Tetranychus truncatus Ehara and Tetranychus pueraricola Ehara et Gotoh, which have wide distributions, short generation times, and large population sizes. We generated genome resequencing of 246 spider mites mostly from China, as well as Japan and Canada at a combined total depth of 3,133×. Based on demographic reconstruction, we found that both mite species likely originated from refugia in southwestern China and then spread to other regions, with the dominant T. truncatus spreading ~3,000 years later than T. pueraricola. Estimated changes in population sizes of the pests matched known periods of glaciation and reinforce the recent expansion of the dominant spider mites. T. truncatus showed a greater extent of local adaptation with more genes (76 vs. 17) associated with precipitation, including candidates involved in regulation of homeostasis of water and ions, signal transduction, and motor skills. In both species, many genes (135 in T. truncatus and 95 in T. pueraricola) also showed signatures of selection related to elevation, including G‐protein‐coupled receptors, cytochrome P450s, and ABC‐transporters. Our results point to historical expansion processes and climatic adaptation in these pests which could have contributed to their growing importance, particularly in the case of T. truncatus.Local adaptation is particularly likely in invertebrate pests that typically have short generation times and large population sizes, but there are few studies on pest species investigating local adaptation and separating this process from contemporaneous and historical gene flow. Here, we use a population genomic approach to investigate evolutionary processes in the two most dominant spider mites in China,  Then, we used CLUMPAK  and nucleotide diversity (θ) in ANGSD 0.929  for each population were calculated in the program BCFtools 1.9  of different species of Tetranychus  based on density of heterozygotes  models to estimate variation in effective population size , we, respectively, chose appropriate value ranges of K = 12–16 and K = 4–7 for latent factors of T. truncatus and T. pueraricola based on the ADMIXTURE analysis , pairwise nucleotide variation (θπ) ratios and selection statistics (Tajima's D) between different groups of the two species. These values were calculated with VCFtools v0.1.13  to calculate the genome‐wide distribution of genetic differentiation  were located in non‐coding regions and 0.88 million SNPs (19.7%) were located in coding regions: 10.6% were synonymous and 7.5% were non‐synonymous, with a non‐synonymous/synonymous ratio of 0.707. For T. pueraricola, 3.02 million SNPs (80.7%) were located in non‐coding regions and 0.72 million SNPs (19.3%) were located in coding regions: 9.6% were synonymous and 7.8% were non‐synonymous, with a non‐synonymous/synonymous ratio of 0.815 , eastern China  and Japan (JA), midland and northwestern China, northeastern China ; Group V and Group VI comprised T. pueraricola populations from southwestern China  and other areas of China .The phylogenetic and ADMIXTURE analyses clearly separated the two species .The principal component analysis (PCA) supported the grouping results Figure . The firs Figure , which hs Figure . PC1 of FST) between Group II and other groups (Table T. truncatus and T. pueraricola in Jiangxi (JX and JXtp).The ML tree inferred from Treemix explained up to 99.99% of the variance between populations when being added with 10 migration edges Figure . Among 1ps Table  also sup3.3πθ) for the 4 spider mites  was 5.54 × 10−4. The genome‐wide πθ value ranged from 2.74 × 10−4 to 6.66 × 10−4 and 3.59 × 10−4 to 1.06 × 10−3 for T. truncatus and T. pueraricola, respectively,  were fewer and shorter for both T. truncatus and T. pueraricola in average number and size in southern (Group I) and southwestern (Group V) China  by pairwise sequentially Markovian coalescent analysis , Asian populations have been gradually expanding  in colonized regions. Meanwhile, a hybrid population, GStp, in midland China was derived from admixture of the ancestors of YNL (43%) and Group VI (57%) in a short time  China diverged ~4,392 years ago from the lineage ancestral to contemporary southern populations, with an effective population size of 545K. Then, the southern lineage admixed with northern populations which diverged an estimated ~4,152 years ago from Group III eastern populations (Group II) and emerged as the eastern lineage Group II.Based on the population structure analysis Figure , we assils Table . Accordis Figure . The T. e Figure . The T. 3.5K = 16 and K = 7, respectively, for T. truncatus and T. pueraricola for which the estimates of genomic inflation factors (λ) were close to 1.0  followed by the exon region  in T. truncatus, higher than for T. pueraricola  and arid  regions, while clusters for T. pueraricola were not related to precipitation  and that of T. pueraricola was 1.7 × higher (25.13% vs. 15.03%), which suggested that precipitation may play a more important role in local adaptation by T. truncatus.The LFMM analysis indicated a number of SNPs that were significantly associated with precipitation  based on the PCA of these two spider mites . The target gene NP‐R9 exhibited markedly higher FSTand log2(θπ ratio) but lower Tajima's D values , and Tajima's D values of associated loci were not always significantly different from adjacent regions . The genome areas associated mostly with significant loci were upstream of the neuropeptide receptor NP‐R9 , and Tajima's D values of candidate loci in T. truncatus along with more genes strongly associated with precipitation, while adaptation to precipitation in T. pueraricola appeared weaker. These results suggest that adaptation to climate might also influence the relative ranges of these pests in the future. Understanding how pests respond to climate stresses can aid in predicting future invasion and outbreaks. For instance, an invasive distribution range may be under‐predicted when temperature adaptation occurs, as in the case of Halotydeus and T. evansi mites  began to increase almost 30 years ago  of spider mites was lower than estimates for most animals and plants that have been characterized, such as the giant panda  is expected to be intense. Given that high genomic diversity can facilitate adaptive shifts, T. pueraricola in Gansu with high diversity  had higher gene flow  with temperature than with precipitation and elevation in both mites (Figure Ne which partly reflected past temperature, these may indicate spider mites are susceptible to temperature selection. There has been much research on temperature effects on development, fecundity, longevity, and pesticide impacts in spider mites (Auger, Guichou, & Kreiter, Many SNPs were significantly associated with climate and elevation in s Figure . Along wT. truncatus. Three genes with amino acid replacements, NP‐R9, TuGR254, and TuGR400 (Figure Tribolium might help this xerophilous insect to effectively control water reabsorption (Hauser et al., Arabidopsis face drought and high‐salinity environments (Uno et al., Many genes were found to be significantly associated with precipitation in 0 Figure , belong 0 Figure . A vasopT. truncatus and T. pueraricola showed many genes associated with elevation, many of them are not well annotated (Table Although both ed Table . A denseed Table c includeed Table . Other sπθ (Table T. truncatus vs. T. pueraricola populations from the same location suggest that T. truncatus may have undergone stronger purifying selection despite having lower levels of genomic variation. Experimental studies suggest that rates of adaptation are linked to genome‐wide genetic diversity (Ørsted, Hoffmann, Sverrisdóttir, Nielsen, & Kristensen, T. truncatus appears to have adapted despite lower diversity. It will be interesting to carry out quantitative assessments of genetically based fitness differences across populations to assess the extent to which populations from the two species are locally adapted and whether the molecular data might link to trait differentiation within and across populations (e.g., Drosophila melanogaster and Carabus japonicus; Weeks, McKechnie, & Hoffmann, The higher number of SNPs associated with local adaptation and the lower θπ Table  in T. trNone declared.X.Y.H., L.C., and J.T.S. designed the research. L.C., P.Y.J., and D.S.Z. collected materials. L.C. performed all experiments and analyses. J.T.S., P.Y.J., X.L.B., X.F.X., and A.H. took part in designing a few analyses and explaining the results. L.C., X.Y.H, and A.H. wrote the manuscript.Fig S1‐S13Click here for additional data file.Table S1‐S14Click here for additional data file.


