Cannabis accessions sampled (25 wild populations and 27 domesticated populations or cultivars), three haplogroups  were identified and these lineages exhibited distinct high-middle-low latitudinal gradients distribution pattern. This pattern can most likely be explained as a consequence of climatic heterogeneity and geographical isolation. Therefore, we examined the correlations between genetic distances and geographical distances, and tested whether the climatic factors are correlated with the cpDNA haplogroup frequencies of populations. The “isolation-by-distance” models were detected for the phylogeographic structure, and the day-length was found to be the most important factor (among 20 BioClim factors) that influenced the population structures. Considering the distinctive phylogeographic structures and no reproductive isolation among members of these lineages, we recommend that Cannabis be recognized as a monotypic genus typified by Cannabis sativa L., containing three subspecies: subsp. sativa, subsp. Indica, and subsp. ruderalis. Within each haplogroup which possesses a relatively independent distribution region, the wild and domesticated populations shared the most common haplotypes, indicating that there are multiregional origins for the domesticated crop. Contrast to the prevalent Central-Asia-Origin hypothesis of C. saltiva, molecular evidence reveals for the first time that the low latitude haplogroup (Haplogroup L) is the earliest divergent lineage, implying that Cannabis is probably originated in low latitude region.Cannabis is one of the most important industrial crops distributed worldwide. However, the phylogeographic structure and domestication knowledge of this crop remains poorly understood. In this study, sequence variations of five chloroplast DNA (cpDNA) regions were investigated to address these questions. For the 645 individuals from 52  Cannabis is one of the oldest crops and has been distributed worldwide by humans. This plant may have been utilized for at least 10,000 years  as a unique species. Later on, two species, C. indica Lam. (1785) and C. ruderalis Jan. (1924), were split from C. sativa based on certain distinct morphological Characteristics  but including two subspecies, subsp. sativa and subsp. indica, where each subspecies includes both domesticated and wild varieties  including seven putative taxa in the genus Cannabis.Based on the content of cannabinoids in this herbaceous annual crop, cannabis plants have been often classified as hemp, mostly referring to a fiber crop with low tetrahydrocannabinol (THC) and marijuana, the drug type with often high THC content. This plant comprises both wild and domesticated populations which can be either dioecious or monoecious cultivars. The flowering is very sensitive to photoperiod and cultivars can be early-, intermediate-, and late-ripening. Compared to the domesticated cannabis, the wild forms usually exhibit the following distinct morphological and physiological features: remarkably smaller seeds , easy seed shattering behavior (seeds readily disarticulate from the pedicel), long-term seed dormancy and the need for cold-moist stratification treatment to facilitate germination. For a long time, researchers have disputed the taxonomy of Cannabis are the most valuable fundamental materials for breeding as they are a potential source of novel genes controlling important traits such as increased seed productivity, improved qualitative characteristics for example fiber quality, or resistance to adverse environmental factors such as cold, drought, strong wind, and pest/disease pressure. The native distribution range of Cannabis is commonly believed to be in Central Asia, Siberia, the Himalayas, and possibly extending into China . Our main objectives were: (1) to estimate the genetic diversity and elucidate the distribution patterns of the wild and domesticated cannabis from China; (2) to determine the main factors that affected the spatial distribution of cannabis and provide information on historical processes of this plant; (3) to infer the genetic relationships between the populations or lineages, as well as domestication origins of cannabis cultivars in China.Chloroplast DNA (cpDNA) markers and phylogeographic methods have been proven to be very useful tools in investigating genetic diversity, population structure, domestication origin, and historical context of species Avise, , 2009. TCannabis individuals (derived from 52 accessions: 25 wild populations and 27 domesticated populations or cultivars), and four closely related out group species, Humulus scandens, Humulus yunnanensis, Humulus lupulus, and Aphananthe aspera. Information relevant to the samples is shown in Table The studied material comprised 645 Cannabis throughout China: Inner Mongolia, Jilin, Liaoning, Shandong, Xinjiang, Tibet, and Yunnan provinces or regions. The population size of wild Cannabis is generally ranging from hundreds to several thousand individuals. Healthy leaves were collected in the field and immediately dried with silica gel until DNA extractions. To increase the possibility of detecting variation within each population, individuals growing at least 10 m apart were randomly sampled and in addition, eight to thirty plants were sampled from the edges and the interior of populations, depending on the actual population size. For domesticated populations, 27 cultivars represented by 215 individuals were included. Eighteen cultivars  from China were obtained from the Industrial Crops Research Institute, Yunnan Academy of Agricultural Sciences, and two European hemp cultivars, Kompolti and Futura75, were obtained from Hungary and France, respectively. About 200 seeds from each cultivar were planted and during the flowering stage leaves were sampled for DNA extraction. Additionally, two marijuana materials (named Afghanica and Dame Blanche) from The Netherlands were used, whereas sequence data for another five cultivars  were downloaded from GenBank and The Cannabis Genome Browser website (http://genome.ccbr.utoronto.ca/cgi-bin/hgGateway)  and 18 domesticated cultivars (L and B)] . These new primers are suitable for the population genetic study of Cannabis and its closest relative Humulus , 1.5 μL dNTPs mix (2.5 mmol/L), 0.5 μL each forward and reverse primers (10 μmol/L), 0.3 μL Taq DNA polymerase , and 17.7 μL double-distilled water. Amplifications were conducted on an ABI Veriti Thermal Cycler  using the following program setting: an initial 4 min pre-denaturation at 94°C, followed by 30 cycles of 45 s at 94°C, 30 s at 47–58°C , 2.5 μL 10 × PCR reaction Buffer  and then bidirectional sequencing was performed on an ABI 3730xl DNA Analyzer  employing the same primers used for PCR amplifications. All sequences of the 2, with a distance between rows of 40 cm . The plots were directly seeded at a depth of 3–5 cm on May 28 in 2016 and all wild-type seeds were pretreated to facilitate germination before sowing about 10 days, and the whole trial was managed with normal management practices. Main phenological and morphological traits for each accession were investigated, including initiation of flowering, full flowering, seed full maturity time, stem diameter, plant height, and number of branches. These data were collected based on 20 individuals randomly selected for each plot .To test whether there are obvious differences among the 43 accessions (including both wild and domesticated germplasms) on phenotypic characteristics, we also carried out a Varieties Evaluation Field Trial in 2016 involving all 43 accessions. The trial site was located in Kunming, Yunnan province of China. This trial was set up as a randomized complete