Rhopalosiphum padi and Rhopalosiphum maidis are two common phloem-sucking pests on maize which can even transmit viruses  leading to severe yield losses of maize. Population genetic studies provide information about how much ecological and genetic divergence has occurred among many near and distant populations. We investigated the genetic diversity of both Rhopalosiphum aphids collected from maize in China and Europe, and we found that different populations of R. maidis showed low genetic variation, indicating a high level of gene flow of both nuclear and mitochondrial genes in this aphid. However, the mitochondrial gene of R. padi exhibited obvious genetic differentiation between Chinese samples and European samples. In conclusion, the domestic populations of both R. padi and R. maidis showed low genetic diversity, and the long distance between China and Europe may interrupt the gene exchange of aphids. Rhopalosiphum aphid species from different geographical regions, 32 populations (n = 535) of the bird cherry-oat aphid  and 38 populations (n = 808) of the corn leaf aphid  from China and Europe were analyzed using one nuclear  and two mitochondrial (cytochrome oxidase I and II) genes. Based on the COI-COII sequencing, two obvious clades between Chinese and European populations and a low level of gene flow (Nm = 0.15) were detected in R. padi, while no geographical-associated genetic variation was found for EF-1α in this species. All genes in R. maidis had low genetic variation, indicating a high level of gene flow (Nm = 5.31 of COI-COII and Nm = 2.89 of EF-1α). Based on the mitochondrial result of R. padi, we concluded that the long distance between China and Europe may be interrupting the gene flow. The discordant results of nuclear gene analyses in R. padi may be due to the slower evolution of nuclear genes compared to mitochondrial genes. The gene exchange may occur gradually with the potential for continuous migration of the aphid. This study facilitates the design of control strategies for these pests.Population genetic studies can reveal clues about the evolution of adaptive strategies of aphid species in agroecosystems and demonstrate the influence of environmental factors on the genetic diversity and gene flow among aphid populations. To investigate the genetic diversity of two  Rhopalosiphum padi Linnaeus; Hemiptera: Aphididae) was detected in Iran [Sitobion avenae Fabricius) collected from different geographical regions in China showed high genetic diversity [Melanaphis sacchari Zehntner) appeared to be more strongly influenced by geography than by host plants [S. avenae populations exhibited life-history divergence and local adaptation in northern and southern areas separated by the Qinling Mountains of China [Intraspecific genetic diversity provides the basis for investigating the evolutionary history of species and offers an opportunity to document the basic level of biodiversity within and among populations . Hence,  in Iran . Seven piversity . Furthert plants . In addiof China . Geograpof China . By contof China .Rhopalosiphum maidis Fitch; Hemiptera: Aphididae) and R. padi are the two common phloem-sucking pests on maize (Zea mays Linnaeus), one of the major crops in China. In addition, R. maidis can also feed on broomcorn (Sorghum bicolor L.), wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and goose grass (Eleusine indica L.) [R. padi often attacks peach (Prunus persica L.), plum , and bird cherry (Prunus padus L.) cyclically besides Gramineae [Rhopalosiphum species can transmit viruses including the maize dwarf mosaic virus (MDMV) and the barley yellow dwarf virus (BYDV) [The corn leaf aphid (dica L.) , while Rramineae . These pramineae ,14,15,16ramineae , Canada ramineae ,19, Austramineae , North Aramineae , New Zearamineae ,23, Indiramineae , Egypt [ramineae , and Chiramineae ,26,27. Bs (BYDV) ,29,30, lR. maidis generally lacks sexual reproduction [R. padi have focused on its life cycles or combination of life cycles and geographical locations [R. padi in China [R. padi. So far, only two studies on the genetic differentiation of R. maidis based on allozymes [Genetic diversity is affected by factors including the life cycle of aphids , the hosoduction , and it oduction . Furtherocations ,38,39,40ocations ,20. Therin China : (1) cycin China , SSR [6,in China ,42, ISSRin China , and mtDllozymes , mtDNA, llozymes  have beeR. padi, it is known that: (1) There is a significant genetic difference between reproductive modes [R. padi clones can be driven as well by longitudinal clines [R. maidis, based on the scarce reports available, Steiner et al. found that the northern populations of R. maidis in North America lacked heterozygosity and were genetically diverse compared with the populations from southern regions [R. maidis was related to the host plants rather than geographical localities [According to previous research on ve modes ,37,38,40ve modes . (2) Theve modes ,23, someve modes ,44, Canave modes , and Ausve modes . (3) Thel clines . As for  regions . Howevercalities . Among all the molecular markers for genetic variation research on insects, mtDNA is considered a useful and efficient tool because of the maternal inheritance, lack of recombination, and high mutation rate . MitochoR. padi collected from maize [R. maidis from maize are available. Therefore, this study was conducted to describe for the first time the geographical genetic differentiation among populations of these two Rhopalosiphum species on maize from most maize-sowing areas in China as well as several European countries, based on the COI, COII, and EF-1α genes. We also investigated whether the genetic diversity of R. padi and R. maidis was influenced by geographical variables of the maize-producing regions, which may provide the basis for the management of these aphids.So far, there is only one report on the genetic divergence of om maize . MoreoveR. padi of 32 sites and 808 R. maidis of 38 sites) were collected from maize in China and Europe from 2014 to 2016. Based on the climate and maize cultivation practices, the maize cultivation areas in China are mainly divided into five regions defined as the north spring maize region (NS), Huanghuaihai summer maize region (HS), southeast hilly maize region (SEH), northwest inland maize region (NWI), and southwest hilly maize region (SWH), respectively (R. padi and maize region in France (FRA) for R. maidis. Collection information and localities are listed in A total of 1343 aphid samples (535 ectively . Furtherhttp://www.premierbiosoft.com/ (accessed on 1 January 2020)) with the sequences downloaded from Genbank . In addition, BSA  (10 mg/mL) with 1% of the total volume was added to the reaction system for all the genes except for the EF-1α of R. maidis in order to improve amplification results. The PCR was implemented under the following conditions: initial denaturation at 94 °C for 3 min; 35 amplification cycles of 94 °C for 30 s, annealing temperature ) and the chromatograms were checked for the nucleotide variations. The unreliable terminal sequences were cut by MEGA v6 software after multiple alignment. The haplotype numbers (Ha), haplotype diversity (Hd), number of polymorphic sites (S), nucleotide diversity (Pi), Tajima’s D neutrality test [R. padi and R. maidis. COI, COII, and EF-1α sequences of the greenbug (Schizaphis graminum Rondani) downloaded from NCBI (http://www.ncbi.nlm.nih.gov/ (accessed on 1 January 2020)) were used as the outgroup for R. padi and R. maidis. Molecular variance (AMOVA) analyses of pairwise FST, ΦST (genetic differentiation), Nm values between geographic populations, as well as five geographical groups  were performed using ARLEQUIN v3.5 [ST and ΦST values according to the equilibrium between migration and drift: Nm = (1 − ΦST)/2ΦST for mitochondrial genes and Nm = (1 − FST)/4FST for EF-1α. In addition, the pairwise ΦST of mtDNA was estimated as the ratio of genetic differentiation between populations weighted by the degree of within-population differentiation [ST/(1 − FST) for EF-1α and ΦST/(1 − ΦST) for mtDNA and the logarithms of geographical distances (km) between all collecting locations.The obtained sequences were verified via BLAST  and EF-1α (672 nt) genes, respectively, among 535 R. padi individuals. All haplotype sequences were submitted to GenBank with the accession numbers of KY612517 to KY612597. We obtained high quality sequences of 496 nt, 499 nt, and 672 nt of COI, COII, and EF-1α, respectively, for iversity  showed tR. padi was 0.663 for the combined COI-COII, being higher than that of R. maidis (0.227). In addition, the Hd values for the EF-1α gene of R. padi and R. maidis were 0.507 and 0.548, respectively. The nucleotide diversity (Pi) of R. padi was 3.52 × 10−3 for the combined COI-COII and 1.04 × 10−3 for the EF-1α, both of which were higher than the Pi of R. maidis (0.22 × 10−3) for the combined COI-COII and EF-1α (0.89 × 10−3). Neutrality tests were conducted using Tajima’s D and Fu’s Fs statistics, and all sequences were included as one group for each species (p < 0.05) for the EF-1α of R. padi and the combined COI-COII of R. maidis. Nevertheless, neutrality tests using Tajima’s D values for each population showed that only four populations  of EF-1α in R. padi and six populations  of the combined COI-COII in R. maidis were significantly negative (p < 0.05)  of EF-1α in R. padi, and 11 populations  of the combined COI-COII in R. maidis were significantly negative (p < 0.05)  was found for EF-1α in R. padi, as well as both sequences in R. maidis (Nm = 5.31 of the combined COI-COII and Nm = 2.89 of EF-1α).The haplotype diversity (Hd) of  species . Tajima’ < 0.05) . Additio < 0.05) . A low lRhopalosiphum aphids are illustrated in R. padi, and 11 and 4 polymorphic sites for the combined COI-COII and EF-1α sequences of R. maidis, respectively. In total, 84.1% of the polymorphic sites (58/69) were transitions, of which 40 sites were T/C transitions and 18 were G/A transitions. In addition, approximately 14.5% (10/69) transversions were found, six of which were T/A transversions and the other four were G/T transversions. One polymorphic site contained both a transition and a transversion at 634 nt for the combined COI-COII sequence of R. padi. No insertions or deletions were detected for all sequences.The polymorphic nucleotide sites of the combined COI-COII and EF-1α genes in the two R. maidis. Similarly, the percentages of variation within populations were also high for R. padi (61.91% of the combined COI-COII and 83.33% of EF-1α). Moreover, the genetic distance (FST) of R. padi (0.167 for EF-1α and 0.381 for the combined COI-COII) had no significant difference with R. maidis (0.046 for EF-1α and 0.065 for the combined COI-COII). When the populations were geographically divided into five groups based on the maize-sowing regions, the genetic variation within populations was predominant  and five groups (the populations were divided into five groups based on the maize-sowing regions) . The resdominant . FurtherST values of EF-1α and ΦST values of mtDNA between geographical populations are displayed in R. padi, the 496 pairwise values among the 32 populations ranged from −0.266 (SYS and HEB) to 1  of ΦST values for the combined COI-COII  of FST values for EF-1α showed statistically significant genetic differentiation (p < 0.05). In general, most pairwise ΦST values of R. padi for populations from different regions were higher than those for populations from the same region. For instance, higher