Y. capensis and Y. valida, that have coevolved with the same pollinator, Tegeticula baja. Both yucca species are endemic to the peninsula, and their current distributions are allopatric. Based on their morphological characteristics, it has been suggested that some plants growing in the southern part of the Magdalena flatland, a spatially disjunct part of Yucca valida’s range, have hybrid origins. We conducted genomic and climatic analyses of the two yucca species as well as the putative hybrid populations. We genotyped 3,423 single nucleotide polymorphisms in 120 individuals sampled from 35 localities. We applied Bayesian tests and geographic cline analyses to the genomic data. Using climatic information from the occurrence sites, we projected species distribution models in different periods to assess changes in the distributional range, and we performed a statistical test to define the niche divergence between the paternal species and the putative hybrid populations. Structure analysis revealed mixed ancestry in the genome of hybrid populations, and the Bayesian models supported a scenario of post-divergence gene flow between the yucca species. Our species distribution models reveal that the geographical ranges of the parental species overlapped mainly during the Last Glacial Maximum, which could facilitate genetic admixture between those species. Finally, we found that most of the assessed environmental axes between the parents and hybrid populations are divergent, indicating that the climatic niche of the hybrid populations is shifting from that of the populations’ progenitors. Our results show that the populations in the southern part of the Magdalena flatland are the result of combination of the genetic components of two species. Hybrid individuals with this novel genomic combination arose in a different habitat than their parental species, and they exhibit ecological divergence, which contributes to reproductive isolation through spatial and temporal barriers.Hybridization can occur when two geographically isolated species are reproductively compatible and have come into sympatry due to range shifts. Yucca and yucca moths exhibit obligate pollination mutualism; yucca moths are responsible for the gene flow mediated by pollen among yucca populations. In the Baja California Peninsula, there are two yucca sister species,  Hybridization, which is defined as the reproduction of members of genetically distinct populations that produce offspring of mixed ancestry , plays aClosely related species often hybridize  if they Yucca valida Brandegee and Yucca capensis Lenz are long-lived monocot trees endemic to the Baja California Peninsula, located in northwestern México. Those species currently exhibit an allopatric distribution and grow under different environmental conditions. Populations of Y. valida grow in arid ecosystems from the Central Desert (30°N) to the Magdalena flatland, and this species show high density of individuals across the landscape  and a statistical test to define the niche divergence among taxa. Our specific goals were to examine (i) whether populations located in the southern part of the Magdalena flatland originated through hybridization between Y. capensis and Y. valida and their level of admixture; (ii) whether Quaternary climate change influenced a shift in species distribution that favored hybridization and the establishment of hybrid descendants; and (iii) whether there is ecological divergence among putative hybrid populations and endemic yucca species.In this study, we integrated genomic and climatic analyses to assess whether populations located in the southern part of the Magdalena flatland are Y. valida Brandegee and Y. capensis Lenz and the known range of the putative hybrid populations, which were located in the southern part of the Magdalena flatland (23.5°–24.5°N). Based in the geographical locations where we collected the individuals, we assigned them to a putative species or to the hybrid. We dried the tissues using silica gel for preservation. We extracted total genomic DNA from 100 mg of disrupted lyophilized leaf tissue using the DNeasy Plant Mini Kit . We assessed the quantity and integrity of DNA using 1.5% GelRed stained agarose gels and a NanoDrop spectrophotometer .Across a transect of 800 km (from latitude 23° to latitude 26° N), we collected 10 g of fresh leaf tissue from 120 individuals from 35 localities . Using tWe used the genomic DNA to generate nextRAD libraries, following previously described strategies , M , and n . We plotted and evaluated the resultant metrics to select the optimal set of parameters that maximizes the amount of reliable information. The parameter r  was fixed at 0.80, as recommended by m = 3, M = 3, and n = 4. When a locus showed more than one segregating site, one variant was randomly sampled from that locus to ensure that the loci were mostly independent. We discarded single-nucleotide polymorphisms (SNPs) with a minimum allele frequency (MAF) smaller than 0.05. Then, we used plink v1.07  using the R v3.41 R Core Team 2017 packages “adegenet” v2.1 (ST) among the species and putative hybrid populations, and we evaluated the statistical significance using the gstat. randtest function of the “hierfstat” package in 10,000 simulations. As a first approach to explore the grouping of individuals as a function of their allele composition, we performed a principal component analysis (PCA) at the individual level using the “adegenet” package.We estimated observed and expected heterozygosities as well as inbreeding coefficients , performing 15 iterations each. The software was executed in parallel using the StrAuto v1.0 script  proposed by To evaluate the genetic structure of the taxa, we used two approaches. First, we ran Structure v2.3.4  using th0 script . To detenno test , which wnno test . We alsoY. valida and Y. capensis, respectively. Scenario C proposed that the hybrid populations diverged before the divergence of Y. valida and Y capensis. Scenario D proposed that Y. valida and Y. capensis diverged and the putative hybrid populations are a result of mixture of the two genetic pools. Scenario E proposed that the three taxa diverged simultaneously in the past, and they have independent demographic histories. We ran 2 × 106 simulations per scenario, as recommended by the software. We divided the entire data set into three sets and ran them independently, resulting in a total of 6 × 106 simulations per scenario.To approximate the evolutionary history of the endemic yuccas and putative hybrid populations, we used DIY-ABC v2.1 . We testST and Nei distances, the mean and variance across loci with non-null FST and Nei distances, and the mean and variance across loci of FST and Nei distances. In addition, we used the mean of admixture across all loci, the mean and variance of non-null admixture estimates, and the proportion of loci with null admixture as the “three sample statistics. To check if the combination of scenarios produced simulated data close to the actual data set , we implemented a PCA using 10,000 simulations. Then, we estimated the posterior probabilities of different scenarios by fitting a multinomial logistic regression using the 1% of simulated dataset closest to the observed data, followed by linear discriminant analysis. The goodness of fit of the scenario (“Model checking” option) was carried out by simulating 1,000 pseudo-observed data sets with the posterior model’s distribution combination with parameter values drawn from 1,000 sets of the posterior sample. The summary statistics of the actual data were ranked with the posterior distribution of the scenarios’ summary statistics. Finally, we estimated type-I and type-II errors for all scenarios implementing the “evaluate the confidence in scenario choice” option.We used the proportion of monomorphic loci, the mean genetic diversity, and the variance across polymorphic loci, as well as the mean genetic diversity across all loci as “single sample statistics.” For the “two-sample statistics,” we used the proportion of loci with null Fq-value) obtained with Structure for K = 2 as admixture index of the two putative parental species, Y. valida, and Y. capensis. Clines were fitted using the R package “hzar” v0.2-5 , 385 of which were from Y. valida, 18 of which were from Y. capensis, and 25 of which were from the putative hybrid populations. The latitude and longitude coordinates for individuals sampled and observed in the field were obtained from a global positioning system tracker. To generate the background predictions for each taxon, we developed a distribution polygon by drawing 5 km circles around each individual and merged them to obtain a continuous area. Then, we placed 2,000 random points inside each polygon and extracted raw data from them. We used the R packages “sp”  axes for further consideration since they comprised the bulk of the variation and were readily interpretable (see the Results section). Niche divergence or conservatism was evaluated on each niche axis by comparing the observed difference between the means for each yucca species and the putative hybrid populations on that axis to the mean difference in their background environments on the same axis. A null distribution of background divergence was created by recalculating the background divergence score over 1,000 jackknife replicates with 75% replacement. Significance for rejecting the null was evaluated at the 95% level. All analyses were conducted using Stata v10.To conduct the multivariate test for niche divergence, we used 19 BioClim layers (Bio1-Bio19)ges “sp”  and “disges “sp” . Because2 , BIO2 , BIO4 , BIO5 (maximum temperature of warmest month), BIO8 (mean temperature of wettest quarter), BIO9 (mean temperature of driest quarter), BIO12 , BIO13 (precipitation of wettest month), BIO14 (precipitation of driest month), BIO15 , BIO18 (precipitation of warmest quarter), and BIO19 (precipitation of coldest quarter).To evaluate the influence of past environmental conditions on possible distribution overlap of the taxa, we built species distribution models (SDMs) using BioClim layers2  for the 2 , Last Gl2 , and Las2  periods.2 . Using bWe constructed the final models based on an ensemble of forecasting models using the committee-averaging criteria  in the Rr2 = 0.72, and more than 97.5% of paired values were lower than r2 = 0.5, so we keep all loci for further analyses. The two endemic yuccas and hybrid populations had an overall genetic diversity of HE = 0.2826 and HO = 0.1255 for the 3,423 analyzed SNPs. The three taxa show differences in genetic diversity, and the putative hybrid populations had the