block design with three replicates and each plot was 6 mRaw sequence data of the five amplified DNA fragments (amplicons) were assembled with SeqMan  and carefully checked for genetic variation together with the chromatograms. Sequences were aligned using the CLUSTAL W  with the maximum parsimony (MP) post-processing option.Based on the combined five-fragment dataset, the relationships among haplotypes were reconstructed by median-joining (MJ) network method  based on geographical coordinates and haplotype distribution data of Cannabis populations from China. Different hierarchical levels of genetic variation including within populations, among populations within groups and among groups were assessed by the analysis of molecular variance (AMOVA) implemented in Arlequin v 3.5.2.2  and haplotype diversity (Hd) were calculated for each population, population groups, and for all samples combined, using Arlequin v 3.5.2.2. Also, Tajima's D and Fu's Fs neutrality tests were conducted. Levels of gene flow (Fst and Nm) were measured using DNASP v5.10. Mantel tests were conducted to examine the correlation between two matrixes  with 9,999 permutations using GenALEx v 6.5  was plotted on maps of China using ArcGIS v 10.2 . To define the most differentiated groups of populations we performed a spatial analysis of molecular variance (SAMOVA) using the software SAMOVA v 2.0  based on the global climate layer data (at 2.5 arc-min resolution) downloaded from the WorldClim v2.0 database (http://www.worldclim.org/), and the mean day length of cannabis growth season  were calculated according to solar geometry  from the Maastrichtian (66–72.1 Ma) in late Cretaceous  for each of the 640 Cannabis individual plants. Five additional sequences of Cannabis lines were retrieved from the published chloroplast genomes , the sequence length and polymorphic informative characters are shown in Table We successfully obtained high quality sequences for all the five target cpDNA genes  was the highest, and the 43 populations from China were divided into three groups: Group H, Group M, and Group L  relationship with latitude of origin, Pearson' correlation coefficients (r) respectively were 0.858, 0.949, 0.906, 0.911, 0.914, 0.815 for initiation of flowering, full flowering, seed full maturity, stem diameter, plant height, and number of branches, respectively. When the phenotype of three genetic groups (above mentioned SAMOVA grouping) were compared, group H had the shortest growth time , thinnest stem diameter (0.54 ± 0.22 cm), shortest plant height (99.2 ± 52.4 cm), and fewest branches (3.2 ± 1.7), while Group L had the longest growth time , widest stem diameter (1.14 ± 0.40 cm), tallest height (238.0 ± 86.5 cm), and most branches (11.0 ± 3.9), and the traits data of Group M were in-between.Interestingly, we also noted that the main phenotypic traits of 43 wild or domesticated accessions originating from different latitudes shifted along latitudinal gradients (23.36–50.21° N), which matched the regular distribution of three lineages. Our phenotype data Table  indicateHd) and nucleotide diversity (Π) of each population are summarized in Table 1. The domesticated population C187 possessed the highest haplotype diversity (Hd = 0.782) and nucleotide diversity (Π = 0.00337), while the lowest number of haplotypes  were found in 18 other populations, including domesticated accessions and wild populations. Among the wild populations, the BM population had the highest haplotype diversity (Hd = 0.571), YN population had the highest nucleotide diversity (Π = 0.00379), and ZW had the highest number of haplotypes .For genetic diversity features, our studies showed that the number of haplotypes is different among the 43 Chinese populations, plus the cultivars Futura75 and Kompolti, ranging from 1 to 5 haplotypes. We observed that out of the 25 haplotypes, 15 private haplotypes were exclusively found in three wild populations  and in nine cultivated accessions . Haplotype diversity  and the “isolation-by-distance” pattern was detected. Furthermore, the testing between Nei's pairwise genetic distances and the latitudinal differentiation also showed a significant positive correlation . Similarly, for the 25 wild populations alone, significant positive correlations were found between the genetic distances and pairwise geographical distances , as well as between the genetic distances and latitude differences .To examine whether the observed genetic distributions are correlated to geographical localization, Mantel tests were performed. Between Nei's pairwise genetic distances Nei,  and the p < 0.05) relationship with haplogroup distribution frequencies for all the 43 populations , Bio2 , Bio8 (Mean temperature of wettest quarter), Bio13 (Precipitation of wettest month), Bio14 (Precipitation of driest month), Bio15  formed a minimum subset of climatic variables. Based on the ANOVA analysis, MDL was the most significant factor influencing the haplogroup distribution frequencies , and the subset of 6 climatic variables totally explained 74.2% of variation, and MDL accounted for the largest fraction of the total explained variation (20.8%).Haplogroup distribution frequencies shifted smoothly along latitudinal gradients and the three lineages distinctively show a high-middle-low latitude distribution pattern Figure . Based ons Table . This rep < 0.001). Population genetic differences (Fst) within the High-latitude lineage (Group H) was higher than that of the lower-latitude lineages (Group M and Group L), while gene flow (Nm) within Group M and Group L was higher than in Group H  revealed that most variance 69.48%) of the total observed genetic variations was due to variations between-groups, 14.43% was attributed to variance among populations within groups, and 16.10% to variance within the same population  genetic differentiation between the two groups. Most variance components were present among populations within groups. The degree of population differentiation was slightly higher in the wild group compared to the domesticated group. Results of the neutrality tests for each group and total sample set are shown in Table Fu's Fs and Tajima's D were statistically non-significance, suggesting stable populations on a different level.When two morphological groups (wild and domesticated) were considered for the same 43 populations, AMOVA analysis indicated low and non-significant  influence on the haplogroup distribution frequencies in each population by RDA analysis and ANOVA partition   areas have extended vegetative cycles and failed to produce seeds when grown in the North (High latitude areas) , 30 to 40° N (Haplogroup H), and South of 30° N (Haplogroup L). Some haplotypes of the haplogroups were aberrantly growing out of the main distribution latitude range  Small, . Due to e Figure . For inse Figure  have staCannabis  at the species level, a strong genetic differentiation among the three groups (Fst = 0.695), and the molecular variations observed are mostly between-cultivars (76.85%) or among groups (69.48%). It is worth noting that genetic variation at different levels of hierarchy contrasts to previous studies based on nuclear markers  were split into three gene pools without exception. On the phylogenetic tree, all Cannabis haplotypes formed a monophyletic clade , compared to the mean divergence of 3.0% that separated five pairs of plants considered as different species such as Humulus lupulus and H. japonicus in Canabaceae  is distributed in areas ranging from 27 to 43° N, is largely consistent with the observations by Small and Cronquist.The genus  Rendle, . This fa Rendle, . The cul Hillig, , 7 polym Hillig, , and