Taxus wallichiana var. mairei. Eight plastid simple sequence repeats (cpSSRs) were used to investigate plastid genetic variation in 22 populations of Taxus wallichiana var. mairei, encompassing nearly its entire distribution range. Low levels of plastid genetic variation and differentiation were detected in the populations, and the findings were attributed to low mutation rates, small population sizes, habitat fragmentation and isolation, and effective pollen or seed dispersal. Hunan and Hubei were identified as major refugia based on the number of private haplotypes and species distribution modeling. Trends in plastid genetic diversity and genetic differentiation from central to peripheral populations supported the predictions of the central–marginal hypothesis. In scenarios wherein the future climate becomes warmer, we predict that some peripheral populations will disappear and southern and southeastern regions will become significantly less habitable. Factors that include the levels of precipitation during the driest month, annual precipitation level, and annual temperature range will be decisive in shaping the future distribution of these populations. This study provides a theoretical basis for the conservation of T. wallichiana var. mairei.The central–marginal hypothesis predicts that geographically peripheral populations should exhibit reduced genetic diversity and increased genetic differentiation than central populations due to smaller effective population size and stronger geographical isolation. We evaluated these predictions in the endangered conifer  Taxus wallichiana var. mairei. We identified Hunan and Hubei as major refugia. Our results supported the predictions of the central–marginal hypothesis. We clarified factors that will be decisive in shaping the future distribution of the populations.We detected low levels of chloroplast genetic variation and differentiation in the populations of  The following parameter settings were applied: a motif size of 1–6 nucleotides, and at least 10 repeat units for mononucleotides and 5 for di‐, tri‐, tetra‐, penta‐, and hexanucleotides, respectively. Primer premier 5.0  denaturing polyacrylamide gel that contained 7 M urea and 1 × TBE. The gel was run at a constant voltage of 200 V for 120 min with a 20‐bp DNA ladder and silver‐stained , the observed number of alleles per locus (Na), the effective number of alleles per locus (Ne), Nei's gene diversity index (h), the genetic differentiation coefficient (GST), and gene flow (Nm). Nm was estimated as Nm = (1–GST)/ 4GST. The mean gene diversity within populations (HS) and total gene diversity (HT) were also estimated.Seven genetic parameters were calculated using FSTAT v. 2.9.3 Goudet, . These wFST) among populations were obtained by the same software. Because of the lack of recombination in the plastid genome, alleles identified at polymorphic loci were combined to generate the plastid haplotype for each individual  was calculated and the minimum spanning network determined. Mismatch distributions were used to investigate whether a population had undergone a sudden population expansion. The goodness of fit of spatial expansion was tested using the sum of squared deviations (SSD) and Harpending's raggedness index (HRag) (1994) with mismatch distributions based on 1,000 bootstrap replicates as implemented using Arlequin software. A dendrogram of 22 populations was inferred based on the unweighted pair group method with arithmetic average (UPGMA).Analysis of molecular variance (AMOVA) was conducted to assess population differentiation within and among populations with 1,000 random permutation replicates using Arlequin software , the Middle Holocene , the last glacial maximum , the last interglacial , and the future  at a spatial resolution of 30 arcs from the WorldClim database . After removing duplicate records, a total of 65 T. wallichiana var. mairei records were used to generate the distribution model.MAXENT software  with two climate scenarios (IPCC‐CMIP5 RCP 4.5/8.5) was selected to ensure predictive accuracy. The difference between these scenarios is the concentration of greenhouse gases. The RCP 8.5 scenario includes a higher concentration of emissions than the RCP 4.5 scenario. Model performance was evaluated using the area under the (receiver operating characteristic) curve (AUC) calculated by MAXENT. Values greater than 0.9 indicate good discrimination Swets, . The key33.1HT and HS ranged from 0.0180 to 0.4626 and 0.0178 to 0.3093, respectively, with a mean of 0.2065 and 0.1323 (Table Na) and the effective number of alleles (Ne) ranged from 2 to 5 and from 1.0239 to 1.6258, respectively, with a mean of 3.5 and 1.2883  were polymorphic. The number of alleles per locus ranged from 3 to 5 with a mean of 3.63. The values of Na ranged from 1.000 to 2.125 with a mean of 1.528, whereas Ne ranged from 1.000 to 1.416 with a mean of 1.181. Nei's gene diversity (h) at the species level was 0.145 and ranged from 0.000 to 0.976 , followed by the SJ and LP populations , whereas no genetic diversity was detected in the QL, WM, and AH populations  values among the populations were highly significant (p < .001), indicating that all the populations had differentiated significantly from the others. Comparing the TK and SJ populations produced the lowest FST value (0.00122), whereas comparing the QL and CQ populations produced the highest FST value (1.0000).The level of population differentiation was significant for all eight cpSSR loci with a mean GST = 0.3592, p < .01) (Table Nm = 408.00) occurred between the TK and SJ populations.The hierarchical AMOVA revealed that 61.01% of the total variation in cpSSRs was attributable to differences among individuals within populations, 16.31% to differences among populations within regions, and 22.68% to differences among regions . Among the 54 haplotypes identified, 29 were private haplotypes. At the regional level, Hunan province had the largest number of private haplotypes , whereas Guangdong had none. The haplotype richness per population and per region ranged from 1  to 12 (TZ) and 1 (Chongqing) to 26 (Hunan), respectively .The cpSSRs produced 54 haplotypes with a mean ly Table . Hunan . However, higher levels of genetic diversity were found in the central populations compared to the eastern marginal populations , although some central populations, such as GD, had low levels of genetic diversity .We divided the 3.3T. wallichiana var. mairei performed well with an AUC value of 0.938. With the exception of eastern Guizhou province, the predicted distribution of T. wallichiana var. mairei under the present climate conditions generally corresponded with its current distribution in Jiangxi, Zhejiang, Guizhou, Guangxi, Fujian, and Guangdong provinces. These regions have climates that are suitable for T. wallichiana var. mairei. Palaeodistribution modeling suggested that T. wallichiana var. mairei had a more restricted range during the last interglacial (LIG) period but occupied a larger area, as a result of subsequent expansion, at the last glacial maximum (LGM) compared with its present distribution  contributed most, followed by annual precipitation level (Bio12), annual temperature range (Bio7), mean monthly temperature range (Bio 2), and mean temperature during the wettest quarter (Bio 8)  were 50–150 mm, the annual precipitation level (Bio 12) was 1,250–1,800 mm, and the annual temperature range (Bio7) was 25–35°C.We investigated the most important climatic factors for determining the distribution of onth Bio1 contribuonth Bio1 contribu4T. wallichiana var. mairei. Overall, T. wallichiana var. mairei had low levels of genetic variation although its PPB was slightly higher than other conifers  was lower than the mean cpSSR‐based gene diversity in 16 coniferous species (HT = 0.801)  was lower than the mean value (Hd = 0.670) detected in 170 plant species investigated by Petit et al. , annual precipitation level (Bio12), and annual temperature range (Bio7) were the most important factors, indicating that T. wallichiana var. mairei prefers moist environments, and rainfall patterns are decisive in determining its distribution , annual precipitation level (Bio12), and annual temperature range (Bio7). It would be interesting in a future study to further compare phenotypic plasticity and epigenetic variation between the central and marginal populations of T. wallichiana var. mairei in the climate change context (Anderson et al., We examined the The authors declare there are no competing interests.Consent for publication: Not applicable.TW designed the research and was involved in writing the manuscript; LL and ZW conducted data analysis and were involved in writing the manuscript and checking English grammar; LH performed the cpSSR experiment and conducted data analysis; and YS helped to supervise the research and was involved in writing the manuscript. All authors read and approved the final version of the manuscript.The acquisition of plant material used in this study complies with institutional, national, and international guidelines. No specific permits were required for the described field studies. No specific permissions were required for the locations/activities described in this study. Click here for additional data file.