pairwise ΦST values for the combined COI-COII were found between the EUR population and populations from other regions compared to those between EUR populations. However, most FST values of the EF-1α gene were low even between populations from different regions. The Nm values of R. padi ranged from 0  to 1785.214 (LF and BJ) for the combined COI-COII  to 0.318 (ZJK and DZ) for the combined COI-COII  to 0.625 (JNa and YC) (p < 0.05) was 16.2% (n = 114) of the ΦST for the combined COI-COII, and 16.1% (n = 113) of the FST for the EF-1α gene. Moreover, some populations, such as YC , DZ , and MS , exhibited high pairwise values for populations both within and outside of the same region. The 703 Nm values of R. maidis varied from 1.071 (ZJK and DZ) to 6249.500 (ZY and NC) for the combined COI-COII  . The proCOI-COII  and 0.15COI-COII . In addiR. padi , 30/53 specimens collected from the SWH region were distributed in HRp2, and 20/41 samples from the NWI region were distributed in HRp3. However, no significant regional distribution was observed for the 32 haplotypes of the EF-1α gene in R. padi, using both the phylogenetic tree  and HRm4 (384/808 specimens) were the dominant haplotypes based on the network results  (R. maidis) and 8d (EF-1α of R. padi), and the values of Tajima’s D were significant for the mtDNA of R. maidis and EF-1α from R. padi (p < 0.05)  . However < 0.05) . In addi. maidis a showed R. padi collected from maize in most of the maize-growing regions in China as well as Europe. Knowledge about the genetic diversity of R. maidis has been so far limited to two studies based on an allozyme analysis of North American populations, which showed regional differentiation [R. maidis exhibited low genetic differentiation among populations. The genetic diversity of R. padi was overall higher than that of R. maidis particularly for the combined COI-COII, which showed the highest Hd values (0.663) and lowest overall Nm values (0.15). However, low geographic genetic diversity was reported for R. padi in Australia, based on the analysis of COI and microsatellites [This is the first study of the genetic diversity of ntiation , and Canntiation . Our restellites . S. avenae [Eriosoma lanigerum Hausmann) [R. padi [R. padi, the variations of the mitochondrial gene among the groups in different maize-sowing regions were significantly larger than those within groups, which is likely explained by the geographical division between Chinese and European specimens. Furthermore, different maize varieties between China and Europe may also contribute to the genetic differentiation of R. padi since the races of host plants act as a trigger for speciation of phytophagous insects [R. maidis, both genes showed greater variation within groups than among groups because of the low genetic diversity in China and the use of only one collection site in France, which may not be representative enough for a region outside of China.According to the AMOVA results, the highest proportion of the genetic variability observed in the mitochondrial and nuclear gene sequences was explained by within-population variation in both aphid species. The genetic variance within populations seems to contribute much more than that among populations for various aphid species including . avenae ,66, the ausmann) , and R. [R. padi . For R.  insects . NeverthST, ΦST, and Nm values exhibited a low level of significant genetic differentiation but a high frequency of gene flow for R. maidis. Less than 20% of the significant genetic differentiation (p < 0.05) for both the combined COI-COII and EF-1α, and none of the Nm values for the combined COI-COII were less than 1, revealing that there was very little genetic differentiation among R. maidis populations [R. maidis reduces the chance of gene recombination, and the parthenogenetic populations show less allelic polymorphism compared with sexual reproduction [R. padi, the results of mitochondrial and nuclear gene analyses were to some extent discordant. The proportion of significant genetic differentiation for pairwise ΦST values for the combined COI-COII (64.5%) was twice as high as that of the FST values for EF-1α (37.1%) (p < 0.05). The discordance between nuclear and mtDNA phylogeny could be explained by the higher rate of evolution of the mitochondrial genome compared to the nuclear genome due to its haploid nature and lack of recombination [R. padi [R. maidis [The pairwise Fulations . Hence, oduction , which mbination . In addi[R. padi ,72,73 an. maidis ,18,43 ar. maidis , which cR. padi revealed that the substantial geographical distance between China and European countries may result in distinct aphid lineages  based on geographical differentiation. By contrast, low genetic diversity has often been detected in insects collected from a small geographical range  [R. padi. This result indicates that there exists some genetic differentiation within China despite the frequent gene exchange. Furthermore, the sampling sites in Europe (temperate maritime climate) have mild winters, whereas the NWI region  and HS region (temperate monsoon climate with high temperature and rainy summer) have cold winters, which may affect the population genetic diversity of R. padi [R. padi in France was described in a previous study [R. padi from the HRp6 (in the European clade) of mtDNA were collected from the NWI region of China. We speculate that three possibilities may explain this phenomenon: (1) European R. padi might have been passively carried to the NWI region through agricultural products and then colonized the region; (2) a spontaneous mutation occurred in Chinese R. padi which resulted in HRp6; (3) a gene exchange might have occurred indirectly through continuous migration across countries between China and Europe, which needs further research. By contrast, the genetic diversity of EF-1α in R. padi was low  and shows the haplotype I, whereas cyclical parthenogenesis populations exhibit distinct haplotypes [R. padi collected from wheat [R. padi clones in France [R. padi populations are objects for further study.The phylogeny and network analyses of haplotypes produced consistent results. The two distinct clades of the combined COI-COII a in R. pcountry) ,75,76,77 R. padi . Regardius study . In addi was low b. The muplotypes . Likewisom wheat . Furthern France . The geoR. maidis specimens were classified in HRm1 and HRm4. In summary, low genetic diversity was detected for both genes in R. maidis. However, three regional clusters of R. maidis were found in North America through an allozyme analysis [R. maidis from North America, Europe, and North Africa determined using several methods, except for the differentiation of the chromosome number in relation to the host plant species [R. maidis could be caused by the limited host plant (only maize) and migration of this aphid (both the combined COI-COII and EF-1α showed a high level of gene flow). The formation of geographically isolated clones can be inhibited by frequent gene exchange [R. maidis specimens from France may be insufficient to represent the real situation in Europe. Thus, more samples from a larger area in Europe are needed for obtaining more accurate results in subsequent studies.Despite the HRm6 and HRm7 of EF-1α being independent haplotypes from France, some French analysis . Simon e species . The gen species . In our exchange . MoreoveR. padi. However, the geographical genetic variation may be counteracted gradually by active or passive migration of the aphids. No correlation was found between the genetic diversity and geographical distance for EF-1α in R. padi. On the other hand, both mitochondrial and nuclear genes in R. maidis showed low genetic variation, which could be the reason why R. maidis exhibited low genetic differentiation. Moreover, the low genetic variation of both genes with a high level of gene flow suggests that R. maidis may migrate frequently in terms of its geographical range in China. Our study demonstrated the genetic variation of two Rhopalosiphum aphids based on both mitochondrial and nuclear gene analyses, focused on the geographical factor, and found a high level of gene flow, particularly among the collection sites in China. Nevertheless, other molecular markers combined with mitochondrial and nuclear genes, as well as the combination of different factors such as geographical distance, host plants, and the life cycle of these aphids may reveal more accurate results, which need further verification. The results reported here are beneficial for understanding the dispersal process of these pests and developing control mechanisms against them.In conclusion, geographical distance may play a crucial role in genetic diversity based on the distinct Chinese and European clades revealed by the analysis of the mtDNA of


The extent and impact of evolutionary change occurring in natural populations in response to rapid anthropogenic impact is still poorly understood on the genome-wide level. Here, we explore the genetic structure, demographic history, population differentiation, and domestic introgression based on whole genome data of the endangered European wildcat in Germany, to assess potential genomic consequences of the species’ recent spread across human-dominated cultural landscapes.Reconstruction of demographic history and introgression rates based on 47 wildcat and 37 domestic cat genomes suggested late introgression between wild and domestic cat, coinciding with the introduction of domestic cat during the Roman period, but overall relatively low rates of hybridization and introgression from domestic cats. Main population divergence found between an eastern and central German wildcat clade was found to be of rather recent origin (200 y), and thus the likely consequence of anthropogenic persecution and resulting isolation in population refugia. We found similar effective population sizes and no substantial inbreeding across populations. Interestingly, highly differentiated genes between wild cat populations involved in the tryptophan-kynurenine-serotonin pathway were revealed, which plays a role in behavioral processes such as stress susceptibility and tolerance, suggesting that differential selection acted in the populations.We found strong evidence for substantial recent anthropogenic impact on the genetic structure of European wildcats, including recent persecution-driven population divergence, as well as potential adaptation to human-dominate environments. In contrast, the relatively low levels of domestic introgression and inbreeding found in this study indicate a substantial level of “resistance” of this elusive species towards major anthropogenic impacts, such as the omnipresence of domestic cats as well as substantial habitat fragmentation. While those findings have strong implications for ongoing conservation strategies, we demand closer inspection of selective pressures acting on this and other wildlife species in anthropogenic environments.The online version contains supplementary material available at 10.1186/s12864-022-08930-w. The anthropogenic alteration of ecosystems has been acknowledged as the single greatest threat to global biodiversity , 2, leavFelis silvestris, hereafter FS), for instance, suffered considerable range declines and population reductions in Central Europe, due to anthropogenic persecution as well as habitat loss and fragmentation during the 19th and early twentieth century [F. silvestris [The European wildcats  showFelis catus, hereafter FC) do not directly derive