highest diversity. We also found a significant deficiency of heterozygotes in the three taxa  was high (FST = 0.2538), the values of the paired comparisons with hybrid populations were lower . Moreover, the PCA performed at the individual level showed clear separation of individuals of different yucca populations  or Y. capensis (q ≥ 0.888) and all individuals with high levels of admixture belonged to the locality of the hybrid populations. Following the PCA analysis, DAPC revealed three genetic groups separating all individuals into their respective taxon  and seasonality of temperature and the lowest temperatures; and the third was associated with the highest temperature and precipitation and annual rain. The results of the niche divergence test showed evidence of conservatism on the first niche axis and divergence on the second and third axes . Thus, the potential distribution of both endemic species overlapped in the past, mainly around latitudes of 25.5–23.5°N  and Y. capensis flowers mainly in September and October  are influenced by the California Current and the associated cold surges (Y. valida is extreme in terms of some environmental conditions, exhibiting, for example, the lowest temperatures and low levels of rain, which can explain the partial divergence in climatic niches observed between the taxa. On the other hand, Y. capensis is endemic to the Cape Region of Baja California Sur, and it is distributed in the undergrowth of the lowland deciduous forest in the mountains, up to 1,000 meters above sea level (Y. capensis is much more seasonal than the habitat of hybrid populations, supporting the niche divergence between the taxa.Regions with high environmental heterogeneity favor speciation. The endemic species d surges . The habea level . The habY. capensis shows the highest genomic variability, although its geographical range is currently the most restricted. Nevertheless, the predicted distribution of this species during the Last Interglacial and Last Glacial Maximum periods was wider than in the present, suggesting that, in the past, there was a larger suitable area that could support a higher effective population size. On the other hand, Y. valida, the parental species with wider distribution, had a low level of genetic diversity and a high number of fixed alleles. This is explained in part by a reduced suitable habitat during the Last Interglacial period that could result in a small effective historical population for this species.Geographically explicit predictions of climatic niches are a good starting point to explore niche differences and discover regions with suitable climatic conditions for species. Our SDMs for the present accurately described the distribution of the two endemic species. For the hybrid populations, the model revealed a wide area with suitable conditions that extends beyond the regions where we recorded hybrid individuals. In addition, projecting the models to different times allowed us to link current genomic patterns with historical distributions. For example, This study confirms how the geographical context influences the specificity of the pollination mutualism between yuccas and yucca-moths. We showed that the hybrid populations in the Baja California Peninsula are the result of combination of the genetic components of the two endemic yucca species. Currently, hybrid individuals with this novel genomic combination occur in different habitats than their parental species, and ecological divergence between them, as well as the spatial and temporal barriers, contributes to reproductive isolation. Finally, to consider these populations as homoploid hybrid species, it is necessary to collect new evidence, which may be related to the role of natural selection in maintaining the distinctions of hybrid taxon as well as the mechanisms through which hybridization generates reproductive isolation .Raw reads are available in NCBI under the SRA numbers: SRR11514779, SRR11514778, and SRR11514777.All work described in this manuscript was original research carried out by the authors. MA and RB-B developed the original research design and field data collection. JG-P and MA carried out the analyses. All authors contributed substantially to the writing and proofreading of the article, and read and approved the final submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Rhododendron is the largest genus of woody plants in China, and many species are threatened, however, to date there has been no conservation genetic research using NGS in this genus. In the present study, we investigated the conservation genetics of R. cyanocarpum, a threatened species endemic to the Cangshan Mountains in Yunnan, China, using a double digest restriction-site-associated DNA-sequencing (ddRAD-seq) approach. Due to the availability of sufficient SNPs, we were able to distinguish between neutral and putatively selected SNPs and were able to further investigate the genetic diversity, population structure, and differentiation in R. cyanocarpum, as well as make an estimation of its demographic history. A total of 6,584 SNPs were obtained, of which 5,729 were neutral (detected using Tajima’s D). In terms of the 5,729 neutral SNPs, R. cyanocarpum had a higher genetic diversity  than other plant species assessed using Rad-seq methods, while population differentiation (Fst from 0.0314 to 0.0452) was weak. Interestingly, contrasting patterns of population structure were revealed from all neutral and selected SNPs, with distinct genetic clusters forming for all SNPs and neutral SNPs, but no distinct subgroups for selected ones. Moreover, we were able to detect changes in effective population size (Ne) of R. cyanocarpum from 150,000 years ago, including a bottleneck event ca. 60,000 years ago, followed by recovery of Ne over a short period, and a subsequent gradual decline in Ne to date. Implications for conserving R. cyanocarpum based on these main results are then discussed.Though it is well-acknowledged that next generation sequencing (NGS) technologies can provide further insights into plant conservation management than traditional molecular markers, studies employing NGS to address conservation genomics and subsequent conservation strategies for threatened plants are still rare.  Biodiversity conservation is key in the field of conservation, and the essence of all biodiversity is genetic variation . Indeed,Population genetics, when based on a relatively wide distribution, can provide a rich and mathematically rigorous framework for understanding evolutionary processes in natural populations. Common marker types, such as microsatellites or AFLP, can only generate limited markers per sample . With hiRhododendron L. (Ericaceae) contains more than 1,000 species and has a global distribution  K. Koch and Subsect. Thomsonii Sleumer, is a threatened species endemic to the Cangshan Mountains in Dali, Yunnan Province, Southwest China  should show more similar patterns than neutral ones. Moreover, we supposed that historical demography  could play an important role in maintaining the current distribution of R. cyanocarpum.st China . R. cyanred list , in the red list  and in tred list . R. cyan m2 plot . Its mai m2 plot , with a  m2 plot  and at l m2 plot . In addinocarpum . Temperanocarpum . Furthernocarpum , reprodunocarpum . HoweverR. cyanocarpum using ddRAD-seq  in China  to cluster and generate loci. All the loci were merged into the catalog using cstacks with the default parameters. The populations program  was used to call the SNPs across all ddRAD sites, the parameter “–write-single-snp” was used to restrict data analysis to only the first SNP per locus , nucleotide diversity (π), and Wright’s F statistics Fst and FIS statistics, were calculated using the “populations” program in Stacks  performed using Plink v.1.9  formatted file with VCF files, and the demographic history was then inferred using the program Stairway plot v.0.2 , 3.162 × 10–8 per site per generation (generation time = 20) and 4.743 × 10–8 per site per generation (generation time = 30) for R. cyanocarpum.After all quality filters, 3,337,583 reads with no rad tag and 12,793 reads with low quality were discarded. We retained a total of 344,001,104 reads from the initial 347,351,480 raw reads, with an average of 5,830,527 reads per sample. After trimming and clustering, we obtained 9,148,349 loci. Mean locus coverage across all samples was 23.91×, ranging from 17.77× to 58.41×, with an average length of 136 bp per loci and with 40–48% GC content. After the “cstacks” module process, we obtained 2,464,683 catalogs . Finallyq < 0.05) with this method. Hence, our final datasets for further analysis were all loci , neutral loci , and selected loci (855) identified by Tajima’s D.After filtering using Tajima’s D in Vcftools, a total of 855 SNPs evolving non-randomly (”selected”), and 5,729 SNPs evolving randomly  were retained. The Tajima’s D value for the whole dataset at the species level was –0.2748. Significantly negative Tajima’s D values were found, indicating that the haplotype frequencies deviated from the neutrality model . SelecteHe and π showed significant difference among the four populations for all loci , neutral loci , and selected loci . The inbreeding coefficients were positive in the four populations, reflecting a deficit of heterozygotes (inbreeding) , neutral loci dataset is in the middle (911–1136), and all loci dataset has the highest number of private alleles (1081–1351). The genetic parameters reeding) . The sumFst values between populations were less than 0.05 , after which followed a population expansion and then a gradual reduction in population size to ca. 100 years ago  was higher compared with previous studies on other plant species using ddRAD sequencing. For example, a much lower level was found in endangered Viola uliginosa (0.013–0.023) (Clermontia fauriei (0.0014), and Cyanea pilosa (0.0012) populations  , Clermonulations ; we are 30 years . It has  Factory , close te period .R. cyanocarpum could be explained by gene flow resulting from long-distance gene dispersal either as pollen or as seeds   , and was0.05 Ma) , and theR. cyanocarpum underwent a population expansion in the period before and after the Last Glacial Maximum  , the Bronze Age   . That th.006 Ma) . Recentliculture . Togethears ago) , the inwars ago) . Taken tars ago) , all posR. cyanocarpum underwent a bottleneck, a subsequent expansion, and a gradual reduction. With intensive anthropogenic activity and global warming, the species has become fragmented and now has a highly restricted range near the summit of the Cangshan Mountains. Based on our main findings, we