Ostrea lurida), patchily distributed from Baja California to the central coast of Canada, has a long history of population declines due to anthropogenic stressors. For such coastal marine species, population structure could follow a continuous isolation‐by‐distance model, contain regional blocks of genetic similarity separated by barriers to gene flow, or be consistent with a null model of no population structure. To distinguish between these hypotheses in O. lurida, 13,424 single nucleotide polymorphisms (SNPs) were used to characterize rangewide population structure, genetic connectivity, and adaptive divergence. Samples were collected across the species range on the west coast of North America, from southern California to Vancouver Island. A conservative approach for detecting putative loci under selection identified 235 SNPs across 129 GBS loci, which were functionally annotated and analyzed separately from the remaining neutral loci. While strong population structure was observed on a regional scale in both neutral and outlier markers, neutral markers had greater power to detect fine‐scale structure. Geographic regions of reduced gene flow aligned with known marine biogeographic barriers, such as Cape Mendocino, Monterey Bay, and the currents around Cape Flattery. The outlier loci identified as under putative selection included genes involved in developmental regulation, sensory information processing, energy metabolism, immune response, and muscle contraction. These loci are excellent candidates for future research and may provide targets for genetic monitoring programs. Beyond specific applications for restoration and management of the Olympia oyster, this study lends to the growing body of evidence for both population structure and adaptive differentiation across a range of marine species exhibiting the potential for panmixia. Computational notebooks are available to facilitate reproducibility and future open‐sourced research on the population structure of O. lurida.Effective management of threatened and exploited species requires an understanding of both the genetic connectivity among populations and local adaptation. The Olympia oyster ( After release, the larvae have been reported to be planktonic from 7 days to 8 weeks before settling on a hard substrate . I specifically tested whether patterns of genetic variation suggest a smooth continuum of allele frequency shifts consistent with isolation‐by‐distance (IBD) Malécot, , regionaA secondary aim of this study was to produce a reproducible computational pipeline to go from raw data to results and figures, using Jupyter Notebooks. Jupyter Notebooks are interactive documents that integrate text, code, and analysis results  at 20 sites ranging from Klaskino Inlet, Vancouver Island (50°17′55″), to San Diego Bay, CA (32°361′9″), in 2014  and E.Z.N.A. Mollusc DNA Kits (Omega Bio‐Tek) with RNAse A treatment following manufacturer instructions and limiting tissue digestion time to no more than 90 min. All DNA samples were quantified using the Qubit dsDNA BR Assay Kit (Life Technologies) on a Qubit v2.0 (Life Technologies). DNA quality was verified by agarose gel electrophoresis of 1–2 μl extracted DNA on an 0.8% TAE gel.A total of 20–25 adult 4 Figure . When po2.2ApeKI restriction enzyme, with an additional size selection step and slight modifications to PCR amplification. A detailed protocol can be found at https://github.com/ksil91/Ostrea_PopStructure. All libraries were size‐selected for fragment sizes between 200 bp and 450 bp on a Blue PippinPrep (Sage Science) to reduce the number of loci sequenced and ensure adequate sequencing coverage. One pool of 90 samples was sequenced across two 100 bp paired‐end Illumina HiSeq 2500 lanes, with only the forward sequencing read used for analysis. Seven other pools with a maximum of 48 libraries each were sequenced on eight 100 bp single‐end lanes . Sampling sites were spread out across all libraries in order to minimize batch effects from library preparation and sequencing. Raw sequencing reads were demultiplexed, quality filtered, and de novo clustered using the API version of the seven‐step computational pipeline ipyrad v.0.7.24  followed the protocol by Elshire et al.  using th4 Eaton,  and impl4 Eaton, . The repFST, did change quantitatively due to missing data but not qualitatively (not shown)  in at least two populations, sample coverage of 75%, and an overall minor allele frequency (MAF) of 2.5%, retaining only GBS loci found in at least one individual from all populations. Preliminary analyses conducted on datasets allowing more or less missing data showed that the inferred population structure was robust to missing data up to 40%. Population genetic summary statistics, with the exception of 2.3OutFLANK v.0.2, and pcadapt v.4.0.2. For BayeScan and OutFLANK, individuals were grouped into populations by sampling site. GBS loci which had SNPs identified as outliers in at least two of the approaches were classified as putative adaptive GBS loci. From these GBS loci, any SNP that had been identified as an outlier by at least one approach was separated from the full SNP dataset to create an “outlier” SNP dataset. Subsequent analyses of population structure were conducted on three SNP datasets: all SNPs (combined), outlier SNPs, and neutral SNPs—which excluded any SNP found on a putative adaptive GBS locus.Following recommendations to utilize multiple methods to detect loci under putative directional selection  of 10%. For the R package pcadapt, individuals are not sorted into predefined populations. Instead, pcadapt ascertains population structure using principal component analysis (PCA) and then identifies markers under putative selection as those that are excessively correlated with population structure. When compared to BayeScan, pcadapt was shown to have greater power in the presence of admixed individuals and when population structure is continuous  for pcadapt, and SNPs with a q‐value threshold of 0.1 were categorized as outliers.BayeScan uses a Bayesian approach to apply linear regression to decompose nr database using the BLASTx algorithm with default parameters and a e‐value hit filter of 10−3, and against EMBL‐EBI InterPro signatures. Gene ontology terms were mapped to annotations with default parameters except for an e‐value hit filter of 10−3 , expected heterozygosity (He), overall FST, and FIS were calculated using the basic.stats function in the R package hierfstat  with a burn‐in period of 50,000 repetitions followed by 200,000 repetitions. Five replicate analyses were performed for each dataset with values of K = 1–10, with each replicate independently subsampling one SNP per GBS locus and using a different random seed. Replicates were summarized and visualized using the CLUMPAK server . The habitat shape followed the shape of the coastline and excluded land regions that O. lurida larvae would not naturally be able to cross . The EEMS model is recommended to be run for various numbers of demes, which establishes the geographic grid size and resulting potential migration routes. Three independent analyses were run for each deme size  for a total of 24 runs, with a burn‐in of 1,000,000 and MCMC length of 5,000,000 iterations. The convergence of runs was visually assessed and results were combined across all analyses and visualized using the Reemsplots R package—producing maps of the effective diversity (q) and effective migration rate (m).Spatial variation in gene flow and genetic diversity was calculated and visualized using the program EEMS (estimated effective migration surfaces) , then run allowing between 0 and 10 migration events. For each value of migration events, I calculated the proportion of variance in relatedness between populations that is explained by the population graph to evaluate model fit . Average read depth per individual per GBS locus ranged from 21 to 120 (mean = 32 ± 14). Further filtering by HWE and MAF >2.5% reduced the dataset to 13,424 SNPs across 6,187 GBS loci (the “combined” dataset).A total of 117 samples remained after removal of 14 samples with <200,000 raw sequencing reads, 49 samples with <15,000 clusters, and 65 samples missing data for over 55% of loci assembled across at least 75% of samples. One of the sampling sites for Willapa Bay, WA, had a low number of individuals after filtering, so individuals from these two sites were combined into one population, for 19 total populations . A total of 41,159 biallelic SNPs across 9,696 GBS loci were genotyped in greater than 75% of these individuals (2.8% of prefiltered loci assembled by Three different methods were employed to identify putative SNPs under selection. The number of outliers detected by each program and the overlap between programs is illustrated in Supporting Information 3.23.2.1FST for outliers (FST = 0.417) was almost four to five times greater than for the combined and neutral SNPs (FST = 0.105 (combined), 0.097 ). The outlier dataset had the lowest Ho, but the highest He , Puget Sound, WA, plus Victoria, BC, and Ladysmith Harbour, BC (Puget+BC), Willapa Bay, WA, plus Coos Bay, OR (Willapa), the other two Oregon sites (Oregon), Northern California  from Humboldt Bay, CA, to San Francisco Bay, CA, and Southern California  from Elkhorn Slough, CA, to San Diego Bay, CA. STRUCTURE results for the outlier SNPs supported K = 2, but visually results were similar between the outlier and neutral SNPs at K = 5 with the exception of Discovery Bay, WA, in Puget Sound showing higher admixture with NWBC   and , PC3 separating NoCal and SoCal, PC4 separating NWBC and Puget+BC, and PC5 separating Oregon from Willapa  , Mugu Lagoon, CA/San Diego Bay, CA (0.0017), and North/South San Francisco Bay, CA (0.0035). Victoria, BC, showed higher pairwise FST with the other British Columbia sites than with sites from Puget Sound, WA. Mantel tests showed a significant correlation between pairwise FST and coastal water distance for both datasets, indicating a strong trend of isolation‐by‐distance   barriers to gene flow: (a) at the mouth of the Strait of Juan de Fuca; (b) around Victoria, BC; (c) extending from Willapa Bay, WA, to southern Oregon; and (d) around San Francisco Bay, CA . Populations from Oregon northwards had much lower genetic diversity than those in California. A linear regression of population‐specific He and latitude using the neutral dataset shows a strong relationship between genetic diversity and latitude .TreeMix produced a population graph that supported a major phylogeographic split between the outer coast of Washington and Puget Sound. When allowing for an increasing number of migration events, the proportion of variance in relatedness between populations explained by the model began to asymptote at 0.994 for seven migration edges , which exhibits high variability in oyster species and is commonly used for metazoan phylogenetics , energy metabolism , heavy metal binding , and muscle contraction   Table . Twenty‐a) Table .4Reduced‐representation genomic methods, such as GBS, can greatly inform reintroduction efforts for threatened and exploited species by resolving fine‐scaled population structure, providing estimates of genetic connectivity, and identifying informative markers for characterizing adaptive variation  The southward direction of the California Current results in asymmetric gene flow and an accumulation of genotypes in the south  . Nevertheless, three outlier loci exhibited allele frequency shifts of at least 50% between these two populations, suggesting some potential adaptive populationdivergence.) Marko, . (c) Ong4.1.2NoCal region, which is encompassed by the northern half of the Montereyan biogeographic province as identified by Fenberg et al. , until 12–13 kya  may havWhile it is encouraging that programs such as TreeMix can recover known human‐mediated migration events, such artificial movement of individuals can complicate the determination of natural connectivity patterns. For example, the area of low effective migration inferred around San Francisco Bay may be due to the introgression of Washington genotypes rather than actual physical barriers to gene flow. Fortunately, intentional movement of Olympia oysters between regions ceased over 80 years ago with the exception of restoration efforts in Netarts Bay from 2005 to 2012, which utilized some broodstock from Willapa Bay.4.3O. lurida genome will aid in detecting loci that may be tightly linked to a gene or regulatory region. Direct information about the function of genes or proteins in oysters is sparse, but rapidly increasing with transcriptomic and physiological studies on the commercially important Crassostrea species. While these 129 GBS loci are likely only a fraction of all loci under divergent selection across the O. lurida genome  also exhibits this hump‐shaped distribution of allele frequencies.Some outlier loci exhibit the opposite of a clinal pattern, where populations in the middle of the range predominantly have a different allele than the northern and southern populations. E3 ubiquitin‐protein ligase (locus_121489) is diverged in 4.4FST; however, the impact of these biases on FST may be limited if effective population size (Ne) is small and if loci with large amounts of missing data are removed from analyses  removed during filtering. First, too many individuals may have been pooled per sequencing lane given the number of loci targeted, resulting in low sequencing depth for some individuals (Andrews et al., FST when >1,000 SNPs are used (Willing, Dreyer, & van Oosterhout, Although genomic methods such as GBS have been proven useful for evolutionary biology and conservation genetic studies (Andrews, Good, Miller, Luikart, & Hohenlohe, 5O. lurida.This study provides the first comprehensive characterization of both neutral and adaptive population structure in the Olympia oyster, an ecologically important coastal species in North America. These results have direct implications for management policies and ongoing restoration efforts, and a future sustainable fishery. Putative adaptive loci identified here are excellent candidates for future research and may provide targets for genetic monitoring programs. Beyond these specific applications, this study contributes to the growing body of evidence for both population structure and adaptive differentiation in marine species. In particular, it is one of the first to utilize thousands of SNPs to characterize population structure from southern California to Vancouver Island. All analyses conducted for this study can be replicated using annotated Jupyter Notebooks, allowing for clear dissemination of bioinformatics methods and future open‐sourced research on the population structure of None decalred. Click here for additional data file.


