TM plus PCR Amplification kit. We reported allelic frequency and forensic parameters in different dataset: combined ethnic Lao groups, combined Lao Isan populations and combined Laotians. Overall, the forensic parameter results indicate that this set of STRs is suitable for forensic investigation. The anthropological results revealed the genetic homogeneity of Tai-Kadai speaking Lao groups from Thailand and Laos, consistent with previous studies, while the Austroasiatic speaking groups from southern Laos showed genetic relatedness to both Lao Isan and Khmer. In sum, STRs allelic frequency results can provide the genetic backgrounds of populations which is useful for anthropological research and also strengthens the regional forensic database in both countries.The Lao Isan and Laotian are the major groups in the area of present-day northeastern Thailand and Laos, respectively. Several previous genetic and forensic studies indicated an admixed genetic structure of Lao Isan with the local Austroasiatic speaking groups, e.g. Khmer, whereas there is a paucity of reporting Laotian’s forensic short tandem repeats (STRs). Here, we newly generated 451 genotypes of seven Lao Isan and three Laotian populations (two Lao Lum and one Lao Thoeng) using 23 autosomal STRs embedded in Verifiler As lands with much common history, the areas of present-day Laos and Thailand share multiple cultural and historical perspectives  and a boIn Laos, geographic criteria are generally used to grouping populations; the major TK speaking Laotians or Lao Lum (∼4.3 million) inhabit in the lowland with various dialects spoken, e.g., Luang Prabang, Vientiane and Savannakhet . There ath century A.D. evidently attest that the Khmer are native to present-day northeastern Thailand prior to the arrival of the Lao , 1 insertion/deletion polymorphic marker on the Y chromosome (Y indel) and Amelogenin (sex-determining marker). This kit has already been validated following SWGDAM  guidelines  DNA and Y chromosome  and genoidelines . This prA total 451 genotypes that were newly generated for 23 autosomal STR loci belonged to ten populations: seven Lao Isan and three Laotian (two Lao Lum and one Lao Thoeng). Buccal swab samples of 39 volunteers from one Laotian population were newly collected from Savannakhet Province, southern Laos; this Austroasiatic-speaking Lao population (LA1) is called Lao Thoeng. To recruit samples, we interviewed volunteers to include subjects who were unrelated for at least two generations and then collected buccal samples with informed consent. Genomic DNA was extracted using the Gentra Puregene Buccal Cell Kit  according to the manufacturer’s instructions. An additional 412 genomic DNA samples from other Laotian and Lao Isan populations were retrieved from previous studies  Table 1Table 1. TM plus PCR amplification kit in a reaction volume of 25 µl with 5 µl of VeriFiler™ Plus PCR Master Mix (Applied Biosystems), 2.5 µl of the primer mix, and the remaining 17.5 µl composed of DNA template and water to adjust the DNA input amount to reach 500 pg. Amplification process was carried out on GeneAmp™ PCR System 9700 in the following conditions; 95°C for 1 min; 2 cycles: 96°C for 10 s, 62°C for 90 s; 27 cycle: 96°C for 10 s, 59°C for 90 s; 60°C for 5 min; 4°C for ∞. The PCR products were genotyped by multi-capillary electrophoresis in an ABI 3500 genetic analyzer (Applied Biosystems). The genotyping data were analyzed by Gene Mapper software v.3.7 (Applied Biosystem).We amplified 23 autosomal STR loci of all genomic samples using Verifilerp values, observed heterozygosity (HO), expected heterozygosity (HE), total alleles, and gene diversity (GD). Significant levels for the HWE were adjusted according to the sequential Bonferroni correction (α = 0.05/23) (STRAF (http://cmpg.unibe.ch/shiny/STRAF/), an online tool for STR data analysis (Arlequin v.3.5.2.2  was used0.05/23) . We usedanalysis , to compFst) using Arlequin, then plotting a matrix in three dimensions by means of multidimensional scaling (MDS) using Statistica v.10 demo . The heatmap visualization of Fst and MDS values were obtained using R package (R Development Core Team). To delineate cryptic population structure, a model-based cluster analysis was investigated by STRUCTURE 2.3.4 under the following prior parameters: admixture, correlated allele frequencies, and assistance of sampling locations (LOCPRIOR model)   . We ran ues (△K)  by STRUCues (△K)  in orderlue of K ; CLUMPAKlue of K .To reveal population relationships with other Thai populations, we collected previously published data of 15 STRs from 14 populations: BlackTai1, BlackTai2, Phutai, Phuan, Seak, Nyaw, Kaleang, Bru, Nyahkur, Mon, Soa, Khmer1, Khmer 2 and Suay . When thhttp://onlineconversion.com/map-greatcircle-distance.htm).Mantel test  in ArleqFst computation by allele frequency from 13 STRs with publicly accessible data from relevant populations  after Bonferroni adjustment (0.05/23 = 0.002) in exception with PentaE in LAO1 and D5S818 in LAO5 , forensic parameters; combined matching probability (CMP), combined power of exclusion (CPE) are presented in HE is greater than 0.7 in all studied populations, ranging from 0.7962 (LA3) to 0.7812 (LAO5). Total number of alleles is highest in LA3  and lowest in LAO6 . The GD ranges from 0.7763 ± 0.3858 in LAO3 to 0.7938 ± 0.3934 in LAO4.A total of 451 individual raw genotypes are provided in  in LAO5 . The genn = 412), comprising two Lao Lum (LA2-3) from Laos and seven Lao Isan (LAO1-7) from northeastern Thailand, is presented in D10S1248, TPOX) departed from the HWE (p > 0.05) after Bonferroni adjustment (0.05/23 = 0.002) , HO (0.9005), PIC (0.8699), TPI (5.0244), MP (0.0276), PD (0.9724) and PE (0.7964) with a combined power of discrimination (CPD) value of 0.999999999999999 and a CPE value of 0.999999995430163. The least polymorphic and discriminative locus was TPOX with the lowest HE (0.5629), HO (0.5122), PIC (0.5163), TPI (1.0250), MP (0.2391), PD (0.7609), PE (0.1984)  . There a(0.1984) .D16S539 and D5S818) to 23 alleles (FGA) (D10S1248) departed from HWE after Bonferroni correction (0.05/23 = 0.002). Among the tested loci, FGA was the most polymorphic and discriminative locus with highest HE (0.8837), HO (0.8957), PIC (0.8712), TPI (4.7931), MP (0.0275), PD (0.9725) and PE (0.7866) with a CPD value of 0.999999999999999 and a CPE value of 0.999999994092542. The least polymorphic and discriminative locus was TPOX with the lowest HE (0.5759), HO (0.5324), PIC (0.5280), TPI (1.0692), MP (0.2275), PD (0.7725), PE (0.2174)   and combes (FGA)  with the(0.2174) .D3S1358, D16S539, TPOX to 19 alleles at FGA and allelic frequency ranging from 0.0029 to 0.6170 (FGA was the most polymorphic and discriminative locus with highest HE (0.8844), HO (0.9017), PIC (0.8706), TPI (5.0882), MP (0.0314), PD (0.9686) and PE (0.7990) with a CPD value of 0.999999999999999 and a CPE value of 0.999999998686772. The least polymorphic and discriminative locus was TPOX with the lowest HE (0.5633), HO (0.5118), PIC (0.5143), TPI (1.0241), MP (0.2432), PD (0.7568), PE (0.1980) (In the combined Laotian (LA1-3) dataset, all of loci are in agreement with HWE even after Bonferroni correction. The total number of alleles is 233, varying from 6 alleles at o 0.6170 . Among t(0.1980) .TPOX had a PD value of more than 0.80  and high CPD values (more than 0.999999999999999) which reflects the high discriminatory power of these 23 loci. In addition, the CPE values were greater than 0.9999999 which indicate that these markers are undoubtedly acceptable for paternal and maternal identification in the studied populations (−23 (LAO6) to 1.2984 × 10−26 (LA3) in this study (−14 to 4.16 × 10−16) in previous studies using AmpFLSTR Identifiler kit  based on 23 STR loci and among 45 pairwise comparisons there are 36 pairs (80%) which showed statistical differences (p < 0.05) (K) from 2 to 10. The most appropriate △K are K = 5 and 7  and seven from northeastern Thailand (LAO1-7), we computed pairwise genetic distance ( < 0.05) . In gene < 0.05) , 3. For  and seve 5 and 7 . The LA1 5 and 7 , indicat 5 and 7 ; they ma 5 and 7 , reflect 5 and 7 .Fst value, three dimensions MDS plots and the model-based clustering STRUCTURE based on the 15 STR loci were analyzed. Among 276 pairwise comparisons of Fst value, there are 263 pairs (95.29%) with statistical differences (p < 0.05)  . The ethThailand  and LAO6Thailand . The MDSt value  revealedt value . The STRulations  and at K studies . Genetic studies . Interes studies , reflect studies ; 2021. Pr = 0.0689, p > 0.05 for dataset of 10 populations and r = -0.1570, p > 0.05 for dataset of 24 populations). Therefore, the overall genetic variation did not correlate with geography. In contrast to the previous study that reported correlation between mtDNA variations and geography in northeastern Thailand  were combined to one group (Lao Lum), while the LA1 was represented by Lao Thoeng (A neighbor-joining (NJ) tree based on o Thoeng . The Laoo Thoeng  and receo Thoeng .TM plus PCR amplification kit of the ethnic Lao groups from northeastern Thailand and Laos and AA-speaking Laotian from southern