recommend the following conservation measures for R. cyanocarpum. (i) Although all populations are located in a national nature reserve, habitat disturbance from anthropogenic activity still occurs frequently, including tourism, path construction, and pasture and land reclamation. Absolute prohibition of anthropogenic activities is not possible and is also not necessary, although in the national nature reserve deforestation and large-scale land reclamation should be banned absolutely, especially near the HDB and XHD populations, where there is a big pharmaceutical farm. (ii) Because most individuals of R. cyanocarpum are situated on ridges of the Cangshan Mountains, and no distinct subgroups were detected when using selected loci, we suppose that the most serious threat to R. cyanocarpum will be not anthropogenic activities but instead be global warming. Given the topographic and landscape constraints, the species has limited migration potential, and ex situ conservation is therefore urgent and should be conducted immediately, including seed collection and conservation, and searching for new suitable habitats. (iii) The DHY population had the highest level of genetic diversity of the four populations, and we observed more connectivity and admixture between DHY and other populations than between any of the others, suggesting its importance in maintaining genetic polymorphism. This population is geographically located in the middle of other populations, which is beneficial for facilitating dispersal and connecting the other populations as a corridor. Therefore, we suggest that more conservation effort be given to the population DHY.https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA640883.The raw sequencing data has been successfully uploaded to SRA in NCBI, YM conceived and designed the experiments and revised the manuscript. LZ carried out investigation and collected materials. DL analyzed the data and wrote the manuscript. YM and JW acquired the funding. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Phoebe zhennan which is distributed around the Sichuan Basin. Genomic patterns revealed two distinct clusters, each largely confined to the West and East. Despite sympatry of the two genomic clusters at some sites, individuals show little or no evidence of genomic introgression. Demographic modeling supported an initial divergence time between the West and East lineages at ~15.08 Ma with further diversification within the West lineage at ~7.12 Ma. These times largely coincide with the two independent intensifications of the East Asian monsoon that were initiated during the middle (Langhian) and late Miocene (Messinian), respectively. These results suggest that the Miocene intensification phases of the East Asian monsoon played a pivotal role in shaping the current landscape‐level patterns of genetic diversity within P. zhennan, as has been found for the interspecific divergence of other subtropical Chinese plants. Based on isolation‐by‐distance and species distribution modeling, we hypothesize that P. zhennan followed a ring diversification which was facilitated by the Sichuan Basin acting as barrier to gene flow. In situ and ex situ conservation management plans should consider the results obtained in this study to help secure the future of this beautiful and culturally significant endangered tree.Understanding the role of climate changes and geography as drivers of population divergence and speciation is a long‐standing goal of evolutionary biology and can inform conservation. In this study, we used restriction site‐associated DNA sequencing (RAD‐seq) to evaluate genetic diversity, population structure, and infer demographic history of the endangered tree,  The Miocene intensification phases of the East Asian monsoon, combined with geographic distance, played a pivotal role in the evolution shaping the plants species of subtropical China. Remaining reads were then assembled into loci in “ustacks” with a maximum distance between stacks of M and minimum read depth of m. The loci were clustered further into “cstacks,” with mismatches allowed between samples. To increase coverage depth and maximize loci, a minimum read depth of 6 (m = 6) and a maximum distance between stacks of 2 in “ustacks” (M = 2), and 6 mismatches in “cstacks” (n = 3) in STACKS was set. After finishing de novo assembly, SNPs calling and genotyping were performed using “populations” model in STACKS. Loci with 100% presence among populations (p = 12) were retained, whereas loci with >25% missing data within populations were removed (r = 75%) to maximize shared SNPs across individuals. The first SNP per locus and SNPs with minor allele frequencies (MAF) ≥ 0.05 were retained. After completing SNP calling, those remaining with a Hardy–Weinberg equilibrium (HWE) p‐value less than .05 were also removed using VCFtools v4.0  using the STACKS 1.35 pipeline , and historical relationships; and (c) the minimum dataset consisting of 5,000 SNPs dataset extracted randomly from 16,210 SNPs for Bayesian clustering in the STRUCTURE v2.3.4  the full matrix with all polymorphic loci for genetic summary statistics; (b) a subset consisting of 16,210 SNPs with HWE filtering based on the full matrix for pairwise P), observed and expected heterozygosity (Hobs and Hexp), nucleotide diversity (π), and inbreeding coefficients (FIS), were estimated using populations in STACKS for all populations (10) with more than six samples. Pairwise FST values were calculated using Arlequin v3.5.2  in order to quantify genetic variation partitioning across the different sampling levels.Genetic summary statistics for RAD‐seq genomic data, including percentage of polymorphic sites (%K) ranged from 1 to 13. For each value of K, 10 independent simulations were conducted with a burn‐in length 100,000, followed by 300,000 iterations. The best K value was identified based on the successive change of LnP(D), Evanno's delta K, and individual assignment probabilities . An admixture model with no priori information for sampling location was utilized to determine whether the number of clusters  tree and residual plot were visualized in R and illustrated in combination with the STRUCTURE results.We used TreeMix v1.13  values used to represent genetic distance. Geographic distances among the sites with “straight‐line distances” and “ring distances” were calculated in the R package geosphere . Populations were grouped into three clusters based on STRUCTURE, PCA, and ML results in order to capture the main characteristics of the population histories for the East group , West1 group (EMS), and West2 group (SF and YJ populations). The dataset used for demographic analysis was generated from the dataset 2 , but using only a SNP with the lowest allele frequency per RAD‐seq locus. The sample sizes of gene copies for the East, West1, and West2 groups were 30, 24, and 24, respectively.Fastsimcoal2.6 , the variable that gave a higher value in the regularized gain and the percent contribution to the Maxent model was retained  was estimated to test the accuracy of the model prediction Method . The dis33.1After filtering reads with an average quality score below 30, the number of reads for each individual (85 bp/reads) ranged from 4,096,070 to 16,201,221  with a GC content of 37.9%. After de novo assembly and SNP calling, there were 43,906 preliminary assembled loci, 31,834 polymorphic loci, and 59,288 SNPs (the full dataset had 1.86 SNPs for each locus), corresponding to the full matrix. After SNP filtering, the minor dataset yielded 16,210 loci and 16,210 SNPs.3.2P) for each population was 1.11 and ranged from 0.72 to 1.95 per population. Private alleles were present in all populations varying from 19 (YJ population) to a maximum of 3,435 (EMS population). Observed heterozygosity (HO) across all populations ranged from 0.227 to 0.252 for each population (average 0.243), and expected heterozygosity (HE) across all populations ranged from 0.118 to 0.186 (average 0.158). Expected heterozygosity for each population was consistently lower than observed heterozygosity, and nucleotide diversity (π) across all populations ranged from 0.0039 to 0.0051 (average 0.0048) for each population  was negative and ranged from 0.0064 to 0.0033, indicating low levels of inbreeding in populations. The summary statistics  showed the same trend when using all nucleotides , indicating interpopulation differentiation. In particular, the short straight‐line distances between QCS and the Western and southwestern populations  relatively high pairwise FST values (between 0.220 and 0.377) suggested population differentiation in this region, while the FST values between QCS and the southern and southeastern sites  were negative, with slightly negative FST values reported as zero  and southeastern sites (TL) was particular high (FST = 0.446) (Table FST between YC and TL sites (20.5 km apart) was 0.444.Pairwise K = 2, suggesting that there were two distinct genetic clusters around the Sichuan Basin , with the SF and YJ populations clustering separately from the remainder. The East cluster showed no clear subdivisions or evidence of differentiation among samples.The STRUCTURE analyses using the minimum dataset revealed a clear peak of Evanno's delta of n Figure . Under tK = 3 results in STRUTURE  revealed three distinct clusters for the 12 populations corresponding to the West1 , West2 (SF and YJ), and East  lineages Figure . The fir Figures  and 2a.w = 47%), (b) from the ancestor of the East group into XY (w = 29%), and (c) from YC into QCS  occurred within populations . The AMOVA results also suggested that there is strong genetic isolation between the East, West1, and West2 groups  values and the straight‐line geographic distances between all sites  was 78,864  for West1, 722,318  for West2, and 757,511  for East. The ancestor of all lineages  was 850,047 before divergence at TA0 . Migration probability from West1 into West2  was the highest, but the reverse was low , as was migration from West1 into East  and the reverse . Overall migration probabilities between West2 and East were very low, but historical migration probabilities were not asymmetrical, with migration from ancestors of West lineage into East at 4.16e−07 (95% CIs: 2.52e−07–1.09e−06) and the reverse at 1.89e−07 (95% CIs: 1.22e−07–2.56e−07)  generations ago, corresponding to 15.08 Ma (95% CIs: 14.17–15.99 Ma with a generation time of 15 years). The second divergence time between West1 and West2 sublineages occurred 474,808  generations ago, corresponding to 7.12 Ma (95% CIs: 6.94–7.31 Ma). The current effective population size  based on RAD‐seq data, allowing