Wild pigs are the most abundant wild exotic ungulate in the United States. In Texas, particularly, they are abundant and represent a threat to ecosystems, agriculture and humans. Our objective was to apply a landscape-scale analysis of population genetic structure of wild pigs to aid in their management in southern Texas. We used microsatellites to assist large-scale applied management. We found that some populations were isolated from one another. However, many individuals and local populations were admixed, which indicates that multiple introductions and artificial movement of individuals has occurred. Wild pig management efficiency and effectiveness may be able to improve if illegal translocations stop  and if management cooperatives are created to manage spatially extensive areas of southern Texas.Sus scrofa) alter ecosystems, affect the economy, and carry diseases that can be transmitted to livestock, humans, and wildlife. Understanding wild pig movements and population structure data, including natural population boundaries and dispersal, may potentially increase the efficiency and effectiveness of management actions. We trapped, conducted aerial shootings, and hunted wild pigs from 2005 to 2009 in southern Texas. We used microsatellites to assist large-scale applied management. We quantify broad-scale population structure among 24 sites across southern Texas by computing an overall FST value, and a Bayesian clustering algorithm both with and without considering the spatial location of samples. At a broad geographic scale, pig populations displayed a moderate degree of genetic structure (FST = 0.11). The best partition for number of populations, based on 2nd order rate of change of the likelihood distribution, was K = 10 genetic clusters. The spatially explicit Bayesian clustering algorithm produced similar results, with minor differences in designation of admixed sites. We found evidence of past (and possibly ongoing) translocations; many populations were admixed. Our original goal was to identify landscape features, such as barriers or dispersal corridors, that could be used to aid management. Unfortunately, the extensive admixture among clusters made this impossible. This research shows that large-scale management of wild pigs may be necessary to achieve control and ameliorate damages. Reduction or cessation of translocations is necessary to prevent human-mediated dispersion of wild pigs. Wild pigs ( Large-scale management of wildlife populations has increased in recent decades in response to invasive species, animal disease, and similar challenges, all of which threaten entire ecosystems and humans. For instance, invasive species may affect ecosystem function by changing the flow of energy and biomass, disrupting disturbance regimes, and changing the physical structure of ecosystems ,2,3. InvSus scrofa) are distributed through much of the world and have become invasive in most of their range. Wild pigs are the most abundant wild exotic ungulate in the United States. Wild populations in the United States are a mixture of domestic pig, Eurasian wild boar, and the hybrids of these two forms [Wild pigs  or with the best available knowledge. Traditional wildlife investigations, involving tagging and radio-telemetry, can provide valuable information on animal movements and dispersal but are time-consuming and limited by constraints on sample size. Accordingly, an increasing number of studies use genetic information to assist large-scale applied management ,17,18,19Our objective was to apply a landscape-scale analysis of population genetic structure of wild pigs to aid in their management in southern Texas. This region includes agricultural areas where landowners experience significant damage to crops, rangeland ecosystems, and natural resources due to abundant populations of wild pigs. This is also an area where wild pigs are hunted recreationally and live-trapped for commercial pork markets. Understanding how wild pig populations are structured will provide a foundation for development of contingency plans in the event of exotic disease outbreaks and assist in the delineation of management zones to establish more effective management strategies. We obtained tissue (muscle) samples from wild pigs at 24 sites  throughoWe estimated allelic richness  and evalST value [q-values) for each individual, based upon MCMC runs where K was set at the best fit, were used to define cluster membership. Individuals were considered to be assigned to a cluster if q > 0.8; individuals with q < 0.8 were considered admixed.We evaluated genetic structure and differentiation among populations using both fixation statistics and Bayesian clustering methods. We quantified broad-scale population structure among the 24 sites by computing an overall FST value , which mST value . We usedST value , to deteSecond, we also performed a Bayesian clustering analysis that used spatial information and implemented in the program BAPS 4.2 . This Baadegenet package [adegenet package [Third, we conducted a Principal Components Analysis (PCA) using the  package ,36 for R package  using thp > 0.09; We genotyped 1258 adult (≥1 year old) wild pigs from 24 sites at 13 microsatellite loci . We deteST = 0.11 ± 0.005). The FST pairwise comparisons among the 24 sites ranged from 0.030 to 0.312, with 236 pairwise comparisons statistically different from 0.0, ST values generally corresponded to the Ds values. The WILL and AR were the most genetically divergent sites . At a broad scale, wild pig populations displayed a moderate degree of genetic structure , LS, SGE, KEN, and SAD, differed from the Structure 2.2 partition . The LS Wild pig populations were structured genetically across southern Texas, indicating that some populations were isolated from one another. However, many individuals and local populations were admixed, which indicates that multiple introductions and artificial movement of individuals has occurred. Furthermore, the genetic clusters were not responding to isolation by geographic distance; some members of the same cluster were widely dispersed. A degree of admixture in populations of wild pig is not surprising. Wild pigs have been present in Texas for more than 300 years and are derived from a mixture of escaped domestics and wild pigs from Eurasia released for hunting . HoweverThe two Bayesian approaches implemented here produced similar results, with minor differences in number of clusters. Whereas the Structure analysis supported 10 clusters as the best partition given the data, BAPS identified 12 clusters when spatial locations were considered. Structure was inconclusive assigning 7 sampling sites to a discrete genetic cluster due to the high degree of admixture. The BAPS algorithm clustered the 7 admixed populations as a single genetic cluster. The discrepancy, although slight, may be partly due to different method of clustering . This incongruence between Structure and BAPS has been frequently reported, and BAPS tends to increase the number of clusters ,39,40,41Unfortunately for practitioners tasked with managing wild pigs, we identified few barriers to movement other than urban areas and expansive agriculture. The conversion of additional rangeland to crops that might form a suitable barrier is not recommended and urban development tends to radiate outward from existing sites. Therefore, wild pig damage will likely continue or intensify in the foreseeable future in the region. Lack of substantial geographic barriers to movements indicates that achieving long-term wild pig control may be difficult due to large geographic extent of populations and ability to re-colonize managed areas from nearby viable populations. Texas has very little public land (<3%), and current management efforts aimed at alleviating local damage are conducted at relatively small spatial scales, from a few hundred to several thousand ha ,48. The Large-scale management of wild pigs may be necessary to achieve control in extreme circumstances, such as a foreign animal disease outbreak . New management tools will be needed for such contingencies, lending support for ongoing research on toxicants ,49,50, fTranslocations had a persistent effect on genetic structure. Therefore, it will be difficult to use molecular tools to verify point of origin for illegal translocations or disease management  because These results are an attempt to understand the genetic structure and movement patterns of feral pigs in southern Texas. We expect that this study will have a significant impact increasing the efficiency of control methods and helping define the geographic area over which control methods should be conducted to achieve long-term results. However, the degree of human-mediated admixture, involving individuals from disparate populations, may have complicated the genetic analyses. The admixed sites are located in an area where large contiguous properties are rare; thus, illegal translocation may be common in the area, exchanging pigs from one property to others. It appears that the Structure partition may be a more realistic and coherent partition due to highly degree of admixture and landscape characteristics among the admixed sites. Differences in USA wild pig populations compared to Australia and Europe include historical and ongoing undocumented translocations and water lack or availability distributed along the landscape for livestock. These two factors contribute to a high degree of admixture among wild pigs in USA. Management cooperatives may be necessary to manage spatially extensive areas of southern Texas. Facing the difficulty of large-scale wildlife management for diseases, damages, and invasiveness, wildlife management personnel may be able to improve the efficiency and effectiveness of large-scale management if they can consider terrain features that affect animal movements and population structuring.


Allium altaicum is a relict plant of the Ice Age and natural populations are located in extreme climatic conditions of Kazakstan’s Altai Mountains. Mobile genetic elements and other interspersed repeats are basic components of a eukaryote genome, which can activate under stress conditions and indirectly promote the survival of an organism against environmental stresses. Detections of chromosomal changes related to recombination processes of mobile genetic elements are performed by various PCR methods. These methods are based on interspersed repeat sequences and are an effective tool for research of biological diversity of plants and their variability. In our research, we used conservative sequences of tRNA primer binding sites (PBS) when initializing the retrotransposon replication as PCR primers to research the genetic diversity of 12 natural populations of A. altaicum found in various ecogeographic conditions of the Kazakhstani Altai. High efficiency of the PBS amplification method used was observed already at the intrapopulation level. Unique amplicons representative of a certain population were found at the intrapopulation level. Analysis of molecular dispersion revealed that the biodiversity of populations of mountainous and lowland A. altaicum is due to intrapopulation differences for climatic zones of habitation. This is likely conditional upon predominance of vegetative reproduction over seed reproduction in some populations. In the case of vegetative reproduction, somatic recombination related to the activity of mobile genetic elements are preserved in subsequent generations. This leads to an increase of intrapopulation genetic diversity. Thus, high genetic diversity was observed in populations such as A. altaicum located in the territory of the Kalbinskii Altai, whereas the minimum diversity was observed in the populations of the Leninororsk ecogeographic group. Distinctions between these populations were also identified depending on the areas of their distribution. Low-land and mid-mountain living environments are characterized by a great variety of shapes and plasticity. This work allowed us to obtain new genetic data on the structure of A. altaicum populations on the territory of the Kazakhstan Altai for the subsequent development of preservation and reproduction strategies for this relict species.Analysis of the genetic diversity of natural populations of threatened and endangered species of plants is a main aspect of conservation strategy. The endangered species  Currently, monitoring and preservation of biological diversity is one of the most important challenges of the contemporary world. Genetic resources and rare populations and their ecosystems form the basis of biological diversity. A change in species and genetic diversity leads to changes in the ecological system, which affects the stability and preservation of any natural ecosystem. Rare relict and endangered plant species with less genetic potential are more susceptible to the threat of extinction due to changes in environmental conditions and impacts of anthropogenic factors . ContinuAllium L. genus are perennial herbaceous plants belonging to the Alliaceae subfamily, the Amaryllidaceae family. Substantially, all onion species are valuable food, medical, or adornment plants and are traditionally preserved by human beings, which leads to significant depletion of their reserves in nature. The Allium L. genus is represented by about 750–800 species. It is one of the largest genera of the Kazakhstani flora, which includes 140 species, 21 species of