Laos. Although there have been some previous investigations on STRs in the region, only 15 loci were previously published. Here, we expanded the study, genotyping 23 STR loci, of which 8: D2S441, D22S1045, D10S1248, D1S1656, D12S391, D6S1043, Penta D, and Penta E were firstly reported. We generated allelic frequency table, calculated forensic parameters and investigated genetic relationships among populations. Previously there were much less forensic STRs data produced in Laos, compared to Thailand; this present study established the complete allelic frequency of STRs. Although no STRs in Laotians showed significant departure from HWE and few loci departed from HWE in other datasets, all forensic parameters indicate that this kit is suitable for forensic investigation. Genetic characterization showed that AA-speaking Laotian from southern Laos was genetically different from northern and central Lao groups who speak TK languages. In fact, the southern Laotian was more related to Lao Isan who live in vicinity. Although the Lao Isan migrated from Laos ∼200 years ago, the ethnic Lao groups (Lao Isan and TK-speaking Laotian) still showed closer genetic relatedness than the other ethnolinguistic groups, reflecting a common ancestry. In sum, the STRs allelic frequency results strengthen the regional forensic database in both countries and provide the genetic backgrounds of populations that are useful for anthropological research.This study genotyped 23 autosomal forensic STRs using Verifiler


Apis cerana, similar to the Western honey bee Apis mellifera, is distributed in different climatic conditions, and each of them is subdivided into more than thirty subspecies and ecotypes. Their sustainability depends on adaptations to the local climate conditions. The VG gene is involved in the development, reproduction, labor division, and caste differentiation of honey bees. We found the nucleotide sequences of the VG gene reflect the adaptation of honey bees to the local climate conditions. The VG gene sequences are acceptable tools to study the sustainability, genetic structure, and adaptation of A. cerana populations and can be applied in conservation genetics of local honey bee subspecies.The Oriental honey bee Apis cerana and Apis mellifera are important honey bee species in Asia. A. cerana populations are distributed from a cold, sharply continental climate in the north to a hot, subtropical climate in the south. Due to the Sacbrood virus, almost all A. cerana populations in Asia have declined significantly in recent decades and have recovered over the past five years. This could lead to a shift in the gene pool of local A. cerana populations that could affect their sustainability and adaptation. It was assumed that adaptation of honey bees could be observed by comparative analysis of the sequences of genes involved in development, labor division, and caste differentiation, such as the gene Vitellogenin VG. The VG gene nucleotide sequences were used to assess the genetic structure and signatures of adaptation of local populations of A. cerana from Korea, Russia, Japan, Nepal, and China. A. mellifera samples from India and Poland were used as the outgroup. The signatures of adaptive selection were found in the local population of A. cerana using VG gene sequence analysis based on Jukes–Cantor genetic distances, cluster analysis, dN/dS ratio evaluation, and Tajima’s D neutrality test. Based on analysis of the VG gene sequences, Apis cerana koreana subspecies in the Korean Peninsula were subdivided into three groups in accordance with their geographic localization from north to south. The VG gene sequences are acceptable tools to study the sustainability and adaptation of A. cerana populations. Apis cerana is the second most widely distributed honey bee species in Asia after Apis mellifera [A. cerana is the basic pollinator and producer of apiculture products in Asia [A. mellifera, A. cerana has high potential for further selection based on genetic markers [A. cerana embraces northern to southern Asia from Russia to Indonesia and eastern and western Asia from Japan to Afghanistan [A. cerana occupies a large range of climatic conditions at different altitudes and latitudes. Similar to A. mellifera, A. cerana has high genetic and phenotypic variations across a range and is subdivided into several ecotypes and subspecies [A. cerana reaches 47°54′ N latitude in Khabarovsky Krai of Russia [A. cerana in Japan (A. c. japonica), in China (A. c. cerana), in Korea (A. c. koreana), in Russia (A. c. ussuriensis), and in Vietnam (A. c. indica) are adapted to their native climate and contain genes linked with adaptation [A. cerana. All populations of A. cerana are understudied using genetic markers. A. cerana subspecies subdivision and their distribution range are studied insufficiently.ellifera . A. cera in Asia . Similar markers . The nathanistan . A. cerabspecies ,5,6. Theaptation . There aA. cerana in all populations significantly changed after the Sacbrood virus eliminated 95% of colonies [A. cerana entails a reduction in the biodiversity of local ecosystems. A. cerana and A. mellifera are not equivalent pollinators of native plants; they cannot replace each other [The gene pool of colonies ,9,10. Decolonies ,8,9. Thech other ,4,11.A. cerana has undergone hybridization that violates the adaptive complexes of its gene pool. Additionally, the genetic pool of local populations of subspecies A. cerana may be completely replaced by the genetic pool of introduced subspecies A. cerana. Conservation of the subspecies A. cerana cannot take place without molecular genetic methods. Genetic markers related to adaptation should be found in genes involved in the development and caste differentiation of A. cerana [A. cerana and study its phylogeography.Within its natural range, the local subspecies of . cerana ,13. MoleVG, is a basic reproductive protein and endocrine development factor, which, together with juvenile hormone JH and insulin-like growth factor IGF, is responsible for the caste differentiation and development of A. cerana. VG is a source of the royal jelly produced by workers and fed to larvae, so just as it affects queen egg laying, it may also affect the rearing of larvae hatching from those eggs. Moreover, VG plays an important role in regulating the labor division that can impact colony fitness by affecting colony foraging rates, foraging efficiency, and growth rates. The VG gene has high rates of molecular evolution in the honey bee, as evident by high rates of within-A. mellifera polymorphisms and high rates of divergence in the genus Apis. The VG gene is located on the fourth chromosome of A. mellifera, which has the highest recombination rate (27.6 cM ⁄ Mb) among all 16 chromosomes. The recombination rate in the VG gene is 5.9 times higher than in other genes [VG gene expression paces feeding behavior and induces shifts in the caste differentiation of A. mellifera [VG gene is connected to the spatial distribution and population structure of A. mellifera [VG gene showed adaptation signatures in A. mellifera populations [VG gene has not been previously studied in A. cerana in the aspects of population genetics.Vitellogenin, er genes ,14,15,16ellifera . The VG ellifera ,17. Compulations . The VG VG gene could be useful for the study of the evolutionary adaptation and population structure of A. cerana. Comparative analysis of VG gene sequences promises to yield interesting results regarding the relationship and distribution of local A. cerana populations in Korea, Russia, Japan, Nepal, and China. The signatures of adaptive selection could be found in the local population of A. cerana based on Jukes–Cantor genetic distances, cluster analysis, and Tajima’s D neutrality test. The aim of the paper is to study the genetic signatures of climate adaptation in Apis cerana populations using nucleotide sequences of the VG gene. The objectives of the paper are to sequence the VG gene exons and perform comparative cluster analysis with reference sequences from GenBank.The A. cerana using VG gene sequence analysis based on Jukes–Cantor genetic distances, cluster analysis, and Tajima’s D neutrality test. The subdivision into three groups in accordance with climate adaptation was found in Apis cerana koreana subspecies population in the Korean Peninsula. Thus, the VG gene sequences are acceptable tools to study the sustainability and adaptation of A. cerana populations.In this paper, the signatures of adaptive evolution were found in the local population of A. cerana were collected from the following five Asian countries: (1) South Korea , (2) Japan , (3) Taiwan , (4) Nepal (province Bagmati Pradesh), and (5) Russia (Primorsky Territory) (The worker bees of rritory) . Worker sh), and  Russia (VG gene of A. cerana (The polymerase chain reaction (PCR) with our primers developed for exons of the . cerana  performe. cerana , 0.5 μL A. cerana and A. mellifera) were deposited to GenBank (All PCR products were purified using the QIAquick PCR Purification Kit (250)  following the instructions of the manufacturer. The PCR products were sequenced on both strands in