investigation of its distribution patterns and evolutionary history around the Sichuan Basin and the processes that may have influenced their formation. Coalescent modeling supported initial divergence into East and West lineages, with subsequent divergence within the West sublineages, likely coinciding with the intensifications of the East Asian monsoon during the middle and late Miocene, respectively. This supports the hypothesis that the development of the East Asian Monsoon notably impacted intraspecific divergence and population dynamics. Further investigations using the ring distance of the IBD patterns suggested that extant P. zhennan populations displayed a ring‐shaped distribution around the Sichuan Basin, supporting the hypothesis that the Sichuan basin may have served as biogeographic barrier  Koidz. generally only travel about 4 km . Levels of gene flow as suggested by estimated FST among these sublineages indicated higher levels of genetic connectivity between these clusters. Cline analysis revealed sharp genetic changes between clades and slow genetic changes within clades  Iljinsk. , with subsequent divergence within the West clade during the early late Miocene (7.12 Ma). Similar Miocene‐aged patterns of deep intraspecific divergence have also been reported for two Chinese tree species: P. zhennan during the middle Miocene. First, fossils attributed to Phoebe have been reported from the Paleocene of the Northeast India . Third, it takes 10–15 years from seed to first flowering in P. zhennan (http://www.nfgrp.cn/), so a generation time of 15 years is both relatively conservative and similar to other long‐lived Lauraceae   and again after the initial intensification of the East Asian monsoon at ~15 Ma.This study also provides an opportunity to explore the impact of Miocene climate change and tectonic events on the phylogenetic structure of plants in subtropical China. The divergence time between the East and West clades during the early middle Miocene corresponds closely to the initial intensification of the East Asian monsoon at ~15–13 Ma  Ching correlates with precipitation brought by the summer monsoon and its radiation matches the initial intensification of the East Asian monsoon ~15 Ma  in southwestern China revealing intraspecific species divergence ~9.6 Ma  are very sensitive to winter temperatures and will die at temperatures below −10°C  M. Cheng (Berberidaceae); Guan, Fu, Qiu, Zhou, & Comes, P. zhennan S. Lee & F. N. Wei (Lauraceae)   . The lack of genetic assimilation between the two groups is particularly evident in populations QCS and YC. Both populations are geographically close to populations belonging to the other genomic group, yet show little sign of genetic introgression  occur in regions where the human disturbance such as fengshui forestry and tree farming greatly limits available habitat in natural reserves. These reduced habitats can also severely limit gene flow and seedling establishment due to habitat fragmentation and anthropogenic disturbance, a situation that has been observed in case studies of other Chinese Lauraceae such as Phoebe bournei (Hemsl.) Yang  Koidz.  and infer its demographic history. We found that P. zhennan displays a pattern of low level of genomic diversity within populations, coupled with three distinct lineages  around the Sichuan Basin, suggesting a long evolutionary history back to the middle Miocene. Geographic isolation‐by‐distance and the historical intensification dynamics of the East Asian monsoon appear to have shaped diversification within P. zhennan. These results thus have the potential to establish effective and efficient strategies for the conservation of this endangered species and to improve our understanding of the origin and evolution of plant biodiversity in subtropical China. Coupled with previous research, this study suggests that the East Asian monsoon and geographic distance are important, ongoing influences on the evolution of the floras of subtropical China and potentially East Asia more generally.This study used population genomics to evaluate genomic diversity and genetic structure in an endangered plant species ; methodology ; resources ; software ; visualization ; writing – original draft . Xin Ding: Data curation . Lang Li: Conceptualization ; funding acquisition ; project administration . Hui Ma: Methodology (supporting). Xiu‐Qin Ci: Supervision (supporting); writing – original draft (supporting). Marlien van der Merwe: Writing – original draft . John G. Conran: Writing – original draft . Jie Li: Funding acquisition (lead); project administration (lead); supervision ; writing – original draft .Supplementary MaterialClick here for additional data file.


Nezara viridula Linnaeus has been recorded from numerous host plants and has two globally distributed mitochondrial (mtDNA) lineages. These mtDNA lineages co‐occur in few locations globally, and the consequences of their divergence and recent secondary contact have not been assessed. We present evidence that both mtDNA lineages of N. viridula are present in Australia and their haplotype groups have a mostly separate distribution from one another. The north‐western population has only Asian mtDNA haplotypes, and the population with an eastern distribution is characterized mostly by European mtDNA haplotypes. Haplotypes of both lineages were detected together at only one site in the north of eastern Australia, and microsatellite data indicate that this secondary contact has resulted in mating across the lineages. Admixture and the movement of mtDNA haplotypes outside of this limited area of overlap has not, however, been extensive. Some degree of mating incompatibility or differences in the climatic requirements and tolerances of the two lineages, and perhaps a combination of these influences, might limit introgression and the movement of individuals, but this needs to be tested. This work provides the foundation for further ecological investigation of the lineages of N. viridula, particularly the consequences of admixture on the ecology of this widespread pest. We propose that for now, the Asian and European lineages of N. viridula would best be investigated as subspecies, so that “pure” and admixed populations of this bug can each be considered directly with respect to management and research priorities.The presence of distinct evolutionary lineages within herbivorous pest insect taxa requires close attention. Scientific understanding, biosecurity planning and practice, and pest management decision‐making each suffer when such situations remain poorly understood. The pest bug  The colour morph , either by removing a leg and extracting with 20% Chelex solution (Bio‐Rad) or dissecting out flight muscle tissue for salt extraction . The nymphs of N. viridula have limited mobility and are gregarious for some time after hatching from the egg mass  mitochondrial gene region was PCR‐amplified using primers LCO1490 and HCO21980  (GenBank accession: KP207595.1) was included as the outgroup for the analysis.A phylogenetic analysis was performed on unique sequences from a 557‐bp fragment of the more usual COI barcoding region for 519 sequences, which included trimmed sequences from this study. A comparison was also made between sequences from this study and shorter sequences from the Kavar et al.  data setN. viridula from each host plant and site combination. Primers for both genes were developed de novo using Primer3  gene regions were also sequenced as previous studies used only mtDNA gene regions, and the evolutionary history of mtDNA is frequently not the same as nDNA  using the Illumina MiSeq platform. Paired end reads (250 bp) were merged using FLASh 1.2.7  using the mantel.randtest function in the ade4 package 1.7  in populations representative of one or both lineages. Some of the 12 loci used to genotype Australian N. viridula showed significant departures from HWE, even after sequential Bonferroni correction within loci. In each case, this departure from HWE was not observed in all populations. No loci showed evidence for linkage disequilibrium. Two of the 12 loci, NEZA05 and NEZA10, had higher null allele estimates than all other loci, and although neither locus had average null allele estimates >10% across populations, these same two loci showed the most frequent departures from HWE . The analysis, most importantly, shows the discordance between the microsatellite and mtDNA data in eastern Australia, with gene flow between individuals with mtDNA belonging to both lineages  versus Kununurra is 0.265, Table 2 values of 0.67 for all populations and 0.57 when the north western populations were excluded from the analysis . Instead, individual‐based clustering analyses (STRUCTURE and PCA) were used to infer that no host‐associated genetic structure was evident. The G, O, F and R colour morphs  data from insects collected at Bowen  all regions analysed together, and b) across the eastern regions only, but these relationships were both nonlinear Figure . The sig4.2N. viridula are ecologically differentiated with respect to one another is still unclear and requires experimental investigation. The genetics results we present provide the framework from which sound ecological tests can be designed and conducted in Australia. Some of the differences documented across N. viridula populations and across localities  mean longevity was further reduced to 8.6 days . Whether these parasitoids have not dispersed to the north‐western region, are not climatically suited to the region or are ineffective at parasitizing Asian lineage bugs remains to be investigated.The possibility of climatic differences between the lineages has serious consequences for the geographic range of 4.4N. viridula should treat the Asian and European lineages of N. viridula independently so that questions about the ecology of these lineages can be resolved fully and ecological tests can be structured according to the genetic background of each population  can be difficult to discern. This point is illustrated by the situation that we have uncovered in  Clarke, . ClarifiThere are no competing interests to declare.All authors designed the research. DRB conducted the sampling, designed the primers, performed the laboratory work and analysed the data. JPH performed the next‐generation sequencing. All authors contributed to the interpretation and writing the paper.https://doi.org/10.14264/uql.2019.6).GenBank accession numbers were assigned to all sequences generated during this study . All microsatellite genotypes and individual gene sequences are hosted at UQ eSpace (Supplementary MaterialClick here for additional data file.