which occur in the territory of the Kazakhstani Altai, the Saur Manrak, and the Zaisan basin  with RNAse A treatment   .A. altaicum populations. Nucleotide sequences of these PBS sequences are universal for all LTR retrotransposons and belong to highly repeated repeats typical for higher eukaryotes . PCR amplification was performed in a Bio-Rad Thermal Cycler T100 under the following conditions: initial denaturation step at 98 °C for 1 min; 30 cycles at 98 °C for 5 s at 57 °C (depending on primer sequence)  GeneRuler DNA Ladder Mix (#SM0332) was used as a standard DNA ladder. The PCR products were visualized with a ChemiDoc-It2 Imaging System  and a PharosFX Plus Imaging System  with a resolution of 50 µm after staining with ethidium bromide. PBS primers generated in the PCR yielded clearly distinct amplification products, showing considerable variability among the isolates belonging to different populations of A. altaicum.The genetic variability of igned in . PCR reaequence)  for 20 sA. altaicum. Each band of a unique size was assumed to correspond to a unique locus  is a rare plant and a glacial relict. In Kazakhstan, A. altaicum grows in the territory of the Kazakhstani Altai in the following geographical regions: Western Altai ; Southern Altai ; Kalbinskii Altai  and on the Ukok plateau  was observed in Al13 population located at an altitude of 2,146 m above sea level, while maximum values (25.1 g) were observed in plants from the Al9 population.The analysis of indicators depending on the altitude of the populations’habitat shows that in the populations located in the mid-mountain regions , the maximum values of productivity of the generative organs were observed. Lowland and high-mountain populations were distinguished by lower productivity with the exception of the Al12 population, which is located in milder climatic conditions in the territory of the Altai Botanical Garden (Ridder town). The polymorphism of phenotypic traits in the studied populations is clearer when differentiated by altitude of distribution range than by geographic location.A. altaicum revealed clearly distinguishable amplicons whose number varied depending on the primer used. The level of the detected polymorphism and saturation of the amplification range were the efficiency criteria for the primers used. 165 PCR fragments were obtained in total, of which 150 were polymorphic between the studied samples  varied from 0.689 for primer 2,257–0.831 for primer 2,373, with an average value of 0.761. All studied primers had PIC values above 0.5, which indicates the efficiency of their use when studying the genetic polymorphisms of Allium altaicum. The minimum values of the Shannon biodiversity index (I) were obtained when using primer 2,373 and the maximum values when using primers 2,221 and 2,249.Depending on the primer, the number of informative amplifiable fragments varied from 15 to 39 and their size varied from 500 to 3,500 bps. The polymorphism level varied from 74% to 100% and was sufficient for differentiation of the studied genotypes. The studied samples were distinguished by the individual bands of polymorphic amplified fragments of various molecular weight . Based oA. altaicum were used for GenAlex 6.5 genetic analysis and for generating the PCoA ordination diagram  varied from 0.570 in the Leninogorsk populations to 1.509 in populations from the Kalbinskii Altai. The average number of effective alleles varied from 1.090 to 1.378. The analysis of genetic structure of A. altaicum populations showed that between the distinguished groups of populations, there were substantial differences regarding the level of heterozygosity; the maximum values were observed in populations from the Kalbinskii Altai and the minimum values were observed in the Leninogorsk populations. The Shannon biodiversity index (I) showed that the average minimum length of a unique binary taxonomic code of one structural unit from the analyzed collection or panel varied from 0.077 (Leninogorsk group of populations) to 0.346 .These results suggest that natural populations of A. altaicum showed that the differences were more pronounced at the interpopulation level  . The PhiST differentiation index (similar to the Fst and Gst indices) had a value of 0.88, which was significant and indicated a high differentiation between populations .The AMOVA analysis of the frequency variation of PBS amplicons for 12 populations of . = 11%) . The datA. altaicum populations performed using the multivariate ordination method and the principal coordinates analysis (PCoA) based on NeiP data showed that only a single compact group was observed, which was formed by the Al10, Al11, Al12, Al13, Al14, Al15, and Al16 populations  is separate from the compact group relative to the PCoA2 coordinate axis. The Al1, Al8 and Al2 populations were also located separately from the general group in the PCoA1 coordinate. The Al17 population, one of the highest mountain populations, was located completely apart from other populations relative to both axes of coordinates. The PBS loci analysis demonstrated the absence of any geographic reference to the geographical areas identified by us, and populations geographically distant from each other were often located nearby.The remaining five populations of A. altaicum depending on the altitude of their habitat. For this purpose, the populations were divided into three groups. Low populations in the form of larch park forests contained six populations . Four populations were included in the group of mid-mountain populations of A. altaicum located at an altitude of 1,000–2,000 m above sea level, where the vegetation is represented by light coniferous taiga and colorful Alpine meadows . Only two populations of A. altaicum were included in the high-mountain group located at over 2,000 m above sea level in the zone of tundra vegetation (Al1 and Al13)  in mid-mountain populations was two times higher, and indicators such as the observed heterozygosity (He) and Shannon biodiversity index I were over three times higher .Analysis of variance of populations depending on the height of the range showed that all differences are at the intrapopulation level  .Rare relict species of plants undergoing super-exploitation are under threat of ecological and biological extinction. Relict plant species are of great scientific value as a reliable source of information on the vegetation cover of past geological eras. To preserve the biodiversity of rare plant species and to reduce the negative influence of anthropogenic factors, it is necessary to thoroughly research natural populations at the molecular genetic level. This allows analysis of the population structure for following selection of relict gene pool preservation and reproduction structure. Currently, in the era of a sharp increase in anthropogenic stress and the threat of ecological catastrophe, the preservation of relict flora is urgent.Allium were mostly conducted on the onion species related to human food and pharmacology and are actively applied in the sphere of selection  (Studies on the genetic diversity of the rare species heating) . Some poheating) .A. altaicum. The polymorphism index (PIC) is an important indicator that evaluates the efficiency of polymorphic loci and determines the efficiency of each primer. Under the classification of Allium genus. There are studies on the analysis of the genetic diversity of onions (A. cepa L.) using RAPD- and ISSR-specific markers. In these studies, the PIC values were much lower and were within the limits of 0.07–0.5 for the studied genotypes for the RAPD markers. The PIC values were between 0.06 and 0.26 for the ISSR markers for the same genotypes , the average meaning of which does not exceed 0.2. In our studies, this level of heterozygosity was only in Allium altaicum populations included in the Kalba local ecogeographic group. The substantial variety of populations of this group was conditioned by the dominance of multiple-aged generative specimens in their composition, notwithstanding the extreme conditions. The ability to adapt to severe conditions was demonstrated by the frozen tops of leaves and buds during the collection period. Furthermore, populations belonging to this ecogeographic group were located in hard-to-reach locations. This restricts mass collection by the population and allows the plants to form full seeds in favorable years. This points to the existence of seed and vegetative reproduction in these populations.In our studies, the total level of genetic diversity of ic drift . OftentiA. altaicum with different adaptive capacity. The middle part has an abundance of vegetation, which provides litter for the subsequent humification of soil cover and ensures its moisture and also favorably affects pollinating insects. These emerging genetic changes in plants can be fixed during clonal reproduction and subsequently ensure the existence of populations in extreme habitat conditions.The low levels of population diversity revealed in the populations of the Leninogorsk and West Altai local groups can be explained by the influence of anthropogenic factors . Due to the collection by the population in favorable climatic conditions, seeds do not have time to develop or juvenile plants die from the influence of climatic stress. Therefore, the vegetative  type of reproduction dominates in the populations and the habitat is reduced, which can lead to decreased plant survival in the populations. The previous studies demonstrate that the habitat altitude of the populations has a more significant effect on the productivity indicators of generative organs . Thus, the lowest indicators were observed in the high-mountain populations, average values were observed in low-mountain populations, and high values were observed in the populations located at 1,000–2,000 m above sea level. It is possible that the more favorable conditions in the middle part of the mountains contribute to the appearance of various morphotypes in A. altaicum, depending on the ecogeographic area and the altitude of habitat , groups were fragmented into isolated remote places. Therefore, these populations have close genetic similarities, resulting in a low level of diversity. In addition, relics are characterized by a slow rate of evolution and therefore they are narrowly adapted to certain specific existence conditions.It is possible that the distribution area of Allium regelianum conducted using ISSR analysis. The expected proportion of heterozygous genotypes for all ISSR loci was 0.192; this was higher than in our studies where this indicator was 0.145.Heterozygosity indicators were also low in analogous population studies of endemic species of Allium altaicum populations is due to both interpopulation and intrapopulation differences. Moreover, the genetic diversity within populations depended on their ecological-geographic location. This also indicates that these populations previously shared a common gene pool but were separated by significant isolation barriers. Despite the rather significant genetic differences between all populations, phenotypic changes were not observed with the corresponding geographic distance. For a long period, due to dispersal of seeds by the wind, the inaccessible territories with different climatic conditions were settled, which led to accumulation of intrapopulation polymorphisms. This was shown indicated by the insular or sporadic nature of population dispersal, as sometimes the density is 3–15 individuals per 10 m2. The results obtained are consistent with the data; high genetic diversity is promoted by large size and density of populations, while a significant number of individuals can prevent inbreeding and genetic drift (A. altaicum, it is possible to identify the most genetically distant and variable populations for conservation in a seed bank and several of the most diverse populations that reflect the genetic diversity of the species in a given territory.In our studies, analysis of DNA profiling showed that the genetic diversity of ic drift . In addiA. altaicum species collected in the territory of mountainous and low-land Kazakhstani Altai. Molecular genetic polymorphisms were studied using the PCR method based on PBS primers informative for the genetic analysis of studied samples. This study revealed that the Kazakh populations of A. altaicum are distinguished by a high level of genetic diversity. We observed that the degree of genetic differentiation mostly depends on the altitude of habitat rather than the ecogeographic location of the population. Using the iPBS amplification method may solve the problem of species identification of rare endangered species of Allium and the preservation of their biological diversity. The A. altaicum onion samples from the most distant populations can be used for the preservation and reproduction of the gene pool of this valuable plant species. Our research led to a better understanding of the genetic diversity of natural populations of the A. altaicum relict species in the territory of the Kazakhstani Altai. Our findings may contribute to the development of a restoration strategy for the endangered relict A. altaicum in the wild.We analyzed 12 populations of various species of the 10.7717/peerj.10674/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.10674/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.10674/supp-3Supplemental Information 3Click here for additional data file.