Macrogen Inc.  using the ABI 3730xl 96-capillary DNA analyzer  and the ABI BigDye Terminator v3.1 Cycle Sequencing Kit . All sequences were analyzed and submitted to GenBank  . In tota GenBank .VG gene sequences of A. cerana and A. mellifera was performed using Clustal W methods of alignment of nucleotide sequences of honey bee samples retrieved from GenBank in MEGA v. 10.0.5 at the Division of Life Sciences of Incheon National University [VG gene exons of A. cerana and A. mellifera were retrieved from GenBank  was calculated for homologous genes. The significance of Tajima’s D test was determined using coalescent simulations with 10,000 runs as implemented in DNAsp [Pairwise nucleotide sequence divergences were estimated using Unipro UGENE 1.28  and CLC Genomics Workbench 11  based on the or model . Pairwisin DNAsp .VG gene sequences using the Nei–Gojobori method [A phylogenetic tree was constructed using the neighbor-joining method, the Jukes–Cantor model, and 1000 bootstrap replications . The peri method .A. cerana samples was evaluated. The dN/dS ratio remains one of the most popular and reliable measures of evolutionary pressures in coding regions. The dN/dS ratio provides information about the evolutionary forces operating on a particular gene [The dN/dS ratio between all lar gene . The dN/lar gene .A. cerana populations from different local populations based on the VG gene sequences. Tajima’s D test is a statistical method for testing the neutral mutation hypothesis by DNA polymorphism [We performed Tajima’s D neutrality test for morphism . Tajima’morphism . The purmorphism .VG gene sequences of A. cerana collected from Korea, Russia, Japan, Nepal, and China were first sequenced (with an average size of 4125 bp) and then aligned with the VG gene sequences of A. cerana and outgroup sequences of A. mellifera (with an average size of 4128bp) retrieved from GenBank , the ratio of nonsynonymous to synonymous substitutions (dN/dS), and Jukes–Cantor genetic distances, were assessed on twenty-one populations (twenty populations of A. cerana and one outgroup population of A. mellifera) (All samples of llifera) .A. cerana populations and from 249 to 270 between A. cerana and A. mellifera populations. The minimal number of nucleotide differences including transitions + transversions varied from 10 to 12 between Korean A. cerana populations . The maximal number of nucleotide differences including transitions + transversions varied from 50 to 61 between Russian and Chinese , Japanese (Kyoto), and Nepalese (Kathmandu) populations of A. cerana.The number of nucleotide differences including transitions + transversions varied from 10 to 61 between A. cerana populations and from 0.496 to 0.538 between A. cerana and A. mellifera populations. The minimal dN/dS ratio varied from 0.236 to 0.295 between Korean  and Japanese  A. cerana populations. The maximal dN/dS ratio varied from 0.711 to 0.999 between Korean , Korean and Japanese (Hongcheon–Kyoto), and Korean and Russian (Samcheok–Vladivostok) A. cerana populations.The dN/dS ratio varied from 0.236 to 0.999 between A. cerana populations and from 0.065 to 0.070 between A. cerana and A. mellifera populations. The minimal Jukes–Cantor genetic distances varied from 0.002 to 0.003 between Korean  A. cerana populations. The maximal Jukes–Cantor genetic distances varied from 0.012 to 0.015 between Russian and Korean , Russian and Japanese (Vladivostok–Kyoto), Russian and Chinese , and Russian and Nepalese (Vladivostok–Kathmandu) A. cerana populations.The Jukes–Cantor genetic distances varied from 0.002 to 0.015 between VG gene sequences based on Jukes–Cantor genetic distances using the neighbor-joining method of clustering and 1000 bootstrap replications , the ratio of nonsynonymous to synonymous substitutions (dN/dS), and Jukes–Cantor genetic distances, were assessed on six populations (five populations of A. cerana and one outgroup population of A. mellifera)  .A. cerana populations and from 255.1 to 269.8 between A. cerana and A. mellifera populations. The minimal number of nucleotide differences, including transitions and transversions, varied from 20.6 to 28.8 between Japanese–Korean and Japanese–Nepalese A. cerana populations. The maximal number of nucleotide differences, including transitions and transversions, varied from 51.5 to 54.3 between Russian–Chinese and Russian–Nepalese A. cerana populations  and Japanese  A. cerana populations. The maximal dN/dS ratio varied from 0.711 to 0.999 between Korean , Korean and Japanese (Hongcheon–Kyoto), and Korean and Russian (Samcheok–Vladivostok) A. cerana populations.The average dN/dS ratio varied from 0.236 to 0.999 between VG gene sequences, the dN/dS ratio between all A. cerana and the A. mellifera outgroup populations, varied from 20.6 to 269.8  and southern  countries and outgroup samples of A. mellifera, to find genetic signatures of adaptations to the local environments based on the nucleotide polymorphism of the nuclear VG gene. Both A. cerana and A. mellifera species have similar exon–intron structures and differ only by nucleotide sequences  was observed between Korean and Japanese populations of A. cerana (A. cerana and A. mellifera outgroup populations were highest (255.1–269.8), which demonstrates their significant divergence. We counted the number of nucleotide differences between the VG gene sequences within the northern populations of A. cerana, which varied from 10 to 52 (the average was 21.9). Additionally, we counted the number of nucleotide differences in the VG gene sequences between the northern and southern populations of A. cerana, which varied from 22 to 61 (the average was 32.4)  . Here, tA. cerana samples varied from 0.158 to 0.999, which demonstrates the functional significance of the VG gene such that nonsynonymous amino acid substitutions are deleterious and purged from the population. Indeed, the VG gene affects multiple aspects of social organization of honey bee colonies and plays a key role in the caste differentiation and maintenance of honey bees. The dN/dS ratio between the northern populations of A. cerana varied from 0.158 to 0.999 (the average was 0.46), which indicates strong negative selection for the VG gene, which characterizes the high significance of the VG gene’s conservativeness in the adaptation of A. cerana to the cold northern climate. Positive selection leads to fixation changes in genes, and negative, or purifying, selection leads to rejection changes in genes. The dN/dS ratio between the northern and southern populations of A. cerana varied from 0.289 to 0.947 (the average was 0.49)  , which i climate . It has  species . On the er genes . Hence, VG gene sequences between A. cerana populations varied from 0.002 to 0.015, and between A. cerana and A. mellifera populations varied from 0.065 to 0.070. The Jukes–Cantor genetic distances based on the VG gene sequences between the northern populations of A. cerana varied from 0.002 to 0.013 (the average was 0.005). The Jukes–Cantor genetic distances based on the VG gene sequences between the northern and southern populations of A. cerana varied from 0.005 to 0.015 (the average was 0.010)  based on the COX1 gene of mtDNA [A. mellifera, A. cerana) based on complete mtDNA [A. cerana; varied from 0.075 to 0.081 between species A. mellifera and A. cerana based on the VG gene of nDNA [Anastrepha based on the COX1 gene of mtDNA [Apis based on the CYTB gene of mtDNA [VG gene sequences between A. cerana populations from similar climatic conditions is half that between A. cerana populations from different climatic conditions. This can explain the important role of the VG gene in the adaptation of A. cerana populations to different climatic conditions from northern to southern Asia. The phylogenetic tree constructed using the neighbor-joining method with the Jukes–Cantor genetic distances based on the VG gene sequences  . In compof mtDNA ; was 0.1te mtDNA ; varied of mtDNA ; and varof mtDNA . Thus, tequences  shows thPCA plot . MoreoveA. cerana. Almost all of the estimated D values in A. cerana bees were not significantly different from zero, implying that A. cerana honey bees are in a state of mutation drift equilibrium [A. cerana and highest in the Chinese population of A. cerana. This may be due to the high genetic diversity that should be observed in the largest Chinese population of A. cerana. The nucleotide diversity was highest in the Russian population of A. cerana and lowest in the Korean population of A. cerana. This can be explained by the fact that the A. cerana population in Russia is feral under natural selection. There are no managed A. cerana populations in Russia , which means that this population could be in a state of bottleneck, selective sweep, purifying selection, and negative selection. Indeed, the Korean population of A. c. cerana experienced an extreme population decline with the kSBV virus, which killed 95% of the local population [A. cerana also had the signatures of the population size expansion after a selective sweep in the past (COX1 gene sequences varied from −1.369 to 2.383 in the Guangdong Province population of A. c. cerana, from −2.293 to −0.048 in the Guangxi Autonomous Region population of A. c. cerana, from −1.670 to 1.276 in the Hainan Island population of A. c. cerana, and from −1.622 to 2.383 in the mainland China population of A. c. cerana [A. cerana based on VG gene sequences were similar to those in China based on the mitochondrial COX1 gene. Thus, both nuclear and mitochondrial genes showed similar results for A. cerana populations, which were characterized by an excess of low-frequency polymorphisms relative to expectations, indicating population size expansion after a bottleneck due to the Sacbrood virus. The Tajima’s D test values and dN/dS ratio can be used as indicators for negative selection and the role of some genes in adaptation of local A. cerana populations [The values of Tajima’s D test in all pulation ,9,10,32.the past . For com. cerana . The valulations .A. cerana populations from South Korea in comparison with A. cerana populations from Russia, Japan, Nepal, and China and the outgroup population of A. mellifera. Based on the VG gene sequences, we assessed the negative selection that characterizes adaptation in A. cerana populations to the local climatic conditions. The cluster and principal component analysis based on the sequences of the VG gene divided populations of A. cerana according to their climatic and geographic distribution into southern and northern groups. The local populations of A. c. koreana were subdivided according to their geographical distribution into southern, northern, and central Korean clusters. The Jukes–Cantor genetic distances based on the VG gene sequences showed the A. cerana populations from northern countries such as Korea, Russia, and Japan are more closely related to each other than the southern populations of A. cerana. The signatures of adaptation were found in the local population of A. cerana. All A. cerana populations showed signs of population size expansion following recent declines. The VG gene sequences can be used as informative markers for monitoring the genetic structure and adaptation processes in A. cerana populations.We performed a thorough genetic analysis on


Alosa) that have independently evolved life cycles entirely completed in freshwater. Three naturally diverged , and the fourth  was artificially landlocked during the last century. To conduct this analysis, we assembled and annotated a draft of the A. alosa genome and generated whole‐genome sequencing for 16 anadromous and freshwater populations of shad. Widespread evidence for parallel genetic changes in freshwater populations within lineages was found. In freshwater A. alosa, which have only been diverging for tens of generations, this shows that parallel adaptive evolution can rapidly occur. However, parallel genetic changes across lineages were comparatively rare. The degree of genetic parallelism was not strongly related to the number of shared polymorphisms between lineages, thus suggesting that other factors such as divergence among ancestral populations or environmental variation may influence genetic parallelism across these lineages. These overall patterns were exemplified by genetic differentiation involving a paralog of ATPase‐α1 that appears to be under selection in just two of the more distantly related lineages studied, A. f. lacustris and A. alosa. Our findings provide insights into the genetic architecture of adaptation and parallel evolution along a continuum of population divergence.Studying the genetics of phenotypic convergence can yield important insights into adaptive evolution. Here, we conducted a comparative genomic study of four lineages (species and subspecies) of anadromous shad ( Here, we studied the genomics of adaptation in anadromous shad that have evolved a completely freshwater life cycle. This included conducting genome scans with a de novo genome assembly and pool‐seq data for 16 populations of shad. We used these data to study patterns of parallel genetic evolution within and across the four lineages examined. When suThe likelihood of parallel evolution can depend on several factors. In the absence of gene flow, unless populations share advantageous polymorphisms, parallelism is dependent upon the same, or similar, alleles arising via de novo mutation within each newly colonized location or ecological setting  , Ireland (A. f. killarnensis), and Greece (A. macedonica) and naturally diverged sometimes during the last 30 thousand years after the retreat of the last Pleistocene glaciers  are the smallest of the three lineages that exist, suggesting the adaptive process is ongoing in this lineage. Studying the evolution of these freshwater shads is therefore an excellent opportunity to gain insight into the factors that influence parallelism including the phylogenetic and temporal scales at which it occurs and the impacts of gene flow.To further our understanding of these topics, we studied the genetics of adaptation in four independent lineages of Eurasian shad  Linck,  that are) Linck, . These a) Linck, . Second,) Linck, . Lastly,A. alosa and conducted whole‐genome resequencing to identify loci that may be under natural selection in freshwater populations of shad. The resulting data were then used to determine whether parallel genetic evolution may have occurred within or across the lineages studied. Here, “parallel evolution” or “parallelism” refers to allele frequency changes in the same gene or genomic region, but not necessarily the same mutation. Loci involved in adaptation to freshwater in these lineages were identified by searching for genomic regions with extraordinary differences in allele frequencies between anadromous and freshwater populations. Such genome scans have yielded some of the most influential insights into the genetic architecture of adaptation and speciation  genome was assembled using a combination of data from short‐read and mate‐pair sequencing libraries. For contig building, one 250‐bp insert library with overlapping reads (2×150 bp paired‐end) was generated using Illumina paired‐end chemistry (V2) and run on three lanes of an Illumina MiSeq 2500. Scaffolding was accomplished by mate‐pair libraries (insert sizes 3 kilobases (kb), 5 kb, 7 kb, and 10 kb) made using the Nextera Mate‐Pair Library Preparation Kit (Illumina). The mate‐pair libraries were multiplexed and run together on three lanes of an Illumina HiSeq 1500. In addition, a 20‐kb mate‐pair dataset was generated by Lucigen Corporation. The A. alosa genome was assembled using ALLPATHS‐LG‐52488  and RepBase23.02. Intron/exon boundaries were inferred by aligning RNA‐seq data generated from liver, muscle, and gill tissue types  between anadromous and freshwater populations within each of the four lineages described in the previous section. To reduce the effect of population history, ΔAF estimates were standardized by subtracting each from the genome‐wide mean (per lineage) and then dividing by the standard deviation. Allele frequency differences between all possible pairs of anadromous and freshwater populations within each lineage were then averaged. Finally, a sliding window approach was used where genomic windows were defined as the average ΔAF for 20 consecutive SNP loci along each scaffold and calculated every 10 SNPs . To avoid high error rates associated with smaller scaffolds enriched with repetitive sequences, windows were only calculated for the largest 1000 scaffolds, which physically covered 813Mb or 91% of the The statistical significance of extreme values of average ΔAF in each lineage was then evaluated using permutations. In each permutation, populations were randomly assigned as anadromous or landlocked, and then, the ΔAF for each SNP window was calculated as described earlier with the exception that the starting location to begin counting consecutive SNPs was randomly chosen to range from 1 to 20, which allows for all possible window combinations of 20‐SNP windows to be sampled. A thousand permutations were conducted per lineage. Significant ΔAF can be a consequence of divergent selection or genetic hitchhiking  to analyze our pool‐seq data with two main goals in mind. First, we tested whether patterns of DXY and Tajima's D in nonoutlier  and outlier regions identified at the 99.9th percentile cutoff level showed signatures of natural selection. For these comparisons, Tajima's D was examined separately in each of the 16 populations studied, while DXY was averaged across all anadromous‐landlocked population pairs per lineage. Second, previous research has shown that mutations maintained by natural selection sometimes segregate in large haplotypes . Similarly, pairwise comparisons of outlier regions in populations from different lineages were conducted. We then estimated the amount of polymorphism shared by each pair of lineages. For this analysis, and throughout the text, a polymorphic site refers to any SNP we found using our methods above that was variable, or fixed for an alternative allele, in at least one of the populations (anadromous or freshwater) studied in a given lineage. Since the total number of SNP loci per lineage varied, we calculated the average of the percentage