Myotis chiloensis), has garnered little attention so far. The species has a north-south distribution of c. 2800 km, mostly on the eastern side of the Andes mountain range. Use of extended torpor occurs in the southernmost portion of the range, putting the species at risk of bat white-nose syndrome, a fungal disease responsible for massive population declines in North American bats. Here, we examined how geographic distance and topology would be reflected in the population structure of M. chiloensis along the majority of its range using a double digestion RAD-seq method. We sampled 66 individuals across the species range and discovered pronounced isolation-by-distance. Furthermore, and surprisingly, we found higher degrees of heterozygosity in the southernmost populations compared to the north. A coalescence analysis revealed that our populations may still not have reached secondary contact after the Last Glacial Maximum. As for the potential spread of pathogens, such as the fungus causing WNS, connectivity among populations was noticeably low, especially between the southern hibernatory populations in the Magallanes and Tierra del Fuego, and more northerly populations. This suggests the probability of geographic spread of the disease from the north through bat-to-bat contact to susceptible populations is low. The study presents a rare case of defined population structure in a bat species and warrants further research on the underlying factors contributing to this. See the graphical abstract here. https://doi.org/10.25387/g3.12173385Despite its peculiar distribution, the biology of the southernmost bat species in the world, the Chilean myotis ( Pseudogymnoascus destructans, which infects insectivorous bats during the hibernation period at latitudes where prey are not widely available during winter .Transmission of infectious diseases has garnered attention as one of the greatest risks to human, agriculture and wildlife health over the last decade . Previoud by WNS  and can P. destructans is native to Eurasia, where it has a large geographic range, with transmission to North America likely facilitated by humans  is the most Southerly distributed species of bat in the world, together with the southern big-eared brown bat , and migratory species such as T. brasiliensis capable of carrying spores across large distances, there is a serious need to better understand the population structure of Patagonian hibernatory bat species before WNS spreads to the region. The lack of knowledge on the extent of migration and mixing, and life history traits in general, means that research in this area is now urgent and essential  from two localities: Chicauma, Metropolitana region (33 °S 70 °W) and Karukinka Reserve, Tierra del Fuego (64 °S 78 °W) respectively  which was stored at -20° until analysis.To describe population genetic structure in We divided samples into four populations according to their geographic origin, with sub-regions within each group to assist in further analyses. Sampling locations are presented in The amount of DNA in the final solution of each sample was tested and quantified using the Thermo Scientific Nanodrop spectrophotometer, giving a result for the amount of DNA in ng/μL. Samples were frozen between DNA extraction and analysis.P.destructans load by qPCR was completed as described previously in Quantification of We sequenced 66 individuals in total. Duplicate samples from 30 individuals were additionally sequenced to estimate repeatability and error rate of the called genotypes. DNA was prepared for genotyping-by-sequencing using a double digestion RAD-seq method as described in As the amount of DNA available may often be very limited in studies where preserved samples from the rabies laboratory are utilized, we wanted to estimate the effect of initial DNA concentration to the resulting read coverage. We compared the total read coverages of the replicate samples with Pearson’s correlation.M. lucifugus genome BioProject ID: PRJNA16951, using BWA mem 0.7.17 with parameters -B 3 -O 5 -k 15. After mapping the reads against the reference, we used SAMtools v. 1.4 and the associated bcftools for calling genotypes for SNPs and for filtering SNPs based on minimum of 40% of the samples genotyped, at least eight alternative alleles detected and SNP quality ≥20 (bcftools filter). We further filtered the SNPs based on exactly two alleles detected and excluded SNPs with particularly low (≤5) or unusually high (≥125) mean coverage based on visual inspection of the mean coverage distribution.The resulting fastq reads, separated by barcode for each sample, were quality-controlled with FastQC v. 0.11.8 and low-quality bases were trimmed with ConDeTri v. 2.3 with parameter minlen = 30 (min. length of a trimmed read) followed by adapter-trim with Cutadapt v. 1.10 for Illumina universal adapters from the end of the reads . Then, reads were mapped against For the final SNP dataset, which only included unduplicated samples, we performed principal component analysis implemented in prcomp function of R stats package v. 3.5.2, and calculated Euclidean genetic coordinates for each individual from PC1 and PC2. The four pre-determined ancestral populations based on the sampling regions of each individual were confirmed by hierarchical clustering of the Euclidean distance, calculated from PC1 and PC2. Individuals clustering to a neighboring population were assumed to have dispersed from their natal populations and were reassigned for the later analysis. We further investigated the relative contributions of the ancestral populations inhabiting regions 1-4 in the present-day nucleotide variation using ADMIXTURE  using a Mantel test with all possible permutations, and a linear model to identify individuals with unusually high or low genetic differentiation. We then studied the systematic differentiation of the individuals sampled in different regions by assessing the differences of the residual distributions of each of the four populations from zero using t-tests and Bonferroni-correction of the P-values.We estimated Isolation-by-distance with two methods: a Mantel test with complete permutations and a linear model FDR≥0.05) in each of the four study regions and compared the observed values to the mean expected heterozygosities using inbreeding coefficient F, calculated as the difference between expected and observed heterozygosity divided by expected heterozygosity . Specifically, we evaluated support for two alternative models . The first model, representing our null hypothesis of no secondary contact among populations, specified four distinct lineages  corresponding to the populations inhabiting the four geographic regions sampled in the present study. These diverged from each other at the time points T1, T2 and T3 as presented in Figure S6A, and exchanged no migrants. Region 1 was used as the lineage from which the other three populations emerged, as this was determined to be the population which is closest to the ancestral M. chiloensis population. The second model, representing our alternative hypothesis of secondary contact among populations, was identical to the first model with the exception that symmetric migration was present between population pairs region 1-2 and region 3-4, and asymmetric migration was implemented from region 2 to region 3 . In addition to identifying the model that was best supported by our data, we also estimated divergence times  and effective population sizes  for the four modeled lineages, as well as migration rates .To formally test whether any of the studied populations experienced secondary contact following glaciation, we implemented a demographic analysis using the software fastsimcoal2  from the fastsimcoal2 runs which yielded the highest maximum likelihood for each model and used these values for model comparison. Finally, we extracted parameter estimates from the best run of the most supported model and calculated 95% confidence intervals based on 100 parametric bootstrap replicates, as described in https://github.com/tiinasa/mchilorad. Supplemental material and graphical abstract available at figshare: https://doi.org/10.25387/g3.12173385.The RAD sequencing reads were deposited at NCBI SRA under BioProject ID PRJNA596389. R scripts are available at Ninety-one of the 96 samples  had reads matched with a barcode. Of the obtained genotypes, 54846 were biallelic and used in the later analysis, while we excluded 88882 non-variable  variants and 1708 variants with more than 2 alleles. After filtering, the mean SNP coverage ranged from 0.5 to 257.0 . We excluded tags with <5 or >125 mean coverage, leaving 47079 tags. The average rate of missing SNPs among the final unique samples was 6.2%, ranging from 0 to 24%.61 = 2.8178, P = 0.0065, Figure S2 A, Figure S3 A-B). In contrast, we found strong and negative association between mean read coverage after sequence assembly and the number of missing genotype calls . Furthermore, read coverages were very similar between the technical replicate samples , allowing us to omit “B” samples (replicated). The removal of the biological replicates was conducted to minimize the possible SNP calling bias induced by some samples having approximately twice the amount of sequence data compared to the others, if replicate samples had been combined. Identical genotype calls ranged from 85.6 to 96.9% with an average of 94.2% identical genotype calls , depending heavily on read coverage . Although the correlation between the initial DNA concentration and identical genotype calls between biological replicates was significant , this seemed to mainly be due to two outlier observations with both very low concentration and repeatability.The correlation between input DNA concentration and the resulting mean per-sample read coverage was only moderate  to 0.113  than the permuted FST distributions, with the 95% confidence intervals of the null distributions between 0 and 0.0205. Both the Mantel test approach and linear modeling between genetic distances  and geographical distances (latitude/longitude coordinates converted to distances in kilometres) strongly suggested that we reject the null hypothesis of geographic and genetic distances being unrelated. For the between-population comparisons with FST, we calculated Mantel statistic r = 0.9497 (P = 0.05) and R-squared estimate of 0.8773  . Also, for the between-individual distances, the observed Mantel statistic r = 0.944 (P = 0.001), and R-squared estimate 0.943  from the linear modeling, suggesting that genetic and geographic distances are strongly positively associated  and 4  were marginally smaller than 0, while the residuals of individuals in regions 2  and 3  were significantly larger than 0  in the southern regions than in north, except for the two northernmost regions (region 1 vs. region 2), where a statistically significant difference was not observed (P < 0.05), which may be caused by within-region population structure (P < 0.05) observed in all comparisons except in region pairs 1-2 and 3-4  received the highest AIC support (Table S3). Parameter priors and estimates, together with their 95% confidence intervals, from the best model are reported in Table S4.M. chiloensis, using individual-based approach with genome-wide markers. We found that geographic distance within the range of the species are reflected in its population structure. Although we found a clear and robust population structure among sampling sites, population structure is correlated with geographical distance, even though populations are separated by ice fields, mountain ranges and stretches of open water. This has implications for the protection of populations that may be susceptible to WNS. Our results also show that the highest genetic variability in the species is at the southern extent of its range.Our results present the first assessment of population structure in the widely distributed bat species, Myotis, with shorter dispersal distances  from South America, ST -values are high, suggesting isolation of the populations. By contrast, our analysis for the relative contributions of ancestral populations suggests mixing of populations. One potential explanation for this apparent discrepancy is that we derived site frequency spectra from a rather small number of individuals, which may carry a signal of migration that is not strong enough to allow a model that includes secondary contact to be favored over a simpler model without migration.P. destructans via one host to another was very rapid in North America  are isolated from their mainland counterparts. To our knowledge, this is also the only population to use extended torpor, a prerequisite for the propagation of P. destructans and the onset of WNS ; M. ch. arescens from 29°S to 39°S; and M. ch. chiloensis from 39°S to 53°S (M. chiloensis.The observed distribution of Antartic . In thison range . It has  to 53°S . That cl to 53°S  and leveP. destructans or another epizootic in the future could spread depends largely on the population structure and connectedness of hosts (The results highlight the importance to assess the population structure which may limit the spread of white-nose syndrome disease. Whether


