAC. This was not observed in studies with other traits comparing GP in MAGIC population and VEF panel . Panels This study evaluated the genetic architecture of cooking time and water absorption capacity using and integrating different tools and methodologies. To our knowledge, this study used the highest genetic variability studied so far in these traits in common bean, using four different populations with lines belonging to both Andean and Mesoamerican gene-pools. The presented results validate the advantage of combining GWAS and QTL analyses to find loci that controlled a complex trait. We identified fast cooking lines in every population evaluated with a high potential to be implemented in a breeding program with perspectives to different markets. Different QTL for the Andean and Mesoamerican gene-pool were located in distinct regions of the genome, suggesting differential genetic control in each of the pools for the traits of interest. Genomic selection looks to be a promising tool in several of the evaluated populations; offspring populations need to be evaluated to see if the understanding of variation in accuracy can be improved in the future. Genomic selection is particularly promising if the investment for genotyping can be used to predict several traits at a time, in which case also a lower accuracy trait can be added to a selection index.https://doi.org/10.7910/DVN/B3YLRF. Data presented in other studies: https://doi.org/10.7910/DVN/XCD67U and https://doi.org/10.7910/DVN/JR4X4C, as published by The SNP marker matrices, the raw and modeled phenotypic data, and genetic maps used in this study are available for download at Harvard Dataverse: SD, RR, NA, and CH carried out the field trial evaluations. SD, DA-S, JA, RR, H-PP, and BR did the phenotypic data analysis. HD and HR developed the hardware and software systems to measure cooking time. SD, DA-S, and RR performed the genotypic data analysis. SD and DA-S did the association, linkage analysis, and genomic prediction models. SD, DA-S, and BR wrote the manuscript. All authors read, contributed to, and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ancestry informative markers are genetic markers that show distinct genetic divergences among different populations. These markers can be utilized to discern population substructures and estimate the ancestral origins of unknown individuals. Previously, we developed a multiplex system of 30 ancestry informative single nucleotide polymorphism (AISNP) loci to facilitate ancestral inferences in different continental populations. In the current study, we first compared the ancestry resolutions of the 30 AISNPs and the other previously reported AISNP panels for African, European, East Asian, South Asian and American populations. Next, the genetic components of the Xinjiang Hui group were further explored in comparison to these continental populations based on the 30 AISNPs. Genetic divergence analyses of the 30 AISNPs in these five continental populations revealed that most of the AISNPs showed high genetic differentiations between these populations. Ancestry analysis comparisons of the 30 AISNPs and other published AISNPs revealed that these 30 AISNPs had comparable efficiency to other AISNP panels. Genetic relationship analyses among the studied Hui group and other continental populations demonstrated that the Hui group had close genetic affinities with East Asian populations and might share the genetic ancestries with East Asian populations. Overall, the 30 AISNPs can be used to predict the bio-geographical origins of different continental populations. Moreover, the obtained genetic data of 30 AISNPs in the Hui group can further enrich the extant reference data, which can be used as reference data for ancestry analyses of the Hui group. A bio-geographical origin analysis can determine the population substructures in a genome-wide association study . This tyNext generation sequencing (NGS), which refers to massively parallel sequencing, can simultaneously detect a number of genetic markers in an experiment. More importantly, it can provide more information than capillary electrophoresis, such as sequence variations and other genetic variations in the neighboring regions of the targeted markers ,9. RecenThe Hui group—the second largest minority group in China—includes more than ten million individuals, according to the report of the sixth nationwide population census. Hui individuals are distributed in many regions, including Ningxia, Xinjiang, Gansu, Yunnan provinces and etc . PreviouPreviously, we selected 30 novel AISNPs for distinguishing African, European, East Asian and South Asian populations and constructed a multiplex system based on the NGS platform . Here, tThe bloodstain samples of 98 Hui individuals in China were collected with their written informed consent. Twenty-six populations from five continents were used as reference populations; the genetic data for 30 AISNPs in these populations were obtained from the 1000 Genomes Project . This reDNA samples were isolated from bloodstain cards using a Magbead Blood Spots DNA Kit  according to the manufacturer’s description. The DNA concentration of each sample was determined using a NanoDrop 2000 instrument . The primer designs for the 30 AISNP loci were conducted using the Primer Premier v6.23 software , and then these primers were mixed into the Primer Mix. Primer information of 30 AISNPs was presented in The DNA library was prepared by two-rounds PCR. Detailed information of two-rounds PCR was shown in http://broadinstitute.github.io/picard/), and mapping reads were used to detect variations. Genetic variations of the 30 AISNP loci were detected by the GATK [p value > 0.05, output vcf = 1, min reads > 2) in the VarScan software [Paired-end sequencing with a read length of 150 bp was conducted on the Illumina NextSeq 500 platform that could produce 100–200 G data in a run. A total of 150 cycles were used to conduct sequencing; other parameters were set according to the manufacturer’s recommendation. Raw data for each individual were saved in the FASTQ format after sequencing. By filtering the sequences with low-quality reads (<80 bp) and sequencing adapters, clean data were obtained from the raw data using the Cutadapt software . After qthe GATK  and the software .Fst) and the informativeness-for-assignment (In) values of the 30 AISNPs between one continent and the other four continents were calculated by the AncestrySNPminer online tool . Then, the Fst and In values of the 30 AISNPs in all continental populations were calculated according to the previous report [http://mathgene.usc.es/snipper/). The correlation coefficient r2 values of pairwise AISNP loci in the Hui group were estimated by the Haploview software v4.2 [The allele coverage ratio (ACR) of each AISNP locus was calculated by the following formula: minor allele coverage/major allele coverage. The Hardy–Weinberg equilibrium (HWE) tests of 30 AISNPs in the Xinjiang Hui group were performed using the Genepop software v4.0  with thes report . By seleare v4.2 . The hethttps://www.xlstat.com). Nei’s AD distances among the Hui group and 26 reference populations were estimated by the DISPAN software [AD values. The pairwise Fst values of the Hui group and other reference populations were calculated using the Genepop software v4.0, and the heatmap of pairwise Fst values was built with the R software v3.3 [K values 2–6; the detailed parameters used in the ADMIXTURE software were as follows: we used the block relaxation algorithm (optimization method), and the log-likelihood increased by less than 10−4 (termination criteria). Then, the estimated ancestral components of these populations were displayed as a bar plot by the CLUMPAK online tool [The population genetic relationships between the Hui group and the 26 reference populations from five continents were determined based on the 30 AISNPs. Principal component analyses (PCAs) of the Hui group and different continental populations were performed using the XLSTAT program  that is the number of sequencing target regions is usually used as the metric to evaluate the data generated from massively parallel sequencing. For the ForenSeqresearch . Guo et research . In thisACR can evaluate the heterozygosity balance or intralocus balance: the locus that has a higher ACR is more beneficial for mixture analysis . Since tFst and In values can also be used as the metrics for evaluating the power of genetic markers to distinguish different populations [Fst and In values of 30 AISNPs in these continental populations, as shown in Fst and In values. Furthermore, relatively low Fst and In values (<0.10) in South Asian vs. other continental populations, and American vs. other continental populations were observed for most AISNP loci, indicating that these AISNPs might have lower divergences between South Asian/American populations and other continental populations. The Fst and In values of the 30 AISNPs among all continental populations were shown in Fst and In values ranged from 0.07 to 0.62, and from 0.04 to 0.34, respectively.Based on the genetic data of the five continental populations in the 1000 Genomes Project, we evaluated the genetic divergences of these AISNPs among these continental populations. δ values are the allelic frequency differences of the genetic markers in different populations, which can measure the genetic divergences of the markers . Generalulations . Thus, wThe cross-validation analysis in the Snipper software can re-estimate the allelic frequencies of genetic markers in training populations after randomly removing one sample successively and then can infer the ancestral origin of the removed individual based on the remaining dataset. This analysis can evaluate the values of a set of novel AISNPs to infer ancestry . Cross-vp-values of HWE tests for 30 AISNPs in the Hui group were presented in p-values of these AISNPs were larger than 0.05, except for the rs590086 locus. Nonetheless, these 29 AISNP loci conformed to HWE