of SNPs shared in each lineage of the pair being examined. To help understand patterns of parallelism, we then compared the percentage of outlier regions shared by populations to the percentage of polymorphism common between their respective lineages.We studied parallelism within the only two lineages in our study that have multiple freshwater populations, s Figure . To measLastly, to help visualize patterns of genetic convergence across lineages, we generated heat maps of ΔAF for all outlier windows. One heat map was made per lineage. Specifically, for each ΔAF window in the 99.9th percentile of the target lineage, the average ΔAF for all SNPs in the same genomic window in each of the other three lineages was calculated. If the corresponding genomic window had fewer than two SNPs, it was excluded from the analysis.2.6A. alosa genome assembly. Studying comprehensive sets of gene copies from both closely related and moderately divergent species relative to the in‐group can increase accuracy when using phylogenetic methods to infer orthology  and a clupeid (like Alosa), Atlantic herring (Clupea harengus). Sequences of alewife (A. pseudoharengus) and several outgroups were also included  . To measure how phylogenetically conserved each amino acid site is across fish species, we aligned the protein sequences for all ATPase‐α1 found in the A. alosa genome annotation and several other fish highly divergent species listed in Table ATPase‐α1.1b shared by A. alosa and A. f. lacustris , we counted the number of cases where any nonsynonymous mutation shared by A. alosa and A. f. lacustris was also in the top 95th percentile of ΔAF (per site) between anadromous and freshwater populations in each lineage.To investigate the potential importance of three nonsynonymous substitutions in l et al. , the pro33.1A. alosa using short‐read and mate‐pair DNA data from a single, wild‐caught individual using the ALLPATHS‐LG‐52488 assembler. The size of the A. alosa genome was estimated to be 889 Mb using the k‐mer method  and 11.3% were present and incomplete, leaving 17.2% missing. While the assembly was sufficiently complete to identify hundreds of candidate regions in each lineage, a significant proportion of loci involved in adaption may have been missed.To allow us to conduct genome‐wide scans for candidate loci in freshwater shad, we generated a draft genome of od Table . The resod Table , and theod Table , the sho3.2A. alosa we examined were all founded after being trapped behind dams built in unconnected drainages during the past century , approximately two to three times higher than the other three lineages   from 16 populations of shad representing four different lineages of ) Tables .Allele frequencies for the resulting SNP loci were then used to conduct genome scans for candidate loci in each of the four lineages studied using a sliding window approach and permutation tests. The effect of natural selection on SNP allele frequencies can be highly variable even when selection is strong  per lineage identified using PCadapt and used for the outlier analysis was two in all cases except for a Figure . The pera Figure , indicatpt Table , our ΔAFpt Table  but cond3.3DXY, Tajima's D, and π. Divergence (DXY) between anadromous and freshwater populations was consistently higher in outlier regions compared with nonoutlier ones in all four lineages , as they are unlikely to be at genetic equilibrium. Nonetheless, the observed patterns of Tajima's D in all three naturally occurring lineages, and those for DXY for all four of them, suggest that the outlier regions examined are targets of natural selection.We studied each lineage using s Figure a. Mean Td Figure , suggestd Figure . Bias ind Figure , may alsA. alosa and A. f. lacustris, outlier regions in both anadromous and freshwater populations showed a significant excess in diversity when compared to neutral ones, suggesting they may be enriched for older haplotypes that contain multiple mutations that are under selection. However, the opposite pattern was found for freshwater A. macedonica. No significant differences were detected in the remaining three comparisons conducted.Differences in π within and outside of outlier regions were detected in five of the eight comparisons we conducted Figure b. In A. 3.4A. alosa and A. f. lacustris, and among all four of the lineages examined. The percentage of shared outlier regions between pairs of populations within A. alosa was generally lower (an average of 18%) than A. f. lacustris (48%), as was it across all three populations in each lineage  provides support for our overall conclusions regarding this topic.Parallelism was measured within e Figure . HoweverA. f. lacustris and A. f. killarnensis (64%), and lowest between A. alosa and A. macedonica (25%)  Figure . DespiteA. f. lacustris, A. f. killarnensis, and A. macedonica), and just several thousand SNPs were shared among all four lineages of freshwater shad . In A. alosa, two additional nonsynonymous mutations in ATPase‐α1.1b that also exhibited extreme ΔAF  were found. To further understand the statistical significance of the ΔAF estimate for the nonsynonymous mutation in ATPase‐α1.1b shared by A. alosa and A. f. lacustris, 67,614/968, we examined the genome‐wide distribution of ΔAF for all nonsynonymous mutations shared by the two lineages. Among all nonsynonymous mutations shared by the two lineages, 67,614/968 in ATPase‐α1.1b had the highest combined ΔAF. It was also the only one with ΔAF in the top 95th percentile of all ΔAF for all nonsynonymous mutations in each A. alosa and A. f. lacustris. All three nonsynonymous changes in ATPase‐α1.1b had similar allele frequencies in all populations studied, suggesting they may be part of the same haplotype.Among the mutations in ATPase‐α1 from a phylogenetically diverse set of fish species, each of the three positions that had nonsynonymous mutations in ATPase‐α1.1b is moderately conserved loci  are part of the same loop within the nucleotide‐binding domain, suggesting they may work in concert to alter how ATP binds to the protein  was found to be in the cell membrane between the cytoplasm and extracellular regions where it may affect ion transport.The functional consequences of these three nonsynonymous mutations were explored using protein modeling and phylogenetic analysis. Based on our amino acid alignment of i Figure . The ami4Here, we studied the genomics of four lineages of anadromous Eurasian shad that have evolved freshwater life histories. Our results show that adaptation to freshwater in these alosines involved a combination of parallel and independent genetic changes. Parallelism varied extensively at each of the two phylogenetic scales investigated but was generally greater within lineages than among them.4.1Alosa lineages we studied , making it possible to investigate parallelism within each of these. The freshwater A. alosa studied here have only been diverging for tens of generations. Our evidence for parallelism in A. alosa . However, in A. alosa, complete parallelism was less common than in A. f. lacustris.Multiple freshwater populations exist for two of the four a Figure  adds to a Figure . We alsoA. f. lacustris than A. alosa is consistent with freshwater A. f. lacustris: (1) having probably been founded by anadromous shad from the same drainage  most closely related anadromous ones . At the 99th percentile level, pairs of populations from different lineages shared <5% (hundreds) of their outlier regions Figure . Fewer rA. f. lacustris and A. f. killarnensis since they are the most closely related of the four examined. While this was found to be the case  studied in the A. f. killarnensis lineage. This provides a clear example of how the genetic distance and overall shared polymorphism is not a good predictor of parallelism within these lineages.Despite the only two subspecies we examined, ATPase‐α1.1b across populations within A. alosa and A. f. lacustris may provide some clues as to what may influence parallelism in these lineages. Although the genomic regions that contained ATPase‐α1.1b in A. alosa and A. f. lacustris exhibited some of the most extreme ΔAF observed, such changes were not consistently observed in all freshwater populations of each lineage  was consistently higher within outlier regions (including ATPase‐α1.1b) identified in A. alosa and A. f. lacustris , which was interpreted as them containing multiple causal mutations ; data curation (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology (lead); writing – original draft (lead); writing – review and editing (lead). Paulo Pereira: Formal analysis ; investigation (supporting); writing – original draft (supporting); writing – review and editing . Miguel Carneiro: Investigation (supporting); methodology (supporting). Jolita Dilytė: Methodology (supporting). John Patrick Archer: Data curation (supporting); formal analysis (supporting). Antonio Munoz: Formal analysis (supporting). Francesco Nonnis‐Marzano: Resources (supporting). Antonio Murias: Data curation .All authors declared that there is no conflict of interest.Appendix S1Click here for additional data file.