Anopheles gambiae and An. arabiensis are major malaria vectors in sub-Saharan Africa. Knowledge of how geographical factors drive the dispersal and gene flow of malaria vectors can help in combatting insecticide resistance spread and planning new vector control interventions. Here, we used a landscape genetics approach to investigate population relatedness and genetic connectivity of An. gambiae and An. arabiensis across Kenya and determined the changes in mosquito population genetic diversity after 20 years of intensive malaria control efforts. We found a significant reduction in genetic diversity in An. gambiae, but not in An. arabiensis as compared to prior to the 20-year period in western Kenya. Significant population structure among populations was found for both species. The most important ecological driver for dispersal and gene flow of An. gambiae and An. arabiensis was tree cover and cropland, respectively. These findings highlight that human induced environmental modifications may enhance genetic connectivity of malaria vectors. Anopheles gambiae s.l. are the primary vectors of human malaria in sub-Saharan Africa, a disease responsible for 405,000 deaths worldwide annually, with around 90% occurring in Africa1. While the species commonly occupy similar ecological niches, An. gambiae s.s. (hereafter referred to as An. gambiae) are generally associated with more humid environments, whereas An. arabiensis have a higher tolerance for drier environments3. Another notable difference between the two species is that An. gambiae are highly anthropophagic5, whereas An. arabiensis are more catholic in their feeding behavior6. Since mosquitoes primarily disperse to seek blood meals and oviposit7, these differences in habitat and feeding preferences may result in ecological variables differentially driving the dispersal patterns of these two malaria vectors. These differences potentially lead to a complex system influencing malaria parasite spread. Knowledge of how geographical factors influence the dispersal of malaria vectors can help in efforts to contain insecticide resistance, planning effective vector control interventions, and identifying potential areas susceptible to parasite re-introduction from infected mosquitoes following antimalarial interventions8.An. arabiensis populations, neither physical barriers nor geographic distance have been identified as factors responsible for An. arabiensis population structuring12. Likewise, geographical distance alone does not appear to be a barrier to gene flow among populations of An. gambiae, as Lehmann et al.13 found high gene flow between populations in Kenya (East Africa) and Senegal (West Africa). However, An. gambiae populations were found to be highly differentiated between western Kenya and eastern Kenya12. The eastern arm of the Great Rift Valley, which bisects Kenya, has been speculated to be the cause of genetic differentiation in An. gambiae populations due to its surrounding low temperatures and arid conditions making it inhospitable to agriculture, and as such, lacks human settlements14. Since the eastern arm of the Great Rift Valley is characterized by several attributes, such as low temperatures, low precipitation, as well as low human population density12, these factors cannot be disentangled for driving population structure of An. gambiae using traditional population genetics.Organism dispersal patterns and population connectedness can be inferred from measuring genetic relatedness among populations or gene flow. While studies have reported genetic differentiation between 15. Broadly, the approach involves inferring population movement from the distribution of genetic markers, quantifying the distribution of ecological factors hypothesized to drive dispersal, and statistically testing the relationships between genetic variation and landscape heterogeneity17. These inferences enable us to identify potential hotspot areas of disease movement for targeted public health interventions and containment of disease and drug and insecticide resistance8. For example, this approach has been used to identify dispersal corridors for Ae. albopictus mosquitoes in the United States, which were found to be primarily highways and non-forested areas18. Moreover, landscape genetics has been used to study infectious diseases, including chronic wasting disease19, rabies21, hantavirus22, H5N1 avian influenza23, and malaria25. The objective of this study is to use a landscape genetics approach to test the hypothesis that genetic connectivity of An. gambiae and An. arabiensis is influenced by environmental, landscape, or social factors, as opposed to geographic distance alone. By testing relationships between population genetic structure of malaria vectors and ecological factors, we can parse out confounding factors and determine the importance of key variables influencing malaria vector dispersal15.However, using a landscape genetics approach, we can test the impacts of ecological variables on organism dispersal to parse out the importance of key variables influencing malaria vector dispersalAnopheles gambiae s.l. larvae were collected in 2014–2015 from thirteen sites across Kenya, which fall within four distinct geographical areas: western Kenya lowlands, western Kenya highlands, Great Rift Valley, and coastal Indian Ocean ; whereas, An. gambiae specimens included in analyses originated from six populations in western Kenya only . To assess genetic diversity and structure of vector populations, six microsatellite loci were genotyped in An. arabiensis and five microsatellites were genotyped in An. gambiae specimens , ranged from 0.461 in an Indian Ocean coastal site to 0.723 in an Indian Ocean coastal study site  ranged from 3.46 in an Indian Ocean coastal site to 6.24 in a western lowland site  compared to the western Kenya lowland sites   for both species. There was no evidence indicating linkage disequilibrium at any locus across all population for An. arabiensis (P > 0.05). By population, there was significant linkage disequilibrium in An. arabiensis detected at two study sites in western Kenya , one study site in the Great Rift Valley (MT: AG3H249/AG2H143), and two study sites in Indian Ocean coastal Kenya . For An. gambiae, linkage disequilibrium was detected in two locus pairs across all populations . By population, there was significant linkage disequilibrium in An. gambiae at three study sites in the western lowlands  and one study site in the western highlands (EE: AG2H46/29C1). Since all of the locus pairs observed to be in linkage disequilibrium for both species do not occur in the same chromosomal region . In comparison to previously published HE values for An. gambiae samples collected in 199426, overall HE was significantly lower in 2014 .For For An. arabiensis, we identified three clusters consistently across ten runs in Structure . Variation within populations  and variation occurred among populations within groups  were also significant. For An. gambiae, we identified two clusters consistently across ten runs in Structure . Variation within populations  and variation occurred among populations within groups  were significant. Based on a linear mixed effects model with maximum likelihood population effects (MLPE), populations did not conform to an isolation-by-distance model for either species  occurred between populations across regions, as well as between populations within regions  were visualized Fig. .Analysisons Fig. . The GreST and DPS. Since the results from both analyses did not vary substantially, FST analyses are presented here, and DPS analyses are presented in the supplementary material (Supplementary Table P < 0.0001 for both species). For An. arabiensis, cropland was the top single-surface model in explaining population genetic structure of An. arabiensis , second lowest average rank (1.891), and highest percentage for being the top model across bootstrap iterations (40.3%).We used landscape genetics to test for associations between landscape factors and gene flow between populations. We created landscape resistance raster files for the following variables, which we hypothesized to potentially influence gene flow of the studied malaria vector species: annual mean temperature, annual precipitation, percent tree cover data, presence or absence of croplands or cropland/natural vegetation mosaics, human population density, and road proximity Table . Landscais Table . The croAn. arabiensis, cropland, areas with croplands or cropland/natural vegetation mosaics had a low resistance to gene flow. Average temperature was the next highest performing model. An average temperature of 15.9 °C had the lowest landscape resistance to gene flow. Areas with an average temperature exceeding 23.3 °C had the highest landscape resistance to gene flow . For the third highest performing model, landscape resistance to gene flow was lowest in areas with annual precipitation 1530.8–1914.8 mm  and highest in areas with annual precipitation less than 1230.8 mm and greater than 1970.8 mm. In the highest performing model for An. gambiae, the lowest landscape resistance values occurred in areas with 9.2–38.2% tree cover and the highest landscape resistance values occurred in areas with less than 4.9% tree cover and greater than 61.2% tree cover. For the second highest performing model, the lowest landscape resistance occurred in areas with an average annual temperature between 18.9 and 22.6 °C and the highest landscape resistance values occurred in areas with an average temperature less than 16.1 °C and greater than 23.0 °C. For the third highest performing model, the lowest landscape resistance to gene flow occurred in areas with 1401.5–1890.8 mm annual precipitation and the highest landscape resistance to gene flow occurred in areas with less than 1017.5 mm and greater than 1963.0 mm annual precipitation. Our visualization of gene flow between study sites based on the highest performing models, cropland