Physa acuta is a globally invasive freshwater snail native to North America. Prior studies have led to conflicting views of how P. acuta populations are connected and genetic diversity is partitioned globally. This study aims to characterize phylogeographic and population genetic structure within the native range of P. acuta, elucidate its invasion history and assess global patterns of genetic diversity. Further, using meta-analytic methods, we test the ‘Enemy-Release hypothesis’ within the P. acuta – digenetic trematode system. The ‘Enemy-Release hypothesis’ refers to the loss of native parasites following establishment of their host within an invasive range. Population genetic data is combined with surveys of trematode infections to map range-wide trematode species richness associated with P. acuta, and to identify relevant host-population parameters important in modeling host-parasite invasion.P. acuta, with some evidence for contemporary geographic barriers between western and eastern populations. Mito-nuclear discordance was found suggesting historical isolation with secondary contact between the two mitochondrial clades. Trematode species richness was found to differ significantly between native and invasive populations, in concordance with the ‘Enemy-Release hypothesis’. Further, our data suggests a positive relationship between nucleotide diversity of invasive populations and trematode prevalence and richness.Phylogenetic analyses using mtDNA uncovered two major clades (A & B). Clade A occurs globally while clade B was only recovered from the Western USA. All invasive populations sampled grouped within Clade A, where multiple independent source populations were identified from across North America. Significant population genetic structure was found within the native range of P. acuta within its native range that provides insight into phylogeographic and population genetic structure, range-wide genetic diversity and estimation of the invasion history. Meta-analysis of P. acuta – trematode surveys globally is consistent with the ‘Enemy-Release hypothesis’. Additionally, results from this study suggest that host demographic parameters, namely genetic diversity as a proxy for population size, may play an essential role in how parasite communities assemble within invasive host populations. This knowledge can be used to begin to construct a framework to model host-parasite invasion dynamics over time.This study includes a wider geographic sampling of The online version of this article (10.1186/s12862-018-1208-z) contains supplementary material, which is available to authorized users. Invasive species are an important consequence of global change , therefoPhysa acuta [P. acuta, specifically in populations’ ability to alter the number of generations per year [P. acuta. Physa acuta is known to displace native gastropods to become the dominant species over very short periods of time [P. acuta populations [One such invader is sa acuta , a globasa acuta , 9, whicsa acuta , 11. Remper year , 13, a c of time –16. For ulations .P. acuta is muddled by two centuries of taxonomic confusion , P. virgata (North America), P. integra (North America) and P. cubensis  to a single species, Physa acuta [. Taylor [P. acuta and closely allied species into the genus Haitia, based primarily on penial morphology, which has demonstrated phylogenetic utility [Haitia in the sense of Taylor [P. acuta occurs globally [The invasion history of  Lydeard ), due inn France  over twon France  from Pen species –21 prior species , 22, 23. species , 24 demosa acuta . Taylor  utility , 21. How utility  has showglobally .P. acuta at both regional [P. acuta primarily in its invasive range in Europe, with limited sampling from native populations. Characterizing population structure within the native range is foundational to resolving invasion history [P. acuta by chacterizing range-wide population genetic and phylogeographic patterns, and reconstruct its invasion history.Efforts have been made to elucidate the population genetic structure of regional –28 and gregional , 25 scal history . Limited history , 25, 28.P. acuta offers a unique lens to understand host-parasite invasion dynamics, which are complex and largely overlooked [P. acuta-trematode species richness globally to test for release of digenetic trematodes within invasive populations and secondarily test for correlations among trematode infections and host population genetic parameters to identify factors that maybe relevant to host-parasite invasion, and discuss a framework to use these data to being to model invasion dynamics.Apart from its remarkable distribution, erlooked –32. Physerlooked , 34. Morerlooked . Despiteerlooked , 32. Folerlooked . Parasiterlooked , which perlooked . Here wePhysa acuta populations were sampled opportunistically, between 1998 and 2015, to document the biodiversity of their trematode parasites. The specimens used in this study were collected from across North America (native range) as well as several invasive localities  using a dissection microscope. Cercariae and their snail hosts, as well as uninfected snails, were isolated and stored in 95% ethanol and deposited into the Museum of Southwestern Biology (MSB), Division of Parasites  following the manufacturer’s protocol.cox1 and 16S) as they are the most abundant genetic markers available in the NCBI database and have been used successfully to recover population genetic variation within P. acuta [ITS1) to assess the potential for mito-nuclear discordance of the recovered subclades.We sequenced two mitochondrial DNA loci  of a subset of the P. acuta individuals chosen to represent the recovered mitochondrial clades. Sequencing reactions were performed using the BigDye sequencing kit 3.1 . Sequences were edited using Sequencher 5.3 , and then aligned using ClustalW [ITS1 and 16S alignments. Sequences generated during this study were submitted to GenBank under the accession numbers MF694400-MF694492, MG001330-MG001338 .We sequenced 509 bases of the AATCA-3′  and 469 ACAT -3′ . AdditioClustalW  and furtClustalW  was usedPhysa species were performed for the purposes of determining the in-group in all subsequent phylogeographic and population genetic analyses. Aplexa elongata was used as an out-group [Physa phylogenetic datasets were analyzed separately as cox1 (509 bp), 16S (611 bp) and cox1 + 16S (1120 bp). Relatively few ITS1 (525 bp) sequenes exist within the NCBI database  using Jion  were excluded from in-group analyses. In-group analyses included 151 individual snails and were performed to evaluate phylogeographic patterns within P. acuta. Each locus was treated as an independent dataset and analyzed separately. Optimal models of nucletotide substitiution were found to be the same per gene region as used for phylogenetic analysis of Physa.Phylogenetic analysis of  Lydeard  and was Maximum Likelihood (ML), Minimum Evolution (ME) and Bayesian Inference (BI) were performed on each phylogenetic dataset. ME and ML analyses were performed in the program PAUP* 4.0 . One thoBayesian Inference (BI) was performed using the program MrBayes v. 3.2.6 , consistHO) using an approximately unbiased (AU) test [p-values. To test the ‘single source’ hypothesis we constrained all invasive individuals as monophyletic, with an Eastern USA origin (HO1), using the cox1 dataset. Secondly, to test for mito-nuclear discordance within P. acuta, we constrained the ITS1 topology for complete concordance with recovered mitochondrial topologies (HO2). Constrained trees were created in Mesquite [Recovered topologies were statistically compared to a null phylogenetic hypothesis (AU) test , where pAU) test  to generMesquite . Per sitMesquite  .P. acuta from each population to be used for genetic analysis.To characterize range-wide population genetic diversity and structure we grouped native populations according to the freshwater ecological complex (FWEC ) from whP. acuta populations were estimated using DNAsp v. 5 [cox1 and 16S gene regions; number of unique haplotypes (h), number of segregating (polymorphic) sites (S), average number of nucleotide differences (K), haplotype diversity (Hd), nucleotide diversity (π) and Watterson’s estimator  were calculated. The dataset of 151 individual P. acuta cox1 sequences consisted of 88 unique haplotypes. A minimum spanning network was constructed to view connections among haplotypes using the program PopART [http://popart.otago.ac.nz/). Relationships among haplotypes (185 bases) were also evaluated using BI, to determine ancestral relationships among haplotypes. Parameters for BI were identical to those used in analyses described previously.Genetic diversity summary statistics of Asp v. 5  based onm PopART , http://P. acuta (cox1) a one-way