Y chromosomal genetic markers in the non-recombining region are commonly used for human evolution research, familial searching, and forensic male differentiation since they strictly follow paternal inheritance. Y chromosomal short tandem repeats (Y-STRs) possess extraordinarily advantages in forensic applications because of their high polymorphisms and special genetic pattern. Here, we assessed the genetic diversities of 41 Y-STRs and three Y chromosomal insertion/deletion (Y-InDels) loci in the Chinese Inner Mongolia Han population; besides, genetic differentiation analyses among the studied Han population and other previously reported populations were conducted based on 27 same Y-STRs. Totally, 425 alleles were observed in 324 Inner Mongolia Han individuals for these Y-markers. Gene diversities of these Y-markers distributed from 0.0306 to 0.9634. The haplotype diversity and discriminatory capacity of these Y-markers in the Inner Mongolia Han population were 0.9999 and 0.98457, respectively. Haplotype resolution comparisons of different Y-marker groups in the studied Han population revealed that higher haplotype resolution could be achieved for these 44 Y-markers. Population genetic analyses of the Inner Mongolia Han population and other reference populations demonstrated that the studied Han population had relatively closer genetic affinities with Northern Han Chinese populations than Southern Han and other minority groups. To sum up, these 44 Y-markers can be utilized as a valuable tool for male differentiation in the Inner Mongolia Han population. TM Y23 System  incorporated six novel Y-STRs into an extant multiplex system of 17 Y-STRs of the Applied Biosystems AmpFℓSTRTM YfilerTM kit , and the novel panel demonstrated higher haplotype diversity and discriminatory capacity than other panels  [Y chromosomal molecular genetic markers in the non-recombining region are paternally inherited, and therefore are widely employed for exploring human paternal evolution history ,2, inveslex Y12) . HoweverTM YfilerTM Plus kit (Applied Biosystems). The novel kit, SureID® PathFinder Plus , can simultaneously amplify 41 Y-STRs and three Y-InDels in a single well via the six fluorescent dye-labeled technology, which might possess better forensic potential for male individual identification. Three Y-InDels in this kit could be used as slowly mutating loci for familial searching. Besides, they also could enhance discriminatory capacity of the kit to some degree. In the previous research, Fan et al. [To further improve haplotype discriminatory capacity among the male lineage, nine rapidly mutating Y-STRs , 13 new Y-STRs/InDels  and a multi-copy locus DYS527 were used to construct a novel multiplex system on the basis of the loci in the Applied Biosystems AmpFℓSTRn et al.  performen et al. . TherefoInner Mongolia is located in North China region. Many ethnic groups live in the Inner Mongolia region. Among these populations, Han population is the largest population in the Inner Mongolia region. To further evaluate forensic values of the SureID PathFinder Plus system in Chinese populations, we investigated the genetic distributions of 41 Y-STRs and three Y-InDels in the Inner Mongolia Han population. Furthermore, phylogenetic relationship analyses between the studied Han population and other published populations ,17–49 weBloodstain samples from 324 unrelated healthy Han male individuals residing in the Inner Mongolia Autonomous Region, China were collected. The studied individuals must live in the Inner Mongolia Autonomous Region, China, for more than three generations. All participants provided their written informed consent. The research protocol was approved by the Ethics Committee of Xi’an Jiaotong University Health Science Center (No. 2019-1039).2O. Amplification reaction of each sample was performed on the GeneAmp PCR System 9700 instrument (Applied Biosystems) according to recommended parameters by the company. Next, 1 µL PCR product/PathFinder Plus Allelic Ladder Mix was added to 8.5 µL HiDi formamide and 0.5 µL SIZE-580. The mixture was detected by the ABI3500xL Genetic Analyzer (Applied Biosystems). Genetic typing of 44 Y-markers was determined by GeneMapper ID-X Manager software (Applied Biosystems). Control DNA 9948 and DNase/RNase-Free H2O were used as positive and negative controls, respectively.Multiplex PCR of 41 Y-STRs and three Y-InDels was conducted according to the description of the SureID PathFinder Plus kit . In short, a 1 mm sample disc was added to the PCR cocktail consisting of 12.5 µL PathFinder Plus Master Mix, 6.25 µL PathFinder Plus Primer Mix, and 6.25 µL DNase/RNase-Free HFurthermore, 10 null alleles at three single-copy Y-STRs  and three multi-copy Y-STRs  were observed in some individuals. These individuals were again detected by the Yfiler™ Platinum PCR amplification kit (Applied Biosystems). The experimental process was conducted according to the kit’s instruction.Supplementary Table S1. Phylogenetic relationship analyses among the studied Han population and other reference populations were dissected via multiple methods. Firstly, based on the genetic data of Y-STRs in different Han populations assembled in the Y Chromosome Haplotype Reference Database , Rst and P values among these Han populations were estimated by the analysis of molecular variance (AMOVA) method [Rst values, multidimensional scaling (MDS) analysis and neighbour-joining tree among Han populations in different regions were conducted by SPSS software v18.0 (https://www.ibm.com/products/spss-statistics) and MEGA software v6.0 [https://www.tableau.com/).Allele frequencies and gene diversities (GDs) of 41 Y-STRs and three Y-InDels in the Inner Mongolia Han population were calculated by the STRAF online programme . Haploty) method . Next, bare v6.0 , respectSupplementary Table S2. Totally 2—59 alleles could be observed at these loci, with allelic frequencies distributing from 0.0031 to 0.9846. The least numbers of alleles (two) were seen at three Y-InDel loci; whereas, the maximum was at DYS385a,b loci. For nine rapidly mutating Y-STRs, they showed relatively high numbers of variant alleles (>8). Besides, allele 15 at DYS456 locus displayed extremely high frequency (>0.9800) in the studied Han population in comparison with those in other Han populations [Allele distributions and GD values of 41 Y-STRs and three Y-InDels in the Inner Mongolia Han population were shown in ulations . Likewisulations  and fourulations , indicatSupplementary Figure S1. Therefore, we stated that the deletion of amplification regions might bring about the silence of alleles at these Y-STRs, which needed to be further validated by Sanger sequencing. Furthermore, there was an individual who showed bi-allelic variations at DYS643 and DYS518 loci. Fourteen tri-allelic patterns were observed at DYF387S1, DYS527 and DYF404S1 loci in 11 individuals. Feng et al. [via Sanger sequencing.Variant alleles commonly include null alleles, intermediate alleles and copy-number variants . In thisg et al.  assessedg et al.  investigSupplementary Table S3. Totally, 319 different haplotypes could be observed in 324 Han individuals with the frequencies ranging from 0.0031 to 0.0062. Among these haplotypes, there were 314 unique haplotypes and five haplotypes observed in two individuals, respectively. The HMP, HD and DC values of 44 Y-markers in the Inner Mongolia Han population were 0.00319, 0.99990, and 0.98457, respectively. The relatively high HD and DC values revealed that these Y-markers could be viewed as a valuable tool for male differentiation in the Inner Mongolia Han population.Haplotype distributions of 44 Y-markers in the Inner Mongolia Han population were presented in Haplotype resolution comparisons of different Y-marker sets in the Inner Mongolia Han population were performed, as shown in 3.4.Supplementary Figure S2. The population information used in this study was presented in Supplementary Table S4. Rst distances among these Han populations were provided in Supplementary Table S5. Since low Rst values meant low genetic differentiations among populations, some negative Rst values were transformed to 0 so as to conduct the following population genetic analyses better. The results revealed that the smallest Rst values between the Inner Mongolia Han and Shanxi Han populations were observed, and then Beijing Han, Shandong Han, and Inner Mongolia Han1 populations. Conversely, most of Han populations in other regions including Hainan Han, Guizhou Han, Shanghai Han, Zhejiang Han and Guangxi Han had relatively high Rst values with the studied Han population. Besides, Rst values between the Inner Mongolia Han and Shanxi Han, Beijing Han and Shandong Han populations were not statistically significant. Next, the MDS plot among these Han populations was conducted based on pairwise Rst values, as shown in Firstly, we explored genetic relationships among Inner Mongolia Han population and other reported Han populations. The geographical distributions of these Han populations were shown in Supplementary Figure S2. Rst distances between the studied Han population and these minority groups were given in Supplementary Table S6. The results revealed that the studied Han population had relatively small Rst values with Ningxia Hui and Sichuan Yi; whereas, it had relatively large Rst values with the Inner Mongolia Daur and Qinghai Tibetan groups. Besides, we found that all Rst values between Inner Mongolia Han and these minority groups were statistically significant. We also performed the MDS analysis of these populations, as shown in via 30 InDels [Genetic differentiation analyses of the Inner Mongolia Han and other reported minority groups in China were also evaluated, as shown in 0 InDels ,57. Thervia 17 Y-STR loci, and they found that Han populations showed low genetic divergences in comparison with other ethnic groups; furthermore, they also revealed a north-south gradient among Han populations. In a word, the studied Han population had close genetic affinities with Northern Han populations at the point of paternal inheritance. Further research on the genetic distributions of autosomal STRs, mitochondrial genetic markers and ancestry informative markers in the Inner Mongolia Han population and its neighbouring populations should be performed to elucidate genetic relationships among these populations.There were many population genetic data of different Y-STR sets in Chinese populations ,33,40,43We firstly assessed the genetic distributions of 44 Y-markers in the Inner Mongolia Han population based on the SureID PathFinder Plus kit. Among these loci, most markers showed high genetic polymorphisms in the studied population. The HD and DC values of these 44 Y-markers revealed that the kit could provide the relatively high-resolution haplotype, implying that the kit could be treated as a valuable tool for forensic male differentiation in the studied Han population. Population genetic analyses among the Inner Mongolia Han population and other reported Chinese populations indicated that the studied Han population had closer genetic affinities with Northern Han populations than Southern Han and other ethnic groups.Click here for additional data file.