from European wildcats (FS), successful hybridization between FS and FC has been found in various regions of their distribution. Particularly high levels of hybridization have been revealed in Scotland and Hungary [F. silvestris is still largely unknown. Archaeozoological data suggests the presence of domestic cat in central Europe at least during the Roman Period, ca. 2,000 ya, introduced by either Celts or Romans [While domestic cats  were found in the full data set containing wildcat and domestic cat, and 28,618,073 SNPs after passing filtering steps.K = 2, Figure SK = 2, Fig. ADMIXTURE showed a clear structure for the dataset including domestic cat and wildcat (Ne) for wildcats in comparison to domestic cats. The PSMC analysis showed no significantly different demographic trajectories between Central and Western wildcat individuals, indicating the existence of a single demographic population for most of the time. Results showed a steep Ne growth of wild cats in the Middle-Pleistocene (ca. 400 thousand years ago (kya)) reaching the peak in the Upper-Pleistocene with an average Ne of 70,000 individuals (ca. 110 kya), and followed by a continuous decrease since then  demographic analysis recovered a proportion of accepted simulations for all demographic models tested. Demographic model 3, which hypothesized a late split of western and central wildcat populations and early introgression, received the lowest support of all. The best-supported demographic model was model 4 Fig. , with 95Model 4 suggested a late introgression event (ca. 600 generations ago) and a recent split (ca. 100 generations ago) of western and central wildcat populations (Table SROH) ranged between 0.004 and 0.2 . Analysis of long ROH (> 2 Mb and > 5 Mb), which can detect recent rather than distant inbreeding, identified 1,771 ROH segments in 45 individuals and 57 segments in 30 individuals, respectively. Thus, while at least some degree of recent inbreeding was detected in 63% of individuals, it was not tied to population structuring within and between populations.The proportion of the genome that was contained in runs of homozygosity  terms were significantly enriched for biological processes  and number of polymorphic sites for the four genes identified in the selection analyses were 77,142 and 34, 111,195 and 59, 35473 and 58, and 57,619 and 33, respectively. A total of 17, 18, 0, and 21 unique haplotypes were found for genes 1–4 respectively. The haplotype network diagrams for genes 1–3 show a clear grouping of wildcat vs domestic cats haplotypes, except for gene four, for which there is not that apparent structure. Almost no haplotypes were shared between wild and domestic cats. Overall, the number of haplotypes shared amongst the three groups was insignificant, while shared haplotypes between Central and Western wildcats were more frequent  were significant for the D estimation. The proportion of the genome introgressed between Western wildcat and domestic cat was relatively low , however, the proportion of the genome introgressed between Central wildcat and domestic cat remains unknown. ABBA and BABA site counts across the genome were similar  for western and central German wildcat have experienced subtle changes, but generally, western and central wildcats present similar Ne. There is also no population separation recovered by the PSMC analyses for the period where this analysis yielded sufficient resolution i.e. before 10000 years ago , which was a period of the Late Pleistocene characterized by wetter and warmer environmental conditions [Ne inference using MSMC2 is most likely biased by phasing errors and results should be taken cautiously. It has been shown that phasing errors in haplotype-based inference methods, such MSMC, break up identity-by-state tracts in closely related haplotypes which leads to inferring large recent effective population sizes [Effective population sizes . The fact that the differentiated genes are ultimately involved in the serotonin production might have important behavioral implications on the wildcats. Tryptophan is the metabolic precursor to serotonin, which is a neuromodulator involved in the regulation of several behavioral processes, including aggression, mood, and stress susceptibility and -resistance in both vertebrates and invertebrates , 47. In It is widely accepted that human activities may negatively impact and have fitness consequences to wildlife, including stress, disease and reproductive success –54. WithWe found some evidence of genome-wide introgression between German wildcats and domestic cats. However, the proportion of genome introgressed is relatively low, which supported previous evidence of low levels of introgression in German wildcats –23. The FC does not seem to play an important role in the differentiation of these genes between Western and Central wildcat populations, as shown by the very few haplotypes shared between domestic cat and the two wildcat populations. This might be due to the fact that introgression started relatively early in German populations and is generally very low [The relationship amongst haplotypes for each of the four highly differentiated genes reveals a distinct structure that corresponds to the different geographical groups defined in the analyses, a pattern which is neatly congruent with the population structure analyses  accession number: GCA_000181335) using BWA mem v0.7.15 [–M option for Picard (Broad Institute 2019) compatibility  with a squared correlation coefficient of more than 0.5 using bcftools v1.9 .K), from K = 1 to K = 15, with default settings and a tenfold cross validation procedure. We performed a second ADMIXTURE analysis for a subset that included only German wildcat individuals, K = 1 to K = 10 using the same settings as the first analysis. We subsequently performed a 10 runs analysis for K = 2, the K that received the highest support for German wildcat only. Results from both analyses were plotted with PONG [Felis individuals and just German wildcat individuals, using the R package Factoextra v.1.0.7 [We used ADMIXTURE version 1.3.0  to inferith PONG . In addi v.1.0.7 .Ne was inferred across 64 interval times (2*3 + 25*2 + 4 + 4) and calculated bootstrap ranges for each individual. Results were scaled with a mutation rate of µ = 1 × 10–8 per base pair and generation, assuming a generation time of two years [Ne history  and uses phased haplotype data of single chromosomes; therefore we separated each of the autosomal chromosomes and used Beagle v.5.4 [https://github.com/stschiff/msmc-tools) to generate the input files for MSMC2 for each chromosome. We used the same groups of unadmixed individuals, generation time, mutation rate and interval times as for the PSMC analysis. For the MSMC2 runs we used the option to skip sites with ambiguous phasing (-s) as recommended by instructions.We implemented a pairwise sequentially Markovian coalescent  model iwo years . We alsowo years  using thle v.5.4  for phasFS and western German FS. The Middle East FC individuals were included in the analysis to polarize derived vs ancestral alleles, and the European FC as potential source of introgression with the FS. We designed four competing demographic models taking into account PSMC results and considering three criteria: 1) temporally different split time between central and western FS; 2) different temporally gene flow between European FC, central FS and western FS; and 3) different temporally introgression between European FC and FS. Based on these criteria we designed four models as follows: Model 1) depicts an early split of Western and Central German wildcat populations and differential introgression in wildcat; Model 2 depicts an early split of Western and Central German wildcat populations and late introgression; Model 3 depicts an late split of Western and Central German wildcat populations and early introgression; and Model 4 depicts an late split of Western and Central German wildcat populations and late introgression  as summary statistics. In order to minimize the effects of selection on demographic inference, we included only neutrally and no linked evolving SNPs at fourfold degenerated sites in the genome by using tbg-tools v.0.2 (https://github.com/Croxa/tbg-tools) for selection. The selected SNPs were pruned for linkage disequilibrium (LD) with PLINK v 1.9 [2 threshold of 0.1. We obtained the observed SFS of the unlinked, neutral SNPs using easySFS (https://github.com/isaacovercast/easySFS). We ran 10,000 simulations with fastsimcoal2 v.2.6.0.3 [abc [We performed a demographic modelling analysis where we defined four groups. Based on the clear population structuring from the ADMIXTURE analyses results we included central German NK v 1.9 , 76, app.2.6.0.3  for each0.3 [abc .--geno option in PLINK before running the ROH analyses to keep only SNPs with a 90% genotyping rate (10% missing). There is a lack of consensus in the literature to whether SNP data should be pruned by LD and/or minor allele frequency (MAF). We followed Meyermans et al. [–homozyg –homozyg-window-snp 20 –homozyg-window-het 1 –homozyg-window-missing 5 –homozyg-window-threshold 0.05 –homozyg-snp 20 –homozyg-het 1 –homozyg-density 100 –homozyg-kb 1000 –homozyg-gap 1000; 2) we increased the –homozyg-window-snp to 50; and 3) –homozyg-window-snp 20 and –homozyg-window-threshold 0.25. We estimated the fraction of the genome in ROH (FROH) as the total length of ROH per individual divided by the length of the genome. We evaluated significance level of the estimate using a pairwise t-test with Bonferroni correction.Runs of homozygosity (ROH) were identified using PLINK v 1.9 , 76. We s et al.  recommenFST; [vs Central) using a non-overlapping 10-kb window with VCFtools 0.1.17 [FST distribution, under the assumption of no selection. We used a custom python script to extract genes for which any of the outliers 10-kb windows above the 99% quantile of the simulated FST distribution fall within the genomic coordinates of genes of the annotated genome of FC. Resulting genes were the candidates for functional enrichment analyses.We estimated the genome-wide fixation index  for wils 0.1.17 . In ordes 0.1.17  to inferFST threshold of simulated FST. GO terms were annotated to all protein sequences using InterProScan v 5.39–77.0 [p-value ≤ 0.05 and used the Benjamini–Hochberg method [p-value correction with a FDR  level of 5%.We ran a gene ontology (GO) term enrichment analysis on candidate genes that fell above the 99% .39–77.0 , resulti.39–77.0  for the g method  for p-vaFelis catus v9.0 reference genome for all cats included in our sampling using VCFtools 0.1.17 [In order to visualize and interpret individual relationships at the population level, we built haplotype networks, which can be more appropriate than hierarchical tree format for intraspecific analyses , 86. We s 0.1.17  and bcfts 0.1.17 . Haplotys 0.1.17  and aligs 0.1.17 , 89. We s 0.1.17  implemens 0.1.17 . We codeD-statistic [D-statistic using the genomics_general toolkit . To test for the consistency of the estimation, we computed the standard deviation of D-statistic with the block jackknife procedure with 95% of the data, and the standard error, Z score and p-value for the test. In addition to this, we calculated D-statistic in 100-kb non-overlapping windows.We tested for genome-wide introgression between wildcat and domestic cat with the ABBA-BABA test  using Patatistic , 94. We general; ) and theAdditional file 1. Supplementary Results, Supplementary Methods and Appendix A.