Boea clarkeana Hemsl., a unique resurrection herb endemic to China, focusing on geographically restrictive effects of habitat distribution on evolutionary history. Variation in three chloroplast DNA (cpDNA) intergenic spacers , the ribosomal internal transcribed spacer (ITS) and simple sequence repeats in expressed sequence tags (EST-SSRs) was investigated across 18 populations to assess genetic diversity, genetic structure and historical dynamics. Genetic diversity was low within populations  but high for species ; 76 alleles were detected in this highly inbred species (FIS = 0.22), with a significantly low average of 1.34 alleles per locus. No cpDNA or ITS haplotypes were shared between regions. Based on cpDNA results, the Mt. Huangshan-Tianmu and Mt. Qinling-Daba haplotypes are ancestral; these two regions represent potential refugia. Although no evidence of significant retreat-migration phenomena during glacial cycles was detected, interglacial range expansion from northern Mt. Qinling-Daba was identified . Rapid agricultural growth caused bottlenecks in many populations, especially on Mt. Huang-Tianmu. Habitat restriction and fragmentation, weak seed and pollen dispersal abilities, and long-term isolation caused by human-induced or environmental changes are considered the main causes of extinction of several populations and low genetic diversity within populations and regions. These analyses clarify the effects of habitat restriction on B. clarkeana, representing an evolutionary reference for similar gesneriads, and enrich our understanding of the molecular phylogeography of East Asian rocky-slope herbs.Subfamily Cyrtandroideae (Gesneriaceae) comprises a broadly distributed group of rocky-slope herbs, with China being the center of its distributional range. The normal growth of many species within the family is particularly dependent on special habitats. Due to the paucity of molecular studies, very little is known regarding East Asian herb phylogeographic pattern. Here, we investigate the molecular phylogeography of  Dysosma versipellis, Primula ovalifolia and Chinese weedy rice (Oryza stavia L. f. sp. spontanea), have been studied to date  to calculate the generation time T (g), where α is the maturation age and S is the survival rate [T) of approximately 5 years was used in this study. TCS 1.21 [For cpDNA, mismatch distribution analysis (MDA) was performed with Arlequin 3.0 , which wx (HRag) . In addix (HRag)  and Fu’sRag) [FS  tests ofT = τ/2u , 54. The.3×10−9) , 55, k ival rate . Based oTCS 1.21  was emplNe-4Ne generations) and long-term demographic changes were detected with BOTTLENECK v. 1.2.02 and MSVAR v 1.3 [P-value < 0.05 using the Wilcoxon signed rank test was considered to represent evidence of a bottleneck. MSVAR was used to detect long-term changes in the effective population size and the timing of the changes. The lineal model was employed to evaluate population size changes [N0), current effective population size (N1), average mutation rate across loci (μ), and time (years) since the onset of decline or expansion (T)) were estimated using Tracer v. 1.4.8 [Based on EST-SSRs, recent bottlenecks , we obtained 1900 bp of cpDNA sequence from 222 individuals. A total of 21 sites with insertion-deletions (indels) and 35 polymorphic sites (substitutions) were observed (see psbA-trnH (22 sites), mainly consisting of sequence differences between CNJ and the other populations. Only substitutions were used in the ensuing data analysis, whereas indels were excluded. In total, 8 chlorotypes (haplotypes C1-C8) were identified  at the species level but low diversity within each population . Only the eastern  and northwest (Qinling and Daba Mts.) regions displayed haplotype and nucleotide diversity , and the other two regions  showed no diversity  (see details in ΦST = 0.994), and significant phylogeographic structure was found . A moderately strong relationship between the genetic and geographic distances between populations was revealed by Mantel tests . In the unrooted network  in the ITS region were higher than in cpDNA. Among regions, the eastern and central regions showed more fixed ribotypes compared with the results for cpDNA. However, in contrast to the cpDNA results, the central region showed the highest haplotype diversity and nucleotide diversity  among the regions (see ΦST = 0.945) variation between groups, indicating obvious phylogeographic structure   see . In cont037) see . Excludi037) see . As a reB. clarkeana surveyed at 15 EST-SSR loci, 76 alleles were obtained, ranging from 2 to 9 per locus. The mean NA, PIC, and HO and HE values were 1.34, 0.07, 0.06 and 0.08  among all regions, followed by the eastern region . The northwest region (Qinling and Daba Mts.) presented the lowest diversity  among the regions (see ΦST = 0.844), and the variation between populations within groups was higher (29.19%) than the values obtained for cpDNA and ITS. The inbreeding coefficient (FIS = 0.22) was significantly positive in 11 populations, with only 4 populations  presenting a negative value, indicating common inbreeding between populations of B. clarkeana. The genetic differentiation between populations and regions was relatively high, and most pairwise FST values for the 18 populations were significantly greater than 0.5, except for those among the 3 populations of Mt. Qinling-Daba . Additionally, the population CNJ exhibited the highest mean pairwise FST value (0.916). According to PCoA, all populations grouped into their regions, which were divided into four clusters . These four regions were arranged in accordance with longitude along coordinate1  values were all less than 0.022. The historical migration rates (mh) calculated by Migrate ranged from 0.008 (from CNJ to SWM) to 0.248 (from SLG to SLB)  see , with a SSD and HRag values was fitted to support the expected expansion of the distribution. In this study, Mt. Qinling-Daba was the only region satisfying the following criteria: non-significant SSD and HRag values  and a significantly negative Tajima’s D . Based on the τ-value (3), the expansion of the Mt. Qinling-Daba region was dated to approx. 121,457 yr BP  revealed through EST-SSR analysis was significantly lower than the mean diversity values for perennial plants  and cross-pollinated plants , based on SSR data from Nybom (2004) [B. clarkeana is a facultatively outcrossing and highly self-compatible species, and these features were reflected in the significant inbreeding coefficient [B. clarkeana and its growth on the north side of rock outcrops (mostly limestone), requirement for scattered light and growth in the shadow of trees and shrubs are all habitat restrictions that might significantly reduce the dispersal capacity of windborne seeds and the frequency of pollination, which could lead to reproductive isolation of a population or across a region [B. clarkeana exhibit a shortage of visiting pollinators as well as a reduced frequency [B. clarkeana.The population genetic diversity of m 2004) . The cpD . The cpm (2004) , 63, 64.fficient . Second,requency . Moreoverequency . All of B. clarkeana has been confirmed to increase gradually from east to west [FST values based on the EST-SSR data were significantly higher (most greater than 0.5), and the differentiation indices GST and NST  were also significantly higher than the mean values  between plants [The different genetic information and evolutionary rates between cpDNA and nuclear DNA (nDNA) , 68 and, to west . Therefo to west , 74–77. n plants .B. clarkeana. In addition, high cpDNA haplotype and nucleotide diversity is a feature of refugia [B. clarkeana distribution. The Mt. Huang-Tianmu and Mt. Qinling-Daba areas were previously shown to harbor refugia for other species during the LGM  [In this study, based on the TCS networks of cpDNA, haplotypes C2 of Mt. Huang-Tianmu and C7 of Mt. Qinling-Daba were both considered to be ancestral for  refugia . In this0 yr BP) , 79–82.rM = 0.54, P < 0.01), reflecting the 'isolation by distance' status of B. clarkeana. However, compared with other studies conducted in this area, the rM value of B. clarkeana was even higher than that of the rare plant Dysosma versipellis (rM = 0.44) [Tetracentron sinense (rM = 0.62) [rM value for B. clarkeana was relatively higher. These findings indicate the occurrence of an extinction event in the Pleistocene [B. clarkeana enabled it to expand throughout the middle and lower reaches of the Yangtze River. The analyses of gene flow and effective population size variation also showed that the studied populations of B. clarkeana were historically large and widely distributed . However, extinction occurred due to climate change in the Pleistocene, and B. clarkeana was forced into two refugia (Mt. Huang-Tianmu and Mt. Qinling-Daba) by the end of Pleistocene [B. clarkeana is not currently found in Mt. Dabie, which may constitute evidence of extinction for this species. A lack of molecular variation within the regions was revealed through phylogeographic analysis , which also supports the fragmentation and extinction of B. clarkeana [B. clarkeana would not have been able to undergo long-distance expansion into suitable territories during interglacial periods, which may also have resulted in distant haplotype relationships in adjacent areas . Therefore, no evidence that B. clarkeana had undergone a significant southward retreat during glacial periods and northward migration during interglacial periods was found. Similar to some other studies [B. clarkeana, only local expansion  occurring under suitable climatic conditions during the interglacial period .For cpDNA, a significant and moderately strong correlation between genetic and geographic distance between the populations was revealed by Mantel tests ( = 0.44)  and was  = 0.62) ; the rM istocene . Similaristocene –86. Accoistocene , 87. Howlarkeana , 84. Bec studies , 88–90, B. clarkeana populations in the lower reaches of the Yangtze River (Mt. Huang-Tianmu region), no bottlenecks were detected in Kirengeshoma palmata populations in this region in a previous study [K. palmata lives in deep forests, whereas B. clarkeana grows on rocky outcrops and is more easily damaged during the clearing of land for agriculture.According to the MSVAR results, the mean effective population size of all populations experienced a dramatic reduction, but the timing of the declines of most populations  did not coincide with major climatic and landscape changes in this area during the Late Pleistocene  . Insteadus study . AlthougB. clarkeana is a resurrection herb species endemic to China. In this study, the genetic structure and evolutionary history of this species were investigated based on cpDNA, ITS and EST-SSR sequence data. Similar to other plant species of Gesneriaceae, this plant is restricted to rocky-slope habitats and exhibits weak seed and pollen dispersal abilities. The genetic diversity of B. clarkeana was found to be exceptionally low within each population and region. More suitable habitats for B. clarkeana were available historically, and the species was likely to be widely distributed. Because of changes in the environment and the influence of human activity, a few populations of B. clarkeana have become extinct, but Mt. Qinling-Daba and Mt. Huang-Tianmu have acted as refugia, conserving ancestral haplotypes of B. clarkeana. Habitat loss and fragmentation are becoming increasingly serious, and we should pay attention to the fact that a small population size is becoming the norm and that the genetic risk for this plant is increasing. Moreover, some populations have suffered genetic bottlenecks, particularly in the Mt. Huang-Tianmu (Yangtze River delta) area. These analyses indicate that climate and environmental change are important for species migration and preservation. We now have a better overall understanding of the influence of habitat restriction on B. clarkeana and for Gesneriaceae.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.S4 Table(DOC)Click here for additional data file.S5 Table(DOC)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.