in the Hui group after applying Bonferroni correction (p = 0.05/29 = 0.0017). We also described the results of linkage disequilibrium analyses of 30 AISNPs in the studied Hui group, revealing that the pairwise r2 values of these AISNPs were less than 0.1  between pairwise populations. The AD distance can give a reliable population phylogenetic tree [AD distances, as shown in AD distances demonstrated that the Hui group featured minor genetic differences from East Asian populations. We also assessed the pairwise Fst values of Hui group and other continental populations, as shown in Fst values compared to East Asian populations. The ADMIXTURE software can discern a population’s substructure, estimate ancestry components, and study the admixtures between populations [K values, populations from the same continent showed similar genetic component distributions. However, American populations showed admixed ancestral proportions of European and East Asian populations. Secondly, no further distinctions could be made between the Hui group and East Asian populations, revealing close genetic affinities between Hui group and these East Asian populations.Based on the 30 selected AISNPs, we explored the population genetic relationships among the studied Hui group and other continental populations using multiple methods. PCA is one of the multivariate analysis methods; it can extract the most important variables that account for most information in the raw dataset. By reducing the dimensionality of the dataset, the studied subjects can be graphically represented in a two-dimensional plane, which can visually recognize the relationships between these subjects . Thus, wtic tree . Next, wulations . To furtYao et al. investigated the genetic structure of the Hui group residing in Gansu province via autosomal STR loci and found that the Hui group might have common genetic ancestry with East Asian populations . He et aIn this study, we compared the ancestry resolutions of previously selected 30 AISNPs and other published AISNP panels and found that studied 30 AISNPs could be used for ancestry analyses of African, East Asian, European and South Asian populations. The obtained population data of 30 AISNPs in the Xinjiang Hui group can be employed as reference data for ancestry origin analysis of the Hui group. Furthermore, population genetic analysis between the studied Hui group and other continental populations based on 30 AISNPs revealed that the Hui group might have similar ancestry origins with East Asian populations.


Pinctada fucata, in the Indo‐Pacific Ocean using genome‐wide genotyping data from multiple sampling localities. Cluster analysis showed that the western Pacific population is distinct from that of the Indian Ocean, and that it is divided into northern (Japanese mainland) and southern  populations. Genetic differentiation of P. fucata can be explained by geographic barriers in the Indian Ocean and a local lagoon, and by environmental gradients of sea surface temperature (SST) and oxygen concentration in the western Pacific. A genome scan showed evidence of adaptive evolution in genomic loci, possibly associated with changes in environmental factors, including SST and oxygen concentration. Furthermore, Bayesian simulation demonstrated that the past population expansion and division are congruent with ocean warming after the last glacial period. It is highly likely that the environmental gradient forms a genetic barrier that diversifies P. fucata populations in the western Pacific. This hypothesis helps to explain genetic differentiation and possible speciation of marine invertebrates.In the open ocean without terrain boundaries, marine invertebrates with pelagic larvae can migrate long distances using ocean currents, suggesting reduced genetic diversification. Contrary to this assumption, however, genetic differentiation is often observed in marine invertebrates. In the present study, we sought to explain how population structure is established in the western Pacific Ocean, where the strong Kuroshio Current maintains high levels of gene flow from south to north, presumably promoting genetic homogeneity. We determined the population structure of the pearl oyster,  In marine environments, ocean currents advect pelagic organisms from one locality to another, allowing wide distributions. Marine animals with long pelagic larval periods can potentially disperse hundreds or thousands of kilometers Shanks, . This loDispersal of marine organisms is, however, confined by geographic factors such as ocean currents and terrain boundaries, and by environmental conditions such as sea surface temperature (SST), oxygen concentration, and salinity. Steady ocean currents restrict the direction of gene flow between localities, resulting in spatial patterns of population structure , shows homogeneity from the Nansei Islands to the Japanese mainland      sequencing and retrieved genome‐wide SNPs from 22.1Pinctada fucata, from five regions in East and South‐East Asia , Cambodia (KHM), and Myanmar (MMR) were also analyzed  on a Maxwell® RSC Instrument (Promega), according to the manufacturer's standard protocol. Then, it was quantified using a NanoDrop™ 1,000 Spectrophotometer (Thermo Fisher Scientific).Genomic DNA was extracted from tissues using a MaxwellFor restriction site‐associated DNA sequence (RAD‐seq) library preparation, genomic DNA was digested with HinfI (NEB) and ligated to a paired‐end sequencing adaptor with a set of 4–8 base barcodes  using T2.3P. fucata reference genome assembly version 2.0 . Reads were then demultiplexed using reaper and tally, parts of Kraken software tools  was performed on all individuals using PLINK 1.9  that minimized marginal likelihood using the "chooseK.py" script provided in the fastSTRUCTURE package. We also conducted discriminant analysis of principal components (DAPC) in R using the adegenet library   was used for estimating the test statistics. An R package q value  using the vegan package in R   were used to retrieve ecological values at 22 sampling localities in the Japanese mainland and the Nansei Islands (JPN_1‐17 and NAN_18‐22). Samples from China, Cambodia, and Myanmar were excluded from the analysis since precise sampling localities were unavailable. Seasonal ecological values (quarterly averages over 8 years) of each environmental factor except CO2 were calculated. For CO2 concentration, an annual average over 19 years was used. These ecological values were scaled for further analyses. Geographic distances between localities were calculated using the Imap package in R  method  the genus Pinctada is mainly distributed in tropical and subtropical areas at present  fossils of P. fucata are absent during the LGP in Japan  analysis  per individual. After quality filtering Table , reads w3.2P. fucata in the region  of all samples showed a distinct population structure of  Figures  and S1. P. fucata was also confirmed with pairwise values of FST and Nei's distance among populations  except for the populations from Anamizu (JPN_04) and Kamikoshiki Island (JPN_17), which are distinguishable from all other JPN populations  with significant q‐values (q = 0.00) for the FST. Genetic distances among southern populations  showed relatively low values . The MMR population is distant from other sites , demonstrating that the population in the Indian Ocean is distinct from that in the western Pacific. A neighbor‐joining tree based on the Nei's distance , the southwestern Pacific , and the northwestern Pacific (JPN), respectively  The MMR population is clearly separated from the western Pacific population, (b) in the western Pacific, northern and southern populations are significantly differentiated, and (c) in JPN region, individuals of Kamikoshiki Island (JPN_17) are distinct from the rest of the northern population.3.3The genomic scan demonstrated outlier loci that may be associated with adaptation to local environmental variables such as temperature and oxygen concentration. BayeScan, PCAdapt and OutFLANK analyses detected signatures of non‐neutral selection at 72 (66 + 6), 289 (66 + 190+33), and 935 (6 + 66+190 + 673) loci, respectively  than in the all‐SNP dataset (R2 = 2.4%–5%).To test the correlation between genetic variation and environmental variables, a series of RDA was performed Figure . When anBased on the RDA results, SNP loci possibly associated with adaptation to local environments were investigated Table . In tota3.5P. fucata that has shaped current population structure after the LGP in the western Pacific. Using DIYABC, we tested two hypotheses: expansion (scenario 1) and migration (scenario 2)  and timing of population events (t) were set as shown in Table Next, we addressed the demographic history of ) Figure a. Prior scenario   to the Nansei Archipelago (NAN) Figure . The proP. fucata by considering results of present population genetics , separated the Pacific and the Atlantic Oceans  exemplifies small‐scale, but distinct allopatric differentiation by a geographic barrier. Pearl oysters inhabit a coastal lagoon called Lake Namako‐ike on the shore of the island. The lake is completely isolated from the open sea by a coastal gravel bar with no tidal inlets. The geological barrier, established in mid‐Holocene about 5,000–6,000 years ago    and a local lagoon in Kamikoshiki Island (JPN_17), whereas environmental gradients can shape large‐scale population differentiation in the western Pacific (northern and southern populations). Genomic loci that may be associated with adaptation to the local environment were identified. The present study highlights demographic history affected by environmental changes that explain the extant marine population in the western Pacific. In addition, the population structure demonstrated by the present study should provide essential information for genetic conservation of the pearl oyster.Using genome‐wide genotyping data, we determined the population structure of None declared. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.