Panthera pardus pardus), a polygynous felid with male‐biased natal dispersal. Using a combination of spatial (home‐range) and genetic (21 polymorphic microsatellites) data from 142 adult leopards, we contrast the structure of two South African populations with markedly different histories of anthropogenically linked mortality. Home‐range overlap, parentage assignment, and spatio‐genetic autocorrelation together show that historical exploitation of leopards in a recovering protected area has disrupted and reduced subadult male dispersal, thereby facilitating opportunistic male natal philopatry, with sons establishing territories closer to their mothers and sisters. The resultant kin‐clustering in males of this historically exploited population is comparable to that of females in a well‐protected reserve and has ultimately led to localized inbreeding. Our findings demonstrate novel evidence directly linking unsustainable anthropogenic mortality to inbreeding through disrupted dispersal in a large, solitary felid and expose the genetic consequences underlying this behavioral change. We therefore emphasize the importance of managing and mitigating the effects of unsustainable exploitation on local populations and increasing habitat fragmentation between contiguous protected areas by promoting in situ recovery and providing corridors of suitable habitat that maintain genetic connectivity.Anthropogenic mortality of wildlife is typically inferred from measures of the absolute decline in population numbers. However, increasing evidence suggests that indirect demographic effects including changes to the age, sex, and social structure of populations, as well as the behavior of survivors, can profoundly impact population health and viability. Specifically, anthropogenic mortality of wildlife  and fragmentation of the spatial distribution of individuals (home‐ranges) could disrupt natal dispersal mechanisms, with long‐term consequences to genetic structure, by compromising outbreeding behavior and gene flow. We investigate this threat in African leopards ( Unsustainable anthropogenic mortality of wildlife and fragmentation of the spatial distribution of individuals disrupts natal dispersal mechanisms, with long‐term consequences to genetic structure, by compromising outbreeding behavior and gene flow. Our study investigates this threat in African leopards, demonstrating novel evidence directly linking unsustainable anthropogenic mortality to inbreeding through disrupted dispersal in a large, solitary felid and exposes the genetic consequences underlying this behavioral change. Although the western boundary of the reserve is adjacent to a densely populated community, the border fence is impermeable to leopards and the population seems unaffected by detrimental edge effects  is a privately owned conservancy est. 1948) in the Lowveld region of the Mpumalanga province  is situated in the Maputaland region of the KwaZulu‐Natal province Figure b and com2, Balme et al., 2 following recovery, Rogan et al., Historically, the SSGR and PMC populations were possibly linked via dispersal  ensures that most of the reserve is traversed daily at a high expected vehicle encounter rate (0.17 ± 0.05 vehicles per km). Drives are not limited to roads, as skilled trackers pursue charismatic species by vehicle or on foot until the animal is located, or the tracks are lost. This intensive search effort results in frequent sightings; on average, 6,428 ± 914 unique leopard sightings are recorded per annum with individual leopards being seen on average every 2.74 ± 0.04 days. Leopards in the SSGR are highly habituated to vehicles and guides are familiar with the individuals residing in their traversing area  in all photographs. We also cross‐referenced data submitted by guides from different lodges to assess the consistency of the information captured, and we found no significant discrepancies  were located every three days on average to within ~100 m using ground homing or triangulation across the PMC (mean road density of 2.6 km per km2), whereas GPS collars (n = 28) were programmed to record 2–6 fixes daily. Ear‐punch biopsy samples from 69 individuals were collected for genetic analyses during captures from 2002 to 2012. Tissue samples were stored in >90% ethanol at −20°C. Capture and collaring of leopards were approved (research permit HO/4004/07) by the provincial conservation authority, Ezemvelo KwaZulu‐Natal Wildlife and by the Animal Ethics Subcommittee of the University of KwaZulu‐Natal Ethics Committee .Spatial data in the PMC were collected using telemetry, following methods detailed in Fattebert et al. . Leopard2.32). Variogram calculations, movement model fits, and home‐range estimations were implemented in the ctmm package  for all sexually mature (≥3 years) leopards postdispersal , while OUF models are described using three . OU models provided home‐range and crossing time estimates, where OUF models provided these metrics as well as the velocity autocorrelation timescale and average distance travelled per individual. Finally, volumetric space‐time UD and HRO (Bhattacharyya's coefficient) were estimated based on these selected models , 2.0 μm each of forward‐labeled and reverse primers, 5 μl DreamTaq™ Green PCR Master Mix (Thermoscientific), and deionized water to a total reaction volume of 25 μl. PCRs were performed on an Applied Biosystems Veriti® Thermal Cycler. Given the generally lower quality DNA extracted from fecal samples, all samples were amplified in singleplex and in triplicate (from extraction to amplification) to ensure reproducibility. Locus‐specific thermal profiles were developed following Menotti‐Raymond et al. . Automated allele calls were manually checked for accuracy. Genotyping error was assessed per triplicate sample run on each individual and ≥2/3 consensus alleles used in subsequent analyses, where no such consensus was achieved or genotypes failed (≤15/22 loci amplified), whole genotypes were removed. Where available, known parent–offspring relationships were used to find mismatches. Stutter errors, large allele dropouts, short allele dominance, and significant departures from Hardy–Weinberg equilibrium (HWE) were examined across loci for each population using a chi‐square test for goodness of fit and sequential Bonferroni corrections performed on the resulting P‐values . Individuals were genotyped at 22 microsatellite loci Table  previousd et al. , and PCRd et al. . A posites Rice, . FSTAT 2es Rice, . The sig2.5rw) in SPAGeDI 1.0 .Parentage assignment and relatedness indices were used to confirm kinship and augment our observed pedigrees for both populations. Individual parentage assignments were estimated within a maximum‐likelihood framework implemented in CERVUS 3.0  and sex‐based dyads  per unit distance from the natal range in our two study populations. We first superimposed assigned maternal home‐range centroids with a concentric ring  surrounded by three concentric rings representing: the nearest‐neighboring maternal home‐range (1st order); the next peripheral neighboring maternal home‐range (2nd order); and all other maternal home‐range areas beyond this periphery. The width of each band represents the average maternal home‐range radius by population. Offspring  home‐range centroids were then plotted in relative x‐y proximity to their natal centroid and their frequencies plotted by concentric ring so as to schematically represent the differences in philopatric home‐range establishment relative to the natal home‐range by sex for each population.ecodist package  were successfully estimated for all 142 adult leopards for which we had genetic data . Due to high sampling intensity, rare forays or peripheral movements were witnessed  and accounted for in all three datasets, where home‐range relocation counts did not differ significantly between individuals of different spatial sampling types . Male home‐ranges were markedly larger than that of females in both the SSGR  and PMC . Female and male home‐range size did not differ between study populations  and genotyping failed (<15/22 loci amplified successfully) for only eight leopards . Locus FCA096 was removed from all further analyses due to poor amplification success . There was no evidence of LD or scoring errors due to large allele dropout and stutter in either population. Mean genotype coverage was higher in SSGR than in PMC . SSGR supports greater heterozygosity , allelic richness , and mean number of private alleles per locus than PMC . With the exception of some locus‐level deviations, the SSGR population was in HWE (see Table p = .003), with no significant sex bias in PMC . As there are likely very few unknown individuals in both populations, these sex ratios are assumed to reflect absolute sex ratios and are thus not expected to create a bias in overlap measures.The final dataset Table  consiste3.3Formal computational assignment of parentage, via a likelihood framework, was successful for both populations Table . Maternix¯ = −0.05; t12 = 4.27; p = .001; CI = −0.08, −0.03). Mean relatedness of confirmed breeding pairs in PMC, however, did not fall within the limits of their expected distribution . Instead, these were more similar to that expected of the half‐sibling distribution .In both populations, kinship pairs showed mean relatedness coefficients within the limits of their expected distributions Figure , includiFIS) was significantly greater in PMC than in SSGR , with evidence of significant outbreeding in SSGR with FIS scores significantly less than 0  and significant levels of inbreeding in PMC with FIS scores significantly greater than 0 .Pedigree reconstruction provided no evidence of direct inbreeding in SSGR, whereas in PMC, one father–daughter and two half‐sibling mating events were identified. The inbreeding coefficient . While the proportion of home‐range overlap was not significant between populations for female–female and male–male dyads, female–male home‐range overlap was significantly higher in PMC than in SSGR . Home‐range overlap between kin‐related pairs was not significant, with the exception of mother–son pairs in PMC being twice that of SSGR  and breeding pair home‐range overlap being nearly 20% greater in SSGR than PMC . Home‐range overlap between mother–daughter pairs was slightly greater than mother–son pairs in SSGR .The mean proportion of home‐range overlap Table  among alst order mean peripheral home‐range, 3% of daughters and 