Morinda officinalis How is well-known as a valuable medicinal plant found in some regions of Vietnam. This species is mainly used for treating male impotence, irregular menstruation, and rheumatoid arthritis. This study aimed to identify the species of and genetic diversity in three M. officinalis populations: one each in Quang Binh (QB), Thua Thien Hue (TTH), and Quang Nam (QN). In this study, four DNA barcoding markers  were used to identify the species and 22 microsatellite markers were applied for population structure and diversity analyses. The results showed that the sequences of gene regions studied in M. officinalis had a high similarity (>95%) to the ITS1, ITS2, matK, and rbcL sequences of M. officinalis on BLAST. Of the four DNA barcoding markers used, ITS1 and ITS2 showed higher efficiency in DNA amplification of M. officinalis. From this study, 27 GenBank codes were published on BLAST. The results also revealed high levels of genetic diversity in populations. The average observed and expected heterozygosity values were HO = 0.513 and HE = 0.612, respectively. The average FST value was 0.206. Analysis of molecular variance (AMOVA) showed 70% variation within populations and 30% among populations. The population structure of M. officinalis inferred in STRUCTURE revealed that the optimum number of genetic groups for the admixture model was K = 2. These findings provided vital background information for future studies in the conservation of M. officinalis in both ex situ and in situ plans. Morinda officinalis is a perennial vine mainly distributed in tropical and subtropical regions [M. officinalis is found in the wild in provinces such as Cao Bang, Lao Cai, Ha Giang, Quang Binh, Thua Thien Hue, and Quang Tri [ regions . In Vietuang Tri ,3,4.M. officinalis contains various bioactive components and has been used for decades as a tonic and an antirheumatic medicinal herb in some Asian countries [M. officinalis has long been used as a tonic or nutrient supplement for alleviating diseases such as depression, Alzheimer’s disease, impotence, osteoporosis, and rheumatoid arthritis [ountries ,5,6. TheM. officinalis has slow growth and poor regeneration, its natural population has significantly shrunk and become endangered [In Vietnam, due to the rapid increase in the demand for medicinal herbs, this plant has been over-exploited, leading to the depletion of raw materials. Additionally, because dangered ,4. With dangered . TherefoNowadays, phylogenetic studies are necessary to conserve rare medicinal plants. In addition to representing the relationships among species in the tree of life, phylogenetic studies provide a framework for interdisciplinary investigations in taxonomy, evolutionary biology, biogeography, ecology, and conservation . More rerbcL and matK plastid coding genes were recommended as barcodes for plant species and have become the most used markers in flowering plants, as the rbcL region is highly suitable for amplification and sequencing [ITS region includes both the ITS1 and ITS2 regions, with relatively strong discrimination power, that serve as complementary barcodes to matK and rbcL in plants. The four markers  used in this study have also proven effective in identifying medicinal species [DNA barcoding is a universally used and reliable method of identifying plant species and has become a major focus in the fields of biodiversity and conservation. This molecular technique is not influenced by external factors or development stage, and DNA can be easily isolated from all tissues, providing an important basis for species identification at the genetic level . Recentlquencing ,11. Mean species ,13,14.Currently, molecular markers help detect variations or polymorphisms that exist among individuals in the population for specific regions of DNA . Among cM. officinalis [Studies on molecular markers have been carried out on icinalis ,20. LiaoThe SSR marker has the advantage of using only a tiny amount of DNA. In addition, this method involves a more straightforward, faster, and more cost-effective technique than other methods.M. officinalis by using SSR markers, we used DNA barcoding to identify this species in three different provinces in central Vietnam . The current study aimed to pave the way for protecting wild M. officinalis populations.In this study, before evaluating the genetic diversity and population structure of M. officinalis trees were randomly collected from 3 populations in the central provinces of Quang Binh, Thua Thien Hue, and Quang Nam in Vietnam. In the field, the samples were placed in plastic bags containing silica gel. Next, the samples were transferred to the Genetic Laboratory of the Biology Department at Hue University of Education and stored at −20 °C until DNA extraction. Sampling locations were recorded using a global positioning system (GPS) (The leaves of 37 em (GPS) .Genomic DNA was extracted from 100 mg of young leaf samples using a Plant Genomic DNA Extraction Kit  according to the manufacturer’s protocol. The quality of the extracted DNA was further estimated via 0.8% agarose gel electrophoresis. Safe dye  was applied for DNA gel stain. Gel imaging was performed using a UV gel imaging system . The isolated DNA was then stored at −20 °C until further analysis.A polymerase chain reaction (PCR) was performed using standard universal plant DNA barcoding primers , with 25To check the presence or absence of bands, amplified PCR products were electrophoresed using 0.8% agarose gel (1 × TAE buffer and 5 μL/mL safe dye). Gel imaging was carried out using a UV gel imaging system . Band size of amplified products was determined using a Thermo Scientific GeneRuler 100 bp DNA Ladder . The PCR products were sent to First Base Laboratories Sdn. Bhd  for purification and sequencing service, using the same primers as those used for the PCR.In all, 37 genomic DNA samples were used in this study. A polymerase chain reaction (PCR) was performed in 25 μL of reaction mixture that contained 2.0 μL of template DNA, 12.5 µL of 2X Taq Master Mix, 0.5 µL of each primer, and 9.5 µL of deionized water.Liao et al.  have desPCR amplification was carried out with an Aeris™ PCR Aeris Thermal Cycler as follows: Initial denaturation was carried out at 95 °C for 3 min. This was followed by 35 cycles of 45 s each at 94 °C for denaturation, 45 s of alignment at the annealing temperature (50–52 °C) for each primer pair, and 45 s of alignment at 72 °C for extension. Finally, 10 min of alignment at 72 °C for the final cycle completed the extension of any remaining products. The samples were kept at 4 °C until they were analyzed.The amplification products were separated on 8% polyacrylamide gels in 1 × TAE buffer using the Mini Vertical Gel Electrophoresis Apparatus  and visualized with safe dye (Phu Sa company). A UV gel imaging system  was used to verify the presence of amplified fragments.ITS1, ITS2, matK, and rbcL), the forward and reverse sequences were aligned using BioEdit version 7.2.5 software [http://www.ncbi.nlm.nih.gov/BLAST (accessed on 20 June 2022) [To obtain the sequence of each region  software for phylogenetic analysis . The maxer model  with 100www.gelanalyzer.com (accessed on 4 January 2022), by Istvan Lazar Jr. and Istvan Lazar Sr).Size of bands was detected by GelAnalyzer 19.1 software (IS). All calculations were performed in GenAIEx v.6.5 [To determine the level of genetic variation within a population, the following genetic diversity parameters were calculated: mean number of alleles per locus (A), number of unique alleles, the effective number of alleles (Ne), average observed heterozygosity (Ho), average expected heterozygosity (He), and fixation index  in GenAIEx v.6.5 [A genetic distance matrix of pairwise FEx v.6.5 . SignifiM. officinalis was carried out in GenAIEx [Principal coordinate analysis (PCoA) based on the codominant genotypic distance for 37 studied samples of 3 populations of  GenAIEx .https://web.stanford.edu/group/pritchardlab/structure.html (accessed on 28 July 2022) [To determine the optimal value of the genetic clusters (K), a Bayesian analysis of the population structure was performed with STRUCTURE v.2.3.4 (ly 2022) . Once thly 2022)  based onITS1 and ITS2 markers gave fragments of molecular weight as expected and bands of PCR products were clear for further research in all samples of the three populations, whereas some samples that used matK and rbcL markers for amplification had negative results and therefore their sequences were not determined.For this study’s DNA barcoding amplification process, we selected three samples per population, using four different primers to identify species. The results showed that ITS1 amplicon, nine assembled sequences of ITS2 amplicon, four assembled sequences of matK amplicon, and five assembled sequences of rbcL amplicon. The BLAST tool was used to identify the plant for each sequence, and the closest species in the GenBank was obtained. The results showed that all markers used and plants deposited in this study belonged to the genus Morinda. Gynochthodes officinalis  was the most closely related species, with a higher extent than other species of the Morinda genus.A total of 27 assembled sequences were obtained and deposited in the GenBank: nine assembled sequences of ITS1 and ITS2 were the most effective in terms of the amplification process (100%)  .ITS1 pair of primers (ITS 5a forward and 4 reverse) and the BLAST tool for identification, the closest species was found to be M. officinalis, at 98.88% similarity (ITS2 region sequences (~235 bp), through use of the ITS2 pair of primers (ITS S2F and ITS S3R), the closest species was found to be Gynochthodes officinalis , at 100% similarity (In the case of ITS1 region sequences (~179 bp), through use of the milarity . The phymilarity . In the milarity . The phymilarity .matK region sequences (ranging from 861 bp to 899 bp), through use of the matK pair of primers (390F and 1326R), the closest species was found to be M. officinalis, at 99.89% similarity , G. parvifolia (accession number NC_054151.1), and Morinda sp. SH-2010 (accession numbers AB586541.1 and AB586543.1), with similarity ranging from 99.31% to 100%  accounted for the highest proportion, ranging from 35.3% to 38.9%, followed by guanidine (G), which ranged from 31.1% to 34.0%. Timin (uracil) was observed with the lowest percentage (ranging from 10.0% to 14.5%) (In terms of the occurrence of each type of nucleotide in the o 14.5%) . For mato 14.5%) .ITS2 gene region (The (G + C) percentage was the highest, with an average of 69.6% in the e region .M. officinalis in the three surveyed populations, with sizes ranging from 106 bp to 328 bp.A total of 140 different alleles were detected from 22 microsatellite markers in IS values of the loci ranged between −0.287 and 0.965, with an average of 0.216. Half of the loci  showed positive FIS values , while the locus MO90 showed the lowest number of alleles, with Na = 2.333. The FS values . The FITST values ranging between 0.127 and 0.554, with an average of 0.262. This result indicated a relatively high genetic differentiation at the locus level in all populations  ranged from 2 to 8 in the QB population, from 3 to 12 in the TTH population, and from 0 to 10 in the QN population. Specifically, the TTH population had the highest number of alleles, with an average of 6.455, whereas the population with the lowest number of alleles (3.955) was the QB population  was observed in the TTH population, followed by the QN population (Np = 2.318) and the QB population (Np = 1.818). Similarly, of the three populations, the effective allele numbers of the TTH population were the highest at 3.786, compared to 3.221 and 2.567 for the QN and QB populations, respectively.ST) was positive for all populations (FST = 0.206).Observed heterozygosity (Ho) and expected heterozygosity (He) averaged 0.513 and 0.612, respectively. The QN population had the highest expected heterozygosity (0.591) of the three populations, whereas the value of the observed heterozygosity of that population was 0.601. The fixation index (FThe results of the AMOVA pointed to higher levels of variation within populations (70%) than between populations (30%) , indicatM. officinalis based on Bayesian analysis using the STRUCTURE program. The population structure of M. officinalis inferred in STRUCTURE revealed that the optimum number of genetic groups for the admixture model was K = 2, with a delta K value of 74.084117. After a PCA analysis, the