EST Hillig,  based on Hillig, . In the e Figure  containie Figure . At firs and Guy . These aronquist  also poiAphananthe aspera, the basal taxon of the family Cannabaceae, and all the three Humulus species (the sister group of Cannabis) as outgroups for the dating analysis based on cpDNA markers and large numbers of Cannabis individuals. The reconstructed phylogenetic tree , which means Humulus and Cannabis diverged from a common ancestor before 18.23 Ma. This time period is in agreement with the divergence time (about 14 Ma) inferred by Zhang et al.  according to the fossil records , which is also the stem age of the three lineages. This diversification time coincides with the Quaternary glaciation, the last of five known glaciations during Earth's history which is thought to have started at 2.58 Ma, indicating that the Quaternary glaciation could have played a major role in the evolutionary history of the three subspecies of C. sativa. The current distribution of the three subspecies could be explained as a consequence of secondary contact after historical divergence events.In the present study, we included e Figure  shows thg et al. . In factTiffney, . The croC. saltiva  possesses the basal group position within Cannabis, indicating that this species is possibly originated from low latitude areas in the evolutionary history of this plant. This finding does not support the hypothesis of the Central-Asia-origin of Cannabis, but is partly in agreement with the speculation of Linnaeus (1737) that the native range of C. saltiva was India Orientali , Japonia (Japan), and Malabaria . Indeed, the seeds from wild Cannabis populations in India are remarkably small, unlike those collected from any other area, also indicating that the wild Indian populations may be an ancient wild form  should have been detected in different cultivars from high-middle-low latitude regions if the cultivars were domesticated from one single region. AMOVA analyses results also demonstrate that there is no significant difference (Fst = 0.023) between the wild population group and domesticated cultivar group based on cpDNA data. This molecular evidence is in accordance with the multiregional origin of human use of the cannabis plant proposed based on archaeological investigation  identified in this study contains haplotypes from both wild populations and cultivars. Within each haplogroup, the wild and domesticated populations shared the most common haplotypes. For instance, haplotype H1, H3, and H4 are the most common haplotypes shared by the wild and domesticated populations in Group H; similar trends are observed for haplotype H9 in Group M, and haplotypes H5 and H10 in the Group L. The fact that the haplotype of the domesticated QZ designed and performed the research, analyzed the data, and wrote the manuscript. QZ and XC contributed equally as first author. LT and ES carried out pre-experiment research and revised the manuscript in detail. HG, RG, MG, and YX conducted field work. XC and MY provided the technical assistance. MY organized this work. All authors contributed to and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


FST = 0.11) among the South American populations. The allele-sharing analysis and the admixture analysis revealed that the current diversity displayed by these populations resulted from multiple admixture events with a strong influence of the modern commercial egg-layer chicken (ranging between 44% and 79%). It also revealed an unknown genetic component that is mostly present in the Easter Island population that is also present in local chicken populations from the South American Pacific fringe.Chicken have a considerable impact in South American rural household economy as a source of animal protein (eggs and meat) and a major role in cultural traditions . A large number of phenotypes and its heterogeneity are due to the multitude of environments  and agricultural systems . This heterogeneity also represents the successive introduction of domestic chicken into this continent, which some consider predating Columbus’ arrival to South America. In this study, we have used next-generation restriction site-associated DNA sequencing to scan for genome-wide variation across 145 South American chickens representing local populations from six countries of South America . After quality control, the genotypes of 122,801 single nucleotide polymorphisms (SNPs) were used to assess the genomic diversity and interpopulation genetic relationship between those populations and their potential sources. The estimated population genetic diversity displayed that the gamefowl has the least diverse population . This population is also the most divergent ( Gallus gallus domesticus, is a major source of animal protein (eggs and meat) and owes its popularity to low-cost production and the inexistence of any cultural or religious prohibition to its consumption. Chicken production is even more important in rural areas with economies based on subsistence agriculture. Additionally, besides being a source of food, in some regions of the globe, the chicken has been also used for cultural, religious, and entertainment proposes  from jungles in South and Southeast Asia is considered the most probable ancestor of the domestic chicken  have been created , which hIn the last decade, access to next-generation sequencing (NGS) has permitted the development of more cost-effective and efficient techniques to measure variation at a genome-wide scale. NGS has permitted major advances in demographic parameters estimation as well as on the identification of genes underlying adaptation and production traits, and this in combination with phenotype data can accelerate breeding in plants and animals  throughout the genome to characterize six SA local chicken populations from Bolivia, Brazil, Colombia, Chile , Ecuador, and Peru. As cock-fighting has an important socio-cultural role in South America in the last centuries , this re2 of the comb of 145 local domestic chickens were collected from six SA local populations representing: Bolivia (N = 6), Brazil (N = 4), Chile , Colombia (N = 17), Ecuador (N = 16), Peru (N = 17), and gamefowl (N = 14). Individuals representing local Iberian Peninsula chicken (N = 17) as well as individuals representing commercial egg layers  and broiler (N = 15) were also sampled. Samples were stored in 95% ethanol at -20°C.Approximately 2 mmSbfI  using a new RAD protocol . After cleavage, unique barcodes were ligated on and the samples were pooled, sheared in a Bioruptor NGS , and used as input for NEBNext Ultra DNA Library Prep Kit for Illumina . The libraries were sequenced on an Ilumina Hiseq 2500 using paired end 100 bp reads.Genomic DNA was extracted using a JetQuick™ Tissue DNA Spin Kit  and quantified using a Qubit Fluorimeter (Thermo Fisher Scientific). RADseq sequencing libraries were prepared using the eight base-pair recognition site restriction enzyme protocol . In briehttps://ftp.ncbi.nih.gov/snp/organisms/archive/chicken_9031/) for matches between our variants and those already identified in genome-wide studies. SNP annotation was performed using the SnpEff 3.0 program , using the galGal4 genome version as the reference.We demultiplexed the libraries filtering solely the reads having a full barcode match and a partial restriction site match. Sequences were aligned to the Galgal4 Chicken Genome assembly , using tST windows were used to measure genetic differentiation between populations  for the same pair of populations as the variable. Averages, standard error, and plots were generated using the R software (The two most common indexes of molecular genetic variation (θ)—mean pairwise