19% of sons within the 2nd order, and 30% of daughters and 56% of sons beyond. In contrast, of the 14 daughters  decreased significantly as the proximity (km) between individuals increased within female–female dyad pairs in SSGR  and within female–female , female–male , and male–male  dyad pairs in PMC  and PMC (a postharvest population in recovery) to reveal the fine‐scale genetic consequences of disrupted dispersal due to these markedly different histories of anthropogenic mortality. As predicted, mothers shared >50% of their home‐ranges with their daughters in both populations. A consequence of this female philopatry is the spatial formation of adult female kin‐clusters, a phenomenon evidenced by the strong spatio‐genetic autocorrelation in female–female dyads in both SSGR and PMC. Matrilineal assemblages are typical among large, solitary carnivores, having been observed in brown bears  to avoid conflict with resident adult males  among breeding pairs in PMC however suggests that historically high levels of anthropogenic mortality promote opportunistic male philopatry and kin‐clustering with translates into significant population‐level inbreeding (high FIS scores). While behavioral avoidance alone does not seem to be a strong enough driver of dispersal, as local inbreeding was observed  in PMC, it may be muting even stronger population‐level inbreeding signals. Similar findings of reduced dispersal and outbreeding benefits linked to sustained harvest have been documented in pumas  which, without kin‐recognition  might correct male dispersal and ultimately outbreeding. Though demographic recovery is plausible, this does not mitigate the “genetic scaring” (evident in reduced heterozygosity and increased inbreeding) accrued by the PMC population and many small reserves like it, when undergoing fluctuations of extreme harvest. Without immigration and effective connectivity between these reserves , genetic recovery through drift alone may not be rapid enough, as the ongoing genetic resilience of these populations is compromised and at risk of stochastic effects. Moreover, mortality need not be unsustainable to induce these effects, as it is not known whether “sustainable mortality” by humans would necessarily eliminate the patterns observed. Certainly, less mortality would have a mitigating effect, but it is not known to what degree. Our study is limited by the comparison of only two reserves on the wide spectrum of anthropogenic mortality and its impacts. Unfortunately, the fine‐scale genetic structure of African leopard populations remains understudied. This hinders the use of heterozygosity, relatedness scores, and conventional inbreeding coefficients as a means of interpreting population‐level effects, as there is no baseline data on allelic frequency and diversity of “natural” (outbred or panmictic) populations. Despite this, we are encouraged that multiple lines of evidence derived from both spatial and genetic data provide consistent support for anthropogenic mortality driving limited dispersal in males which in turn results in kin‐clustering and ultimately inbreeding.Potential alternative explanations for this observed pattern include within‐reserve habitat fragmentation and/or typical density‐dependent dispersal contributing to the differences between these populations, because they are at different stages of “development.” The former posits that high levels of human‐caused mortality (such as in the PMC) are correlated with anthropogenic barriers to movement (Tucker et al., Given time and adequate protection, territorial turnover among male leopards in PMC may slow and stabilize, re‐establishing male‐biased dispersal and restoring the typical in situ outbreeding effect of genetic drift as capacity is reached Couvet, . An alteFew protected areas sufficiently encompass the wide range of these species and large, solitary carnivores effectively confined to small reserves often suffer edge effects and even localized extinction (Woodroffe & Ginsberg, None declared.VN, GB, and JB conceived the study and designed the experimental protocols with input from JOR. Data were collected by VN, GB, LH, JF, and TD. Analyses were conducted by VN and JB. All authors discussed and interpreted the data. VN, GB, LH, JF, TD, JOR, and JB contributed critically to the writing of the manuscript and gave final approval for publication. Click here for additional data file. Click here for additional data file.


Dendrobium huoshanense, an endangered species with extremely small populations, was used as a model system to test whether the comparative plastomic approaches could screen available molecular markers for the phylogeographic study. We sequenced two more plastomes of D. huoshanense and compared them with our previously published one. A total of 27 mutational hotspot regions and six polymorphic cpSSRs have been screened for the phylogeographic studies of D. huoshanense. The cpDNA haplotype data revealed that the existence of haplotype distribution center was located in Dabieshan Mts. (Huoshan). The genetic diversity and phylogenetic analyses showed that the populations of D. huoshanense have been isolated and evolved independently for long period. On the contrary, based on cpSSR data, the genetic structure analysis revealed a mixed structure among the populations in Anhui and Jiangxi province, which suggested that the hybridization or introgression events have occurred among the populations of D. huoshanense. These results indicated that human activities have played key roles in shaping the genetic diversity and distributional patterns of D.huoshanense. According to our results, both two markers showed a high resolution for the phylogeographic studies of D. huoshanense. Therefore, we put forth that comparative plastomic approaches could revealed available molecular markers for phylogeographic study, especially for the species with extremely small populations.Comparative plastomics approaches have been used to identify available molecular markers for different taxonomic level studies of orchid species. However, the adoption of such methods has been largely limited in phylogeographic studies. Therefore, in this study,  D. huoshanense. According to our results, both two markers showed a high resolution for the phylogeographic studies of D. huoshanense.Based on the comparative plastomic approaches, a total of 27 mutational hotspot regions and six polymorphic cpSSRs have been selected to assess the genetic diversity and distributional patterns of  Z. Tang & S. J. Cheng, an endangered herb endemic to China, has been extensively used as traditional Chinese medicine (TCM) in many Asian countries for hundreds of years. It is believed by TCM practitioners to contain great medical values, such as nourishing the kidney, clearing away “heat‐evil,” benefiting the stomach, enhancing the body's immunity, resisting cancer, and prolonging life. These purported medicinal merits of D. huoshanense bring a great market demand for it. As a perennial plant, D. huoshanense has a long‐life cycle and require a warm and humid habitat; however, due to their low germination rate, slow growing, habitat deterioration, and being overexploited, the wild populations of D. huoshanense are extremely in danger of extinction. As documented in Tsi , one of the largest families in the monocots, are well known for their tremendous diversity and innovative characters, including specialized pollination syndromes, epiphytic habits, and the presence of crassulacean acid metabolism  DNA sequence (trnC‐petN and trnT‐trnE). Hou et al. . Unfortunately, though cpDNA sequence data use increase, most researchers continue rely on regions of relatively low variability. For example, the commonly used cpDNA regions, psbA‐trnH, trnL‐trnF, and trnL intron present lower variability than most of other regions  are the most important genetic tools for plant studies at low taxonomic levels, especially for phylogeographic analysis  approach over the last decade has largely facilitated gathering of plastome sequence data in public databases, which led to the use of comparative plastomics approaches  to identify rapidly evolving regions appropriate for low taxonomic level studies use  Could the comparative plastomic approaches screen available molecular markers? (b) If so, could these markers use to infer the phylogeographic relationships among the populations of D. huoshanense. To address these questions, we sequenced two more complete plastome sequences of D. huoshanense and compared them with our previously published one. Based on the comparative plastomic approaches, a total of 27 mutational hotspot regions and six polymorphic cpSSRs have been selected to assess the genetic diversity and distributional patterns of D. huoshanense.Therefore, in this study, the plastome sequences of 22.1D. huoshanense were used in this study  province were collected as outgroups. The voucher specimens of D. huoshanense  and all samples were stored in College of Life Sciences, Nanjing Normal University, Nanjing, China.A total of 28 samples from five populations of dy Table . These pFor the DNA extraction of two individuals from Dabieshan Mts. (Huoshan) and Longhushan Mts., 2 g of fresh leaves were harvested. The total genomic DNA was extracted using the DNeasy Plant Mini Kit (Qiagen) according to the manufacturer's instructions. The quality of obtained DNA was measured on NanoDrop 8,000 Spectrophotometer (Thermo Scientific). DNA samples that met the quality requirements  were used for sequencing. The genomic DNA of other samples were isolated from about 0.5 g of leaves using a standard CTAB DNA extraction protocol  as reference. The gaps and junctions between inverted repeat (IR) regions and single copy (SC) regions were confirmed by PCR amplification. Genes were annotated using DOGMA  with the plastome of 2.3D. huoshanense. Three plastomes of D. huoshanense were compared by using D. moniliforme (AB893950) as reference. The complete plastome sequences were aligned with MAFFT program  sites and insertion‐deletion (InDel) events for each bin  and manually refined with Adobe Illustrator CC 2015.The comparative plastomics approaches were employed to select the most informative regions, which could be used for the phylogeographic analysis of 2.4D. huoshanense (Table dH) and nucleotide diversity (iP) for each population and for all samples. Within‐population diversity (SH) and total diversity (TH) were determined using