Analysis of Molecular Variance test  was pert  was determined by permutation tests of 10,000 random permutations, calculated in Arlequin v. 3.5 [To further evaluate population genetic structure within wise ΦST  values wn v. 3.5 .p-distances were calculated for cox1, 16S and ITS1 datasets within and between FWEC, countries within the invasive range, within and between the invasive and native ranges, and within and between recovered clades identified through MSN and phylogenetic analysis using MEGA 6 [Pairwise uncorrected g MEGA 6 .Ne) over time by fitting a Bayesian Skyline demographic model (BSP [cox1 dataset in *BEAST v. 1.7.0 [cox1 evolution based on other gastropod systems [We estimated changes in the effective population size (del (BSP ) for eacv. 1.7.0 . The HKY systems –64. Conv systems . BSP datP. acuta outside of North America.In conjunction with the molecular data generated by this study, a literature search was carried out to compile reports of P. acuta outside of North America and 2) surveys of trematode assemblages of P. acuta within both its native and invasive range. Data complied was published from 1805 up to the end of 2016, and recovered using combinations of keywords; Physa acuta, Physa, Physella, Costella, Haitia, trematode, parasites, invasive gastropod, malacological survey, trematode survey and cercarial survey. Further, studies cited by recovered articles were also included. In total the final dataset included 196 published reports of Physa acuta outside of North America and 7 trematode surveys from the native range of P. acuta and 15 within its invasive range. Physa acuta trematode surveys carried out by the authors for the purposes of this study were also added to the meta-dataset. From each trematode survey, observed species richness (So) and prevalence  were calculated. So is defined as the number of different trematode species occurring within a surveyed host population [So was taken: ‘species’ were considered unique based on trematode family. Consequently, reported measures of So from the native range are likely underestimates [P. acuta were not included as the relationships between trematodes and invertebrate second intermediate hosts are generally less specific [P. acuta trematode surveys undertaken in Africa. Australasian samples were excluded from these analyses due to small sample size. Estimates of haplotype diversity (Hd) and nucleotide diversity (π), were assigned as population parameters. Time since invasion (tsi) was estimated by assigning each surveyed population into an ‘invasion phase’ category: phase 4: < 80 years since invasion, phase 3: 80–180 years since invasion, phase 2: 180–280 years since invasion and phase 1: 280 + (native range). ‘Invasion phases’ were determined based on published reports of P. acuta invasions and genetic evidence provided by this study. Pairwise correlation analyses of So,tsi and pr with Hd, π, and Ɵ were evaluated using Pearson’s correlation coefficient. p-values were adjusted for multiple comparisons using both Bonferroni and Benjamini-Hochberg corrections [ISI Web of Knowledge was searched for 1) all reports of pulation . Becausestimates , 66. Onlspecific , 68. Genrections .Cox1, 16S, 16S + cox1 and ITS1 gene tree analyses  and posterior probabilities from BI were strong . Clade A (n = 123) is the larger, containing all invasive populations sampled in addition to populations recovered across the native range. While some individuals from clade A and B were found sympatrically in the Western USA, clade B (n = 26) was only recovered west of the Rocky Mountains. Clades A and B were not recovered from the ITS1 phylogeny, possibly suggesting mito-nuclear discordance  and of strict concordance of mitochondrial clades A and B within the ITS1 dataset .Phylogenetic analyses of the cox1 and 16S) for each population sampled are summarized in Table Hdnative = 0.97, Hdinvasive = 0.615; πnative = 0.0289, πinvasive = 0.0098) was found within the native range. Haplotype diversity is consistently high among FWECs sampled, often reaching 100% .Indices of genetic diversity cox and 16S cox1 and 16S datasets, 88 and 43 unique haplotypes were recovered, respectively. More genetic variability was recovered from the cox1 dataset and haplotype relationships were estimated by constructing a Minimum Spanning Network  are connected by haplotypes recovered from the Eastern United States (Mississippi and Atlantic FWECs), indicating that these regions are likely a source of invasions from the native range of P. acuta.Within the CladeA = 0.019, πCladeB = 0.024). All haplotypes were recovered from the Western United States (west of the Rocky Mountains). While sampling is not sufficient to know if Clade B is truly geographically restricted, our data suggest (1) clade B is a Western USA clade and (2) FWEC’s may play a greater role in shaping western populations of P. acuta . In the native range 76.55% of genetic variation is attributed to within population variation, indicating that overall FWEC’s, and the biogeographic regions tested in general, are not important in structuring P. acuta populations.Overall population genetic structure of VA Table . Both rap-distances within and between populations of P. acuta were calculated from the cox1 dataset (Table p = 0.0006). Within population genetic distances between the Western USA and Eastern USA (native range) vary significantly (p = 0.05), and average 0.0346 (~ 3.5%) and 0.022 (2.2%) respectively. Overall western populations exhibit the highest within population genetic distances while Africa and Asia demonstrate the lowest .Pairwise uncorrected et Table . Within ST values were calculated (Table ST are shown). The Mississippi FWEC, the largest complex sampled, shows significant (p <  0.05) genetic differentiation from four of the six other FWECs  as well from Africa and Middle East. Similarly, the Atlantic FWEC shows significant (p <  0.05) genetic differentiation from four of the six other FWECs  as well from Europe, Australasia, Asia and the Middle East.Pairwise genetic distances and Φed Table  and assecox1 evolution  and invasive (n = 15) range were complied to estimate range-wide species richness (Table So within the native range (So = 3.25) was significantly greater (p = 0.0016) than within the invasive range (So = 0.3125). Western European (n = 2) and Iranian (n = 1) populations of P. acuta were the only invasive populations surveyed where patent infections were reported. Prevalence varied significantly (p = 0.04) among invasive (0.00319%) and native ranges (0.2%). Variables were analyzed using Pearson’s correlation coefficient (ρ), summarized in Table So, tsi, pr and the demographic variables  resulted in significant unadjusted p-values, with the exception of pr and Hd. To correct for multiple comparisons, p-values were adjusted using BH and Bonferroni methods . π and Ɵ were found to have a correlation coefficient of 1  and So (ρ = 0.8) and a moderate correlation with pr (ρ = 0.57), supporting the prediction that genetic diversity increases with time since invasion. In total, these results suggest a significant relationship between background genetic variation, a proxy for population size, and the richness of trematode assemblages.ss Table . Averageive n = 1 range weive n = 1 range weive n = 1 range weP. acuta. While haplotype diversity within the invasive range is not low relative to other invasive snails, like Melanoides tuberculata [Haminoea japonica [Hd relative to the native range. Our analyses reveal that invasive populations have substantially less mtDNA diversity relative to native populations  across the native range with evidence of geographic structuring between the Eastern and Western USA populations. Phylogenetic analyses suggest the existence of two clades (A & B) within the native range, interestingly these clades are sympatric in the Western USA, while clade B appears to be restricted to Western USA. Field surveys and subsequent molecular analysis reveal that individuals belonging to clade A and/or B can be collected side by side from the same water body in New Mexico, Colorado, California and Nevada. Phylogenetic analysis  worse phylogeny was recovered. Gene trees of the non-recombining mitochondrial markers may suggest historical isolation between the Western and Eastern USA. It may be hypothesized that the Rocky Mountains, or associated waterways, have played a role in restricting gene-flow, which has been shown relevant in structuring populations of other freshwater organisms [cox1, 16S and ITS1 sequence from Nolan et al. [This study is the first to compare and assess discordance among nuclear and mitochondrial markers within rganisms –84. It crganisms , and conrganisms . cox1, 1n et al.  was inclP. acuta globally .Figure  in 1805 , over 20Anderson  was the aparnaud , in the d 1800’s , 89. Weslonizers , 90. If lonizers , 92. Thilonizers  topologyP. acuta in Western Europe roughly 200 years ago, and has subsequently spread east. It is more parsimonious to hypothesize that genetically depauperate European populations expanded east than to assume that identical haplotypes from a genetically diverse source (North America) founded three distinct invasive regions.Our data supports that there have been multiple independent invasions into Western Europe, likely from different sources Fig. . Data frPhysa acuta invasions into Africa have been more recent relative to European invasions. Extensive malacological surveys across the African continent suggest the African invasion occurred in the range of 1940–50’s, with populations reported from South Africa [Samples from Africa, South America and the Caribbean are related and are likely the result of an independent invasion event, though it is currently not possible to determine the directionality without more samples. h Africa , 94, 95,h Africa , Moroccoh Africa , Nigera h Africa , and Kenh Africa . Recordsh Africa , 101. Suh Africa  suggest P. acuta from other continents into the Western USA. Our data supports that all source populations have originated from Clade A, however, it remains unclear if Western haplotypes of Clade A originated from the Eastern USA or are the result of secondary contact from invasive populations, though these scenarios are not mutually exclusive. Increased sampling within the western range is necessary to fully elucidate the source of Clade A members recovered from the Western USA. Founding events, within and from the native range, are likely the result of the aquaria or aquatic plant trade as posited by multiple investigators [Our data suggests haplotype connections between invasive populations and Clade A individuals collected in the Western and Eastern USA and Canada. While our data supports the initial invasions from the Southeastern USA to Western Europe, we also find evidence of haplotype connections between the Coastal FWEC  and the Middle East and Eastern Europe. Currently, based on our sampling it is unclear if there are in fact Western source populations, or if this relationship is the result of the re-introduction of invasive tigators , 87, 103P. acuta occurrence with our genetic data we found a significant relationship between genetic diversity (π and Ɵ) and trematode prevalence (pr), and richness (SO). Nucleotide diversity (π) is a better measure of background genetic variation than haplotype diversity, as it is more robust to the stochastic effects of drift [Combining published reports of of drift . Higher of drift .tsi) significantly correlated with π, Ɵ as well as pr and SO. Of all the invasive populations screened for trematodes and included in this study there were only three reports of P. acuta shedding larval trematodes (cercariae) within its invasive range  is inhibited by a lack of taxonomic resolution. Inclusion of parasite genetic data is required to better understand Physa-trematode invasion dynamics.We also found that time since invasion , Strige (France ) and Xip (France ). Determπ of invasive populations sampled. These data suggest that richness of trematode infection increases positively with background genetic variation and time since invasion, and leads to the prediction that over time as invasive P. acuta populations increase in size their role in local trematode transmission will increase. Meta-analysis was limited by population genetic sampling within the invasive range, which will be necessary to more robustly model the relationship between genetic diversity and trematode prevalence.Populations from Western Europe (presumably the first invasive populations) and allied populations from the Middle East have the greatest P. acuta – trematode system. Firstly, most founding populations likely consisted of eggs or young snails, as common with the aquarium trade, and were therefore uninfected. Secondly, there might be incompatibility among native parasites and invasive host populations. An additional ecological explanation is that invasive P. acuta populations often establish in highly modified habitats , whVinarski ).P. acuta populations might play a role in diluting or enhancing transmission of indigenous parasites in several ways. Physa acuta may act as a decoy host [P. acuta overtook Bulinus forskalii, a primary transmitter of human schistosomiasis (Schistosoma haematobium), as the dominant snail. It has been shown experimentally Schistosoma haematobium can penetrate P. acuta in Nigeria, though the parasite cannot reach patency [P. acuta acting as a reservoir for larval parasites, specifically as a second intermediate host to trematodes. Similarly, non-host specific larvae of the invasive nematode Angiostrongylus (=Parastrongylus) cantonensis were reported in Saudi Arabia [P. acuta.Apart from directly hosting trematodes, invasive coy host –111 to icoy host , 16. Dob patency . There ai Arabia  and Egypi Arabia  from P. P. acuta, we aim to begin to use this system to address the role of host demographics in the acquisition of local parasite assemblages specifically, to identify potential predictors of parasite invasion success for the purposes of modeling host-parasite invasion over time.Host-parasite invasion dynamics are often underappreciated when considering the impact of invasive species, especially when the associated parasites are not causing notable pathology. Most commonly it seems hosts acquire a distinct assemblage of indigenous parasites within their invasive range  over timPhysa acuta within its native range, where mtDNA analyses reveal two phylogenetic clades (A & B) and previously unknown population structure between the Eastern and Western USA. Increased sampling of native populations allowed the estimation of the invasion history of P. acuta. We report evidence for the occurrence of multiple independent invasion events from different source populations across the USA and Eastern Canada. The initial invasion into Western Europe occurred over 200 years ago, with more recent invasions into the Southern Hemisphere  occurring within the last 20–80 years.This study provides improved sampling of tsi, pr, So and host-population genetic parameters  to identify parameters of relevance for modeling host-parasite invasion dynamics over time. We found a significant positive relationship among π with trematode pr and So. These data suggest that, (1) host demographic parameters might be integral in the assembly of parasite communities within invasive host populations and (2) background genetic diversity may be an important parameter to consider in future efforts to model host-parasite invasion dynamics. Overall, our data supports predictions based on the ‘Enemy Release hypothesis’ [We also examined the relationship between othesis’ , 37. HosAdditional file 1:Physa acuta locality and database information. (XLSX 27 kb)Additional file 2:Physa acuta locality and database information (XLSX 13 kb)Non-Additional file 3:Physa estimated using Bayesian inference. Posterior probability values ≥.95 are shown. Taxon names are reflective of the names assigned to sequences in the original NCBI records. (PDF 14 kb)CO1 phylogeny of Additional file 4:cox1 phylogeny. Branch support values ≥.95/70 (PP/BS) are shown. Taxon names are reflective of the names assigned to sequences in the original NCBI records. (PDF 165 kb)Concatenated 16 + Additional file 5:ITS1 phylogeny estimated using Bayesian inference. Physa acuta samples are colored according to the clade they were recovered from based on mitochondrial gene tree analysis: pink = Clade A, green = Clade B. Physa acuta taxa labeled as black did not group within P. acuta based on mitochondrial gene trees, and were excluded from all in-group analyses . ITS1 data only exists for HQ283259 and Pacuta_18S/ITS and were therefore not included in mitochondrial gene tree analyses. Posterior probabilities are illustrated as branch support values. (PDF 143 kb)Additional file 6:16S in-group analysis. Taxa are colored according to the FWEC they were collected from. Phylogeny (A) was generated using ML methods and phylogeny (B) was generated using BI. Branch support values ≥70 bootstrap (A) and ≥ .95 posterior probabilities (B) are denoted by a black circle. (PDF 188 kb)Additional File 7:n = 79), Central and South America , Eurasia  and Africa and Oceania . North America dataset ran for 50,000,000 generations, Eurasia 20,000,000 generations, Central/South America and Africa/Oceania ran for 5,000,000 generations. B. Estimates by FWECs sampled: Rio Grande , Coastal , Colorado , Atlantic , Mississippi , the Great Basin and St. Lawrence FWECs were excluded because of low sample size. All FWEC datasets were run for 5,000,000 generations, with the exception of Atlantic . C. Estimates of recovered Clades, Clade A  and B  compared to total . The total dataset and Clade A ran for 80,000,000 generations, Clade B ran for 10,000,000 generations. Bayesian skyline plots were constructed in TRACER, the data was exported and visualized using Excel. (PDF 144 kb)Bayesian Skyline Plots. Effective size over time plots estimated in BEAST using a Bayesian Skyline prior, mean values are shown and confidence values were excluded for clarity. Three mutation rates (per million year): 1% (solid line), 0.04% (dashed line) and 4%(circle line) were tested. (A) Range-wide estimates for North America