three populations were classified into two distinct clusters. K = 2, thus, can be considered to be the most suitable number of clusters for the structure of the populations in this study  region genetic markers have been proven highly efficient in distinguishing plant species and therefore identified as potential candidates for barcoding plants [ITS1 and ITS2 regions of M. officinalis were amplified more effectively compared to the other two markers (matK and rbcL).In previous studies, the g plants . This stMorinda and the most closely related species was Gynochthodes officinalis . In the present study, the ITS2 marker showed the highest efficiency in terms of amplification and species identification. The higher capacity of ITS2 in terms of phylogenetic reconstruction has been proven in previous studies [Sequence analysis using the above four primers showed that the samples studied in this experiment belonged to the genus  studies ,13,29.The origin and ecology of a species are often expressed through its genetic diversity . Many prM. officinalis had high genetic diversity (Ho = 0.513 and He = 0.612) in this study compared to in Luo’s publication for the same species (Ho = 0.3436 and He = 0.2881) [Heterozygosity can reflect the genetic variation in natural populations and is considered a measure of genetic diversity. The higher the heterozygosity in a population is, the more the genetic variability in it is. ST is considered one of the measures of genetic variation in populations. An FST value of higher than 0.15 can indicate significant differentiation in a population [ST value ranged from 0.076 (QN population) to 0.451 (TTH population), with an average FST value of 0.206. This result was higher than that in the study of P. vietnamensis (FST = 0.13) [Cinnamomum balansae (FST = 0.601) [Pulsatilla patens (L.) (FST = 0.22) [ST = 0.13) using microsatellite markers.Fpulation . Therefo = 0.13)  and lowe= 0.601)  and Puls = 0.22)  and  was within subpopulations. These results indicated a relatively low genetic differentiation among the three populations and a high genetic divergence within those populations. Genetic variation among populations was highly influenced by gene flow, selection, genetic drift, and other factors.M. officinalis. Even though the populations were separated by large geographical distances, the majority of individuals from the QB and QN populations shared the same ancestral origin.A Bayesian analysis in STRUCTURE showed two different groups of genetically mixed individuals of ITS1 region and the ITS2 region as reliable markers in the barcoding of M. officinalis. In addition, the results confirmed that M. officinalis had low genetic differentiation among the three studied populations and high genetic divergence within those three populations. The three populations of M. officinalis were divided into genetic groups on the basis of the codominant genotypic distance. Our study of M. officinalis in terms of genetic diversity and population structure is intended to make a large contribution to the conservation of this species.The study proved the


Ziziphus jujuba var. spinosa  were investigated to improve our understanding of plant phylogeographic patterns in Central China. Single‐copy nuclear gene markers and complete chloroplast genome data were applied to 328 individuals collected from 21 natural populations of sour jujube in China. Nucleotide variation of sour jujube was relatively high , which resulted from the mating system and complex population dynamics. Analysis of molecular variation analysis revealed that most of the total variation was attributed to variation within populations, and a high level of genetic differentiation among populations was detected (Fst = 0.197). Relatively low long‐distance dispersal capability and vitality of pollen contributed to high genetic differentiation among populations. Differences in the environmental conditions and long distance among populations further restricted gene flow. Structure clustering analysis uncovered intraspecific divergence between central and marginal populations. Migrate analysis found a high level of gene flow between these two intraspecific groups. Bayesian skyline plot detected population expansion of these two intraspecific groups. Network and phylogeny analysis of chloroplast haplotypes also found intraspecific divergence, and the divergence time was estimated to occur at about 55.86 Ma. Haplotype native to the Loess Plateau was more ancient, and multiple glacial refugia of sour jujube were found to locate at the Loess Plateau, areas adjacent to the Qinling Mountains and Tianmu Mountains. Species distribution model analysis found a typical contraction‐expansion model corresponding to the Quaternary climatic oscillations. In the future, the distribution of sour jujube may shift to high‐latitude areas. This study provides new insights for phylogeographic research of temperate plant species distributed in Central China and sets a solid foundation for the application of the scientific management strategy of Z. jujuba var. spinosa.Phylogeographic research concerning Central China has been rarely conducted. Population genetic and phylogeography of  Nucleotide variation and population differentiation of Ziziphus jujuba var. spinosa were relatively high and a central and marginal population structure was revealed. Multiple glacial refugia were found in central and east China. Population dynamic was found to conform to the contraction‐expansion model corresponding to the Quaternary climatic oscillations and may shift to high latitude areas under future climate conditions. However, the phylogeographic pattern and population demography of sour jujube corresponding to various climate conditions were still yet to be clarified. Phylogeography study of sour jujube may add acknowledgement of the species' evolutionary history in Central China and provide some clues for the potential migration between this area and other adjacent areas.rns Liu, . Genome‐rns Liu, . As the Z. jujuba var. spinosa, (ii) describe the phylogeographic history and the potential location of glacial refugia, and (iii) investigate the population dynamic of sour jujube in China. The present study will improve our knowledge of plant phylogeography in Central China and set a solid foundation for future management and utilization of this important germplasm resource.In the present study, single‐copy nuclear gene markers were utilized to investigate the genetic diversity and population structure of sour jujube distributed across China. Furthermore, chloroplast genome data was used to detect the phylogeographic history of sour jujube. The population dynamic of sour jujube responding to the Quaternary and future climatic changes was also documented. The aims of this study were as follows: (i) determine the genetic diversity and population structure of 22.1Z. jujuba “Hupingzao”) and one Z. mauritiana individual as outgroup in the following analysis. Individuals sampled in the same population were at least 100 m apart. Total DNA was extracted for all sampled individuals from silica gel‐dried leaves using the modified cetyltrimethyl ammonium bromide (CTAB) method.In this study, 328 individuals were sampled from 21 sour jujube populations distributed in China. The geographic information of the populations sampled in this study was illustrated in Figure 2.2Single‐copy nuclear gene markers have been widely used in plant population genetic studies, resulting from their cross‐utility, high variable, and easily processed features  were analyzed for the five loci using Dnasp 5.10.0 , genetic structure analysis was performed in Structure 2.3.4 ) and ΔK was calculated using Structure Harvester  implemented in Arlequin 3.5  as outgroup. The divergence time of the chloroplast haplotypes was detected with BEAST 1.10 , Z. mauritiana, Z. spina‐christi (NC_037152), and Morus indica (NC_008359) were utilized as outgroups. A likelihood ratio test  and this time with a standard deviation of 5 Ma was used to constrain the maximum root age of the phylogeny. Four independent MCMC replications were performed, and each replication was run for 100,000,000 steps and sampled every 1000 steps. The first 25% of the sampled trees were discarded as burn‐in. The program Tracer 1.7.1 (http://tree.bio.ed.ac.uk/software/tracer) was used to confirm that the runs had reached a stationary distribution with sufficient mixing. Figtree 1.3 (http://tree.bio.ed.ac.uk/software/figtree/) was used to visualize the phylogenetic tree.To understand the phylogeography history of sour jujube in China, we sequenced and assembled the complete chloroplast genome of 21 individuals . The chloroplast haplotypes were assigned using Dnasp 5.0, and the median‐joining (MJ) haplotype network was generated in Popart 1.7 .To reconstruct the demographic history of sour jujube and the two intraspecific groups revealed in Structure analysis (see below) over time, the historical demography was inferred from Bayesian skyline plot analyses (BSP) implemented in BEAST 1.10  and M (immigration rate divided by the mutation rate) were calculated with the implemented Fst estimations. Five independent runs by 10 short chains of 5000 steps and 3 long chains of 50,000 steps were run. Genealogies with a sampling increment of 100 and 10,000 burn‐in were recorded.An MCMC maximum likelihood method was utilized to estimate gene flow between two intraspecific groups using Migrate 4.4.3 Beerli, . Two imp2.8The biogeographic boundaries were calculated by Monmonier's maximum difference algorithm in Barrier 2.2  among these sampled populations was calculated by Mantel test using Vegan package implemented in R. Twenty‐three environmental variables of the 21 sampled populations were determined for the current climate layers as used in species distribution modeling analysis (see below). EnvD matrix was computed based on the population score on each bioclimatic variable.2.10www.worldclim.org], soil variable was downloaded from the National Geomatics Center of China, slope and aspect were generated from elevation variable through surface analysis in Arcgis 10.5 ). These environmental variables were held in a GIS as ESRI grids using China Map Grid coordinates. The multi‐collinearity test was conducted by using the Pearson correlation coefficient (r) to examine the cross‐correlation among the variables and variables with cross‐correlation coefficient value |r| ≥ .8 were randomly discarded one and kept the other to minimize the negative influence on modeling. Finally, 10 environmental variables including Bio3 , Bio7 , Bio11 (mean temperature of the coldest quarter), Bio15 , Bio18 (precipitation of the warmest quarter), Bio19 (precipitation of the coldest quarter), elevation, slope, aspect, and soil were kept and utilized in species distribution modeling  and distribution information listed in Zhang et al. (https://esgf‐node.llnl.gov/projects/cmip6/), the value of distribution possibility was reclassified into three hierarchy in Arcgis 10.5: 0–0.33 means unsuitable distribution area; 0.33–0.66 means suitable area and 0.66–1.0 means higher suitable area.Species distribution modeling was performed with Maxent 3.4.4 , indicating that the significant results of Tajima's D, Fu, and Li's D* and F* detected in these loci may result from the presence of recombination within loci or the population structure . Most of the total variation was derived from variation within populations (72.04%–90.94%). The average Fst was 0.197, indicating the relatively high level of genetic differentiation among populations.AMOVA analysis was used to investigate the overall distribution of genetic variation Table . Variatir = .2619, p = .02; EnvD/GenD, r = .3873, p = .001). Analyses of landscape genetics using Barrier 2.2 identified four significant barriers among sampled populations . The MJ network of the chloroplast haplotypes showed that the chloroplast haplotype native to population YCRC was ancestral, which was also supported by BEAST analysis  data containing tens of thousands of SNPs have been widely applied in population genetic research . Nucleotide variation of sour jujube was higher than that of other species distributed in China, such as Populus davidiana , Zea mays ; writing – original draft (lead). Xiaoyan Hu: Formal analysis ; writing – original draft (supporting). Wendong Yu: Investigation . Zhaoshan Wang: Investigation .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.Appendix S1.Click here for additional data file.