Zaprionus indianus, to quantify genetic relationships among them, identify potential sources of the introductions, and test for selection at different spatial scales. We find that geographically widespread populations in the western hemisphere are genetically more similar to each other than to lineages sampled across Africa, and that these populations share a mixture of alleles derived from differentiated African lineages. Using patterns of allele‐sharing and demographic modelling we show that Z. indinaus have undergone a single expansion across the western hemisphere with admixture between African lineages predating this expansion. We also find support for selection that is shared across populations in the western hemisphere, and in some cases, with a subset of African populations. This suggests either that parallel selection has acted across a large part of Z. indianus's introduced range; or, more parsimoniously, that Z. indianus has experienced selection early on during (or prior‐to) its expansion into the western hemisphere. We suggest that the range expansion of Z. indianus has been facilitated by admixture and selection, and that management of this invasion could focus on minimizing future admixture by controlling the movement of individuals within this region rather than between the western and eastern hemisphere.Introduced species have become an increasingly common component of biological communities around the world. A central goal in invasion biology is therefore to identify the demographic and evolutionary factors that underlie successful introductions. Here we use whole genome sequences, collected from populations in the native and introduced range of the African fig fly,  IntroduStudies of introduced species have identified a number of demographic or evolutionary processes that may contribute to successful introductions , is also central to our ability to effectively manage biological introductions. For introductions that are geographically widespread, knowledge of shared versus independent aspects of their colonization and evolution will inform whether a single management strategy can be applied across broad geographic regions or whether each introduced population needs to be treated as a unique case. For example, researchers could monitor the movement of individuals between specific sets of countries to limit the opportunity for admixture or the movement of adaptive alleles among regions.Genetic data are a powerful tool that can be used to estimate demographic and evolutionary events associated with introduced populations or range expansions  dynamics of admixture and selection acting in this species. Our results show that Z. indianus in the western hemisphere are genetically differentiated from Z. indianus found across geographically distant locations in Africa and share a pattern of mixed ancestry across their genomes, suggesting an admixture event that predated (or occurred early during) their introduction into the western hemisphere. We also find a strong signal of selection shared across introduced populations in the western hemisphere, consistent with a scenario of either shared selection across introduced populations, or selection in the ancestor of the lineage that went on to colonize regions in the western hemisphere.6 Gupta,  and, ove6 Gupta, . More re22.1Z. indianus sampled from four locations in their introduced range  and from four locations across their native range in Africa . Zaprionus gabonicus and Z. africanus are the two most closely related species to Z. indianus, and each of these species are reproductively isolated from one another  to map reads, for each individual, to a previously published Z. indianus reference genome generated from an isofemale line established from a female collected in Florida in 2014 , marked duplicates using picard’s markduplicates tool (v2.2.4), and realigned around indels using gatk’s realignertargetcreator and indelrealigner tools  with options “‐‐emitRefConfidence GVCF”, “‐‐minReadsPerAlignmentStart 4”, “‐‐standard_min_confidence_threshold_for_calling 8.0”, and “‐‐minPruning 4” and performed joint genotyping using gatk’s genotypegvcfs tool. We then filtered SNPs using gatk’s VariantFiltration tool with option “‐‐filterExpression “QD < 2.0 || FS > 60.0 || SOR > 3.0 || MQ < 40.0 || MQRankSum < −12.5 || ReadPosRankSum < −8.0””. We hard‐filtered genotypes using vcftools with options “‐‐max‐missing 0.5” and “‐‐mac 2”.We estimated genotypes for each individual using XY or ZW sex determination), the smaller effective population size of the sex chromosomes can exacerbate the impact that genetic bottlenecks have on genetic diversity  across scaffolds for five male and four female Z. indianus, and identified X scaffolds as those in which normalized mean sequencing depth was <0.85 for at least four of the five males and >0.85 for at least three of the four females  of the assembly being assigned to autosomes or the X chromosome, with 24.6% (33.7 Mb) being identified as belonging to the X chromosome . Our estimate of X chromosome size is within the range of X chromosomes of other Drosophilid flies .In species with heterogametic sex chromosomes , and India, but did not find any evidence of population structure associated with geography  and genetic cluster inference with pcangsd  threshold of 0.2 to thin sites and allowing a maximum of 15% of individuals to be missing genotype information at a given site . astral was run using 7085 gene trees that were randomly sampled from 14,165 gene trees constructed from alignments of phased 500‐SNP nonoverlapping genomic windows generated along the 40 largest scaffolds of our assembly  and estimated a mitochondrial tree using raxml . When calculating FST, we first estimated the site frequency spectrum (SFS) and genotype likelihoods, for each population, using Z. africanus as the outgroup, and filtered SNPs using options “‐minMapQ 1”, “‐minQ 20”, “‐setMinDepth N*6”, and “‐setMaxDepth N*60” options, where N is the number of individuals sampled from a population. We then estimated all pairwise 2D‐SFS using angsd’s “realSFS” tool, and FST in 5 kb genomic windows using angsd’s “realSFS fst index” and “realSFS fst stats2” tools . We next explored the relative support for relationships among east African, west African, and introduced  lineages, across the genome, using “topology weighting by iterative sampling of subtrees” , (ii) , and (iii)   from the São Tomé population, six individuals from the Zambian population, and six individuals of Z. africanus, extracted these individual's phased haplotypes from phylip alignments  estimated from a random sample of 600 subtrees per window. We summarized weights as supporting a given topology if more than 50% of sampled subtrees supported that topology. All other windows were classified as “ambiguous”.We estimated relative weights for each of the three topologies described above by running ignments , and useUnder a scenario where the introduced populations were independently colonized by different populations from the native range, we do not expect patterns of ancestry across the genome to be shared across introduced populations. To test this prediction, we summarized ancestry information for each genomic window, for each introduced population, as the difference between topology weights for topology 1 (shared west African ancestry) and topology 2 (shared east African ancestry). We then calculated correlations in this “ancestry score” between all pairs of focal introduced populations.twisst, we estimated sharing of derived alleles among populations of Z. indianus with treemix. Unlike the three‐population window‐based approach we used when running twisst, treemix allows us to test for multiple admixture events and across all populations simultaneously. We first used treemix to infer maximum likelihood ancestry graphs with and without migration among Z. indianus populations using allele frequency estimates from each population we sampled. We specified Z. africanus as the outgroup, grouped SNPs in windows of 500 to account for nonindependence among adjacent SNPs (‐k option in treemix), and ran treemix allowing for 0–5 migration events across the tree.In addition to the window‐based approach implemented with Z. indianus populations using four‐population tests as implemented with treemix’s “fourpop” function. This test computes f4 statistics for trees in the form , where a significantly nonzero f4 value indicates an excess of allele sharing, consistent with introgression, between taxon B and C (negative f4) or B and D (positive f4). We computed f4 statistics holding Z. africanus as the outgroup (“A” taxon in the aforementioned tree). Because treemix analyses utilize information from allele frequencies within each population, we did not analyse the Z. indianus sample from India because this sequence was derived from two males collected from a single isofemale line.Finally, we tested patterns of allele‐sharing among explicitly defined 2.4Z. indianus's expansion into the western hemisphere. We first computed SFS for populations sampled in São Tomé, Zambia, and the eastern USA using angsd (v0.920) with options “‐domajorminor 1 ‐gl 1 ‐domaf 1 ‐dogeno 3 ‐doCounts 1 ‐dopost 2 ‐doHWE 1 ‐minHWEpval 0.01 ‐minMapQ 20 ‐minQ 20 ‐doSaf 1”. The two African populations were chosen to reflect the two differentiated lineages we sampled in African and the population from the eastern USA was chosen because we had the largest sample size from this population  and this population represents the most recently colonized in the western hemisphere. SFS were polarized using