Cricetulus kamensis was investigated using phylogeographical methods. In particular, population divergence, demographic history, genetic variation, and the prediction of species distribution area were investigated.The evolutionary process of an organism provides valuable data toward an understanding of the Earth evolution history. To investigate the relationship between the uplift of the Qinghai–Tibet Plateau (QTP) and mammalian evolution since the late Cenozoic, the geographic distribution of genetic variations in the Tibetan hamster The Qinghai–Tibet Plateau.C. kamensis were analyzed, and the probable factors in the QTP uplift and the Quaternary glacial periods were inferred from one nuclear and four mitochondrial genes. Furthermore, the species distribution model (SDM) was used to predict changes in potentially suitable habitats since the last Interglacial.A total of 53 specimens, representing 13 geographic populations, were collected from the QTP. The phylogeographical pattern and demographic history of C. kamensis population occurred during the Early Pleistocene that were influenced by the Qing‐Zang tectonic movement from the Middle Pliocene to the Early Pleistocene. Genetic distance between two major clades indicated low genetic divergence. Demographic history analysis showed that the C. kamensis population was affected by the Quaternary glacial period. SDM analysis indicated that C. kamensis was endemic to the QTP and the suitable habitat was affected by climate change, especially during the Last Glacial Maximum (LGM).Phylogenetic analysis demonstrated that two major genetic differentiations of the C. kamensis, and vicariance well accounted for the geographic distribution of genetic variation in C. kamensis as a result of genetic divergence and lack of gene flow. The genetic distance shows that C. alticola may be a subspecies of C. kamensis. Demographic history analysis suggests that the QTP was affected by the last glacial period. SDM analysis supports that almost the entire QTP is covered by a huge ice sheet during the LGM.Our results indicated that the QTP uplift led to the population divergence of  MoleculOchotona also indicate that the speciation of pikas is consistent with the historical episodes of geologic and climatic changes of the QTP  was influenced by the uplift of the QTP   from different biogeographic populations based on their respective morphological characteristics , while Lebedev and Potapova  are synonymous of C. kamensis. Subsequent taxonomic publications on Tibetan hamster adopt the classification conclusion of two separate species  are subspecies of C. kamensis rather than that of a separate species  and climatic change  of the QTP. In the present study, one nuclear and four mitochondrial genes were used to (a) detect the relationship between the phylogeographical pattern of C. kamensis and the uplift of the QTP, (b) examine both the population genetic structure and demographic history of C. kamensis, (c) assess the likely cause for the decrease of habitats suitable for the survival of C. kamensis during the Late Pleistocene glacial period, and (d) discuss the taxonomical issue of C. kamensis by using phylogenetic analysis and genetic distance.Prior phylogenetic analysis suggests that 22.1C. kamensis were trapped in the QTP area from 13 geographic locations .A total of 53 ns Table . Muscle 2.2C. kamensis using the TIANamp Genomic DNA Kit (Tiangen). Polymerase chain reaction (PCR) was used to amplify both mitochondrial DNA (mtDNA) and nuclear DNA (nuDNA) fragments of C. kamensis, in which four primer pairs were used to amplify four mtDNA markers (cytochrome c oxidase subunit 1 (Cox1), cytochrome c oxidase subunit 3 (Cox3), cytochrome b (CYTB), and control region (D‐loop), Table C. kamensis based on other conservative hamster homologous sequences of vWF , 0.5 μl Taq polymerase , 1 μl DNA template, and 17 μl ddH2O. The strand PCR was run with pre‐denaturing for 3 min at 95°C, followed by 35 cycles of denaturing for 30 s at 95°C, annealing for 45 s at 50–60°C, extension at 72°C, and a final extension at 72°C for 10 min. All PCR products were detected using 1% agarose gel electrophoresis and then directly sequenced using the Sanger sequencing method (Genewiz Biotech (Suzhou) Co., Ltd.). DNA sequences were manually edited and assembled using Lasergene version 5.0 (DNASTAR). Here, five DNA markers  have been deposited in the GenBank database and GenBank accession numbers please see the section of The total genomic DNA was extracted from the muscle samples of WF Table . PCR was2.3p = 0.956 > 0.05) and indicated that five genes can be concatenated together. The program DnaSP v5  were used as outgroups  were used to build the phylogenetic relationships between 13 geographic populations. Each concatenated sequence had a length of 5,078 bp, including outgroup taxa. A concatenated sequence consisted of four mtDNA genes (Cox1 + Cox3 + CYTB + D‐loop) and one nuclear gene (vWF) fragment, and each marker was separately aligned and these sequences were then manually concatenated using the program Sequence Matrix v1.7.8   from comparisons of the focal species and an outgroup species using the formula: d = (tv + tvR)/m, where tv is the number of transversions between the gth Nei, . Transitgth Nei, . The ratgth Nei, . The mutv et al. ), and thC. kamensis were estimated using BEAST version 1.7.4  was used as calibration interval   and unique haplotypes (UH), haplotype diversity (Hd), nucleotide diversity (π), and the average number of pairwise nucleotide differences (K). The percentages of unique haplotypes per population were calculated via unique haplotypes divided by the number of haplotypes in a given population. Here, three sample sites were removed because only one sample was available or the nucleotide diversity was zero Table . Analysi2.6C. kamensis. Potential signals of population growth were detected using Fu's FS , the layers contained four periods: the last interglacial ), the last glacial maximum , the Mid‐Holocene , and the present . Among these, the paleoclimate data were downloaded from the community climate system model (CCSM) with 30 arc‐second and 2.5 arc‐minute resolutions . To eliminate a potential overfitting effect, the percent contribution between 19 bioclimatic variables were tested using the ENMeval package in R language  of suitable habitats for 33.1The phylogenetic tree showed two major evolutionary clades (A and B) with high nodal posterior probability (PP) values PP = 1) inferred from DNA concatenated sequences Figure a. The A  inferredDivergence time analysis also resulted in two major clades that represented two derived populations in the species tree with the same topological structure, corresponding to Bayesian tree Figure c. As suc3.2C. kamensis populations had a higher UH ratio among populations except for the LS population (Table C. kamensis populations. The average number of nucleotide differences (K) between geographic populations indicated that population DR had a higher K value (K = 68.571) and showed fine DNA heterogeneity . AMOVA analysis resulted in a significant pattern of variation within two clades (75.04%) based on concatenated mtDNA sequences, and the variance between sampled localities within clades and within sampled localities was 17.82% and 7.14%  was found between A and B lineages in the QTP. Moreover, pairwise STF values were high and significant, which indicated restricted gene flow between two recovered populations. Furthermore, the K2P distance was 0.064 between Clades A and B based on concatenated mtDNA haplotypes, was 0.067 for CYTB haplotypes and was 0.003 for vWF haplotypes.The gene flow was low , and significant genetic differentiation  in lineages A and B were found. They exhibited an observed multimodal mismatch frequency distribution . SDM showed that the suitable habitat was the most widespread during the LIG  inferred from the BI and BEAST. Moreover, the Bayesian tree and median‐joining network resulted in the same topological structure  due to the east‐west extension of the Eurasian plate after the collision, which reaches very high elevations and was sufficient to block the colonization of animal with low dispersal abilities such as rodents   caused the average altitude of the QTP to exceed 3,000 m (a.s.l.) after the Qing‐Zang tectonic movement, and a large area of the plateau entered the frozen circle , this region had a typical subtropical climate and a large number of mammalian fossils can be found in the QTP, for example, of 4.2C. kamensis specimens were collected from 13 geographic populations in the QTP, all of which were part of two recovered populations and were subjected to population genetic analysis. It is worth noting that there was no shared haplotype among populations, and each population had higher UH ratio, and individuals in the population had higher nucleotide differences    in 1902 and named the specimen with a pale pelage from Qilian Mountain as the C. kozlovi . As such, Smith and Xie  in 1933. However, Corbet  are synonyms of C. kamensis  are synonyms of C. kamensis.The classification of Tibetan hamster has been controversial over the past century. Historically, Satunin named the female hamster from the southeastern part of the Qinghai–Tibet Plateau for the first time as an  Thomas, . Consequ and Xie  identifigyropulo  sorted t, Corbet  admitted Corbet, . Moreove Corbet,  accepted Corbet, ’s opinioen Zheng  confirmeen Zheng  and Luo en Zheng  also sugM. meridianus complex is 8.6% and does not meet interspecific divergence level, for instance, suggesting that smaller degrees of divergence tended to characterize major within‐species phylogroups . Bradley and Baker  suggestePotapova ’s infereRattus species (Yom‐Tov, Yom‐Tov, & Moller, C. kamensis. Further work is needed to assess morphological variation and subspecific differentiation on C. kamensis.Theoretically, it appears that phenotypical changes are regarded as responding to environmental and climatic changes (Mayr et al., The authors declare that they have no competing interests.JC L conceived the study; L D was responsible for obtaining and analyzing data, and wrote the manuscript with the help of JC L.