Zymoseptoria tritici. First, we performed genome scans in four field populations that were sampled from different continents and on distinct wheat cultivars to test which genomic regions are under recent selection. Based on extended haplotype homozygosity and composite likelihood ratio tests, we identified 384 and 81 selective sweeps affecting 4% and 0.5% of the 35 Mb core genome, respectively. We found differences both in the number and the position of selective sweeps across the genome between populations. Using a XtX‐based outlier detection approach, we identified 51 extremely divergent genomic regions between the allopatric populations, suggesting that divergent selection led to locally adapted pathogen populations. We performed an outlier detection analysis between two sympatric populations infecting two different wheat cultivars to identify evidence for host‐driven selection. Selective sweep regions harboured genes that are likely to play a role in successfully establishing host infections. We also identified secondary metabolite gene clusters and an enrichment in genes encoding transporter and protein localization functions. The latter gene functions mediate responses to environmental stress, including interactions with the host. The distinct gene functions under selection indicate that both local host genotypes and abiotic factors contributed to local adaptation.The genetic and environmental homogeneity in agricultural ecosystems is thought to impose strong and uniform selection pressures. However, the impact of this selection on plant pathogen genomes remains largely unknown. We aimed to identify the proportion of the genome and the specific gene functions under positive selection in populations of the fungal wheat pathogen  In each location, all isolates were collected from a single field and cultivar, except for the Oregon isolates that were collected from two different wheat cultivars, Madsen and Stephens, growing in the same field  was used to mark PCR duplicates in the alignment (bam) files. Average coverage ranged from 8× to 29× for all 123 isolates and no evidence of chromosomal aneuploidy was found . We retained 1,678,238 SNPs with a genotyping rate >90% from freebayes. To identify the most stringently called SNPs, we retained only SNPs called using HaplotypeCaller and freebayes using the option –diff‐site of vcftools version 0.1.13  calling and variant filtration were performed using the Genome Analysis Toolkit (GATK) version 3.3‐0  and four Z. ardabiliae isolates  version 3.3‐0. Then, we repeated the SNP calling to include all Z. tritici, Z. pseudotritici and Z. ardabiliae isolates. SNPs were filtered for quality as described above. For each of the two Z. tritici sister species, we retained SNPs with a genotyping rate >50% and no intraspecific polymorphism. We assigned ancestral alleles for any Z. tritici SNPs if an identical allele was retained in both sister species. We were able to assign ancestral alleles for 584,327 SNPs .To identify ancestral alleles at SNPs, we analysed whole‐genome sequencing data of the two closest known sister species of 2.4Zymoseptoria tritici isolates using three methods. We performed a principal component analysis (PCA) based on all SNPs using the software tassel version 5.2.14  replicates. Parameter convergence was inspected visually. Cluster assignment probabilities were computed using the clumpp program  test of SweepFinder .We detected selective sweeps using an extended haplotype homozygosity (EHH) and a composite likelihood ratio (CLR) tests. We performed each test for the four allopatric populations separately and included only SNPs with known ancestral states. For both tests, we used conservative percentile thresholds of the test statistics distribution to identify the strongest selective sweep regions. For the EHH test, we computed the integrated haplotype score (iHS) measure as implemented in the Nielsen, . The CLRNielsen, . We calcNielsen, . Based o Tajima,  statisti2.6baypass (formerly bayenv) using the software default parameters  test  across the four populations.To detect SNPs harbouring signatures of population divergence, we calculated the XtX statistic implemented in the program Gautier, . We usedGautier, . To deteoci Nei, . We used Goudet,  that imp Goudet,  to calcu2.7interproscan v.5.16‐55.0 using default settings  and the iHS based method (rehh software). We used the r packages {GSEABase} and {GOstats}  3 gene cluster on chromosome 5. For this, we used all SNPs with a minor allele frequency >0.1 in the Swiss, Israel and Oregon populations. We calculated the linkage disequilibrium 33.1Z. tritici isolates sampled from single wheat fields in Australia, Switzerland, Israel and Oregon, USA , we identified a total of 90, 126 and 114 selective sweep regions in the Swiss, Israel and Oregon populations, respectively. Detected sweep regions were found on all 13 core chromosomes  scores , we detected 6, 15, 29 and 31 regions affected by selective sweeps in the Australian, Oregon, Swiss and Israel populations, respectively  and Tajima's D values were significantly lower for genes contained in selective sweeps identified by the CLR test than for genes not contained in selective sweeps  to be shared among multiple populations. The majority of shared selective sweep regions were between two populations . Selective sweep regions were shared among three populations on chromosomes 4 , 9 (986–987 kb) and 10  in at least one pairwise population comparison , including the polyketide synthase (PKS) genes PKS10 (1_01966), PKS3 (5_00021) and PKS2 (9_00441), and the nonribosomal peptide synthetase (NRPS) gene NRPS1 , 10 peptidases, five peroxidases and 23 small secreted proteins (SSPs) lacking conserved domains  and a MFS transporter gene  in the pairwise comparisons of Israel–Oregon and Israel–Switzerland  was also detected by the CLR test in the Swiss population  for pairs of SNPs at >10 kb distance in the Swiss, Israel and Oregon populations  identified through the divergence scan among the four populations were located in intergenic regions. The remaining SNPs were distributed across 36 different genes  of the genome experienced recent positive selection. Selective sweep regions were narrow but widespread across the genome in all analysed populations. We chose very stringent thresholds for selective sweep detection to identify the strongest selective sweep regions. The number of detected selective sweeps would likely be higher by including all acceptable sweep regions based on demographic modelling. The extent of signatures of positive selection was consistent with studies in other fungi based on the same CLR tests. Genome scans in European populations of the anther smut fungus Microbotryum, a plant pathogen found in natural ecosystems, revealed that 1%–17% of the pathogen genome was affected by selective sweeps . The CLR test allows detection of hard sweeps, whereas iHS is more powerful for detecting incomplete sweeps  were associated with host‐specific virulence  and secondary metabolite production. The roles of secondary metabolites produced by Z. tritici remain poorly understood, but the clusters are likely to play roles in host adaptation, competition with microbes and environmental stress . EHH and CLR tests may be unsuitable to detect the very rapid diversification into dozens of haplotypes that are typically observed at the CYP51 locus.Environmental factors are also likely to impose significant selection pressure (Stukenbrock & McDonald, Howlett, . The PKSHeterogeneity in both biotic and abiotic stresses creates the opportunity for local adaptation in plant pathogens (Croll & McDonald, The sequencing data are available at the Nucleotide Short Read Archive under BioProject Accession nos PRJNA327615 and PRJNA178194.The study was conceived by F.E.H. and D.C. The analysis was performed by F.E.H. The data were interpreted by F.E.H., B.A.M. and D.C. The manuscript was written by F.E.H. and D.C with contributions from BAM. Click here for additional data file. Click here for additional data file.