differences between sequences π;  and Wattulations  using thulations . Additiosoftware .To count the number of shared SNPs among South American chicken populations, we created Variant Call Format Files (VCF) for four groups of samples according to their geographical location. One group, composed by the individuals from South American countries located at Pacific fringe , another group formed by individuals from the Atlantic fringe (Colombia and Brazil), and the potential source populations were kept in two separated groups. The number of shared variants between the groups was determined using the module vcf-compare included also in the VCFtools software, which conducts simple comparisons between VCF files. Venn diagrams  were user2 parameter was estimated to identify SNPs in linkage disequilibrium (LD) using the software PLINK v1.9  . The method implemented takes into account the genotype uncertainty and uses the output of the analyses performed in ANGSD to identify the polymorphic sites , estimate the major and minor alleles (doMajorMinor 1), and infer the minimum allele frequencies (doMaf 2). Finally, we only retained loci with a minor allele frequency of <0.05 (minMaf). The posterior genotype probabilities were calculated with uniform a priori (doPost 2). The covariance matrix between individuals was calculated weighting each genotype for its posterior probability  implemented in the ngsTools package  and the bability .To explore the relatedness among the chicken populations, we used the admixture model implemented in NGSadmix . This meHypothetical ancestral admixture events among local South American chicken populations and the four possible population sources  were assessed using TreeMix , which cf3 , and when significantly negative values of the f3 statistic are obtained, it implies that population A is admixed. Finally, ROLLOFF software  estimated per 1,000 bp window attained the lowest values (θS and θπ) in the gamefowl population, and the Chile local chicken population showed the highest values for θS and the Brazilian and Bolivian population the highest values for θπ , all the populations showed a higher number of variants shared with the Pacific group, ranging from 108 in Peru up to 750 in Chile. In the Pacific group, the lowest number of private variants was found in Peru (19) and was highest in the Bolivian population (105). The Atlantic façade populations had a higher number of unique variants compared with the Pacific, with the maximum found in Brazil (113). The number of variants shared between the South American chicken and the egg layer was lower (between 1 and 46) than the number of variants shared with the broilers (between 17 and 124), the Iberian Peninsula (between 29 and 169), and the gamefowl (between 32 and 130). Individually, the Easter Island population displayed the highest values in terms of private and shared variants. A deeper analysis showed that 643 SNPs were exclusively found in the Easter Island population; 106 were shared only with egg layers, 367 only with broilers, 487 shared with gamefowl, 504 shared with the Iberian Peninsula, and 1,024 and 345 shared with the Pacific and the Atlantic South American groups, respectively Figure 1As for θπ Figure 1BRegarding the population structure and genetic relationships, the most remarkable finding revealed in the PCA plot Figure 2 ST values ranging from 11% (Colombia) to 28% (egg layer). All the remaining populations showed lower differentiation levels ranging between 1% between Brazil and Bolivia and 17% between egg layer and Easter Island populations. A one-way ANOVA and Tukey’s post hoc analysis of the weighted FST estimates (50 kb sliding windows) showed that the differentiation between South America and the hypothesized population sources  is highly significant (P < 0.001). When ranking the potential source populations according to their degree of differentiation from the SA, the Iberian Peninsula showed the lowest differentiation (FST = 0.014), followed by the egg layer (FST = 0.039) and the broiler (FST = 0.056), and the gamefowl displayed the highest value (FST = 0.1)  Figure S1The Bayesian clustering analysis performed with NGSadmix was consistent with the PCA results. The relatively closely related group formed by all South American populations depicted by the PCA is also confirmed by plotting the admixture analysis results Figure 3.As the previous analysis pointed to a large influence of commercial breeds in the South American chicken, we have quantified this influence using TreeMix analyses. The obtained phylogenetic tree reflects the divergence patterns among the different chicken populations Figure 3 f3-statistics analysis, through 3-population test, to confirm the introgression events identified using the TreeMix method, returned significant values for the combinations f3  and f3 . For the Pacific–egg layer–gamefowl combination, the calculated values were f3= -0.0017, Z = -12.44 and for the Atlantic–egg layers–gamefowl combination, calculated values were f3= -0.0017, Z = -16.599  showed similar diversity per population Figure 1BThe patterns of the genetic variants shared among the different populations also provide insights about the continental South American chicken population diversity. Interestingly, the Easter Island population is the one displaying the highest number of unique variants (643), and this can be interpreted as the result of its different demographic history and/or different population origins. The high number of unique alleles could be explained by the different origins of the chicken introduced on this island across time . Alternafaçade  or the Pacific façade .The PCA plot Figure 2 ST estimates between the gamefowl and all the other South American populations (Table S2) is not very surprising. The different breeding objectives  and the observed low levels of diversity are the two most probable causes of this high differentiation regarding the other South American populations. Indeed, the admixture analysis shows the absence of influence from the other tested breeds in the gamefowl  to explain most of the variance (99.8%) depicted by the phylogram Figure S2roll off admixture analysis detected signs of a strong introgression in SA population dating between 35 and 70 years ago, which is concordant with the worldwide expansion of poultry industry based on highly productive chicken lineages. If this is correct, then the current SA local chicken accumulates the legacy of the older chicken introduced with those modern highly selected varieties.It has been hypothesized that European and Asian chickens were introduced in SA after 1500 ; neverthIn Ecuador, Peru and, Colombia, cock-fighting is a popular part of their culture and local recreation activities . Howeverhttps://www.ncbi.nlm.nih.gov/bioproject/573756 (Accession: PRJNA573756).The datasets generated for this study can be found in the BioProject database: Standard techniques were used to collect very small piece of tissue from each animal, by local veterinary trained personnel. The procedure was reviewed and approved by CIBIO-University of Porto Committee of ethics.AB-P, AL-N, GV-R, and FC-C conceived the study. AL-N, SO’R and AB-P drafted the manuscript. AL-N, LP-P, and MM participated in the data analysis. AL-N and SO’R did the laboratory work. AL-N, AU-N, GE-S, J A-P, MV and MR-Q did the sampling. AB-P and MRM supervised the study. All the authors read and approved the manuscript.This work was supported by funds from the project NORTE-01-0145-FEDER-000007, from the Norte Portugal Regional Operational Program (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). AL-N was supported by a doctoral grant from SENESCYT, LP-P was a recipient of a postdoctoral grant from the Portuguese Science Foundation (FCT) (SFRH/BPD/94518/2013), and AB-P was a recipient of an IF contract from the FCT.