PERMUT version 1.0  analyses. The best substitution model was “GTR + I+ G”, which was determined according to the Akaike Information Criterion (AIC) in Modeltest 3.7 Posada, . The BI 2.6D. huoshanense by using cpSSR data  was varied from 1 to 7 with 10 independent runs. The most probable number of clusters was estimated by calculating the natural logarithm of the likelihood function, and the ΔK statistic was estimated using Structure Harvester   and separated SSC  and LSC  regions  which contains full set of functional NDH genes in orchids. Like other Dendrobium species, D. huoshanense also experienced the loss of plastid NDH genes. Among them, only ndhB genes in IR regions contain full reading frames, whereas other ten plastid NDH genes were truncated or completely lost.The two newly sequenced plastomes of s Figure . The ove3.2r = .406, p < .01). Moreover, negative correlations between GC content and the distribution of SNP and InDel were also detected . These results indicated that the plastomic mutational hotspots of D. huoshanense were accompanied by biased AT compositions. In addition, we also calculated the number of SSRs that present in the same loci of both plastomes .A total of 372 bins with 400 bp per length were achieved from three plastomes. The relationship between GC content and distribution of SNP and InDel in pairwise comparison of each bins were showed in Figure s Figure . ConsistD. huoshanense  of all sampled populations was substantially higher than the average within‐population diversity (sH = 0.663). The high levels of haplotype diversity (dH = 0.815) and nucleotide diversity (iP = 0.00017) were estimated at species level, but diversified at population level. The highest level of haplotype diversity was 0.810 in the population of Dabieshan Mts. (Lu'an), followed by Dabieshan Mts. (Huoshan) and Longhushan Mts., while, the value of haplotype diversity was estimated 0 in both Huangshan Mts. and Funiushan Mts.  was 0.1161. (ii) Among three groups, the total genetic variation was partitioned into 9.10% among groups, 4.85% among populations within groups, and 86.05% within populations  was substantially higher than STG (0.296), revealing strong phylogeographic structure in this species.The AMOVA analysis showed that: (a) The genetic variation within populations 88.39%) was significantly higher than that among populations (11.61%). The estimated value of genetic differentiation  analyses to infer the phylogenetic relationships among 11 8 Figure .D. huoshanense haplotypes was congruent with the phylogenetic tree, with all three clades recovered  not only contained the highest frequency of H2 (44.45%) but also had the highest number of haplotypes, indicating that the existence of haplotype distribution centers was located in Dabieshan Mts. (Huoshan)  Figure . As show) Figure . These r3.5D. huoshanense populations was determined by means of the STRUCTURE program with the admixture model. According to estimated values of ΔK, when K = 3, the genetic structure analysis should achieve the best result  for hundreds of years  with a narrow geographical distribution which has resulted from some negative external factors over a long time; (b) contains less individuals than the minimal number that required to prevent extinction  27 mutational hotspot regions and (ii) six polymorphic cpSSRs have been selected for the phylogeographic study of 4.2D. huoshanense. With carefully calculation and statistical analysis, two groups of opposite results have been revealed. (a) We have observed a high level of total genetic diversity (tH = 0.815), which implicated that D. huoshanense has a long evolutionary history and wide distribution. While the documented distribution of D. huoshanense was limited in Tsi (dH) was diversified for different populations, for example, the values of dH were 0.810, 0.750, and 0.733 for Dabieshan Mts. (Lu'an), Dabieshan Mts. (Huoshan), and Longhushan Mts., but 0 for Huangshan Mts. and Funiushan Mts.. (b) The estimated value of D. huoshanense population differentiation based on cpDNA data (STΦ = 0.1161) was lower than other seed plants in China . Inferred from the BI tree, three major clades were identified in relation to geographical distribution, suggesting that geography might have played a role in shaping the extant genetic structure of D. huoshanense populations. Although most of the haplotypes were distributed in nearly all regions, there were still five haplotypes restricted to Longhushan and Funiushan Mts., indicating that these two populations were isolated for long periods , and reproduced them in artificial conditions. The D. huoshanense species have not only been grown in greenhouses, but have also been cultivated in conditions imitating those in the wild. For example, breeders have grown D. huoshanense species on the trunk of pear trees or on cliffs, which has afforded an opportunity for its artificial migration. Therefore, the hybridization or introgression events would occur between cultivated and natural populations, which has resulted in the mixed genetic structure among D. huoshanense populations. Hence, human activities should have played a key role in shaping the distributional patterns of D. huoshanense over the past 100 years, but the level of artificial migration should be evaluated in the future.Human activities not only influence the genetic diversity and structure of D. huoshanense. To protect the wild population of D. huoshanense and meet the great market demand, the conservation strategy should be implemented in three steps: (a) establish a germplasm bank by collecting seeds from different populations; (b) raise the cultivation size and increase the gene flow among populations by artificial hybridization; (c) plant the species of D. huoshanense back into the wild.In summary, based on phylogeographic analysis, we proposed that human activities have played key roles in shaping the genetic diversity and distributional patterns of 4.3D. huoshanense. According to our results, the phylogeograpy of D. huoshanense has been well resolved. Therefore, we put forth two implications for future phylogeographic studies: (a) Molecular marker screening is necessary before phylogeographic studies, (b) comparative plastomices approaches could revealed available molecular markers for phylogeographic study, especially for the species with extremely small populations.The cpDNA sequences have been widely used in plant phylogeographic studies. However, with extensive comparative analyses of noncoding cpDNA sequences, Shaw et al.  concludeNone declared.Zhitao Niu: Data curation ; formal analysis ; funding acquisition ; investigation ; software ; validation ; visualization ; writing‐original draft (lead); writing‐review & editing (lead). Zhenyu Hou: Data curation ; formal analysis ; software . Mengting Wang: Data curation ; formal analysis ; validation ; visualization . Meirong Ye: Validation . Benhou Zhang: Data curation ; formal analysis ; investigation ; software . Qingyun Xue: Writing‐review & editing . Wei Liu: Data curation ; formal analysis ; investigation . Xiaoyu Ding: Funding acquisition ; investigation ; supervision ; writing‐review & editing .D.X.Y. and N.Z.T.: Study design. N.Z.T., H.Z.Y., Y.M.R., and L.W.: Perform the experiments. N.Z.T., H.Z.Y., W.M.T, X.Q.Y., and Z.B.H.: Data analysis. N.Z.T.: Manuscript writing. All authors approved the final version of the manuscript.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Figure S4Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Table S4Click here for additional data file.Table S5Click here for additional data file.


East Asia constitutes one-fifth of the global population and exhibits substantial genetic diversity. However, genetic investigations on populations in this region have been largely under-represented compared with European populations. Nonetheless, the last decade has seen considerable efforts and progress in genome-wide genotyping and whole-genome sequencing of the East-Asian ethnic groups. Here, we review the recent studies in terms of ancestral origin, population relationship, genetic differentiation, and admixture of major East- Asian groups, such as the Chinese, Korean, and Japanese populations. We mainly focus on insights from the whole-genome sequence data and also include the recent progress based on mitochondrial DNA (mtDNA) and Y chromosome data. We further discuss the evolutionary forces driving genetic diversity in East-Asian populations, and provide our perspectives for future directions on population genetics studies, particularly on underrepresented indigenous groups in East Asia. In the past two decades, novel methods were developed and facilitated in the generation of large genomic data that researchers have used to improve our understanding of the population genetic architecture and evolutionary history of humans . HoweverEast Asians represent about 38% of the Asian population and 22% of the global population. Their population occupied a unique geography, located on the crossroads connecting the Americas and Pacific Islands, which plays a pivotal role in human evolutionary history. The whole-genome population genetic studies on East Asians can be traced back to 2009, when the HUGO Pan-Asian SNP Consortium (HUGO-PanAsia) reported the first cohort of large-scale genome data on Asians –8. TheseHere, we review the recent progress in population genomics of East Asia, concentrating on three typical populations, namely, Chinese, Japanese and Korean. We describe differences in the genetic architectures of these populations, explore the mechanisms that maintain the genetic diversity among EA populations, and decipher the evolutionary scheme of East Asians. This review improves our understanding of East Asian population genetic structure and more importantly, emphasizes the need for additional genetic studies on the under-represented ethnic groups.According to geographical distribution and ethnicity, East Asians can be roughly divided into three major groups: Chinese, Korean and Japanese. Although these three populations share many physical similarities, genomic studies show that the genetic makeup of the these populations differ from each other , 10. TheAccording to the studies based on mtDNA, Y chromosomes and genome-wide sequence data, the historical periods of Japan follow a dual structural model that consists of three periods –13. The These ancestries have different genetic contributions to various present-day