Z. africanus (‐anc option in angsd). We then estimated the joint‐SFS for the three focal populations using angsd’s “realSFS” function.We took a demographic modelling approach to explore support for different demographic events occurring during fastsimcoal2 v.2.6.0.3 .Results from the analyses of genetic differentiation introduced above support a scenario where angsd (v0.920) as described above when estimating FST . Finally, genomic windows with a PBS in the top 99% of values in a within‐native range comparison were classified as windows experiencing selection in Z. indianus's native range. We tested whether the overlap in the number of outlier windows identified among these different comparisons was greater than expected by chance using randomization tests.First, we estimated selection within individual populations using the population branch statistic  compared to the native range .Using whole‐genome sequence data we identified 22,911,754 hard‐filtered SNPs across all samples included in this study. As expected, when comparing across species, the majority of sites were fixed between 3.2Z. indianus samples, the majority of genetic variation was structured between individuals from introduced and native parts of the species’ range . Phylogenetic analysis with snphylo and astral provided further support for differentiation between introduced and native populations: all individuals sampled from the western hemisphere were more closely related to each other than to individuals sampled from Africa, and all African individuals were more closely related to each other than to individuals from the western Hemisphere . Phylogenetic analyses also indicate differentiation between west African and east African populations .Principal component analysis (PCA), genetic clustering, and phylogenetic analyses all identified genetic differentiation between introduced and native populations Figure . Among ZFST estimated within 5kb genomic windows was highest between native and introduced populations  and the Hawaiian and São Toméan populations (median FST = 0.220). The strongest genetic differentiation within the native range was between Kenyan and São Toméan populations (median FST = 0.084) followed by Zambian and São Toméan populations (median FST = 0.077). Among introduced populations, populations from Colombia and Hawaii were the most differentiated (median FST = 0.160), with the eastern USA samples being less differentiated from both Colombia (median FST = 0.042) and Hawaii (median FST = 0.089). Consistent with patterns of genetic differentiation, clustering analysis grouped Z. indianius into four genetic clusters loosely defining individuals with ancestry from west Africa, east Africa, Colombia, or Hawaii  haplotypes across African populations and two distinct mitochondrial lineages present within the western hemisphere Figure . The majt Figure . The sina Figure . However3.3Z. indianus populations , the model with no migration already accounts for 99.95% of covariance in allele frequencies among populations  provide support for admixture among certain populations. The strongest evidence for admixture was among populations sampled in Z. indianus's native range . Evidence for admixture from the f4 statistic and twisst  and 29 (16.8%) unique outlier windows identified in between‐range comparisons were identified as outliers in at least two of the three populations from the western hemisphere  and found that for all comparisons made above, the observed number of overlapping windows was greater than expected by chance  between introduced populations in the western hemisphere and native populations in São Tomé and Zambia, (ii) among introduced populations in the western hemisphere, and (iii) across both introduced and native populations. Analyses using the PBS classified 1047 and 389 unique 5 kb genomic windows  as outliers based on having a PBS value in the top 99% of windows in comparisons made between introduced and native populations (between‐range comparisons), among introduced populations (within‐introduced range comparisons), and among native populations (within‐native range comparisons). To determine the degree to which these outlier windows were shared among different populations we focused on the 383 and 173 unique windows identified on the autosomes and X chromosome) windows that were outliers in at least one of the three between‐range comparisons and at least one of the two within‐native range comparisons  windows that were outliers in between‐range and among‐introduced comparisons  and 13  losing a larger amount of genetic diversity than autosomes during demographic bottlenecks  highlight the usefulness of genome‐scale data when testing demographic histories of introduced species in both their introduced and native ranges.Patterns of genetic differentiation among populations varied across the genome. For example, differentiation between populations in the western hemisphere and those in Africa, and among populations within Africa, was approximately twice as high on the s Figure . In diplo Figure  support 4.2Anolis sagrei have signatures of mixed ancestry consistent with colonization from multiple regions in their ancestral range  on the Galapagos islands and introduced populations of Mytilus mussels—provide examples where admixture, or introgression, occurs either during or after species are introduced into novel environments  during colonization and range expansion (A. sagrei and Mytilus spp.), (ii) after being introduced into a novel geographic region (S. pimpinellifolium and Mytilus spp.), or (iii) prior to introduction into a novel geographic region (Z. indianus). Temporal dynamics such as these are important to consider both from the perspectives of better understanding the evolution of introduced species and in devising appropriate strategies for their management. For example, management strategies could use information on the temporal and geographic dynamics of admixture to prioritize blocking the movement of individuals either between their introduced and native ranges or within their introduced and native ranges. More generally, knowledge of introduced species’ colonization history and adaptation can be used to mitigate the negative impacts that introduced species can have on ecosystems  this range expansion.Similar to admixture, populations of introduced species can experience selection at different times and locations during their range expansions and there is increasing evidence of rapid genetic differentiation consistent with selection acting within populations of introduced species  in which they were identified as outliers (Z. indianus's range could confound our ability to identify truly selected regions of the genome. Some outlier regions support this hypothesis, where almost the entire scaffold shows elevated differentiation (FST; see Figures Genomic windows with evidence of selection in at least one of the comparisons we made overlap a total of 658 unique genes that are annotated in the reference genome we used here (see Dryad submission associated with Comeault et al.  for genooutliers . This geoutliers  and deteoutliers . However4.4Z. indianus harbour both west‐ and east‐African ancestry, suggesting that admixture between these two lineages has played a role in introducing adaptive genetic variation into the population expanding across the western hemisphere. The relative frequency of genomic windows with shared east or west‐African ancestry is different between differentiated windows and the genomic background (compare Figures Z. indianus further work that identifies potential traits affecting fitness, and their underlying genes, is needed. Quantitative‐trait locus and admixture mapping represent promising approaches through which this goal could be achieved (Buerkle & Lexer, Z. indianus's introduced and native ranges we cannot comment on the relative importance of admixture for adaptation in this system. However, highly differentiated genomic windows that harbor east‐ or west‐African ancestry provide an obvious starting point from which to explore links between genetic variation, phenotypic variation, and fitness. Identifying these links could provide valuable insight into the geographic and evolutionary origins of the genetic variation that help facilitate successful range expansions.We found that regions of the genome that are strongly differentiated between introduced and native populations of 5Z. indianus, where there is a signature of admixture and selection that is shared across geographically widespread populations in the western hemisphere. Further work is needed to increase our understanding of the adaptive consequences of admixture and the timing of selection on phenotypes that help to facilitate range expansions displayed by many invasive, weedy, or human‐commensal species.Understanding when and where admixture and local adaptation occur during the evolutionary history of introduced species is an important challenge in modern evolutionary biology. Previous work has shown how introduced species can experience admixture within their introduced range and adapt to novel environments they experience (Barker et al., The authors declare no conflicts of interest.Aaron A. Comeault and Daniel R. Matute designed the study and conducted fieldwork; Aaron A. Comeault collected genomic data; Aaron A. Comeault and Andreas F. Kautt conducted population‐genomic analyses; Aaron A. Comeault wrote the manuscript with input from all authors. All authors approved the final manuscript and declare no conflicts of interest.Supplementary MaterialClick here for additional data file.