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ammopiptanthus mongolicus, a broad-leaved evergreen psammophyte in eastern Central Asia, was previously thought to follow an isolation by distance pattern. However, recent studies have emphasized the effects of environmental factors on its growth and distribution, suggesting an important influence of local adaptation on the genetic structure of the species. Using inter-simple sequence repeat (ISSR) markers, we verified the previously inferred low intra-population variation and high inter-population differentiation. However, in contrast to previous studies, the results of partial Mantel tests and a maximum likelihood population effects mixed model (MLPE) suggested that local climate differences, rather than geographic distances or resistance distances, are the main factor affecting population differentiation. Further analysis with removal of multicollinear climatic variables and univariate MLPE found that summer and winter precipitation were crucial for shaping the current population genetic structure. Since local precipitation is related to the regeneration, colonization, and overwintering survival of A. mongolicus, its influence on demographic change may explain its effect on the population genetic structure. In addition, precipitation is related to terrain despite westward decreases, which explains the independence of genetic difference and geographic distance. The identified role of IBE suggests that collecting germplasm resources from genetically differentiated populations could be a more effective strategy to preserve the overall genetic diversity of the species than the establishment of corridors to enhance gene flow among populations.Whether the effect of migration-selection-drift equilibrium on population structure is governed by spatial or environmental differences is usually elucidated by isolation-by-distance (IBD), isolation-by-environment (IBE), and isolation-by-resistance (IBR) tests. The population structure of  Geographic distance and environmental difference are two key factors affecting genetic structure between populations2. The former is related to the interplay of genetic drift and movement, while the latter is usually related to the adaptability to environmental pressure3. In changeable environments, selection determines genetic diversity of adapted genes, and the genetic diversity of neutral genes would be also reduced by random associations with genetic backgrounds of different fitness (i.e. genetic draft)4. Due to the combined effects of genetic drift and variation-reducting selection, the distribution of genetic variation among populations may be uneven and the genetic diversity may be lower than expected predicted by census population size6. Such decline in genetic diversity may in turn limit the adaptability of populations to environmental change. Gene rescue by gene flow can reduce the threat of local extinction7, although the influx of genes may be still constrained by environmental selection8.Random genetic drift, environment-leading selection, genetic draft (hitchhiking), and background selection may affect the genetic diversity of organisms10. The additive effect of such autocorrelations is due not only to the proportional alignment of environmental differences with geographic distance but also to the promotion of divergence by ecological barriers to gene flow3. That is, when environmental conditions differ, the reduced establishment success of immigrants may accelerate the genetic fixation rate due to the decreased chance of outcrossing, thereby enhancing genetic isolation. This phenomenon not only appears in adaptive loci but could also extend to the whole genome via genetic draft caused by selective sweeps1. In this situation, the synergistic effects of environmental-driven and draft selection will lead to positive correlations of both neutral and adaptive loci (instead of adaptive loci only) with environmental differences3.The population structure of a species distributed across an environmental gradient may be affected by both geographic and environmental factors simultaneously. Autocorrelations of geographic and environmental distances can be additive for genetic differentiation among populations but often confound each other11. Spatial resilience focuses on the patterns and processes of connectivity among locations. The local system resilience may be affected by the geographic distance and environmental heterogeneity among localities. Populations with isolation-by-distance (IBD) reveal positive correlations between genetic distances and geographic distances among populations, in which the genetic diversity turnover relies on the genetic rescue from neighboring populations. By contrast, isolation-by-environment (IBE) indicates populations harboring different genotypes. Variations in genetic composition of IBE populations are sensitive to environmental changes. Populations that are already adapted to alternative environments could harbor higher resilience and potential to adapt to environmental change. Therefore, the resilience of IBE populations is determined by the degree of environmental differences and the adaptability of the population. In addition, terrain and environmental variation may impede the direction and success of dispersal, i.e. isolation-by-resistance (IBR)13. IBR represents the ecological process or physiological limitation of organisms to dispersal14. Lower terrain and environmental resistance and unimpeded habitat connectivity enhance the resilience for species persistence. Since populations affected by IBE potentially have more restricted niche tolerance than a population of a comparable species with only IBD, the mechanism structuring populations must be considered when formulating conservation policies.The impact of geographic distance or environmental difference on genetic differences among populations of a species reveals differences in resilience in adapting to heterogeneous environmentsex situ conservation should be adopted for species with a signature of local adaptation, whereas a single-large strategy may be appropriate for species with IBD or low genetic structure15. In other words, the test of IBD, IBE, and IBR can help to understand the process of population genetic differentiation, which will provide a reference for habitat conservation and management of endangered species.An understanding of local adaptation and dispersal limitation can support the development of more appropriate management strategies. For example, when evaluating “single-large or several-small” (SLOSS) strategies for planning a protected area, the several-small strategy and/or collection of germplasm resources from different populations for 16. External changes on the landscape and environment in combination with adaptability can also affect their population structure17, especially in desert areas where the environment is poor. The xeric plant Ammopiptanthus mongolicus (Maxim. ex Kom.) Cheng f. (Leguminosae) is the only broad-leaved evergreen shrub in the deserts of eastern Central Asia. A. mongolicus is listed as a second-grade vulnerable (VU) plant in the Red List of Threatened Species of China (the Red Book)18. Understanding the population genetic structure not only increases the understanding of its demographic dynamics, but also provides information for conservation 19. Previous research using inter-simple sequence repeat (ISSR) markers concluded that the genetic differentiation of A. mongolicus was related