Japanese sub-populations. The Japanese population is currently divided into three separate groups: mainland Japanese , Ryukyuan, and Ainu . MainlanThe Korean Peninsula is located to the north of China and its northeast region is bound by Russia. The Korean population has been thought to be highly homogeneous with few admixtures in its history , 18, 19.Chinese is the largest population in Eastern Asia, consisting of 56 officially identified ethnic groups, with Han Chinese as the major ethnic group. The minorities are distributed throughout the country; for instance, Tibetans and Sherpas in the Qinghai-Tibet Plateau, Uyghurs in western China, Dais in southern China, Mongolians in central and northern China. Extensive research studies have been made to uncover the genetic structure and evolutionary history of Chinese populations. One remarkable genetic pattern is the distinction between northeastern and southeastern Chinese groups, based on phylogeographic studies of mtDNA variations and non-recombined Y chromosome (NRY) haplogroups , 6, 7. TExcept for the north-to-south cline, later genome-wide studies on select minority population such as the Uyghurs in Xinjiang also show a west-to-east cline, which is associated with an admixture between EAs and Europeans . XinjianAnother essential minority for inferring human population history is the Tibetan ethnic group. Settled in the highest plateau with an average elevation of > 4500 m worldwide are the Tibetan high-landers constituting a distinct population in China. It is estimated that 90% of the Tibetan genome was inherited from modern humans and about 6% originated from mixed archaic hominoids, including Neanderthals (~ 1%) and Denisovans (0.4%) . Some arEPAS1, PKLR, and CYP2E1 [Mongolians are another important ethnic group that has been used in inferring EA population history. Located in central and northern China, southern Russia, and other neighboring countries, Mongolians play a pivotal role in shaping the culture and genetic makeup of modern Eurasia along with the Mongolian Empire expansion in the thirteenth century based on mtDNA and Y chromosome data , 30. Gend CYP2E1 . This grMost of the genetic variations among populations of non-European ancestry are enigmatic, which may affect both disease prediction and treatment efficacy. Moreover, the unique genetic mosaic of minority populations, like the SUNDer in Tibetan’s genome, is the distinguished material that has been to comprehend the function and phenotypic effect of selected variations, bypassing genome-wide association studies (GWAS) or traditional laboratory research. Therefore, in the future, it is essential that more data could be collected to better understanding the genetic structure of human populations.In the previous section, although we discussed the genetic pictures of three EA groups separately, no geographic region can be regarded as isolated in human population history, especially in terms of migration and admixture that form the basal genetic materials of present-day EA . TherefoBased on mtDNA, NRY, whole-genome sequencing data and recent ancient DNA data, the common ancestor in EA is characterized as two layers of ancestry: pre-Neolithic hunter-gatherers as the first layer and northern East Asians since Early Neolithic as the second layer , 18, 34.FST) and effective population size (Ne) inferred from the modern genome data, researchers estimate the divergence time between present-day Han Chinese and Japanese to be ~ 3600-3000 ya, and the divergence time between Han Chinese and Korean as ~ 1200 ya while Japanese and Korean separated ~ 1400 ya [3 test, gene flow occurred from Chinese and Japanese to Korean and between Han and Japanese populations. These admixtures partly attenuate the population differentiation and homogenize the groups.These ancestries mixed in EA compose the embryonic gene pool of present EA continent populations, while later migration and human expansion events have built neighboring Japanese and the Korean populations. Based on genetic differentiation , FADS (fatty acid desaturase), OCA2 and ADH (Alcohol dehydrogenase) gene [EDAR has a variety of pleiotropic effects, including sweat gland density, incisor shoveling, and mammary gland ductal branching. A nonsynonymous V370A mutation in the EDAR gene has been reported to have elevated derived allele frequency in North and East Asians and associate with “East Asian phenotypes. Further studies have confirmed the EDAR gene harbors a strong selective sweep signal that is associated with an increase in the number of active eccrine glands during the LGM. FADS genes encode rate-limiting enzymes for the biosynthesis of long-chain fatty acids and underwent positive selection in multiple populations, including EA [FADS gene [FADS genes help modulate the relative proportion of long-chain polyunsaturated fatty acids during breast milk synthesis under low-vitamin D condition. In contrast, vitamin D deficiency is relevant to an increase in mammary ductal branching during the hormone-induced stages of breast development, which is established via the NF-κB signaling pathway and that is activated by EDAR. In conclusion, selection for polymorphisms in the FADS gene cluster and for EDARV370A may result from the intertwined advantage in transmitting nutrients from mother to infant through breast milk in the low UV environment. The ADH gene has three subtypes, ADH1A, ADH1B, and ADH1C. An ADH1B Arg47His variant increases the alcohol metabolism rates and is predominant in EAs but rare in Europeans and Africans. The positive selection signal and culture-related selective forces on this gene have been proposed. Further population studies elucidated an east-to-west cline  in the allele frequency distribution in EAs with a relatively low frequency in Sherpa and Tibetan (10–20%) [After the population settles down in a particular place with a certain environment, natural selection might play an important role in driving population differentiation, especially when mutation is rare and genetic drift is weak in large populations. Previous studies have shown that some genes are associated with adaptation in EA which also results in genetic differentiation between EA and other non-EA populations. These EA-specific genes include se) gene , 37–39. uding EA , 23. A rADS gene . Under t(10–20%) . MoleculEPAS1, EGLN1, and TMEM247, some genes were specifically underlying natural selection in Sherpa, such as ALDH3A1, ANGPT1, and OXR1 [Except for the shared adaptive genes, selection also contributes to the genetic differentiation among closely related populations. We have reviewed the genetic diversity between Sherpas and Tibetans resulted from admixture and migration; however, natural selection also imparted an effect. Although Sherpas and Tibetans shared some plateau adaptive genes including and OXR1 , 41. TheOverall, selection and adaptation are complex processes that yield different consequences in the population genome, which may increase or decrease the genetic diversity.The increasing availability of data, especially whole-genome data, largely facilitates our understanding of the genetic mechanisms and evolutionary history of EAs Table . AlthougMKL1 gene that is associated with lower systolic pulmonary arterial pressure, which is a crucial adaptive trait in Tibetans [Another gap lies on studies of the structural variations (SVs) of human populations. The history of study of structural variants can be traced back to the early twentieth century. Current studies have mostly focused on variations such as SNPs and microsatellites in the scope . Recent Tibetans . As manyThe biological meaning of human genome sequence remains at its infancy. The functions and phenotypic effects of the majority of our genome are unknown. There are three typical approaches to understand the biological meaning of our genome sequence: i) medical studies start from a certain phenotype (or disease) and aim to identify the corresponding genotype; ii) model-organism-based experimental studies starting from a gene by knocking in/out some sequences to observe its molecular function or phenotypic effects; and iii) evolutionary studies evaluate functional importance of many variants in parallel across the genome by estimating their conservation or adaptive potential.The medical approach relies on phenotypes observed, and results are usually inconsistent among different studies due to poor phenotyping; experimental approaches are expensive, inefficient and can only be done in non-human organisms. Evolutionary analysis of diverse populations is equivalent to doing direct knock-in/out studies  in human genomes, thus is an economic and efficient way to understand biological meaning of our genome sequence. For instance, by whole-genome sequencing 1055 healthy Korean individuals, the Korean Variant Archive database has reported 293,049 variants, of which 88,047 (30%) variants are novel compared with the dbSNP database . FunctioST = 0.0002–0.0009), is sufficient to induce an inflated false-positive rate with a moderate sample size [Moreover, comprehensive studies on population genetics also facilitate our understanding of biological meaning of our genome data, especially in the GWAS. First of all, population stratification is a significant confounding factor in GWAS. Researchers have uncovered that the genetic differentiation among the Han Chinese, although very small (Fple size . The prople size . To bettThere is thus a need for additional studies that focus on under-investigated indigenous populations, such as people living in tropical forest and highland in EA and Southeast Asia, whose genomes harbor an enormous number of variants that might not have been observed in earlier population studies, especially those of European ancestry.Previous studies have taken advantage of population genetic data, especially whole-genome sequence data to illuminate the evolutionary history of EA populations. In this review, we summarize recent researches and focus on novel evolutionary insights on three EA groups, namely, Chinese, Japanese and Korean, and illuminate how a wide range of evolutionary forces including migration, admixture, genetic drift and natural selection form the populations while driving population diversity. Finally, we anticipate additional investigations on under-researched indigenous minor populations as well as fine maps of high-quality sequence data to resolve the genetic structure of human genetics.