Juglans regia L.) and identify loci underlying the variation in nut and kernel related traits using the new Axiom J. regia 700K SNP genotyping array. We genotyped a diversity panel including 95 walnut genotypes from eight Iranian provinces with a variety of climate zones. A majority of the SNPs  fell into the “Poly High Resolution” class of polymorphisms, which includes the highest quality variants. Genetic structure assessment, using several approaches, divided the Iranian walnut panel into four principal clusters, reflecting their geographic partitioning. We observed high genetic variation across all of the populations (HO = 0.34 and HE = 0.38). The overall level of genetic differentiation among populations was moderate (FST = 0.07). However, the Semnan population showed high divergence from the other Iranian populations (on average FST = 0.12), most likely due to its geographical isolation. Based on parentage analysis, the level of relatedness was very low among the Iranian walnuts examined, reflecting the geographical distance between the Iranian provinces considered in our study. Finally, we performed a genome-wide association study (GWAS), identifying 55 SNPs significantly associated with nut and kernel-related traits. In conclusion, by applying the novel Axiom J. regia 700K SNP array we uncovered new unexplored genetic diversity and identified significant marker-trait associations for nut-related traits in Persian walnut that will be useful for future breeding programs in Iran and other countries.Persian plateau (including Iran) is considered as one of the primary centers of origin of walnut. Sampling walnut trees originating from this arena and exploiting the capabilities of next-generation sequencing (NGS) can provide new insights into the degree of genetic variation across the walnut genome. The present study aimed to explore the population structure and genomic variation of an Iranian collection of Persian walnut ( Juglans, one of the most important genera of the Juglandaceae family, contains approximately 21 species, of which Persian walnut (Juglans regia L.) is the most economically important for nut production. Persian walnut is a long-lived, monoecious, open-pollinated and dichogamous tree, widely cultivated across temperate and subtropical regions4. Persian walnut trees are native to the mountainous regions of central Asia7, and today are distributed and grown commercially over a wide geographical range, including west-central Asia, southern Europe, North and South America, Australia and New Zealand10.The genus 11. In Iran, walnut has been planted widely for both nut and wood production, grows in extensive naturalized populations, and plays a key role in the country’s economy and culture11. Iranian walnut populations inhabit areas of widely varying precipitation, temperature, altitude and latitude12. Walnut trees have been seed-propagated in this area for thousands of years and dichogamy has promoted considerable genetic variation within existing natural or planted seedling populations14. Due to propagation primarily by seed, considerable phenotypic variability can be observed for different traits in the natural walnut populations of Iran14. Therefore, this valuable native walnut gene pool, located throughout the country and containing widely varying alleles, could be a valuable resource for the development of walnut breeding programs in Iran, either by direct selection or by use of superior genotypes in cross-breeding programs14.Iran and Afghanistan are thought to be among the main centers of origin and domestication of walnut16. During recent decades the genetic diversity and structure of Persian walnut populations in Iran has been studied using both morphological and molecular markers, and some promising genotypes  have been selected and introduced14. However, there are wide areas populated by walnut trees in different parts of Iran that are still genetically unexplored15. These genetic materials are most likely adapted to the local environmental conditions and may have high levels of tolerance to biotic and abiotic stresses17. Hence, these native populations potentially could provide resources for sustainable high yields under the climate change scenario16. Therefore, assessing the genomic variation and differentiation of Iranian walnut genotypes will facilitate the effective use of these valuable genetic resources in future breeding programs, not only in Iran but also in other countries.Information regarding the amount of genetic divergence between geographically separated walnut populations in Iran can be used to enhance the effectiveness of breeding programs15, and simple sequence repeat (SSRs)24. However, there is no information in the literature on analysis of walnut genetic resources in Iran using high throughput genotyping platforms. Advances in next-generation sequencing (NGS) and the continuous decrease in cost have facilitated the discovery of whole genome single nucleotide polymorphisms (SNPs)27. SNP markers are the most abundant type of sequence variations. Distributed throughout the genome, they are the best candidates for performing advanced genetic analyses such as genome-wide association studies (GWAS) and genomic selection (GS)28. Ciarmiello et al.29 developed a simple technique for genetic characterization of walnut through exploiting SNPs in internal transcribed spacers (ITS). You et al.30 released a 6K Infinium SNP array based on ‘Chandler’ for use in walnut genetic improvement. A full walnut genome sequence (‘Chandler’ reference genome) has recently been published31. In addition, Marrano et al.25 released a high density Axiom J. regia 700K SNP array after high depth re-sequencing of 27 founders of the Walnut Improvement Program of University of California, Davis.Patterns of walnut population genetic diversity and structures have been studied using several molecular marker systems, including randomly amplified polymorphic DNA (RAPDs)28. This approach makes it possible to simultaneously screen a large number of individuals for genomic variation, allowing identification of novel alleles underlying various traits28. However, few GWAS studies in nut tree crops have been reported so far, due to complex population structures that arose during a long domestication process28. Understanding the genetics of characters related to nut and kernel quality is crucial for walnut breeding programs worldwide and no study has identified regions  in the walnut genome associated with these traits. Therefore, it may be beneficial to use a diverse panel of walnuts of varied geographic origin in GWAS studies to identify useful new genetic variation for nut and kernel-related traits.GWAS takes advantage of natural genetic variation, which is found extensively in many fruit species32. Although the fourth phase of the walnut improvement program at HSRI based on traditional breeding continues, climate change and increasing environmental stresses  make it vital to initiate a new scion and rootstock breeding program using genomic-based approaches. Thus, we characterized a representative collection of the natural genetic and phenotypic variation present in Iran as first step towards future walnut sampling and the introduction of molecular breeding for Persian walnut in Iran.The walnut improvement program of the Horticulture Science Research Institute (HSRI) in Iran was launched in the early 1980’s with the aim of developing new cultivars. As a first step, in 1983 selected superior genotypes from the Iranian walnut gene pool were established in Karaj, Shahrood, Mashhad and Uremia. In 1994, seven genotypes from the Karaj collection were propagated by grafting and planted, along with eight French/Californian commercial cultivars, at Karaj. This resulted in the release of the first Iranian walnut cultivars, Jamal (Z63) and Damavad (Z30) in 2009–2010J. regia 700K SNP array on Iranian walnut genetic resources, and (iii) identify SNPs significantly associated with nut and kernel-related traits using GWAS. The present study is the first to directly assess the population diversity of Iranian walnut genotypes using high-density SNP markers. Although some of these materials have low agronomic value compared to commercial walnut cultivars, they may contain useful resilience alleles that have been lost in the modern genetic resources of walnut.The main objectives of the present study were to: (i) assess population structure, genomic variation and differentiation among Iranian walnut populations, (ii) evaluate the performance of the newly designed Axiom We measured 22 seed-related traits in a walnut collection comprising 95 genotypes, assembled from different parts of Iran Table . These pCorrelation coefficients were used to determine the relationships between seed-related traits Table . SignifiPrincipal component analysis (PCA) was used to identify patterns of diversity among genotypes, based on phenotypic traits , which comprises polymorphic SNPs with three high-resolution genotypic clusters; 2) No Minor Homozygote (NMH), SNPs with no samples of the minor homozygous genotypes; 3) Mono High Resolution (MHR), SNPs which are monomorphic across the genotypes studied; 4) Call Rate Below Threshold (CRBT), SNPs with genotype call rate below threshold (97%); 5) Off-Target Variant (OTV) polymorphisms, where the genotyping data with low-intensity cluster resulted from dissimilarity between the probe and the target sequences and; (6) Other, which includes SNPs with no clear cluster pattern of the genotypic data.The SNPs were categorized into the six default classes using Affymetrix Power Tools (APT): 1) A summary of the distribution of all SNPs in the different categories is shown in Table To study the structure of Persian walnut populations and the genetic relationship among samples, three different analyses were performed. Principal Component Analysis (PCA) and cluster analysis (CA) were used to assess the genetic distances among Iranian walnut genotypes by using a linkage disequilibrium (LD)-pruned SNP subset of 33,336 PHR polymorphisms. Figure In contrast, the cluster analysis on a genome-wide Identical-By-State (IBS) matrix grouped the Iranian walnut genotypes into five groups  within our Iranian walnut collection. According to the best choice algorithm function of fastSTRUCTURE, the most likely K ranged from 2 to 5 Fig. . At K2 to) and expected heterozygosity (He) were 0.34 and 0.38, respectively but the level of genetic diversity varied among the Iranian walnut populations  was found in the West Azerbaijan population (1.44), while the Ilam and Kerman populations both showed the highest value of Ar (1.62) (Table o) ranged from 0.30 in the Markazi population to 0.34 in the Ilam and West Azerbaijan populations (0.33) (Table e) varied from 0.26 (West Azerbaijan) to 0.34 (Kerman). The lowest (0.31) and highest (0.35) unbiased expected heterozygosity values (UHE) were identified in the Semnan and Ilam populations respectively (Table IS) ranged from −0.29 in the West Azerbaijan population to 0.03 in Kerman and Fars populations, but on average, we observed low values of FIS in all Iranian walnut populations, indicating a deficit of homozygotes  Table . The obs3) Table . The expghest 0.3 unbiasedghest 0.3 unbiased′ST, DJost and FST) for each pairwise comparison between the Iranian walnut populations  among our Iranian walnut populations indicate moderate genetic differentiation  value > 99% and were therefore considered to be genetically identical. The first and second-degree relationships, the most