to geographic distance, i.e. IBD20. Codominant marker evidence (isozymes) indicated that this species is an outcrossed but self-compatible entomophilous plant21. The small pollination range of insects and the gravity propagation of seeds were suggested as limiting factors for long-distance gene flow in A. mongolicus20. Ammopiptanthus mongolicus grows in rocky, gravelly, sandy soils of dry valleys, basins, and rocky dunes with a soil depth of less than 30 cm22. Most of the desert psammophytes exhibit a spatial distribution strongly associated with scattered fertile soils 24. In contrast, A. mongolicus can grow in heterogenous microhabitats25. Despite the environmental versatility of A. mongolicus at a fine spatial scale, recent studies have shown its global distribution is limited by local climatic conditions , soil organic matter and total nitrogen26. Given that environmental variation can critically influence distribution and population sizes of A. mongolicus, the isolation-by environment is expected to exert a relevant influence on the genetic structuring of the species. However, previous genetic studies have failed to consider the impact of the local environment on the genetic differentiation of A. mongolicus populations27.Each plant occupies its own niche, and spatial and resource competition and environmental adaptation determine plants’ distributionsA. mongolicus populations are genetically differentiated as inferred by Ge et al.20. We further explored the factors that hinder gene flow among genetically differentiated populations. In addition, since this species has a wide-ranging latitudinal distribution with a varying altitudinal distribution (ranging from ~1000 to 2000 m above sea level), we hypothesized that geographic distance, differences in local climate, and resistance of gene flow to altitudinal and climatic differences drive population genetic differentiation, i.e. isolation-by-distance (IBD), isolation-by-environment (IBE), and isolation-by-resistance (IBR). Accordingly, by outlining the genetic structure and identifying the influencing factors of A. mongolicus, conservation suggestions for this endangered Tertiary relict are provided.In this study, we explored the effects of geographic distance and local climate on population structure by performing population genetic analyses. We used a multilocus marker, the ISSR, to verify whether HE) was below 0.12 and the Shannon index (I) was below 0.16 in all studied populations, with two distant populations (WLTH and ALSY) exhibiting the largest values . The high genetic diversity of the total population relative to each single population suggests high differentiation among the populations.From a total of 200 samples collected from 10 populations  of genetic components was two based on the logarithmic probability change rate of successive K-value data. When K = 2, the populations ALSZNRG, EJNYG, ALYSHT, and HLS clustered together, while the remaining populations formed another group  instead of IBD , IBRclim , or IBRalt  , implying that the farther the geographic distance, the greater the environmental difference. Model selections for the maximum likelihood population effect mixed effect (MLPE) revealed that the IBE was the first-ranked model explaining the population genetic structure according to the ranking of the AIC and BIC  process of organisms by climate differences. However, despite small ΔAIC between IBE and IBRclim, the effect size of the fixed effect (climatic composite resistance distance) is small (fixed estimate = 0.020) in IBRclim, suggesting that the environmental resistance during migration contributes less than the selective pressure after colonization.Models of IBD, IBE, and IBR were tested to explain the genetic differentiation patterns among populations of 28. Therefore, we removed the bioclimatic factors with multicollinearity and conducted the partial Mantel test again using each retained single factor . Bio12 , bio13 (precipitation of the wettest month), bio16 (precipitation of the wettest quarter), and bio18 (precipitation of the warmest quarter) are all bioclimatic dimensions related to precipitation. According to the monthly precipitation records  revealed significant IBE patterns, including 37.1% (27 studies) revealing spatial autocorrelation (i.e. covariates with IBD)9. Similarly, from 106 IBE studies, Shafer and Wolf10 reported effect sizes of 0.34 (95% CI 0.24–0.42) and 0.26 (95% CI 0.13–0.37) for a mixed-effect model with and without controlling spatial autocorrelation, respectively, suggesting that spatial autocorrelation reduces IBE correlations for environmental variables. These studies indicated the relevance of environmental autocorrelation for the spatial effect (i.e. IBD). That is, the previous inference that the population differentiation of A. mongolicus aligns with geographic distance20 probably reflects differential adaptation to the local climate. Differential adaptability to heterogeneous environments provides a better explanation than IBD in A. mongolicus, i.e. divergent selection is more important than neutral processes.The population genetic structure of et al.20, which included populations located farther south but no populations in Alashan . The genetic diversity of A. mongolicus was also lower than that of other desert species estimated by ISSR, e.g. Achillea fragrantissima in Egypt35, Citrullus colocynthis in India36, and Lasiurus sindicus in India37. Although the factors affecting the genetic diversity of species vary, the selection pressure of local precipitation with genetic draft may be the limiting factor affecting the genetic variation of desert plant populations, such as A. mongolicus in this case.The low estimates of genetic diversity are consistent with the previous estimation by Ge 39, and the constraint of the range of distribution may lead to deleterious erosion of genetic diversity due to increased inbreeding and genetic draft39. Precipitation is an important limiting factor for the reproductive success of desert plants. The growth pattern of A. mongolicus is similar to that of desert deciduous plants or summer annuals, with blossoming and germination during the high-rainfall season40. Rapid blooming is advantageous for plant reproductive success in the desert40. However, pollinators tend to visit flowers of the same or adjacent plants instead of distant flowers in the short blooming season, which may reduce the outcrossing rate of A. mongolicus .Environmental heterogeneity would reduce the chance of dispersalA. mongolicus. With a selective sweep, genetic variation of adjacent genes decreases along with adaptive loci, which will even expands to most genome regions. Compared with other plants that may also be affected by genetic draft, such as Dactylis glomerata L. in the plateau of Central Asia and Western China41, A. mongolicus exhibits extremely low intra-population genetic variation, suggesting that regional environmental pressures  in the desert have a more severe impact on this broad-leaved green plant. Rainfall-induced declines in outcrossing opportunities and strong selective sweeps could explain the low genetic variation of A. mongolicus, which may also be resistant to the rescue effect of gene flow among populations.In addition, rainfall restrictions in deserts may also result in strong selection on A. mongolicus. In general, the annual precipitation tends to decline in a southeast-to-northwest direction across the Asian continent42, but fluctuations in terrain  make the local climate more complicated. Such local differential precipitation may have long been the selective pressure not only for the breeding and dispersion of A. mongolicus but