Anthropogenic influences on global processes and climatic conditions are increasingly affecting ecosystems throughout the world.Hawaii Island’s native ecosystems are well studied and local long‐term climatic trends well documented, making these ecosystems ideal for evaluating how native taxa may respond to a warming environment.Drosophila, D. sproati, that are separated by only 7 km and 365 m in elevation.This study documents adaptive divergence of populations of a Hawaiian picture‐winged Representative laboratory populations show divergent behavioral and physiological responses to an experimental low‐intensity increase in ambient temperature during maturation. The significant interaction of source population by temperature treatment for behavioral and physiological measurements indicates differential adaptation to temperature for the two populations.Significant differences in gene expression among males were mostly explained by the source population, with eleven genes in males also showing a significant interaction of source population by temperature treatment.The combined behavior, physiology, and gene expression differences between populations illustrate the potential for local adaptation to occur over a fine spatial scale and exemplify nuanced response to climate change. While less mobile species, such as the endemic Tetragnatha spiders, have been found to display neutral population differentiation among these kipukas, neutral differentiation among more mobile species has not been well studied in this habitat mosaic and only rarely at this scale  where the species can be found in this region against those from the highest (“High” at 1625 m), which is approximately 7 km upslope. The suitability of the two sites as representing mature wet forest habitat was quantified through a surface cover and tree/tree fern surveys conducted at the center and edge of each kipuka. The presence of a climatic gradient corresponding to elevation was assessed through concurrent measurement of temperature and humidity during a 2‐week period using HOBO Pro v2 data loggers placed under shaded covers at the center and edge of each kipuka.This study focuses on populations of 2.2D. sproati were captured from the center of each kipuka using fermented banana bait. The flies were immediately transferred to one‐gallon breeding jars kept in a climate‐controlled laboratory and maintained at 18°C, the standard rearing temperature for picture‐winged Drosophila . Subsequent analyses were performed on adult flies between 3 and 4 weeks old from each population/sex/temperature group, with different flies used for each physiological and behavioral analysis.Flies from the sixth laboratory generation were isolated by sex within 24 hr of emergence. Half of each population/sex group were maintained at 18°C for the first week of maturation, moved to a 24°C climate‐controlled laboratory for the second week, and returned to 18°C for the third week, while the other half matured at a constant 18°C .The physiological analysis measured the response of each population/sex/temperature group to subsequent high‐intensity heat and cold shocks. Heat knockdown resistance was measured by exposing flies to 32.5°C and recording the time until knockdown at half hour intervals. Cold chill coma recovery was measured by chilling flies at 2°C for 1.5 hr to induce a comatose state, then returning them to 18°C and recording the number of minutes until each fly righted themselves. These two tests are conventional measures of thermal tolerance in 2.6p < 0.05.A two‐way analysis of variance (ANOVA) was used to assess the significance of source population, temperature treatment, and the interaction of the two factors on the behavioral and physiological measures, using the statistical program MiniTab version 15, with all data first tested for normality. For response variables that exhibited significant block effects due to differences among the weeks of the study, the residuals from an analysis of variance for the block effect were used in subsequent analysis of source population and treatment effects. The ANOVA analyses were performed on all response variables  in a two‐way interaction model with source population and temperature treatment as the main factors considered random variables . Pairwise significance testing was performed among all population/sex/temperature groups for each measure using Tukey's multiple comparison tests and a significance threshold of 2.7D. sproati sampled among multiple locations within the large eastern wet forest region of Hawaii Island that encompasses the study site . The RNA was normalized to a concentration of 30 ng/μl and submitted to the John A. Burns School of Medicine at the University of Hawaii at Manoa core genetics facility for microarray processing. Briefly, an Agilent Technologies low‐input quickAmp Labeling kit was used to reverse transcribe RNA into cDNA and amplify it in the presence of dye‐labeled nucleotides (Cyanine‐3 CTP). Labeled samples were hybridized at 65°C overnight on a commercially prepared Agilent Technologies  microarray slide, with males and females loaded on to separate slides. Each microarray contained 14,850 probes, of which 14,766 produced signals and represented 14,319 D. grimshawi genes. After hybridization, microarray slides were washed at room temperature (37°C) for 1 min each using Agilent wash buffers, followed by slide scans using Agilent scanner G2565CA. Adherent dye intensities were recorded using Agilent Technologies Feature extraction software. Statistical differences in log2 gene expression were measured using a two‐factor ANOVA with main factors source population and temperature treatment and a factor for their interaction. Data were analyzed separately by sex. In cases where the Agilent chip contained multiple probes per gene (828 probes for 383 genes), the probe expression values were averaged across each gene. To adjust for multiple tests, a Benjamini–Hochberg false discovery rate (BH‐FDR) was applied to ANOVA p‐values using a statistical significance threshold of q < 0.05 implemented in the R package “stats” v. 3.1.1.A total of 44 flies (three to seven per population/sex/temperature treatment group) were subjected to microarray‐based gene expression analysis upon completion of their three‐week maturation period Figure , Table 12.9D. sproati genes  were assigned to gene ontology (GO) categories and tested for overrepresentation utilizing Protein ANalysis THrough Evolutionary Relationships  showed multiple significant differences in behavior that were explained by source population or the interaction between source population and temperature treatment  at either the COII or YP1 gene as measured by pairwise FST  or by an exact test of population differentiation . Internal characteristics of the two populations were similar in both loci , despite nonsignificance for that term. Although no significant changes in gene expression were solely attributed to the main factor temperature treatment , 11 genes in males were significant for the population and temperature treatment interaction term  genes in the male group and for 96  genes in the female group Appendix . Females3.6D. melanogaster gene symbols to 84% (566 of 671) and 93%  of the DEGs upregulated in the low‐ and high‐elevation population groups . Based on these gene symbols, 471 and 777 DEGs were assigned to PANTHER GO category terms, after accounting for paralogs  and genes with no mapping information. Allocations of these genes to each of the three major GO categories—molecular function, biological process, and cellular component—indicate a greater number and diversity of overrepresented GO terms (n = 36) in the high‐elevation relative to the low‐elevation population groups (n = 4) , D. silvestris , to be differentially upregulated in the low‐elevation population. Clearly, temperature is only one of many selective pressures that drives adaptive divergence, and assessing ecological responses to anthropogenic climate change may benefit from broader surveys of gene expression responses under a variety of environmental conditions . Our findings add to the growing body of literature that identifies candidate genes and biochemical pathways that may underlie physiological adaptations to local environmental conditions.In addition to HSPs, several non‐HSP genes associated with temperature tolerance in other studies were differentially expressed between the low‐ and high‐elevation male population groups. Most notably, Glutathione S transferase (GstD2 and GstD5) genes have been identified as heat resistance genes through multiple lines of research: QTL mapping, differential gene expression, and gene deletion approaches (Leemans et al., Drosophila species, including natural populations of D. melanogaster and D. buzzatii (Michalak et al., D. sproati are large and able fliers, and the previous island‐wide study did not find genetic structuring within the larger wet forest region on the eastern side of Hawaii Island (Eldon et al., The evidence for adaptive divergence between the low‐ and high‐elevation populations is supported by significant differences in behavior, physiology and gene expression, and no significant population genetic structure as estimated using the COII and YP1 genes in the wild‐caught flies collected from the source populations. Further studies are needed to determine whether the underlying DNA sequence divergence between populations result in the important differences in behavioral and physiological traits and thus represent rapid local adaptation following recent isolation. Differentiation in the presence of ongoing gene flow is known to occur in Drosophila species found 99.6% insemination across the group, and 100% among D. sproati females (Kambysellis & Craddock, D. sproati females to have the highest potential fecundity of the sampled Hawaiian Drosophila species, having on average 65 ovarioles per fly and 1–3 mature eggs per ovarioles (Kambysellis & Heed, This observation of potential adaptive divergence without differentiation at putatively neutral loci could also be explained if the laboratory populations were not in fact representative of the wild populations. This might occur from strong founder effects or selective bottlenecks during the establishment of the laboratory populations, or from dramatic genetic drift during the five generations in the laboratory. However, a previous survey of wild‐caught mature females from multiple Hawaiian D. sproati separated by only 7 kilometers and 365 m in elevation, but no evidence of population differentiation at genes commonly used to estimate population genetic structure. This finding suggests that the ecological responses to climatic differences may occur at finer scales and be more complex than is often assumed. For example, a common assumption is that close proximity or a lack of differentiation at putatively neutral gene sequences indicates lack of adaptive population divergence, but clearly that is not the case in this study. This finding is relevant to conservation planning efforts, which often use the former assumptions to determine management units. In addition, rather than observing a simple range shift, where one population was more stressed and the other less so, this study found that the marginal D. sproati populations are making opposing adaptive trade‐offs under increasing ambient temperatures. Such results caution against the reliance on neutral loci alone or broad ecological assumptions when planning conservation actions. Instead, the findings of this study suggest that we need to adopt a more precise and integrated approach to investigating ecological responses to global climatic change and a more data‐driven approach to drawing conclusions, predictions, and management recommendations.In this study, we found evidence that indicates there is adaptive divergence of populations of None declared.D. sproati population used in this study and conducted the behavioral, physiological, and neutral genetic analysis. DP and RB conducted the gene expression analysis. RB modeled and analyzed gene expression profiles and performed functional annotation. DP guided the project design and supervised all research activities. All authors contributed critically to the drafts and gave final approval for publication.JE collected and maintained the  Click here for additional data file. Click here for additional data file. Click here for additional data file.