informative, are shown in Table Due to the great phenotypic variability observed in our collection for nut-related traits, we ran GWAS to dissect, for the first time in walnut, the genetic basis of these traits. GWAS was performed using as phenotypic entrance, both the average of 12 kernels per tree and the individual best linear unbiased predictors (BLUPs), as well as the first five PCs of the phenotypic data. We applied the SUPER and FarmCPU algorithms, accounting for both population structure and kinship. A total of 55 loci on 11 chromosomes were significantly associated with six nut and kernel-related traits and the first five PCs of the phenotypic data Fig. . Three SConsidering the suggestive threshold, we identified 56 loci associated with 13 nut and kernel related traits . Other genes identified as involved in the studied traits included were the WD repeat-containing protein RUP2, the acidic endochitinase-like, the LRR receptor-like serine/threonine-protein kinase GSO1, the classical arabinogalactan protein 9-like, the cysteine-rich receptor-like protein kinase 25, and the NAC domain-containing protein 43 genes (Supplementary Table The 55 significant (41 unique sequence) and 56 suggestive SNPs associated with nut and kernel-related traits were annotated using BLASTx queries (Supplementary Table 33). Most walnut trees grown in Iran originated from seed, and exhibit considerable diversity in yield, quality, and resistance to abiotic and biotic stresses12. Environmental stresses and climate change are reducing walnut yield17. To face these challenges, native genotypes with interesting phenotypic traits need to be explored and preserved for future development of improved scion and rootstock varieties16. In this regard, as a pre-selection step, we evaluated various Iranian walnut populations in their native habitats for traits including climatic adaptations, precocity, yield, nut quality and resistance to biotic and abiotic stresses. Based on the profiles of all these traits, we selected the most interesting and variable 95 genotypes for the assessment of walnut genomic variation as a first step towards future walnut sampling and the introduction of molecular breeding for Persian walnut in Iran. These individuals originated from eight Iranian provinces  was similar to that observed for the California material25, confirming this array’s value in assessing the population structure and genomic variation of Iranian walnut populations.Compared to previous surveys of Iranian walnut40.Using the genetic profiles of high-quality SNPs evenly distributed across the genome, we identified four distinct genetic groups in our walnut collection Fig. . Such poet al.25 using the same SNP array. In contrast, our Iranian collection was more heterozygous than six J. regia populations from Kerman province studied by Vahdati et al.16 (0.23), but less heterozygous than other Persian walnut germplasm described in previous genetic surveys41. This discrepancy can be explained by the use in this study of SNP markers, which are bi-allelic and therefore detect polymorphisms differently from the multi-allelic SSRs42. In the Kerman, Fars, and Ilam populations, He was slightly higher than Ho, probably due to the Wahlund effect or inbreeding. On the other hand, the values of Ho and He in the West Azerbaijan population suggest low inbreeding and large genetic variation. However, these findings could also be due to the small sample size of our walnut panel. Collecting additional walnut material from Iran will be essential in providing further support for our conclusions.The average heterozygosity (Ho = 0.34) was similar to that of UC Davis WIP accessions (Ho = 0.3) examined by Marrano et al.25, overall most of the Iranian populations exhibited little inbreeding and considerable genetic variation, as expected due to the dichogamous nature of walnut which promotes outcrossing. The high inbreeding coefficient found by Vahdati et al.16 suggests significant heterozygote deficiency, likely due to crossing between closely related individuals. We observed greater genetic variation than Vahdati et al.16, probably because we assessed more diverse populations from eight provinces and using genome-wide markers. In addition, although walnut is a mixed-mating tree species, negative FIS values are expected in adult trees because breeding is usually purged at an early age, thus age of the tree and sampling is an important indicator in determining FIS values41. Absence of inbreeding may also be due to an “isolate breaking effect” that occurs when previously isolated populations interbreed44.As in Marrano ST values for most wind-pollinated tree species tend to be lower than 0.1041, indicating that more than 90% of the neutral genetic variation is maintained within populations. Our global FST value of 0.07, indicates that 93% of the genetic diversity of our walnut collection occurs within the seven Iranian populations  that were genetically identical and likely propagated by natural layering. Based on our observation at the site, natural layering occurred when a branch of the older tree (more than 500 years old) touched the ground, producing adventitious roots and eventually a new tree. Vahdati and Khalighi47 have previously reported vegetative propagation by layering in walnut. This is the first report of vegetative propagation in an Iranian walnut population.To date, there is no published parentage analysis of Iranian walnut populations. Although walnut can be propagated by several methods48 that stated the parents of Chandler might have originated from Iran. These parentage results, together with the genomic variation and differentiation analysis, are of interest both for clarifying the relationships between walnut accessions in view of GWAS analysis, and for accurate planning of future breeding programs in Iran.Parentage analysis identified seventeen pairwise relationships among the Iranian genotypes, nine classified as first and eight as second-degree relationships. All of these were between individuals within given populations, probably due to open pollination or seed exchange between local walnut growers. Interestingly, we identified a second-degree relationship between the cultivar Chandler and two individuals from the Ilam population, possibly indicating one of the ancestors of ‘Chandler’ could have originated from Iran. Our results are consistent with TuleckeDue to the limited number of individuals per population, our conclusions about genetic differentiation among populations have to be considered preliminary. The results of this study can be improved by increasing the sample size from the populations that we had a limited number of samples of them in our survey , and from the Semnan population as the most genetically differentiated from the other populations. In addition, in future studies, sampling of young and old trees from the same locations might reveal if local regeneration methods tend to preserve local genetic diversity or obscure it by the importation of new genetic types. Additional collections from other Iranian provinces and further genomic analysis will provide additional evidences to our results.49 and, therefore, the determination of seed size50, as well as in the development of the epidermal surface in embryos and cotyledons51, seed size/weight52, and seed maturation53. The SNPs identified in this study, if appropriately validated, could be used as potential markers for marker-assisted breeding in walnut.As further proof of the value of our walnut collection, we performed association mapping for nut and kernel-related traits, identifying marker-trait associations for 19 of the 22 traits studied. Our GWAS results revealed 55 significant SNPs (41 of unique sequence) associated with the variation of six traits, and 56 suggestive SNPs associated with 13 traits. None of the markers identified for the studied traits were previously mapped. In some cases, the same SNP was associated with different traits, which could be explained by the high correlation observed among them, or pleiotropic effects. Limited information exists in walnut regarding the genetic based of nut and kernel-related traits. The annotation of the significant and suggestive SNPs revealed genetic mechanisms for the studied traits also identified for other plant species. In particular, it has been already reported that the genes encoding for the WRKY transcription factor, the LRR receptor-like serine/threonine-protein kinase GSO1, the NAC domain-containing protein 43, and cyclic DOF factor 2-like are likely involved in embryo developmentJ. regia 700K SNP array to characterize Iranian walnut genotypes and to verify that the genetic variation available in our panel was suitable to perform an informative association mapping study. We observed a conversion rate similar to that obtained using the same SNP array in a Californian walnut collection. This indicates the Axiom J. regia 700K SNP array is a robust and valid genomic tool for further exploring the genetic variation and differentiation of walnut worldwide.Genome-wide markers offer new opportunities for better understanding genomic variation and architecture of horticulturally important traits in walnut. We used the Axiom ST analysis found the Semnan population to be the most genetically differentiated and further in-depth examination of it should be prioritized in view of its value for future breeding programs. Overall, we observed consistency among the different genetic analyses employed and results were in accord with geographical and ecological information. Our findings demonstrate that large genetic variation still exists within Iranian walnut populations located in one of the main centers of origin and domestication of Persian walnut. Also, the potential of our population for future GWAS studies was confirmed through the results of association mapping for nut and kernel-related traits. The information generated in this study will be useful for better understanding the genetic basis of adaptation in walnut and identifying resilience alleles to be used by future breeding programs in addressing the challenges of climate change. Our invaluable collection of walnut genotypes adapted to diverse climates and altitudes across Iran were maintained at the Nut Crops collection orchard of Aburaihan Campus, University of Tehran. All the seven populations investigated in present study, along with additional material collected from other parts of Iran, have been established in a common garden to investigate in the future the genetic architecture of local adaptation and the correlation among genotypes and both environmental variables and drought-related traits using GWAS approaches.Population structure analysis of this Iranian walnut collection showed four main groups. Total differentiation among the populations was moderate, reflecting the occurrence of cross-hybridization events between native populations. Pairwise FIn the first step, pre-selection of Iranian walnut genotypes based on phenotypic records from the Iranian Ministry of Agriculture and local growers was performed with the aim of selecting superior genotypes to be used in future scion and rootstock breeding programs. We selected 95 genotypes to characterize at both phenotypic and genomic levels. In particular, the selected 95 individuals inhabit disjunctive mountainous areas, and are old walnut trees from open pollinated seedlings (50- to 500-year-old) with trunk diameters greater than 50 cm. They represent local populations (seedlings) that were randomly