Colossoma macropomum) is one of the most important neotropical freshwater fish used for aquaculture in South America, and its production is concentrated at low latitudes , where the water temperature is warm. Therefore, understanding how selection shapes genetic variations and structure in farmed populations is of paramount importance in evolutionary biology. High‐throughput sequencing to generate genome‐wide data for fish species allows for elucidating the genomic basis of adaptation to local or farmed conditions and uncovering genes that control the phenotypes of interest. The present study aimed to detect genomic selection signatures and analyze the genetic variability in farmed populations of tambaqui in South America using single‐nucleotide polymorphism (SNP) markers obtained with double‐digest restriction site‐associated DNA sequencing. Initially, 199 samples of tambaqui farmed populations from different locations , a wild population , and the base population of a breeding program  were genotyped. Observed and expected heterozygosity was 0.231–0.350 and 0.288–0.360, respectively. Significant genetic differentiation was observed using global FST analyses of SNP loci . Farmed populations from Colombia and Peru that differentiated from the Brazilian populations formed distinct groups. Several regions, particularly those harboring the genes of significance to aquaculture, were identified to be under positive selection, suggesting local adaptation to stress under different farming conditions and management practices. Studies aimed at improving the knowledge of genomics of tambaqui farmed populations are essential for aquaculture to gain deeper insights into the evolutionary history of these fish and provide resources for the establishment of breeding programs.Tambaqui or cachama ( Moreover, ddRAD‐Seq could be employed in genomic studies of several aquaculture species, even when limited genomic information was available . Furthermore, the genomic selection signatures were investigated to identify the regions associated with the variations in economic traits and/or adaptation to captive environments in farmed tambaqui in tropical and subtropical regions of South America.22.1Samples were obtained from 361 tambaqui breeders across 12 commercial fish farms in Brazil (BR), Colombia (COL), and Peru (PER) as well as a wild population from the Amazon River  (WILD). A base population used in breeding program research conducted by the Laboratory of Genetics in Aquaculture and Conservation (LaGeAC) at the Universidade Estadual Paulista (UNESP), Jaboticabal  (BRGEN), was also sampled. This population includes individuals from different fish farms and is studied to obtain genomic information, aimed at advancing aquaculture breeding programs for native fish species, with a particular focus on improving growth performance and disease resistance  correspond to samples from subtropical regions, which are characterized by wide variations in temperature . Farmed populations from Colombia (COL1 to COL5) and Peru (PER) correspond to samples from the equatorial regions  of South America, which are characterized by constant and high mean temperatures (~30°C) with very little annual variations. Unfortunately, environmental variables were not recorded during the collection period of farmed fish.The fish farms in Brazil and Colombia are over 20 years old and have adopted intensive breeding systems in large facilities, with more intensified management to supply the increasing demand. The fish farms in Peru are relatively recent (10‐year‐old) and considered less developed than those in other main South American producers. Furthermore, Peruvian aquaculture is dominated by marine species, and tambaqui production remains small scale and at the subsistence level. The commercial identity and localization of the fish farms are confidential. The number of samples collected per population is presented in Table −1) , and all efforts were made to minimize suffering. Fin samples were stored in 95% ethanol at −20°C.All procedures were performed with strict adherence to the recommendations of the National Council for Control of Animal Experimentation (CONCEA) , and the study approved by the Animal Use Ethics Committee (CEUA), number 019006/17. Fin samples were collected from each fish under anesthesia administered using benzocaine solution (200 mg·L2.2Piaractus brachypomus) and pacu (Piaractus mesopotamicus).Prior to genomic analysis, a purity analysis was performed using species‐specific multiplex polymerase chain reaction (PCR)  and standardized to the concentration of 10 ng·µL−1. The purity of the nucleic acid samples was determined using spectrophotometry with NanoDrop™ One (Thermo Scientific™), and the absorbance ratio (A260/A280) was between 1.80 and 2.00. DNA integrity of the samples was visualized using 1% agarose gel electrophoresis. Genomic analyses of data from COL5 and WILD were restricted to a few individuals and affected by the difficulty in obtaining DNA from biological samples. For DNA digestion, the final reaction mixture contained 2.5 µl of DNA  digested with 0.1 µl (10 U·ml−1) of the restriction enzyme MluCI (5′‐…AATT…‐3′) and 0.1 µl (20 U·ml−1) of the restriction enzyme SphI (5′‐…GCATGC…‐3′); 0.6 µl of the CutSmart 10× buffer; and 2.8 µl of water. The conditions for enzyme digestion were 37°C for 60 min. Based on the genome of tambaqui (GCA_904425465.1), computer simulations were performed to evaluate the cut frequency for each restriction enzyme using Nebcutter v2.0 .The ddRAD‐Seq libraries for SNP identification were constructed based on the protocol originally described by Peterson et al. . Briefly Vincze, . The ave Vincze, . Ligatio® High‐Fidelity PCR Kit. This step was necessary to incorporate the Illumina flow cell sequence and regions of the Illumina primer sequences. To increase the number of DNA fragments, 20 independent PCR assays were performed. All reactions were performed in a final volume of 20.0 µl, containing 9.5 µl of H2O, 0.4 µl of 10‐mM dNTPs, 4.0 µl of 5× Phusion HF Buffer, 2.5 µl of P1 5.0 µM Primer, 2.5 µl of P2 5.0 µM Primer, 0.12 µl of Phusion DNA Polymerase, and 1.0 µl of digested DNA. All reactions involved an initial stage of 68°C for 1 min, followed by 12 cycles at 95°C for 10 s, 60°C for 30 s, and 72°C for 30 s, and a final stage of 72°C for 7 min. The PCR samples were grouped in a final volume of 400 µl and were repurified using AMPure XP beads , according to the manufacturer's protocol. The pool of amplified sequences was analyzed by agarose gel electrophoresis. The concentration of each final library was verified by fluorometry using Qubit® 3.0 (Thermo Scientific™). The samples were sequenced on the Hiseq 4000 platform, generating 1.7 G (billions) of paired‐end reads.The enrichment step was then performed via PCR amplification using the Phusion2.3https://catchenlab.life.illinois.edu/stacks/manual/#align), the analysis was initiated with the “process_radtags” module, in which the barcodes were assigned to individuals, and low‐quality sequences and adapters were excluded. After demultiplexing and cleaning, the data were aligned against the tambaqui reference genome (GCF_904425465.1) using Burrows–Wheeler Aligner  with the standard parameters . The resulting variants were filtered to consider only one SNP per locus.Stacks v. 2.1  and expected (He) heterozygosity, average number of alleles per locus (Na), and MAF were estimated using Plink v. 1.07  were predicted with the exact test in Plink v. 1.07  for each fish farm was estimated using the R package hierfstat  for each fish farm was calculated using the linkage disequilibrium method in NeEstimator V2.01   and sampled fish farms. All remaining SNPs were pruned for linkage disequilibrium (LD) using the indep‐pairwise option (‐‐indep‐pairwise 50 10 0.1) in Plink v. 1.07 , Colombia (group COL), and Peru (group PER). BRGEN and WILD were excluded from the analysis. Subsequently, data from the adopted fish farms were grouped into different clusters according to the results of structure analysis and DAPC. The first and second methods were performed using Arlequin v 3.5 . The significance threshold for homologies  was <e33.1p‐value of <1 × 10−6. Subsequently, 1276 SNPs presenting MAF < 0.05 and proportion of missing genotypes >30% were discarded, leaving 5047 SNPs for downstream analyses. All remaining SNPs attained a minimum call rate of 70% individuals in a population .Approximately 300 Gb (billions of nucleotide bases) reads were sequenced through the libraries, resulting in an average of approximately 220 M reads per library. After the application of the quality filters on sequences, approximately 180 M reads per library were retained for SNP characterization. On average, approximately 4 M reads per individual were considered, and a total of 207 M reads were excluded due to ambiguous barcodes. For genomic analysis, 199 samples were considered . A total of 6323 SNPs were obtained after aligning the sequences against the tambaqui reference genome (GCA_904425465.1), excluding SNPs with a quality score of <20, minimum allele count of <4 reads, and HWE 3.2The descriptive statistics of genetic diversity for each population are presented in Table a, Ho, and He values than the farmed populations from Brazil (BR). The diversity estimates of farmed populations from Colombia and Peru were similar to those of the wild population (WILD). Markers with rare alleles and lower MAF values were more abundant in farmed populations from Colombia , except COL3, whereas farmed populations from Brazil presented higher MAF frequencies. All inbreeding coefficients (FIS) were positive, ranging between 0.060 (BR1) and 0.357 (BR3), and the SNP loci were in Hardy–Weinberg disequilibrium in most populations (except COL5 and WILD)  was low and variable among the farmed populations, ranging from 9.8 in BRGEN to 75.6 in COL5. Ne could not be estimated for WILD because the confidence interval extremely large (infinite), making the values unreliable. Ne estimates for COL5 should be interpreted cautiously because of the small number of individuals analyzed. The Ne estimates for inbreeding rate (∆F) per generation ranged from 0.9% in BR6 to 5.1% in BRGEN  and Peru (PER) presented lower N to COL5 3.3FST values using SNP loci . In FST pairwise analysis  (~93%), whereas the genetic variance among groups (FCT = ~3%) and among populations within groups (FSC = ~3%) was significantly low  and DAPC results . There were no significant differences between the two models. The highest proportion of genetic variance was present within the populations  and H (obs FST = 0.335–0.430)  models. The visualization of IBS and DAPC (5 PCs retained) revealed two distinct clusters: one formed by the COL and PER samples and the other formed by the BR samples , and the second group was composed of farmed populations from Colombia  and Peru (PER). The analysis was performed using two different software and three different methods. A graphical representation of the outliers identified by the Arlequin  and Bayescan methods is provided in Figure s Figure  and b.Regarding annotation of the putative SNP outliers, 36.6% SNPs were found in transcript regions, 35.1% were classified as intron variants, 9.3% were classified as upstream gene variants, and 9.0% were located in intergenic regions, and the closest gene was identified. Regarding the effects of SNP outliers, we imputed the overall impact of all variants as largely modifying (97.6%)  in the farmed populations was moderate or high, contrary to the pattern of low genetic variability in farmed tambaqui populations demonstrated in a previous analysis based on mitochondrial DNA and microsatellite data  to unveil the genetic variability and population structure of farmed tambaqui populations in South America. Considering the massive amount of genetic data, the genetic diversity . Moreover, AMOVA revealed the highest significant differentiation within populations  and not between groups . Considering the panmictic nature of the wild populations from the Amazon Basin , nine were related to stress response and six were related to immunity (Table ATF6) , which were involved in the muscle development and growth of threespine stickleback (Gasterosteus aculeatus) under different temperatures , which is involved in stress response to repeated handling in Senegalese sole; suboptimal rearing conditions in Gilthead seabream , which has been mapped to differentially expressed transcripts related to handling and confinement stress response in rainbow trout , which is involved in the neuroendocrine regulation of feeding and, possibly, in the reallocation of energy under stress response  and the 12 outliers detected by both Arlequin methods  and Bayescan methods in the tambaqui populations.Click here for additional data file.Fig S2a. Population structure analyses based on the putative SNP outliers using IBS method.Click here for additional data file.Fig S2b. Population structure analyses based on the putative SNP outliers using DAPC method, visualized after retaining 5 optimum PCs.Click here for additional data file.Table S1Click here for additional data file.