Salmo salar L.) populations follow an anadromous life cycle, spending early life in freshwater, migrating to the sea for feeding, and returning to rivers to spawn. At the end of the last ice age ~10,000 years ago, several populations of Atlantic salmon became landlocked. Comparing their genomes to their anadromous counterparts can help identify genetic variation related to either freshwater residency or anadromy. The objective of this study was to identify consistently divergent loci between anadromous and landlocked Atlantic salmon strains throughout their geographical distribution, with the long‐term aim of identifying traits relevant for salmon aquaculture, including fresh and seawater growth, omega‐3 metabolism, smoltification, and disease resistance. We used a Pool‐seq approach  to sequence the genomes of twelve anadromous and six landlocked Atlantic salmon populations covering a large part of the Northern Hemisphere and conducted a genomewide association study to identify genomic regions having been under different selection pressure in landlocked and anadromous strains. A total of 28 genomic regions were identified and included cadm1 on Chr 13 and ppargc1a on Chr 18. Seven of the regions additionally displayed consistently reduced heterozygosity in fish obtained from landlocked populations, including the genes gpr132, cdca4, and sertad2 on Chr 15. We also found 16 regions, including igf1 on Chr 17, which consistently display reduced heterozygosity in the anadromous populations compared to the freshwater populations, indicating relaxed selection on traits associated with anadromy in landlocked salmon. In conclusion, we have identified 37 regions which may harbor genetic variation relevant for improving fish welfare and quality in the salmon farming industry and for understanding life‐history traits in fish.Most Atlantic salmon ( Rearing and sampling of salmon from Connecticut River and Sebago Lake have been described previously . The sequenced pools of anadromous salmon from Norway have been used in previous studies , and fluorometric quantification with Qubit (Thermo Fisher) was used to measure DNA concentrations of each sample. DNA pools were made by pooling equal amounts of genomic DNA from 10 individuals from the same population . Read pairs were filtered using Cutadapt (v. 1.18)  and Northern Norway (n = 5) were grouped as two populations by summing the allele counts for the populations contained in each of the two groups , resulting in a total of 9 populations ‐p(1‐p)¯p¯(1‐p¯) presented in   and anadromous (n = 3) populations, respectively. Our aim was to uncover differentiated genomic regions, indicating selective sweeps, so we performed a genomewide screen for regions containing several highly differentiated SNPs. Selective sweeps were predicted in 100 kb sliding genomic windows with 50 kb step size, only considering windows having at least 10 SNPs with a minimum dAF of 60%. Each window was then extended 50 kb to each side, and overlapping windows were merged. Regions passing these criteria were considered as putative selective sweeps.Identification of SNPs that were differentiated between anadromous and landlocked populations was done by calculating the difference in allele frequency between the two groups (dAF) , where ip is the allele frequency of the global major allele for the i‐th SNP in a given window containing n SNPs. This is similar to what has been done in Qanbari et al.  using the formula ZHp=Hp‐μHpσHp for each genomic window in a population, where µHp is the mean and σHp is the standard deviation of all the Hp values in a given population, resulting in a distribution of ZHp where µZHp = 0 and σZHp = 1 for each population  and White Sea (n = 22) and landlocked populations from the Russian lakes Ladoga (n = 6) and Onega (n = 5). Each population is represented by allele frequencies of DNA pools of >22 individuals per population obtained from a SNP array comprising 197,431 SNP markers. To analyze the data, allele frequencies were averaged over the populations from each of the four groups  and heterozygosity was analyzed similarly to what was done for the sequenced populations in the present study. Briefly, Hp was calculated in 50 kb sliding genomic windows with 1 bp step size followed by conversion to Z‐scores. Genomic windows where max(ZHpA) < 0 and min(ZHpL) > 0, where ZHpA and ZHpL are the ZHp values of a given genomic window from anadromous and landlocked populations, respectively, were considered as having reduced heterozygosity in the anadromous salmon. Regions with consistent reduction in heterozygosity in anadromous salmon were defined as regions with reduced ZHp in anadromous salmon in our sequence‐based data that overlapped with windows showing reduced ZHp in anadromous salmon from the dataset presented in Zueva et al. (L) < 0 and min(ZHpA) > 0, where ZHpL and ZHpA are the ZHp values of a given genomic window from landlocked and anadromous populations, respectively, were considered as having consistently reduced heterozygosity in the landlocked salmon.One of our main aims was to identify regions with consistently reduced heterozygosity in anadromous populations. Because our dataset only included three anadromous populations, we extended the number of populations by including additional populations from a study performed by Zueva et al. , in whica et al. . The sam2.7To obtain individual‐specific genotype distributions and to investigate more anadromous and landlocked populations at the genome regions of interest, Custom TaqMan SNP Genotyping Assays  were designed for the SNPs Chr13: 66061636 and Chr15: 41215721, see Results (primers and probes are listed in Table 2.8n = 84) and controls (n = 83) divided into six different sampling points (the fish were approximately 7 months of age at experiment start). Read counts were summed for each gene ID and normalized by total mapped read counts.The Atlantic salmon reference gene model GFF file (v. ICSASG_v2)  was determined by aligning the Cadm1 amino acid reference sequence (accession: XP_013992853) against the refseq_protein database using BLASTP (https://blast.ncbi.nlm.nih.gov), only including matches to teleost fishes (taxid: 32443).Ancestral state of a missense SNP in the candidate gene 3Landlocked salmon have been isolated in freshwater lakes for millennia, where they have been shaped by subsequent evolution as they adapted to a life without oceanic migration. Traces of the underlying evolutionary forces they have been subjected to including those they are no longer influenced by can be revealed by genome sequencing. By pooled whole‐genome sequencing, we have compared the genomes of 6 landlocked and 12 anadromous salmon populations from a wide geographical range across the Northern Hemisphere Figure , Table 1Sequence reads mapped to the Atlantic salmon reference genome were used to identify a total of 43,329,247 single nucleotide polymorphisms (SNPs) in the genomes of landlocked and anadromous salmon. Atlantic salmon inhabit the entire coast of Norway; however, due to gene flow between neighboring populations, they are quite homogeneous and were therefore divided into two major groups representing the western and northern Norwegian populations . This allowed us to identify parallel selection on genetic variation in multiple landlocked populations, where SNPs present in the ancestral anadromous populations were subjected to strong positive selection for the same allele after the formation of the landlocked populations. We used two different thresholds for reporting differentiated SNPs; dAF > 0.5, which resulted in 15,038 SNPs, and dAF > 0.6, resulting in 2,194 SNPs. Regions harboring at least ten differentiated SNPs (dAF > 0.6) in 100 kb sliding genomic windows were regarded as selective sweeps, and genomewide screening revealed 28 sweeps containing many differentiated SNPs, potentially resulting from different selection pressures in the landlocked and anadromous populations Figure , Table 23.2Z‐scores (ZHp) for each population. Difference in heterozygosity was quantified based on the difference of average ZHp between the two groups in the genomic windows (dZHp)  can be used as a measure of the amount of genetic variation present in a given region of the genome of a population, where reduced Hp can indicate recent directional selection  Figure . To iden) Figure . We beli) Figure . Reduced) Figure . When th) Figure . Interes3.3Heterozygosity is commonly used as an index of genetic diversity and can also provide indications of purifying selection that keeps genomic regions from accumulating deleterious mutations. If a gene or region becomes less relevant in a population, it is more likely to accumulate mutations that are not purged from the population. This can be used to identify genomic regions that are under purifying selection due to a conserved function of the genes in that region. For example, genes that are vital for survival at sea can be expected to accumulate more mutations in landlocked salmon that no longer require that specific function to be maintained since they no longer migrate to the sea, and therefore experience a reduction in selection pressure. Therefore, we aimed to uncover genomic regions and genes that show increased genetic diversity in landlocked salmon compared to anadromous salmon, potentially leading to discovery of genes associated with seawater‐related traits relevant for aquaculture, such as resistance to seaborne diseases or smoltification.n = 485), and to see whether any of the regions are conserved in other datasets and other populations, we analyzed allele frequency data from Zueva et al. (insulin‐like growth factor 1 (igf1) , which is involved in regulation of many different processes in salmonids , WD repeat domain 17 (wdr17), and ankyrin repeat and SOCS box containing 5 (asb5). Their functions in fish are not well characterized; however, Wdr17 has a function in eyes in mice  such as “Viral mRNA Translation,” and “Class I MHC mediated antigen processing and presentation”, respectively, suggesting that these might be related to resistance against seaborne diseases.To narrow down the list of regions showing consistently reduced heterozygosity in anadromous salmon in our data  Figure , and tra) Figure . Togethe) Figure . Igf1 is) Figure , and in We also identified regions with consistently reduced ZHp in landlocked populations included on the SNP array data presented in  in at least one sampling point in fish challenged by saltwater for 24 hr at six sampling points over a 110‐day period  at all sampling points , SERTA domain‐containing protein 2 (sertad2) and a threonine tRNA (GeneID: 106455098), and in close proximity to G protein‐coupled receptor 132 (gpr132). Four SNPs were almost fixed in opposite directions in landlocked and anadromous salmon (dAF > 0.8), even across the Atlantic Ocean. These SNPs were found in the 3′ UTR and 1,160 bp downstream of sertad2, and 817 bp upstream and 835 bp downstream of the threonine tRNA. Genotyping a larger number of fish  on position Chr17:48969956 and transmembrane protein 187  on position Chr8:871592. A total of 112 missense SNPs were differentiated between the landlocked and anadromous populations (dAF > 50%), listed in File cell adhesion molecule 1  and kinesin family member 3a (kif3a). While kif3a is a microtubule motor protein involved in organelle organization and vesicle‐mediated transport, sh3rf1 is assigned to the Reactome pathway (https://reactome.org) “Class I MHC mediated antigen processing & presentation” and can regulate T‐cell differentiation and activation in mice  which contains a SNP previously found to explain 5.83% of phenotype variation in resistance to infectious salmon anemia (ISA) in commercial Saint John River Atlantic salmon (Holborn et al., The selective sweeps presented in this study provides a basis for identification of genetic variants with potential for increasing welfare of farmed animals. However, further studies are required to determine the precise function of genes and genetic variants under selection to be able to evaluate if any of these contribute to life‐history traits relevant for aquaculture, including growth, smoltification, and disease resistance. When selective sweeps have been connected to specific tissues, pathways, and traits in salmon, this knowledge can be further used to identify potential targets for introducing genetic variants possibly conferring relevant traits into farmed salmon strains to increase their robustness, for example by the use of marker‐assisted breeding or gene editing.4gpr132, cdca4, sertad2 and threonine tRNA in Chr 15, cadm1 containing a highly differentiated missense SNP in Chr 13, and ppargc1a on Chr 18 which display increased expression in gills upon saltwater exposure. Further, we identified regions in the genome where the landlocked salmon show consistent signs of relaxed purifying selection, including the gene igf1, indicating genomic regions containing genes that are important during the seawater phase. Further studies will aim to characterize candidate genes and genotypes from the selective sweeps to pinpoint causative variants with potential for improving welfare in farmed salmon strains and to enhance our understanding of the underlying biology of transition into seawater.We describe genomic regions under divergent selection in anadromous and landlocked populations of Atlantic salmon across the Northern Hemisphere, and we report genes and genetic variants that may be of relevance for improving fish welfare in aquaculture production and for conservation and management related issues. The analyses were done using pooled whole‐genome sequencing of 12 anadromous and 6 landlocked salmon populations, which were used in a large genomewide association study. The study revealed 28 highly differentiated selective sweeps with SNPs close to fixation in all assayed landlocked populations, indicating parallel selection of alleles beneficial for a landlocked life cycle. Among the most interesting selective sweeps, we found None declared.Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. government.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.