planted by humans or birds (mostly crows), and grow across wide areas in different parts  of Iran. Seeds of the studied genotypes collected from walnut populations located in eight main walnut producers provinces in Iran. The walnut trees investigated in the present research were separated from each other by 366–1768 km (approximately 890 km on average). We sampled four locations from Kerman , two each from Fars (Eqlid and Bavanat) and Ilam (Ilam and Eyvan) and one each from Semnan, Yazd, Markazi, West Azerbaijan and Hamadan Table ; Fig. S154. These included nut length (NuLe), nut width (NuWi), nut thickness (NuTh), nut weight (NuWe), kernel percentage (KePe), shape index (ShIn), size index (SiIn), round index (RoIn), nut shape (NuSh), shell thickness (SheTh), shell color (SheCo), shell texture (SheTe), shell seal (SheSe), shell strength (SheSt), packing tissue thickness (PaTiTh), kernel weight (KeWe), kernel color (KeCo), kernel plumpness (KePl), kernel shrivel (KeSh), kernel vein (KeVe), kernel fill (KeFi), and ease of kernel removal from nuts (EKeNu). Statistical analyses including descriptive statistics and normality testing on data and their residuals were performed in Minitab 18 statistical software . Multivariate statistical analyses, including principal component analysis (PCA), and correlation analysis were conducted using R55. Pearson and Spearman’s rank correlation coefficients were used to determine the relationships between two continuous variables and two continuous or continuous-ordinal variables respectively.Leaf tissue and open-pollinated seeds (at least 60 nuts per mother tree) were sampled. Twelve nuts of each selected genotype were used to evaluate 22 fruit-related traits, based on International Plant Genetic Resources Institute (IPGRI) or BI descriptorsThis study examined 95 adult walnut trees grown locally in diverse parts of Iran with various climates. The plant material was collected from eight Iranian provinces: Kerman, Fars, Ilam, Semnan, Yad, Markazi, West Azerbaijan and Hamedan. A detailed list is presented in Table Total genomic DNA was extracted from 40 mg of dry leaves using the E-Z 96 Plant DNA Kit  according to the manufacturer’s instructions. DNA was quantified using Qubit dsDNA High Sensitivity (HS) Assay Kits . The quality of DNA samples was checked by agarose gel electrophoresis.www.affymetrix.com) for genotyping using the new Axiom J. regia 700K SNPs array25 on the Affymetrix GenTitan platform. Genomic DNA of the cultivar Chandler was used as a control.DNA samples were adjusted to the recommended concentration of 15 ng/µL in 50 µL aliquots and sent to Affymetrix . The samples with a dQC value ≥ 0.82 and a QC call rate ≥ 97% were considered for further analysis. SNPs were then classified into six major classes: PHR, NMH, OTV, MHR, CRBT and Other.SNP allele calling was performed by the Bioinformatics Core of Affymetrix as described in the Axiom Genotyping Solution Data Analysis Guide  ranging from 2 to 10 were tested, with ten replicates each using the default convergence criterion and priors. The most likely K value was chosen by plotting the marginal likelihood of the data, and with the best choice function implemented in fastSTRUCTURE. The results of all replicates for each K cluster were summarized using CLUMPAK (http://clumpak.tau.ac.il/)58.PHR SNPs filtered for missing rate (>20%) and MAF (<5%), and LD-pruned (plink commands: indep-pairwise 50 5 0.25) were used to perform the population structure analysis. Two approaches were used: (i) Principal Component Analysis (PCA) and (ii) fastSTRUCTURE analysis. The PCA analysis was performed using the R package ‘SNPRelate’56.To confirm further the subgroups identified by the above analysis, individual dissimilarities for each pair of individuals were calculated and used for hierarchical cluster analysis by the R package ‘SNPRelate’59, which is available in R55. Mean number of alleles per locus (A), mean observed heterozygosity (Ho), expected heterozygosity (He), unbiased expected heterozygosity (UHe), allelic richness per population (Ar), and inbreeding coefficient (FIS) were calculated for SNPs with a missing rate < 20% and MAF > 5% across the different sub-populations of Iranian walnut accessions. Populations with only one individual were excluded from the analysis.The genomic diversity of populations was estimated using the ‘diveRsity’ packagee or gene diversity) and the observed heterozygosity60. These are computed as:k is the number of distinct alleles at a locus, and pi  is the frequency of allele i in the population.Two important measurements of within-population genomic variation at a marker locus are the expected heterozygosity (HF ranges from 0 (no inbreeding) to 1 (completely inbred population)And′ST = Hedrick’s standardized “differentiation” per locus61, DJost = Jost’s true allelic differentiation per locus62, and the three unbiased estimators of Wright’s F-statistics63 within-population inbreeding coefficient (FIS), total-population inbreeding coefficient F (FIT), and the among-population genetic differentiation coefficient θ(FST). The index FST was computed as:w is the variance of the allele frequencies between populations, σb is the variance of the allele frequencies between individuals within populations, and σa is the variance of the allele frequencies between gametes within individuals.Genetic differentiation statistics between subpopulations for each locus and across all loci were computed using the R package ‘diveRsity’. These included: G64 was used to convert PLINK files (PED and MAP) to Genepop format as data input format for ‘diveRsity’ R package.PGDSpider version 2.1.1.565 was employed on each pair of the Iranian walnut genotypes to infer relatedness for all pairwise comparisons among the 95 Iranian walnut accessions. Pairwise IBD analysis was used to explore the first-degree and second-degree relationships among individuals as the proportion of the SNPs at which there were zero, one, or two shared IBD alleles represented by Z0, Z1, and Z2 respectively. Relatedness was then measured using the PLINK PI_HAT parameter, which indicates the proportion of SNPs in IBD between individual pairs. Pairs of accessions with PI_HAT value > 95% were considered to be genetically identical. We considered indvidual pairs to be first and second-degree relatives if they had PI_HAT values ≥ 0.47 and 0.22 respectively.The PLINK 1.9 software66, SUPER67 and Fixed and random model Circulating Probability Unification (FarmCPU)68 method, as implemented in GAPIT69. Population structure and familial relatedness were taken into account in all models. We determined suggestive thresholds to correct the p-value for multiple testing using the approach described by Gao et al.70. The significant and suggestive P values were 5e−07 and 1.006e−05 respectively. Manhattan plots were constructed accordingly using the GAPIT. For each trait, the significant SNPs were compared and annotated using the walnut gene annotation v1.0 (taxid: 51240)31.Association mapping was performed for 22 seed-related traits using the average performance of each genotype, BLUPs and the first five PCs of the phenotypic data. GWAS was carried out by applying three models: MLMMGenome-wide patterns of population structure and association mapping of nut-related traits in Persian walnut populations from Iran using the Axiom J. regia 700K SNP array


Cunninghamia konishii occur in Taiwan. A pattern of genetic isolation by distance was not found and variation partitioning revealed that environment explained a relatively larger proportion of genetic variation than geography. The effect of mountains as barriers to genetic exchange, despite low population differentiation indicating a high rate of gene flow, was found within the distribution range of C. konishii. Twelve AFLP loci were identified as potential selective outliers using genome-scan methods (BAYESCAN and DFDIST) and strongly associated with environmental variables using regression approaches  demonstrating adaptive divergence underlying local adaptation. Annual mean temperature, annual precipitation, and slope could be the most important environmental factors causally associated with adaptive genetic variation in C. konishii. The study revealed the existence of physical barriers to current gene flow and environmentally dependent adaptive divergence, and a significant proportion of the rate of gene flow may represent a reflection of demographic history.Populations can be genetically isolated by differences in their ecology or environment that hampered efficient migration, or they may be isolated solely by geographic distance. Moreover, mountain ranges across a species’ distribution area might have acted as barriers to gene flow. Genetic variation was quantified using amplified fragment length polymorphism (AFLP) and 13 selective amplification primer combinations used generated a total of 482 fragments. Here, we tested the barrier effects of mountains on gene flow and environmentally dependent local adaptation of  Understanding connectivity among populations and pattern of gene flow has been important for deciphering how species adapt in response to environments and has clear practical implications for conservation of forest genetic resources . Low levTaiwania cryptomerioides occurring in Taiwan was detected probably due to random neutral drift because of the high rate of gene flow among populations that eroded the adaptive local mutations  is a coniferous species disjunctly distributed in northern and central Taiwan and along part of the border between Vietnam and Lao People’s Democratic Republic (http://threatenedconifers.rbge.org.uk/taxa/details/cunninghamia-konishii). C. konishii is closely related to Cunninghamia lanceolata (Lamb). Hook. distributed in mainland China (http://threatenedconifers.rbge.org.uk/taxa/details/cunninghamia-konishii). In Taiwan, C. konishii is a dominant species among other conifers associated mainly with Chamaecyparis, Pinus spp., and Pseudotsuga wilsoniana at elevations of 1,300–2,800 m (C. konishii(ca. 60 hectares) in Shiangshanshan, Hsinchu County, northwest Taiwan, was entirely vanished by logging. Low level of population differentiation was revealed for C. konishii based on allozyme (C. konishii populations based on 357 AFLP markers derived from three AFLP selective amplification primer pairs. Populations of C. konishii are separated not only by major mountain ranges including the Hsuehshan Mountain Range (HMR) and the Central Mountain Range (CMR) trending from north to south, but also by mountains in between of the HMR and the CMR , though within a small latitudinal range, with wide variety of habitats because of varied geographical topologies and climates  test the barrier effects of mountains to current gene flow and 2) assess the relationships of genetic variation with environmental variables underlying local adaptation, in the light of usefulness in the future conservation of C. konishii.Environment may play an important role in driving population divergence . Howeverclimates . It is lC. konishii from 11 populations (EcoRI-MseI primer combinations (E00: 5’-GACTGCGTACCAATTC-3’ and M00: 5’-GATGAGTCCTGAGTAA-3’) with additional five and three bases were added, respectively, at the ends, were used  at the 95% level with rarefaction to the smallest sample size (n = 3) was calculated using AFLPDIV software v.1.1 (PBr) was estimated separately for each population using ADZE software v.1.0 (IA) (rD) (ia function of R poppr package (uHE)  with population and locus