Manduca sexta). We show that hornworms from Arizona, Kansas, and North Carolina are genetically distinct, with Arizona being particularly differentiated from the other 2 populations using Illumina whole-genome resequencing. Peaks of differentiation exist across the genome, but here, we focus in on the most striking regions. In particular, we identify 2 likely segregating inversions found in the Arizona population. One inversion on the Z chromosome may enhance adaptive evolution of the sex chromosome. The larger, 8 Mb inversion on chromosome 12 contains a pseudogene which may be involved in the exploitation of a novel hostplant in Arizona, but functional genetic assays will be required to support this hypothesis. Nevertheless, our results reveal undiscovered natural variation and provide useful genomic data for both pest management and evolutionary genetics of this insect species.Many species that are extensively studied in the laboratory are less well characterized in their natural habitat, and laboratory strains represent only a small fraction of the variation in a species’ genome. Here we investigate genomic variation in 3 natural North American populations of an agricultural pest and a model insect for many scientific disciplines, the tobacco hornworm ( One of the main objectives of evolutionary genetics is to unite the proximate molecular function of genes with the long-term evolutionary forces that govern their change . The 2 hDrosophila. Early pioneers of evolutionary genetics noted that Drosophila collected from different locations often had differing arrangements of genes along their chromosomes, in other words, inversion polymorphisms within and between populations  is a well-established laboratory model , tomatoes, peppers, and generally other plants in the nightshade family, Solanaceae , Kansas (n = 4), and Arizona (n = 8); see For an initial characterization of genetic variation in this broadly distributed species, samples were chosen, based on availability, to maximize the geographic range represented while still sampling local populations with enough individuals to detect large changes in allele frequency. Specifically, samples from 3 states in the United States were examined in this project: North Carolina , following the manufacturer’s protocol. DNA was isolated via phase-separation with chloroform and precipitated with ethanol. DNA pellets were resuspended in buffer and sent for Illumina sequencing with Novogene Sequencing . Quality control and library preparation followed the company’s standard and sequencing generated 150 bp, paired-end reads sequenced to an average depth of 14–20× coverage across the genome  genome assembly for several years .For some of these analyses, it was necessary to analyze the genotypes of single nucleotide variants. To generate sets of high-confidence variants, the curated alignments were taken through GATK v 3.7’s best practices pipeline for SNP calling  for use in polarizing allele frequencies, using the following parsimony logic.Finally, some inferences of population differentiation relied on differences in allele frequency between locations. For polymorphic sites, estimation of allele frequency depends on inference of which of the alleles  is ancestral, otherwise allele frequencies are collapsed to the range  and information is lost. To infer ancestral state at a given site, variation in M. sexta but not in M. quinquemaculata showed the reference allele in the outgroup; thus, the reference allele was taken to be ancestral and left as was. For each site that varied in both M. sexta and M. quinquemaculata, allele identities were compared between species. If the alternate allele in M. quinquemaculata was shared with the alternate allele in M. sexta the alternate allele was inferred to be ancestral, and the reference derived. Likewise, if the outgroup was heterozygous at the site, but shared only one allele with the focal species, that allele was inferred to be ancestral . Considering both of these scenarios, a total of 1,327,986 sites were updated in the reference. In a minority of cases , there was no most-parsimonious solution. These sites were updated to “N” at the site in the new ancestral reference to mask them from analysis . The code to generate the updated reference was written in R and can be found in the git repo listed in Data accessibility.In a majority of cases, polymorphic sites did not overlap with divergent sites as well. In other words, these sites that varied in M. sexta reference contains no chromosomal linkage information for its scaffolds. The older assembly does have linkage information however, from previous ortholog counting analyses comparing M. sexta to B. mori to identify and separate sex-linked scaffolds; this effort generated a chromosome identity for each scaffold, but did not contain information about the ordering of scaffolds within a chromosome . Curiously, the newer romosome . To anchK) was determined by assessment of ten bootstrapped replicates each for possible K values from 2 to 6, evaluated using the logic from CLUMPAK’s web-hosted application  could create spurious patterns. The autosomal genome was used to infer population structure while accounting for uncertainty in genotyping using the software NGSAdmix v. 3.2 . For theFST (excluding the Z chromosome) analyzing the curated alignments with the population genetic software ANGSD v. 0.916  and nonsilent (zero-fold degenerate) sites to assess whether differentiation skewed toward silent sites or those more likely to be under selection. Identification of zero-fold and 4-fold degenerate sites was completed in previous analyses with custom R scripts . All pairwise comparisons were performed: North Carolina (NC)—Arizona (AZ), Kansas (KS)—Arizona, and NC—KS. For these analyses, published chromosome assignments of scaffolds were employed for the older assembly  carried the ancestral or derived orientation in the putatively inverted regions, genetic diversity was examined as follows. Single-nucleotide polymorphism (SNP) frequencies were examined in each population, under the logic that if loci within an inversion cannot freely recombine with the noninverted orientation, they should share allele frequencies across longer distances than those outside of the inversion. For these analyses, the polarized allele frequencies described above were used. SNP variant files (vcfs) were generated for each population and alternate allele frequencies were extracted and examined. Beyond allele frequency, the allele identity was also examined. The VCFtools utility “extract-FORMAT-info GT” , π4 (variation at 4-fold degenerate sites), Tajima’s D0, and Tajima’s D4 . These metrics were all calculated using alignments to the Kanost et al. assembly for reasons of gene model quality described below. Metrics related to pN/pS relied on SNP calls from the vcf files but estimates of π and Tajima’s D were performed directly from alignments using angd’s “saf2theta” command. In addition, we calculated ρ2 linkage disequilibrium for nonoverlapping 50-bp windows across the more contiguous Gershman assembly using the vcftools utility “–geno-r2”. These results are reported in Finally, in the interest of establishing baseline metrics for these populations, we calculated a number of population genetic summary statistics. In particular, we calculated measures of variability: pN (nonsynonymous changes per nonsynonymous site), pS (synonymous changes per synonymous site), pN/pS the scaled ratio of nonsynonymous variation, Manduca sexta has a wealth of available RNA sequence data from both sexes and different life-stages, aggregated as a set of RNAseq collected by M. sexta based on a set of tissues collected in all 3 stages . Tissue specificity within a stage was based on tissue types available for that stage  but also extensive conservation of sequence along these chromosomes  are lowest in Kansas, the population with the fewest sampled individuals. Still, the relative amount of nonsynonymous variation scaled by synonymous variation (pN/pS) is remarkably consistent across populations, suggesting the strength of selection relative to drift is comparable across states. Moreover, Tajima’s D is more negative at zero-fold sites (i.e. those exposed to selection) than 4-fold  in each population, which further implies a role for directional selection in each population. Finally, apparent linkage disequilibrium is inversely correlated with sample size, as expected if artificially tight associations are observed between common alleles due to shallower sampling failing to capture rare alleles.To start, we provide population genetic summary statistics for each state in FST set a baseline level of differentiation of 0.04–0.09, depending on the pairwise comparison between states , 3 heterozygous for it , and one homozygous for the ancestral orientation (A85). Note that the heterozygous individuals correspond to those inferred to be admixed with Kansas and the one homozygous noninverted individual was grouped with Kansas completely in structure analyses. As discussed above, removing chromosome 12 from structuring analyses leads to less similarity between AZ and KS samples, suggesting the inversion presence/absence is large portion of the signal of the Arizona population. A scan of linkage disequilibrium along the chromosome  showed eΧ22 = 1.31, P = 0.518), lifestage-biased composition , or tissue-biased composition  compared to the rest of the genome. Thus, even if there is a set of locally adaptive alleles in this region, it is not one enriched for any of the annotations available to us. Nevertheless, we identified one gene of interest in this region thanks to a misassembly.The large size of this inferred inversion (roughly 8 Mb and 321 genes contained within) makes identifying a causal adaptive locus challenging. We used the RNA sequencing metadataset to classify genes as specific to one sex , life stage , and tissue  if a given gene showed 70% or more of its expression exclusively in that category. By this metric, the putative inversion on chromosome 12 does not differ in sex-biased composition (Msex2.02572 and Msex2.02573) with highly differentiated SNPs localized to areas outside the coding region of either. These variants may be truly neutral or impact the regulation of the nearby genes, but without a better understanding of regulatory elements (e.g. promoter sequences) in this species, it is impossible to say. The peak previously assigned to chromosome 13, deserves more consideration however.Both the ostensible chromosome 2 and 13 peaks from the more fragmented assembly belong to the putatively inverted region of chromosome 12 in the newer assembly. The former is rather unremarkable, some 50 kb of a scaffold containing 2 annotated genes  starting around 200 kb and continuing for the remaining 100 kb . This reM. sexta appear