also for the water supply in the dry season.Summer rainfall almost completely determines the annual precipitation in the distribution of 43 and seedling growth44 of A. mongolicus. In summer (July and August), the legume of A. mongolicus is ripe and dehiscent, and seeds fall off, quickly absorb water and germinate43. In a manipulation experiment, 85% of seedlings wilted in a 5-day drought treatment44, indicating that the demand for water is a limiting factor for the regeneration of A. mongolicus. Due to the lack of defoliation in winter, supplementing evapotranspiration with some precipitation may also affect A. mongolicus survival in winter. Although the local precipitation is small and varies little in winter (the cumulative precipitation ranges from 0 to 6.06 mm in Dec~Feb), such differences may cause local adaptation. Differential adaptability to precipitation among populations might accelerate the process of population differentiation by stalling maladaptive immigration.Several studies have indicated that water is the key factor affecting the seed germination45. Differences in precipitation could vary the ratio of bee pollinators to fly pollinators; the former require dry soil for nesting, whereas the latter require moist environments for larval growth and metamorphosis46. Changes in the abundance of pollinators could affect the success of pollination and seed yield, even though the connectivity of the plant and pollinator relationship may not be disturbed by precipitation47. In addition, precipitation can also affect rhizobium symbionts48 and pathogen infectivity49, thereby affecting plant health and population regeneration. The presence of some endosymbiotic fungi (dark septate endophytes) can facilitate the growth of A. mongolicus under drought conditions50. We have not explored differences in soil microorganisms and endophytes among different populations, but distributional differences of these endophytes may also cause differential adaptability to precipitation among populations. The local adaptation caused by differential precipitation may lead to divergent directions of genetic draft, which may explain apparent population differentiation in A. mongolicus.As described above, differential local precipitation might also affect pollinators’ species and visiting frequencyA. mongolicus and likely explains the low genetic variation within populations and high population differentiation. Most individuals carry not only locally adapted genes but also homogenized genomic variation, which decreases successful emigration to populations with different environments, i.e. selection against maladapted dispersers31. A. mongolicus is the only evergreen shrub in the desert of Northwest China and is an important wintering place for several small animals, i.e. an umbrella species. Given the low genetic variation within populations and maladapted gene flow among populations, every population is a unique evolutionarily significant unit and should be considered as a unique management unit for conservation. The high dependence of adaptability on precipitation is not propitious for effective gene flow among populations. Therefore, the establishment of ecological corridors53 may not be an appropriate strategy for conservation. Germplasms from different populations should be actively preserved to maintain the complete gene pool and increase the evolutionary resilience9 of A. mongolicus in the face of increasingly severe climate change.In conclusion, the selective pressure of the environmental gradient (differences in precipitation) is strong for Ammopiptanthus was suggested to have originated from the broad-leaved evergreen Tethyan flora54, as supported by molecular dating indicating that the genus Ammopiptanthus split from its sister taxa in the early Miocene 55. Ammopiptanthus mongolicus is discontinuous distributed in western Inner Mongolia, northern Ningxia and Northern Gansu in China, ranging from 36°27′N–42°01′N, 102°36′E–108° 49′E26. The sampling area of this study was the core distribution of A. mongolicus in Inner Mongolia, China. We chose 10 populations covering the main distribution range of A. mongolicus (Table The genus 260/OD280: 1.7~1.9) in a WD-9403C UV Viewing Cabinet . ISSR amplification was performed using fifteen primers . DNA quality was checked by agarose gel electrophoresis and by the DNA absorbance ratio (ODNA), effective number of alleles per locus (NE), Shannon’s information index (I), expected heterozygosity (HE), and unbiased heterozygosity (UHE) using GenAlEx v. 6.556. The contributions of genetic variation between and within populations were assessed by analysis of molecular variance (AMOVA). The significance of genetic differentiation between populations was estimated by ΦST under 999 permutations. We also conducted DAPC to determine if the spatially structured population was also genetically structured using the package adegenet57 in R58. The best clustering number (k) was inferred by the k-means algorithm with 106 simulations evaluated by BIC . The optimal number of PCs retained for DAPC was evaluated by a-score optimization. A component plot and scatter plot were drawn to illustrate the population clustering pattern of A. mongolicus. Patterns of genetic admixture were assessed by Bayesian clustering analysis, a population model-based approach based on Hardy-Weinberg and linkage equilibria59, with the assistance of STRUCTURE 2.3.460. We estimated the posterior probability of the grouping number (K = 1–20) by 10 independent runs using 106 steps of Markov chain Monte Carlo (MCMC) replicates after 10% burn-in for each run to evaluate consistency. The best grouping number was evaluated by ΔK61 in STRUCTURE HARVESTER ver. 0.6.9462. In addition, to understand the relationships between each of the lineages, we transformed the number of differences in ISSR loci between individuals into a triangular matrix and then constructed an NJ tree using MEGA663.The genetic diversity was estimated by the indices of percentage of polymorphic loci (%P), average number of different alleles per locus 65. Euclidean distances of geographic distance were calculated using the R package fossil66. We also collected 19 standard bioclimatic variables of 10 sampling sites as environmental data from WorldClim version 2.067. We considered the 19 bioclimatic variables as different environmental space vectors and used the Canberra distance to calculate the distance between populations in this vector space. To test IBD, the genetic distance was used as the response, the geographic distance as the predictor, and the environmental distance as the condition factor. To test IBE, the roles of environmental distance and geographic distance were interchanged. In addition, to test whether these environmental factors impeded gene flow, the climatic composite resistance surface was transformed from raster layers of the bioclimatic variables using Circuitscape 4.068. We also transformed the altitudinal layer into an altitudinal resistance surface. These two resistance surfaces were used to test IBR, namely IBRclim and IBRalt, respectively. The Mantel statistic was based on Spearman’s rank correlation with 9999 permutations.To test the effects of geographic distance and environmental differences on genetic structure, the partial Mantel test was conducted using the R package vegan69. Therefore, we fit linear mixed-effects models using the MLPE parameterization, which has been found to perform better than other regression-based statistical approaches70, to account for the non-independence of values within pairwise distance matrices and to distinguish the effects of multiple independent variables. Mixed-effects