We genotyped 738 individuals belonging to 49 populations from Nepal, Bhutan, North India, or Tibet at over 500,000 SNPs, and analyzed the genotypes in the context of available worldwide population data in order to investigate the demographic history of the region and the genetic adaptations to the harsh environment. The Himalayan populations resembled other South and East Asians, but in addition displayed their own specific ancestral component and showed strong population structure and genetic drift. We also found evidence for multiple admixture events involving Himalayan populations and South/East Asians between 200 and 2,000 years ago. In comparisons with available ancient genomes, the Himalayans, like other East and South Asian populations, showed similar genetic affinity to Eurasian hunter-gatherers , and the related Bronze Age Yamnaya. The high-altitude Himalayan populations all shared a specific ancestral component, suggesting that genetic adaptation to life at high altitude originated only once in this region and subsequently spread. Combining four approaches to identifying specific positively selected loci, we confirmed that the strongest signals of high-altitude adaptation were located near the Endothelial PAS domain-containing protein 1 and Egl-9 Family Hypoxia Inducible Factor 1 loci, and discovered eight additional robust signals of high-altitude adaptation, five of which have strong biological functional links to such adaptation. In conclusion, the demographic history of Himalayan populations is complex, with strong local differentiation, reflecting both genetic and cultural factors; these populations also display evidence of multiple genetic adaptations to high-altitude environments. The Greater Himalayan Region is a geographical area containing the world’s highest mountain peaks and a diversity of environments that have required substantial genetic adaptations by the humans who live there. This mountain barrier has also shaped the genetic, cultural, and ethnolinguistic mosaic of South and East Asia. At present, the area falls into the countries of Nepal, Bhutan, India, Pakistan, and the Tibetan Plateau in China. Opinions are divided about whether the Himalayas were used as a corridor that facilitated human migrations from the Tibetan plateau to South Asia in ancient times, or alternatively remained uninhabited due to their inhospitality until more recent times . ArchaeoEPAS1) haplotype, whose frequency is strongly correlated with altitude in the Himalayan populations, has been suggested to have been acquired from an extinct hominin species, Denisovans  . Howevernisovans . In the K between 2 and 5 usually leads to a single population being distinguished, suggesting extensive genetic isolation and drift. Toto, an outlier in the PCA, is also characterized by an independent ancestral component even at a K value of 2  which is shared among all the high-altitude populations and is significantly positively correlated with altitude  (We first investigated the population history and demography of the region  online blue of 2 C. By con2×10−18)  online.A long-term Ne value can be estimated using SNP genotyping data, but has limitations and can only be used as a proxy for the variability of their effective population sizes and thus the overall genetic diversity, but nevertheless allows some informative comparisons. The Chetri have the highest long-term Ne, whereas Toto have the lowest  online, We explored whether or not Himalayan populations show extended runs of homozygosity (ROHs), which may arise from endogamy. Overall, Himalayan populations are characterized by a high number of autozygous segments of different lengths across the genome . NepalesThe phased Himalayan and worldwide population data were also used to reconstruct phylogenetic relationships between the samples and to identify population structure through a Bayesian clustering algorithm implemented in fineSTRUCTURE. The inferred phylogenetic tree shows two main branches splitting Nepalese from Bhutanese plus Tibetans A. All thD-statistics  for pairs of Sherpa, Tibetan, and Bhutanese populations , with just 36 out of 210 tests statistically significant at a Z score ≥4 , showing that some high-altitude Himalayan populations have increased genetic affinity with the low-altitude East Asians . This difference may reflect the smaller range of longitude of our samples.Finally, we computed ulations . D-statit Asians  online. f3-statistics, ALDER, and TreeMix. All the tests provide evidence of admixture between Himalayan and other populations , and the related Bronze Age Yamnaya, than to European farmers  genome-wide Spearman’s correlation between derived allele frequency and altitude; 2) EMMAX, a genome-wide statistical test for association between SNP frequency and altitude that accounts for population substructure ; 3) the pulation ; and 4) pulation .rho >0.72) (EPAS1 and Disrupted in Schizophrenia 1 (DISC1) previously identified by Tibetan exome sequencing   online wo >0.72)  online. quencing   which falls in a CTCF binding site, shows single-tissue eQTLs associated with the ATP6V1E2, CXXC repeat containing interactor of PDZ3 domain (CRIPT) and Transmembrane protein 247 (TMEM247) genes (TRIM67) near Egl-9 family hypoxia inducible factor 1 (EGLN1), which has previously been associated with high-altitude adaptation in Tibetans (r2 = 0.87) with another nearby variant, rs844335, that was picked up by PBS because of its high derived allele frequency, between 80% and 97% in high-altitude populations, compared with a maximum frequency ≤61% in 1000 Genomes Project populations. rs4702062 lies in an intergenic region upstream of the ANKH inorganic pyrophosphate transport regulator (ANKH) gene on chromosome 5, while rs844335 lies within an open chromatin region nearby, and is also in LD (r2 = 0.73) with a third variant, rs1550825, that lies in a transcription factor binding site (ANKH gene codes for a transporter that regulates the passage of inorganic phosphate through the cell and contains two hypoxia-responsive elements (HREs) in proximity to its promoter region, and thus its expression is regulated by hypoxic factors (HIFs)  genes  and has 7) genes  online. Tibetans . The thiTibetans F. This ving site  online. s (HIFs) .P values from the first three methods provides a concise way to merge their findings, although not a measure of the type-1 error rate because the tests are not completely independent. This approach identified 398 variants with Bonferroni-adjusted P value <0.01 , Collagen type IV alpha 4 chain (COL4A4), Solute carrier family 52 member 3 (SLC52A3), Megakaryoblastic leukemia (translocation) 1 (MKL1), and Growth factor receptor bound protein 2 (GRB2) genes (10(BF) >2] <2] and substantial  candidates, respectively.Combining the ue <0.01  online. to EMMAX . Multiplto EMMAX  online. 