to truly differ from the other populations with regard to the molecular evolution of this gene, which begs the question of the gene’s functional role. Msex2.10493 is overwhelmingly (98.2%) expressed in larvae compared to 1.8% adult expression and vanishingly small pupal expression. Within larvae, this gene shows 97% of its expression in the antennae and another 2.8% in the head.The massive difference in called variants theoretically could arise from population-specific differences in mapping rates in this region, either through poor mapping in populations with low SNP counts or (far less likely) a pile-up of reads in Arizona owing to a collapsed segregating paralog. To rule out these artefactual explanations, we examined per-base coverage around this gene and found no differences between populations , but the remaining 1/3rd, including the coding region for osome 12 . This paMsex2.10493 is homologous to the new assembly’s XM_037442453.1, which lies in the inverted region (roughly 9.257–9.261 Mb into chromosome 12). Additionally, the frequency of the stop-loss is 0.6875 (=11/16) and matches that of the most common SNP frequency within the inversion. Moreover, the genotypes  of the inversion perfectly match the stop-loss variant’s genotype. In conclusion, this potential pseudogene sits in the middle of the inferred inversion on chromosome 12, but it was only identified thanks to a serendipitous misassembly in the older version of the M. sexta reference.More direct evidence suggests that this potential pseudogene lies within the chromosome 12 inversion. First, the coding sequence of the old assembly’s The Z chromosome’s outliers are attributable to roughly 1 Mb in the middle of the chromosome-level scaffold (HiC_scaffold_19). The scale of elevated differentiation suggests another inversion, and our structural variant scan identified an inversion that precisely overlaps this region . Further evidence for a lack of recombination in this region can be seen in the nonreference allele frequencies which vary across the scaffold in both NC and AZ but show a tract of SNPs with a common frequency of 0.93 (=13/14) within the putative inverted region in Arizona .Χ22 = 11.36, P = 0.0034), compared to the rest of the Z, which is significantly masculinized, as reported previously . This region contains 3 full annotated genes , but no SNPs within coding regions.Chromosome 6 shows a single peak of divergence, though this region is only weakly differentiated, barely meeting our cut-off threshold for exploration (Msex2.05775-Msex2.05786), but none of these shows skews in coding region SNPs between populations as extreme as seen on the potential pseudogene mentioned above. However, 2 genes do show more modest deviation between states. Msex2.05777 is variable in both North Carolina  and Kansas  but monomorphic  in Arizona. Conversely, Msex2.05784 is nonvariable in the North Carolina and Kansas samples but contains 3 nonsynonymous variants and one synonymous variant in Arizona.Two outlier scaffolds in the older assembly localize to chromosome 19; both represent differentiation between Arizona and the other 2 states. In the newer, more contiguous assembly, these peaks remain distinct from each other , suggestFST window size. In any case, the entire scaffold contains 11 annotated genes, many of which have no expression data and no called SNPs in any population. As such, we do not place much emphasis on the differentiation around these dubiously annotated regions.The second peak, on scaffold00419, seems to span the length of this 200 kb scaffold, but this may reflect the limits of resolution of our M. sexta populations across the United States. In brief, we found that individuals from 3 populations across an east-west transect are genetically differentiated. This result may not seem surprising, but studies of other Lepidoptera have at times found evidence for continent-wide panmixis  is on par with the differentiation between migratory North American monarchs and the Hawaiian population that is thought to have split roughly 200 years ago  putative inversions, are key contributors to the variation between populations. Sustained tracts of differentiation are most apparent on 2 chromosomes, the Z chromosome and chromosome 12. In both cases, the Arizona population is distinct from Kansas and North Carolina. We note that the smaller sample size of Kansas The inversions discussed below are the most apparent sources of regional differentiation, but chromosomes 6 and 19 also showed elevations in differentiation at smaller scales. For the most part, differentiated regions fell outside of coding regions or near dubiously annotated genes (i.e. those not supported by expression data). Lacking further information for hypothesized importance, they are not discussed in detail here for brevity’s sake.ST scan. This signal belonged to a single block of sequence, spanning 8 Mb , containing over 300 annotated genes, and found at a frequency of almost 70% in the Arizona population. Individuals that are heterozygous for this putative inversion or lacking it entirely cluster more closely with the Kansas population than other Arizona samples which are homozygous for it. When removing chromosome 12 from analyses, all Arizona samples cluster more closely with each other than with Kansas however, suggesting that the 2 populations are differentiated across the genome, but that the sheer number of variants associated with the putative inversion swamps other signals. These 2 observations combine to suggest that the inversion has been segregating in the population for some time or that selection on some variant(s) in the inversion has driven frequency changes at all linked loci.A long tract of chromosome 12 showed high levels of differentiation in our Fare fitness costs in other environmental backgrounds. Indeed, linkage disequilibrium is higher within the bounds of the inverted region even in populations in which we did not detect the variant, suggesting a dampening of gene flow between populations here. From this perspective, the common chromosome 12 variant seems likely to be at least selectively neutral, if not beneficial, in Arizona. However, the large number of encompassed genes present a challenge for identifying selectively relevant loci from purely computational methods. Still, one gene of interest arose from our efforts to cross-check results with the older M. sexta reference . In this regard, this single gene is one of many potential candidates for ecologically significant differentiation in the inversion; its misassembly is the main cause of our additional scrutiny and it may hold no special relevance for the Arizona population. Still, the patterns of variation are striking here. This gene carries almost no variation in North Carolina or Kansas but has a wealth of high frequency variants (61 SNPs in our sample) in the Arizona population, one of which is a predicted stop loss in the coding region. A large-effect SNP like this could easily break the protein function via translation of otherwise noncoding DNA. While inconclusive from molecular data alone, a relaxation in selective pressure at this gene would allow for pseudogenization and subsequent accumulation of numerous variants. And indeed, the high frequency of this stop-loss suggests that it cannot have an appreciable fitness cost, or it would not have persisted in the population. Naturally, this raises the question of what function this gene has that it could be lost without strong selective consequences. Or, alternatively, could a loss of function be adaptive under certain circumstances?An Msex2.10493 gene is almost exclusively expressed in larval antennae, which are known to play a role in olfaction and food choice in M. sexta  has shown that knockout of a single chemoreceptor is sufficient to turn naturally specialist larvae into generalists  in all but one individual. As discussed above, an inversion is unlikely to reach such high frequency without some selective advantage.M. sexta , compared to the rest of the Z chromosome, which is male biased . As has Moreover, these sex chromosome dynamics intersect with the population genetics of local adaptation in synergistic ways. Modeling suggests that the exposure of recessive alleles to selection should facilitate local adaptation and make the sex chromosomes hotspots for this phenomenon . This finer-scale sampling will be particularly important for agricultural centers on the applied side, and additional sampling will also provide more insight into the large-scale variation we report here.We report that M. sexta, with each sampled state separated from the others by at least 1,500 km, it is impossible to say if these segregating variants also follow a cline in the region or to which climactic variables they may relate. Additional sampling of the Southwest will be required to assess how widespread the inversions are.At least 2 large inversions and a potential pseudogene differentiate Arizona from the Kansas and North Carolina populations. All of these variants are high frequency (>0.5) within Arizona but absent in the other populations. However, the nature of our sample collection limits the inferences we can make at present. For instance, the high frequency of the variants suggests they are not deleterious, but with only a single time-point of sampling in Arizona, it is hard to say whether or not these variants have reached an equilibrium frequency. Additionally, other studies have shown inversion polymorphisms to follow geographic or environmental clines (Likewise, controlled laboratory studies will be required to assess the fitness consequences of the segregating stop-loss in a larval antennal gene within the chromosome 12 inversion. In particular, the coincidence of a novel larval hostplant in Arizona and a large-effect mutation in a gene expressed in a larval chemosensory gene are suggestive but far from conclusive. The relationship between the 2 will require hostplant choice experiments for larvae with and without the stop-loss mutation.Finally, it is worth noting that these dramatic differences between populations could not be observed in standard lab strains, which are all derived from the North Carolina population to our knowledge. On the other hand, without extensive lab studies and RNA-sequencing, we would not have the information to form functional hypotheses for these variants found in wild populations. Beyond the immediate utility of these data, the results we present here serve as a reminder of the efficacy of integrating laboratory and field research within the same study system.All newly generated sequencing data are available with the following accessions: SRP144217, PRJNA639154 on NCBI. Accessions for RNAseq used in functional inference can be found in G3 online.jkac047_Supplemental_MaterialClick here for additional data file.