for An. arabiensis and tree cover for An. gambiae, identifies likely pathways for gene flow between study sites  in An. gambiae from 199426 to 2014 (this study), which were collected from neighboring populations within the Lake Victoria basin area of western Kenya. For An. arabiensis, we did not observe a comparable reduction in HE in between similar time points, 199612 to 2014 (this study). Notably, we do not report on diversity from within the 18 to 20-year period, so we cannot describe how diversity may have fluctuated within this time frame. With that said, these findings of reduced HE in An. gambiae are consistent with a population decline, which has been observed throughout much of East Africa in response to mass distribution and increased coverage of insecticide-treated bed nets (ITNs)32. Conversely, the maintenance of HE in An. arabiensis suggests that An. arabiensis populations have remained relatively more stable despite the high coverage of ITNs in Kenya. Anopheles gambiae are known to be more susceptible to malaria interventions than An. arabiensis due to their preference for feeding on humans and resting indoors5. Whereas An. arabiensis are more catholic in their feeding behavior, taking blood meals from both human and non-human hosts, especially cattle35, as well as more commonly feed and rest outdoors37. These findings highlight the role that An. arabiensis may play in maintaining residual malaria transmission in sub-Saharan Africa38 and the need for alternative intervention strategies to target this species. Moreover, understanding how ecological features influence An. arabiensis dispersal will likely become increasingly important to interrupting residual malaria transmission.In this study, we observed a significant reduction in diversity  and high (> 61%) tree cover were found to be gene flow barriers for An. gambiae in western Kenya. Whereas an intermediate tree cover of 9–38% was associated with enhanced gene flow for An. gambiae. This finding is consistent with a previous study in Kenya, which found that a canopy cover of 26% was associated with the presence of the An. gambiae complex, while a canopy cover of 44% was associated with the absence of the An. gambiae complex42. Moreover, this finding may also be consistent with the broad-scale population structuring observed across Africa14, as unlike with the western arm of the Great Rift Valley, a wide swath of land to the East of the eastern arm of the Great Rift Valley is characterized by short vegetation and a tree cover < 5% . Potential corridors for An. arabiensis are areas with cropland or cropland/natural vegetation mosaics. These findings underscore that human induced land cover and land use modifications may enhance connectivity of these species. Specifically, agricultural deforestation may promote dispersal and gene flow for both species. Understanding the factors that limit and promote movement (gene flow) of malaria vectors can help us to more effectively deploy interventions to maintain vector control by identifying areas susceptible to invasion from neighboring mosquito populations. Moreover, this knowledge can be leveraged to help limit the spread of malaria parasites by mosquitoes from nearby areas, as well as contain insecticide resistance8. Finally, knowledge of factors influencing malaria vector dispersal are likely to become increasingly important as malaria transmission becomes increasingly heterogeneous46.To conclude, we found that corridors for An. gambiae s.l. larvae were collected between May 2014 and January 2015 from thirteen sites across Kenya  assay49.An. gambiae and five loci were selected for An. arabiensis based on evidence of polymorphism in previous studies, reliable amplification, and distribution across chromosomes , 0.5 µl of 10 µM primer (forward primer with M13 tail), and 1 µl of DNA template. Thermocycling conditions for An. gambiae and An. arabiensis were as follows: initial denature of 94 °C for 3 min, followed by 35 amplification cycles of 94 °C for 30 s, annealing temperature  for each loci and then compared. We used paired t-tests to assess statistical significance between expected heterozygosity in pre-ITN scale-up populations (1994/1996) and post-ITN scale-up (2014) populations at matching loci. In addition, for populations from this study (2014), we tested for deviation from Hardy–Weinberg equilibrium and linkage disequilibrium (LD), independence of microsatellite loci, as well as estimated the inbreeding coefficient in Genepop 4.254. We also estimated allelic richness at each study site in the R package diveRsity55.To test whether population genetic diversity has been altered over the past two decades in the face of intense malaria vector control campaigns, namely the increase in use of insecticide-treated bednets (ITNs)56. We tested K = 1–7 for An. gambiae and K = 1–10 for An. arabiensis, with ten replicates for each K-level, an initial burn-in of 100,000, and then 500,000 Monte Carlo Markov Chain iterations. The program was run using an admixture model. ∆K was used to detect the number of K (clusters). The output data for the best estimate of K were analyzed using CLUMMP to calculate the mean cluster membership coefficients across multiple runs57. An analysis of molecular variance (AMOVA) was conducted in Arlequin to test for significance of genetic differentiation52. To test for isolation-by-distance, we used linear mixed effects models with the maximum likelihood population effects58 to fit pairwise geographic distance to FST measured in Genepop 4.254. Gene flow frequency among populations was estimated for each species in Migrate-N v3.7.2 with the Brownian motion model and Bayesian inference search strategy59. Bidirectional gene flow between all pairwise population comparisons was considered. Four independent runs were conducted with a burn-in of 104 steps, sampling increment of 100 steps, and 5,000 recorded steps in each chain for a total of 2 × 106 visited parameter values.We estimated population structure using STRUCTURE v. 2.3.4, which uses a Bayesian algorithm to group samples into genetically distinct clusters60. Hence, landscape resistance surfaces were created based on factors hypothesized to prevent or promote gene flow between sites. Since mosquitoes primarily disperse to seek blood meals and oviposit, as well as have physiological constraints regarding development and desiccation, we selected variables which influence these phenomena, i.e., the availability of blood meals and oviposition sites  and environmental suitability. Further, we selected variables that did not closely correlate with each other, which can lead to erroneous model selection results. All pairs of variables had a Pearson correlation coefficient <| 0.6 | 63, cropland from NASA (MOD12Q)63, human population density from WorldPop64, and road proximity from OpenStreetMap  values indicated that FST values obtained from each individual locus positively correlates with overall FST for both species, but loci contribution to overall FST was not even, particularly with regard to the 29C1 locus for An. arabiensis  was used to compare model fitness to genetic data. We excluded eastern Kenya sites from landscape genetic analysis for Anopheles arabiensis due to the biases uneven sampling can introduce in analysis, as population sampling was not evenly distributed across the country69.We used the R package ResistanceGA to unbiasedly optimize resistance surfaces to our genetic dataSupplementary Information.


Euptelea in China (24 E. pleiosperma populations) and Japan (11 E. polyandra populations) to elucidate their divergence and demographic histories, genome‐wide associations with current environmental variables, and genomic vulnerability to future climate change. Our results indicate that Late Miocene changes in climate and/or sea level promoted species divergence, whereas Late Pliocene uplifting in southwest China likely fostered lineage divergence within E. pleiosperma. Its subsequent range expansion into central/east (CE) China bears genomic signatures of climate‐driven selection, yet extant CE populations are predicted to be most vulnerable to future climate change. For E. polyandra, geography was the only significant predictor of genomic variation. Our findings indicate a profound impact of Late Neogene geological and climate change on the evolutionary history of Euptelea, with much stronger signals of local adaptation left in China than in Japan. This study deepens our understanding of the complex evolutionary forces that influence the distribution of genetic variation of Tertiary relict trees, and provides insights into their susceptibility to global change and potential for adaptive responses. Our results lay the groundwork for future conservation and restoration programs for Euptelea.The warm‐temperate and subtropical climate zones of East Asia are a hotspot of plant species richness and endemism, including a noticeable number of species‐poor Tertiary relict tree genera. However, little is understood about when East Asian Tertiary relict plants diversified, how they responded demographically to past environmental change, and to what extent their current genomic composition (and adaptive capacity) might mitigate the effects of global warming. Here, we obtained genomic (RAD‐SNP) data for 171 samples from two extant species of  Region (HMR) to central/east China, with populations occurring in isolated stands of MRF across a wide range of altitudes . By contrast, E. polyandra is restricted to south/central Japan where it occurs in similar habitats of lower altitude  , although it has long been recognized that they are at risk of loss of their MRF habitats  how they responded demographically to past environmental change; (c) to what extent historical, geographical, and/or climatic factors contribute to their current genomic variation; and (d) which populations of E. pleiosperma might be most vulnerable to future climate change. Hence, for comparison with our earlier study using plastid/nuclear DNA sequences and nSSR loci  framework  approach  climate scenarios  when and how the two extant species of 22.1Euptelea are diploid (2n = 28), small‐ to medium‐sized (c. 2–15 m), broad‐leaved deciduous trees with bi‐sexual, wind‐pollinated flowers that develop into winged fruitlets (“samaras”), dispersed by gravity, wind, and/or water  and 11 of E. polyandra , with 2–6 individuals per population  below 33 were replaced with an ambiguous base (“N”), and reads with more than 10% “N”s were discarded. Filtered reads of each individual were first assembled de novo into putative loci. For within‐sample clustering, sequences were clustered at 90% similarity. In order to ensure accurate base calls, only clusters that had a minimum depth of coverage ≥ 6 were retained. After clustering, error rate (E) and heterozygosity (H) were jointly estimated from the base counts in each site across all aligned clusters for each sampled individual  by Beijing Genomics Institute  using the restriction enzyme 7 Eaton, . Any RADl Lynch, , and the1 Edgar, . A final1 Edgar, , as this1 Edgar, . The remTo explore the effect of missing data (locus dropout or low coverage) and ensure enough SNPs for analyses, we assembled three data matrices with different minimums for sample coverage (the number of samples for which data must be recovered to include a RAD locus in the dataset): (a) the data matrix that includes all loci shared across at least 85 samples (“maximum” dataset); (b) the median data matrix that contains all loci shared across at least 120 samples (“median” dataset), and (c) the data matrix that includes all loci shared across at least 160 samples (“minimum” dataset). Following a previous study's suggestion  with and without filtering loci with MAFs < 0.01 using faststructure v1.0  was set to vary depending on the dataset. The most probable values of K for explaining population structure were determined by estimating the minimum value of K that accounts for almost all of the ancestry in the three datasets and maximizes the log marginal likelihood lower bound. In addition, for each of the three datasets, population structure was also investigated by discriminant analysis of principal components (DAPC) for Euptelea and each species, respectively, using the r package adegenet  and average expected and observed heterozygosities (Hexp/Hobs) were calculated for each population with n ≥ 5 using arlequin v3.5 . Five Euptelea populations  with small sample size (n < 5) were removed from all population‐level analyses of genetic diversity  were regressed against latitude and longitude, respectively, using the ggplot2, iswr, and scales packages implemented in r v3.3 , mean nucleotide diversity  across all 171 samples, as the two extant Euptelea species apparently underwent climate‐induced expansions : the simultaneous divergence of three regional groups  from a common ancestor .We used the coalescent‐based approximate Bayesian computation (ABC) implemented in r Figure a, and andiy‐abc  and E. polyandra. We tested three simple models of population size changes: (a) population growth following a constant population size (“expansion”); (b) expansion followed by shrinkage (“shrinkage”); and (c) expansion followed by shrinkage and a new expansion event (“expansion‐shrinkage‐expansion”)  Figure . We used2.5E. pleiosperma populations (n ≥ 5) and the eight E. polyandra populations (n ≥ 5), respectively. GDM is a nonlinear extension of matrix regression that models spatial patterns of pairwise genetic dissimilarity between sampling sites caused by pairwise site differences in environmental and geographic variables . To retain only the predictors that significantly contributed to the model in each GDM analysis, we employed a backward elimination procedure  and the eight E. polyandra populations (n ≥ 5)  Table , respect2.6E. pleiosperma and E. polyandra  shared by all populations and a population‐specific component (beta) shared by all loci. We ran the program bayescan with the following settings: 5,000 iterations; 20 thinning intervals; 20 pilot runs of length 5,000; 50,000 additional burn‐in; uniform distribution between 0 and 1; and a prior odd of 10 for neutral model. Positive values of alpha indicate diversifying selection, whereas negative values indicate balancing or purifying selection  were filtered to retain loci with q‐values below 0.001. For the hierarchical model in arlequin, 20,000 simulations were conducted with 100 demes per population, with the false discovery rate (FDR) set at 0.01. Loci bearing signatures of diversifying selection identified by both methods were segregated into an outlier matrix, and the remaining loci without outliers constituted the neutral dataset.We scanned the “minimum” dataset for outlier loci in E. pleiosperma (see Results), we calculated population allele frequencies in arlequin and used multiple linear regressions  values > 0.5 and significant correlation with at least one variable were considered “adaptive” loci  with an average read depth of 28.78 (range: 11.17–60.68) . Clustering of consensus sequences across all 171 samples by ipyrad yielded 29,494 informative sites (unlinked SNPs) for the “minimum” dataset, 89,158 for the “median” dataset, and 107,839 for the “maximum” dataset. After filtering loci with excess missing data within population, 18,182 (“minimum” dataset), 75,101 (“median” dataset), and 76,365 (“maximum” dataset) SNPs were retained, of which 51.70%, 48.71%, and 48.69% SNPs had a MAF ≤ 1%  Table . For eac% Figure , respect3.2n = 171), genetic structure analysis in faststructure , most populations located west versus east of the Sichuan Basin were assigned to clusters I (“southwest China”: SW) versus II ; as an exception, two populations from northwest of the basin  and a population from southeast of the basin (HP) clearly belonged to cluster II as well, while showing traces of admixture with the SW lineage  exclusively formed a distinct cluster (III). Separate faststructure analyses of E. pleiosperma and E. polyandra resulted in similar patterns. For each of the datasets, the DAPC for Euptelea  at K = 4 , and those of E. pleiosperma were also monophyletic (BP = 100%), with two subclades (each 100%) representing the SW versus CE lineages, respectively. Within the latter group, all samples from east of the Sichuan Basin (except for HP) occupied a nested position relative to those from the northwest (BM/LX) and southeast (HP). The AMOVA based on the neutral “minimum” dataset (Table E. pleiosperma (ΦST = 0.44) than in E. polyandra (ΦST = 0.13), and c. 69.74% of the total genetic variation resided among species (ΦCT = 0.70). In E. pleiosperma, the SW lineage showed much stronger population differentiation (ΦST = 0.27) than the CE lineage  within‐population genetic diversity than those of E. pleiosperma . Moreover, neutral within‐population estimates of π in this species significantly decreased with longitude , or between Hexp/Hobs and longitude . In E. polyandra, all three diversity measures  were independent of latitude and longitude .For the RAD‐SNPs from the three datasets with or without filtering loci with MAFs < 0.01 . For E. polyandra, although Scenario 3 (“expansion‐shrinkage‐expansion”) showed the highest posterior probability, Scenario 1 (“expansion”) was also found to have a high posterior probability  Ma, and the origin of E. pleiosperma's CE lineage (from within the SW lineage) at about the Late Pliocene, c. 3.96 (95% CI: 2.22–5.93) Ma (Table SW and CE lineages (see above) were estimated to have occurred at c. 4.24 (95% CI: 1.52–6.48) Ma and 3.43 (95% CI: 1.47–4.68) Ma, respectively  Ma, then experienced a long‐term (c. 2.50 Myr) reduction in population size (c. 8.5‐fold), and expanded again at the beginning of the Late Pliocene, c. 2.67 (95% CI: 0.83–4.65) Ma. By contrast, Scenario 1 indicated that the expansion of E. polyandra was estimated to have occurred at the Mid‐Pliocene, c. 3.88 (95% CI: 0.71–9.21) Ma  Table . TherefoMa Table , 4a. In ly Table , 4b. For3.4E. pleiosperma and E. polyandra, the GDM analysis explained, respectively, 63.90% and 81.35% of the deviance in spatial patterns of genetic (RAD‐SNP) turnover , indicating good fit of the models to the data. There were seven variables  that explained the observed genetic variation for E. pleiosperma, and the significant predictors were BIO7 , GEO , and BIO11   Table . By contor Table , indicat3.5bayescan detected 203 outlier loci in E. pleiosperma and only one outlier in E. polyandra. Using arlequin, 368 outlier loci were identified in E. pleiosperma and four outlier loci were identified in E. polyandra. In E. pleiosperma, 49 loci were identified as FST outliers by both programs but none in E. polyandra. At these loci, the SW lineage showed much higher average within‐population genetic diversity than the CE lineage . Across the species’ entire range, there was a significantly negative relationship between outlier‐derived π and longitude . Based on the MLR analysis, only six outliers qualified as “adaptive” loci by showing R2adj values > 0.5 and significant correlations (p < .05) with four temperature‐related variables, including temperature seasonality (BIO4), minimum temperature of the coldest month (BIO6), temperature annual range (BIO7), and mean temperature of the coldest quarter (BIO11) . By contrast, genomic vulnerability for E. polyandra was low across its range  within the SW lineage of E. pleiosperma from our RADseq data  and E. polyandra (Japan) at about the Late Miocene, c. 6.39 (95% CI: 3.90–8.92) Ma  and cpDNA phylogenies (c. 6.04 Ma) of Euptelea , the landbridge likely served as a migration corridor  identified the SW lineage as being ancestral to the CE group  likely served as a source area for the species’ colonization of central/eastern China. In turn, this would suggest that its ancestral range initially retracted to southwest China  rather than occupying large portions of mainland  China, as depicted in the poor‐fitting vicariant scenario  Ma  speciation and associated changes in landscape and environmental conditions, as reported for numerous other plant and animal species from the HMR and adjacent areas  Ma; Table E. pleiosperma out of the HMR. In support of this, we found a significant decrease of within‐population genetic diversity (in terms of π) with longitude  and southeast (HP) of the basin . In sum, therefore, the present data suggest that the CE lineage of E. pleiosperma originated in the HMR from within the SW lineage but then expanded its range eastward, predominantly along the Yangtze River valley and its tributaries. Similar scenarios of southwest‐to‐east migration have also been invoked for other tree species from China  largely represent genetically cohesive units, with little evidence for admixture at RAD‐SNPs  Ma and c. 3.88 (95% CI: 0.71–9.21) Ma for Scenario 3 and Scenario 1, respectively. However, the ABC point estimates of expansion time and population size changes for E. polyandra have to be treated with caution, as our data could not provide reliable posterior distributions for these parameters due to lack of power , indicating that E. polyandra experienced a strong increase of Ne from c. 0.5 Ma onwards   shaped the spatial distribution of genomic variation in this species  structure of s Figure . Howevern Figure . In addia Figure . This paa Figure .E. pleiosperma, of the 49 outlier loci identified by both FST outlier approaches, only six were inferred to be under diversifying selection using MLR analysis. They were significantly associated with four temperature‐related variables   significantly decreased with longitude  Table . Neverthe Figure , suggestCE lineage are at the greatest risk of climate‐induced extinction, followed by those of the SW lineage, and E. polyandra  that are adapted to different ecological niches and thus should be managed as two separate conservation units. As the locally adapted but genetically impoverished populations of the CE lineage are facing a particularly high risk of losing more genetic variation due to future climate change and habitat loss, conservation measures are urgently required. Broadly, therefore, our study highlights the significance of combining genomics with environmental data when assessing the impact of future warming on East Asia's Tertiary relict flora by quantifying the ecological factors that have produced genomic variation in this system.To our knowledge, this study is the first that uses a multidisciplinary approach combining phylogenetics, phylogeography, and population‐ecological genomics to unravel the historical demography and climate‐related adaptation of an East Asian Tertiary relict genus, along with predictions about its “genomic vulnerability” to future climate change. The present data seem to suggest that the more complex geological history and greater environmental  heterogeneity of subtropical China more readily promoted lineage diversification and a signal of adaptation in a Tertiary relict tree than was the case in Japan. This is evidenced by the deep intraspecific lineage divergence and the strong signal of local adaptation in Supplementary MaterialClick here for additional data file.