2) genes G. The re(BF) >2]  online. SLC52A3 region includes a missense variant  with derived allele frequency >70% in most high-altitude populations compared with a maximum frequency ≤35% in the 1000 Genomes Project populations, and a synonymous variant (rs3746807) with overall high derived allele frequency in Himalayan populations (42–100%) compared with a maximum frequency ≤24% in 1000 Genomes Project populations . This region also contains a missense variant (rs3752895) that shows single-tissue eQTLs in brain tissue for the Rhomboid domain containing 1 (RHBDD1) gene and a synonymous variant (rs2228557). These two variants show high CADD scores of 17.2 and 16.7, respectively. The GRB2 region on chromosome 17 shows four intronic SNPs and has previously been associated with hypoxia-induced oxidative stress level at the intestinal mucosal barrier in Tibetans compared with Han Chinese . The missense variant rs3746804 in the SLC52A3 locus also shows a high derived allele frequency of 0.67 in the ancient Himalayans. Variants in COL4A4, ANKH, RP11-384F7.2/AC068633.1, and HLA-DBP1/DBP2 show derived allele frequencies in the ancient Himalayans of 0.56–1.00, while two variants, rs4542691 and rs4789182, in the GRB2 locus show a derived allele frequency of 100% in the ancient samples. Finally, rs3826597 in ZNF532 region show a derived allele frequency of 0.95 in the ancient Himalayans  and Vitamin D receptor (VDR), suggested previously by Hu et al. to be under selection for high-altitude adaptation, are also predicted to be in the same protein–protein interaction network , and the absence of correlation between the increased genetic affinity to lowland East Asians and the spatial location of the Himalayan populations  and HIF1A  production in hypoxic environments and it has been shown that, in Tibetans, downregulation of its expression reduces ROS damage and improves glucose and fat metabolism in intestinal tissues  suggested by Hu et al. are predicted to be in the same protein–protein interaction pathway as some of our candidates, COL4A4 and GRB2, and linked with other genes  involved in the hypoxic response  highlighted by our work , four araptation  online. aptation , none ofc region , show siIn conclusion, the current analyses have established the broad features of Himalayan genetic variation: a South or East Asian substrate influenced by local differentiation and mixing in ways that are now understood in outline, including extreme genetic drift in several populations. It has provided a comprehensive data set from the region for the community to use in future studies. In addition, there is evidence for early strong genetic adaptation to high-altitude living followed by spread of the adapted population. Future functional investigations will allow these phenomena to be understood in more detail.Eight hundred and eighty-three individuals belonging to 49 Himalayan populations were genotyped and analyzed after obtaining informed consent. The data set included 26 populations from Nepal, 16 from Bhutan, two from North India sampled in Bhutan, and five from Tibet in China  online. P value <0.0000001 were removed. We also removed related samples (PI_HAT > 0.35) and outliers using EIGENSOFT 6.0 (r2 > 0.5). The pruned Himalayan data set consisted of 256,506 SNPs, and the pruned worldwide data set included 190,287 SNPs. For comparison with ancient samples, we generated two further data sets: 1) we merged our data with the Human Origins data, a data set comprising both modern and ancient individuals including archaic genomes from Denisovans and Neanderthals, and a chimpanzee (The samples were genotyped using three Illumina SNP-chips: 1) HumanOmniExpress-12 v1.0 Bead Chip  at the Wellcome Sanger Institute; 2) HumanOmni1-Quad BeadChip (∼1 M SNPs) at the Leiden University Medical Center; and 3) HumanOmniExpress-24 BeadChip  at BGI-Shenzhen. Genotype calling and QC on all samples were performed using the Sanger Institute’s variant calling pipelines, and SNP positions were mapped to the human reference assembly GRCh37. Genotypes from the three arrays were merged using PLINK 1.92 , resultiSOFT 6.0 . These fSOFT 6.0  online  for each Himalayan population and population divergence time was performed using the NeON R package (r2) and recombination distance (c) we estimated the effective population size using the nonlinear regression model: iy =1/(α + βic)+ie, with iy = (r2 1/n) (r2 adjusted for chromosome sample size) for SNP pair i at recombination distance ic (in Morgans). We estimated the change in population size over time, as LD between loci with a recombination rate of c that reflects the ancestral effective population size 1/(2c) generations ago (c) should be viewed only as an approximate but useful indication of timeframes (r2), thereby biasing the estimate of divergence time downward. Nevertheless, this method is still useful to assess isolation and difference in Ne between populations (r2 > 0.5) with only common variants (MAF >0.05) was used. The minimum number of SNPs to call an ROH was set to 100, the heterozygote allowance was set up to zero, the missing SNP allowance was set to 5 (5% of SNP threshold), and the window threshold to call an ROH was set to 0.05. The coefficient of inbreeding (F) was calculated with PLINK  using EIGENSOFT 6.0 was performed using the LD-pruned data sets. For the worldwide data set, the eigenvectors were calculated using the global diversity and the Himalayan individuals were projected onto the plot . ADMIXTU package , which cions ago . The modmeframes . Furtherulations . Only poulations . ROHs weulations  with speulations  and otheth PLINK .A worldwide data set using a maximum of ten individuals from every population was used in the ChromoPainter and fineSTRUCTURE-2.0.6  analysesD-statistics (qpDstat function in ADMIXTOOLS v3 package) using the following phylogeny: D where high-altitude Himalayan 1 and high-altitude Himalayan 2 are pairs of Sherpa, Tibetan, or Bhutanese populations from an altitude of 2,500 m or above sea level (D-statistics with the above phylogeny using our worldwide data set (D-statistics with pairwise differences in longitude and latitude for each pair of populations using the Mantel test implemented in the “Ade4” R package (mantel.rtest function)  but more markers  using the same parameters. To test whether or not genetic similarity among high-altitude populations correlates with their geographical location, we used YRI  as an outgroup and calculated ea level . We compdata set  online. unction) .f3)   where X are different modern human populations from the worldwide data set).Population admixture was studied using ALDER v1.03 , three-pf3) , and Tref3) . Only po Yoruba)  with Yor Yoruba) ; 2) Bron Yoruba) ; 3) Neol Yoruba) ; 4) Meso Yoruba) ; 5) Eura Yoruba) ; 6) five Yoruba) . We also Yoruba) . We alsoP value for multiple tests by applying the Bonferroni correction (requiring <0.05/number of tests). Second, we calculated a genome-wide association between allele frequency and altitude using a mixed model approach implemented in the Efficient Mixed-Model Association eXpedited program (EMMAX)   we calculated a rank P value of the PBS values ; 2) we combined the P values of the three statistics genome-wide; and 3) we adjusted the P value for multiple tests by applying the Bonferroni correction (requiring < 0.01/number of tests). Finally, to further validate our selection signals, we calculated genome-wide associations between allele frequency and altitude using BayEnv v2 (r2 > 0.5) pruned SNP file using PGDSpider (10(BF) > 2] were considered significant. Where possible, we also calculated allele frequencies in the five Himalayan ancient genomes for our top candidates of selection.Signals of positive selection were evaluated in four ways. First, we considered the Spearman correlation between derived allele frequency and the residence altitude of each population , adjusti (EMMAX) . EMMAX dex (FST)  for eachex (FST) . To reduex (FST) , assuminex (FST) . For thiex (FST) . The topex (FST) . We alsoex (FST)  for combayEnv v2 , a BayesGDSpider  and altiGDSpider : only caSLC52A3 onto the protein structure using PyMOL . We predicted protein–protein interaction networks using the STRING software (v. 10.5) (We generated a protein homology model for SLC52A3 using Phyre2 software  and mappv. 10.5)  for our v. 10.5)  to prediv. 10.5)  of our tv. 10.5) . All the genotype data are available from European Genome-phenome Archive under accession number EGAS00001002731.http://grch37.ensembl.org/info/docs/tools/vep/index.html, last accessed May 10, 2018Ensembl VEP: https://www.gtexportal.org, last accessed May 10, 2018GTEx Portal: http://www.sbg.bio.ic.ac.uk/phyre2, last accessed May 10, 2018Phyre2: https://www.cog-genomics.org/plink2, last accessed May 10, 2018PLINK: https://www.pymol.org/, last accessed May 10, 2018PyMOL: http://string-db.org, last accessed May 10, 2018STRING: http://cadd.gs.washington.edu/, last accessed May 10, 2018Combined Annotation Dependent Depletion (CADD): Molecular Biology and Evolution online.Supplementary DataClick here for additional data file.