treated as fixed and random effect, respectively, based on reduced maximum likelihood estimation using the lmer function of R lme4 package   and modiA) (rD)  using th package  in the R package  to assese (uHE)  within ae (uHE) . In AFLPe (uHE)  for uHEIN v.6.0 . Assessm package . Signifi package , and P v package .via analysis of molecular variance (AMOVA) using the poppr.amova function of R package poppr, and significance tested using the randtest function of R package ade4 with 9,999 permutations , considering the uncertainty associate with the inbreeding coefficient (f) for dominant markers. To check the convergence of parameters, two HICKORY runs were performed with sampling and chain length parameters include burnin = 5,000, samples = 100,000, and thinning = 20. Genetic data was evaluated fitting to the full model, f = 0 model, θII = 0 model, and f-free model, and the best fitting model in estimating θII was determined by the deviance information criterion (DIC). The f-free model was used to estimate f within populations because other models produced unreliable f estimates. The f-free model selects f values from a uniform prior distribution without generating a posterior distribution of f independent of assumptions.The level of genetic differentiation among populations was analyzed utations . Across RY v.1.1  was usedC. konishii individuals were assessed based on sparse nonnegative factorization (sNMF) algorithm . The find.clusters and dapc functions of R adegenet package (K in DAPC was indicated by an elbow in the curve of Bayesian information criterion (BIC), as suggested by the authors of the R adegenet package, estimated using the find.clusters function.Genetic homogeneous groups of lgorithm  and disclgorithm . Individ package  was perf package  were useC. konishii populations distributed across mountains, Monmonier’s maximum difference algorithm . We obtained ecological factors including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) derived from moderate resolution imaging spectroradiometer (MODIS) dataset MOD13A2 (1-km resolution), and leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (fPAR) derived from MOD15A2 dataset (500-m resolution). The annual total potential evapotranspiration (PET) was calculated based on MOD16A3 dataset (500-m resolution). All the MODIS datasets were acquired from Land Process Distributed Active Archive Center (http://lpdaac.usgs.gov) during 2001‒2013, and monthly mean values of NDVI, EVI, LAI, and fPAR were computed using a maximum-value composite procedure  at spatial resolution of 1 km using a universal spherical model of the Kriging method in ArcGIS  conducted in 1969‒1986 from the Agriculture and Food Agency of Taiwan  were downloaded from the WorldClim v.1.4 . Topograrocedure . Monthlyn ArcGIS . Additiof Taiwan . Annual f Taiwan .cor function of R was used to calculate correlation coefficients between environmental variables. Variance inflation factor (VIF) was calculated using the vif function of R package usdm (r| < 0.8). The eight retained environmental variables were aspect, BIO1 , BIO7 , BIO12 , NDVI, PET, RainD, and slope (Results) using the adonis function of R package vegan (pairwise.perm.manova function of R package RVAideMemoire (The age usdm . We retage vegan . PairwiseMemoire . Signifimantel function of R vegan package.Mantel test was used to assess genetic isolation by distance (IBD) by analyzing the correlation of the population Euclidean distance matrix of AFLP with the population Euclidean distance matrix of geography (latitude and longitude) using the varpart function of R package vegan, and significance tested using the anova.cca function with 999 permutations  to assess the relative contribution of environmental variables explaining the total AFLP variation using the utations . The totutations . Adjustefraction . LongituFST outliers indicating signature of selection across populations. Hierarchical Bayesian method implemented in BAYESCAN v.2.1 ; strong (log10PO > 1.0); very strong (log10PO > 1.5); and decisive (log10PO > 2)  . We consFST ; smoothing proportion = 0.06; 500,000 resamplings; critical P = 0.05; and level of differentiation (target average θ) = 0.063254. Empirical loci considered to be the outliers potentially under directional selection were those with FST values significantly greater (P < 0.01) than the simulated distribution.DFDIST incorporates the Beaumont and Nichols model modified for AFLP . The proFST  and uHEST . We ran LFMM five times for each value of K with 10,000 iterations in Gibbs sampling algorithm and a burn-in period of 5,000 cycles. Z-scores from five independent replicate runs were combined using Fisher–Stouffer method . P values were further adjusted based on an FDR correction of 1% using the R qvalue package  of estimate were calculated using the posterior_interval function of R rstanarm package.For those potential selective outliers identified by either genome scan method (BAYESCAN or DFDIST), a Bayesian logistic regression approach implemented in the  package  was alsoC. konishii (PBr ± SD was 0.017 ± 0.007 (ranged from 0.0098 for the population YH to 0.0296 for the population DY) (%P ± SD was 53.9 ± 15.1 (ranged from 32.2 for the population DY to 74.3 for the population KW). The average level of uHE ± SD was 0.252 ± 0.016 and ranged between 0.227 (population DT) and 0.284 (population CT). Within C. konishii, the level of uHE per locus was significantly different among populations using LMM . However, significant difference in the level of uHE per locus was not found for all pairwise comparisons  and PBr , respectively, was found based on Spearman’s rank correlation test. However, significant positive correlation was found between sample size and the percentage of polymorphism . Using HICKORY, an estimate of f within population was 0.4969 (95% CI: 0.022–0.976) using the f-free model representing the contemporary reproductive mode of C. konishii  of the 11 populations examined (We obtained 482 AFLP loci (mean ± SD: 37.08 ± 7.87) for tion DY) Table 1.full model was the best model fitting to the genetic data based on DIC in HICKORY analysis . Significant population pairwise FST estimated using ARLEQUIN was commonly found .In the LEA analysis, the means of minimal CE was minimized at  and between the three genetic clusters (P = 0.001). Significant pairwise differences between populations were found (P = 1). Total explainable genetic variation was 7.38% , and adjusted P value of candidate outlier loci identified using LFMM were summarized in stan_glm function of R package rstanarm). In summary, 12 AFLP loci (2.49%) were identified either by BAYESCAN or DFDIST and associated strongly with environmental variables using Samβada, LFMM, and rstanarm. Results showed that annual mean temperature, annual precipitation, and slope were closely associated with a large proportion of the 12 FST outliers identified by BAYESCAN and DFDIST; and aspect, annual temperature range, NDVI, PET, and RainD associated strongly only with a minor proportion of these FST outliers.  in the present study was found to be higher compared to that of the previous study examined for C. konishii  for 13 plant species in general summarized in C. konishii covers only a small latitudinal range, it distributed across complex topography and habitat heterogeneity in mountain ranges . However, the level of genetic differentiation of the present study is consistent with the levels of genetic differentiation found based on allozyme (FST = 0.029) (GST = 0.073)  in the present study were consistent with the results found in other conifers occurring in Taiwan including K. davidiana var. formosana   and ptDN= 0.073) . The hig= 0.073)  could haormosana  and T. cerioides  based onerioides .FST were found (C. konishii may not follow a stepping stone migration model (C. konishii. Moreover, mountains surrounding the AL population could have played a damping effect on dispersal between the AL and all other C. konishii populations, particularly between the AL and its nearby CT population, genetically (C. konishii. However, environment could also be an important factor contributed to C. konishii population divergence because genetic variation is structured more by pure environment than by pure geography as revealed by the analysis of variation partitioning (C. konishii populations. Ecotypes are likely to have arisen at local scales and the emergence of clusters of locally beneficial mutations forming genomic islands of divergence (Although low levels of across population and population pairwise on model  due to ton model  rather ton model . In the vergence .C. konishii individuals among populations could be limited as suggested by significant population-level IA and rD in 7 of the 11 populations examined, indicating nonrandom association of loci within these populations (Current mating of ulations . Howeverulations  and LD wulations .C. konishii. Environmental variables including aspect, annual temperature range, NDVI, PET, and RainD could have played only minor roles as selective drivers in shaping adaptive divergence in C. konishii.Our results based on analyses using BAYESCAN, DFDIST, Samβada, LFMM, and rstanarm found adaptive divergence of genetic variation Table 4.Strong correlations between environmental variables and population genetic variability can be provided as evidence for local adaptation and selection . TemperaRhododendron oldhamii, occur in Taiwan (T. cryptomerioides, occurring in Taiwan, mainland China, and Vietnam (Environmental variation has been correlated with forest ecosystem properties in various geographic regions, suggesting the sensitivity of species composition responding to environmental conditions . NDVI isn Taiwan . PET was Vietnam .C. konishii. Spatial environmental heterogeneity might have invoked genetic divergence among populations and in consequence the formation of local adaptation.Our results suggest that ecologically relevant selective drivers involved in population adaptive divergence of C. konishii populations. In addition, geographic barriers to gene flow exerted by mountain ranges could have played an important role in restricting adaptive genetic divergence at local scales. The three genetic clusters revealed by LEA and DAPC can be employed as evolutionarily significant units for the future conservation program of this species.The maintenance of genetic ecotypes adapting to varying environmental conditions can be critical for the conservation of species in the face of global climate change. Environmental variables might have exerted effects in shaping adaptive evolution of genetic variation. In the present study, we found annual mean temperature, annual precipitation, and slope could be the most important environmental factors that played crucial roles in shaping adaptive genetic divergence. Nonetheless, aspect, annual temperature range, NDVI, PET, and RainD, though might have played only minor roles, could still be important selective drivers of local adaptation in S-YH proposed, funded, and designed the research; Y-SL, K-MS, J-DC, and S-YH collected samples; Y-SL, K-MS, and C-TC performed research; S-YH, Y-SL, K-MS, and C-TC analyzed data; S-YH and Y-SL wrote the paper. All authors have read and approved the final manuscript.This work was funded by the Taiwan Ministry of Science and Technology under grant number of MOST 106-2313-B-003-001-MY3.All plant materials collected conformed to the regulations of the Taiwan Ministry of Science and Technology.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.