Cyprinus carpio, is a cyprinid fish species cultured in Europe and Asia. It accounts for >70% of freshwater aquaculture production worldwide. We conducted a population genomics analysis on C. carpio using high-throughput SNP genotyping of 2,198 individuals from 14 populations worldwide to determine the genetic architecture of common carp populations and the genetic bases for environmental adaptation. Structure analyses including phylogeny and principal component analysis were also conducted, showing distinct geographical patterns in European and Asian populations. The linkage disequilibrium block average lengths of the 14 populations ranged from 3.94 kb to 36.67 kb. Genes within selective sweep regions were identified by genome scanning among the different populations, including gdf6a, bmpr1b, and opsin5. Gene Ontology and KEGG enrichment analyses revealed potential trait-related loci and genes associated with body shape, scaling patterns, and skin color. This population genomics analysis may provide valuable clues for future genome-assisted breeding of C. carpio.The common carp,  Cyprinus carpio, is one of the most important cyprinid species due to its food value and complex paleotetraploidized genome. It is cultured in >100 countries, and the annual global production of C carpio is > 4.56 million metric tons. This is approximately 10% of the global freshwater aquaculture production (C. c. carpio) and the East Asian subspecies (C. c. haematopterus)  . The valtopterus .fgfr1a1 in the selective regions , have been used in population genetics. Many studies have demonstrated that SNP arrays can improve the resolution of the differentiation of genetic stocks . SNP assMany SNP markers have been identified from common carp , and a hC. carpio  were randomly collected across Europe, North America, and China. DANU, TZ, and Szarvas 22 (SZ) were collected from the carp live gene bank of the Research Institute for Fisheries, Aquaculture and Irrigation of Hungary (HAKI). North American carp (AME) were collected from the Chattahoochee River in Alabama in the USA. Ten other populations were sampled from China, namely, the YR from Zhengzhou of Henan Province, HB from Wuyuan of Jiangxi Province, XG from Xingguo of Jiangxi Province, OUJ from Oujiang of Zhejiang Province, KOI from Beijing, QSJ from Guiyang of Guizhou Province, JIAN from Wuxi of Jiangsu Province, SH and SP from Harbin of Heilongjiang Province, and HLJ from Mudanjiang of Heilongjiang Province. The numbers of samples from each population are shown in The 14 populations of https://www.cog-genomics.org/plink2) was used for quality control (https://www.ebi.ac.uk/ena/data/view/PRJEB33066).Genomic DNA was extracted from blood or fin samples using a DNeasy 96 Blood & Tissue Kit  following the manufacturer’s protocol. Extracted DNA was quantified by a Nanodrop-1000 spectrophotometer . DNA integrity was examined on a 1.0% agarose gel by electrophoresis. The final DNA concentration was diluted to 50 ng/μl for genotyping with an amount of 2 μg per sample. The common carp 250-K SNP array was developed using Affymetrix Axiom genotyping technology. Genotyping was performed by GeneSeek . After genotyping, PLINK v1.9 software ( control . SNPs wihttp://itol.embl.de/upload.cgi). Principal component analysis (PCA) was conducted using GATK software  decays for the main populations and all of the samples were calculated within a range of 50 kb using PLINK . The avelculated . All of D values were also calculated using Vcftools with the parameters “–weir-fst-pop” and “–TajimaD,” respectively. We identified the regions with the 5% highest π ratios and the regions with the 5% highest Fst values. Together with regions identified on the basis of the above two thresholds, genes within selective sweeps were annotated using GOEAST for Gene Ontology (GO) (http://cran.r-project.org/package=ggplot2).We calculated the π distribution for each linkage group using a sliding window method in Vcftools. The window width was set to 100 kb, and the stepwise distance was 100 kb. The π values from the main populations were compared, and the ratios were sorted. Fst and Tajima’s ogy (GO)  and the ogy (GO)  for KEGGC. carpio were collected from 13 locations in China, Hungary, and the USA  were calculated using a 200-kb sliding-window approach with Vcftools software. In comparison to the Scaled carp in Asia , the SP population had distinct genetic diversities across the whole genome (gdf6a), also named cartilage derived morphogenetic protein 2, is a member of the BMP family. The expression of the gdf6a gene has been detected in both fetal and post-natal cartilaginous tissues involved in the development of long bones. The gdf6a gene may play a role in suppression of ossification (igfbp5) is a member of the IGFBP family that can either inhibit or stimulate the growth-promoting effects of the IGFs on cell culture. It is involved in the Ras/p38 MAPK signaling pathway in regulating cell proliferation and apoptosis , which showed distinct body shapes or body color, respectively. YR and HB were compared because they represent the typical populations in central China and southern China, respectively. QH and FY were compared due to their high similarity in genome background and the possibility that it might be easier to screen out potential genes associated with body color. We identified a total of 321 significant windows corresponding to 64.2 Mb in size for each comparison , which included 293 and 287 candidate genes, respectively. To further validate the genome regions under strong selective sweeps in the HB or FY population, the genome regions with Fst greater than 0.2588 or 0.1622 (top 5%) were also identified, including 278 and 292 candidate genes, respectively. A total of 38 and 65 candidate genes shared by both the π ratio and Fst analysis were recognized, respectively, as genes potentially affected under selective sweeps (trhr and bmpr1b) were screened out for their potential functions in bone and muscle development . The protocol was approved by the ACUC-CAFS. Before the blood or fin samples were collected, all of the fishes were euthanized in MS222 solution.PX initiated and coordinated the research project. JX and YJ conducted the analysis and drafted the manuscript. ZZ, HZ, and JF engaged in sample collection and genotyping analysis. CD, WP, BC, and RT took part in enrichment analysis. All authors read and approved the final manuscript.This work was supported by Central Public-Interest Scientific Institution Basal Research Fund, CAFS , the National Natural Science Foundation of China (No. 31502151 and No. 31422057), the National High-Technology Research and Development Program of China (2011AA100401), the National Key Research and Development Program (2018YFD0900102), and the National Infrastructure of Fishery Germplasm Resources of China (No. 2018DKA30470).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.The handling editor is currently editing co-organizing a Research Topic with one of the authors PX, and confirms the absence of any other collaboration.