models were fit by maximum likelihood to test the effects of fixed factors  with the random effect of populations. AIC and BIC were used as the objective criteria to evaluate model fit from four models of single fixed factor, six combinations of double fixed factors, four combinations of triple fixed factors, and the full model  and then calculated the distances of the retained bioclimatic variables among populations to test the IBE hypothesis  test has been suggested to be more credible than testing multiple variables28. Second, we performed model selection to evaluate 19 models with every single bioclimatic distance as the fixed factor in MLPE. These single-bioclimate-distance IBE models were ranked by AIC, and the model with the lowest AIC was suggested as the best one for the prediction of population genetic structure.Since IBE was suggested as the first-ranked model by both the partial Mantel test and model selection for MLPE (see Results), we further identified the most crucial environmental factors affecting genetic distance using two strategies. First, we re-executed the partial Mantel test by calculating the distance of each environmental factor between populations. To avoid unnecessary weighting due to intercorrelations among bioclimatic variables, we used variance inflation factor (VIF) analysis to reduce multicollinearitysis Fig. . This reDataset1


Lymantria dispar, a prominent polyphagous species native to Eurasia, causes severe impacts in deciduous forests during irregular periodical outbreaks. This study aimed to describe the genetic structure and diversity among European gypsy moth populations. Analysis of about 500 individuals using a partial region of the mitochondrial COI gene, L. dispar was characterized by low genetic diversity, limited population structure, and strong evidence that all extant haplogroups arose via a single Holocene population expansion event. Overall 60 haplotypes connected to a single parsimony network were detected and genetic diversity was highest for the coastal populations Croatia, Italy, and France, while lowest in continental populations. Phylogenetic reconstruction resulted in three groups that were geographically located in Central Europe, Dinaric Alps, and the Balkan Peninsula. In addition to recent events, the genetic structure reflects strong gene flow and the ability of gypsy moth to feed on about 400 deciduous and conifer species. Distinct genetic groups were detected in populations from Georgia. This remote population exhibited haplotypes intermediate to the European L. dispar dispar, Asian L. dispar asiatica, and L. dispar japonica clusters, highlighting this area as a possible hybridization zone of this species for future studies applying genomic approaches.The gypsy moth,  Lymantria dispar L. , is a polyphagous pest feeding on more than 400 plant species with a preference for species within the genus Quercus [Lymantria dispar is native to the Palearctic region [L. dispar is considered one of the most notorious forest pests worldwide [L. dispar dispar) and two Asian (L. dispar asiatica in Russia and Asia and L. dispar japonica in Japan), and each of them is described separately based on morphological and behavioral traits [The gypsy moth,  Quercus . Lymantrc region ,2 and bec region . Currentorldwide . Nonetheorldwide  as in caorldwide . For allorldwide  and disporldwide ,10 to thorldwide ,12. Threl traits , as recel traits .First genetic analysis based on DNA sequences resulted in developing an mtDNA marker that verified the close resemblance of North American and European population, that both were distinctly separated from Asian populations . This paUntil recently, studies on European populations of gypsy moth were mostly integrated into broader investigations that aimed at a global overview of this species ,15. A stSamples (larvae) were collected from 36 localities in sixteen European countries and two additional sites from Georgia between 2010 and 2014 , with spST(obs) was greater than NST(exp) using heuristic permutation test with 1000 replicates in PERMUT 1.0 [ST in order to assess the depth of differentiation.Haplotype diversity, nucleotide diversity, mean number of pairwise differences and allelic richness were calculated for each population using ARLEQUIN  and ContRMUT 1.0 , and subCT), among populations within groups (FST), and within populations (FSC)), objective grouping and Analysis of Molecular Variance were performed using ARLEQUIN [6 generations, with a sampling frequency of 100 generations in order to define the trees to be discarded in the second run. As a plateau between standard deviations was reached after 5 × 105 generations, 500 trees were discarded from the estimation of the consensus tree. To better understand the assignment of haplotypes in clades and their geographic distribution, we also used sequences deposited in NCBI GenBank from previous investigations of L. dispar , HM013736 (Japan), HM013737 (Japan) [To separate the source of variation in three hierarchical levels  ; KX43620 (Japan) ; KY92305 (Japan) ).specaccum of the vegan package [Locality map and haplotype distribution map were constructed using ArcMap 9. 3  and Genetic Landscape Toolbox  and arra package .L. dispar COI sequence) were used for further analyses. Cladistic analysis resulted in 60 haplotypes (T was 0.81 and intrapopulation diversity HS was 0.437 (data not shown). The lowest genetic diversity values were spotted in populations from the continental basin of the Balkan Peninsula between Dinaric Alps, Alps and Carpathian Alps and in northern Continental regions. On the other hand, the highest genetic diversity was observed in Coastal Croatia, Italy, and France. Populations from the Aegean coast and Black sea coast showed rather low diversity, while populations from Georgia showed intermediate values  = 0.463 (0.056) was smaller than observed fixation index NST(obs.) (se) = 0.521 (0.059) which was significantly greater than theoretical fixation index NST(theor.) (se) = 0.456 (0.001) (p = 0.010), confirming the existence of a limited phylogeographic structure (GST < NST(obs.) > NST(theor.)) (p < 0.01), with the main source of divergence being found among populations within groups , and within populations , rejecting the hypothesis of host-driven divergence at least among the broadleaved hosts analyzed in the current study. Fixation index Gtheor.)) . NeverthL. dispar asiatica/L. japonica haplotypes  retrieved from NCBI  is congruent with previous findings that this clade arose around 200 thousand years (kyr) [L. dispar dispar in Europe seems to have been shaped by at least two refugia, one located near the Carpathian Mountains (green) spreading to Central Europe and the Pontic-Mediterranean region (blue) spreading to the Balkans and the north of Europe. Furthermore, it is likely that contemporary pattern of gypsy moth phylogeography in Europe was also influenced by anthropogenic migration. This has been already hypothesized in the recent study of the Asian gypsy moth based on COI barcode sequences [Major ,39,40 an of them . Intrasprs (kyr) . In partequences  that revL. dispar populations would have been expected to exhibit deep intraspecific divergence as different selection pressures are associated with different host plants, something that favors the emergence of barriers to gene flow [Pityogenes chalcographus [Heliconius melpomene [L. dispar as the combination of the migratory pathways  could fmovement .L. dispar asiatica and L. dispar japonica, shows that there are likely many more genotypic entities than recently described [Despite the relatively large sample, we were able to determine only limited inferences of phylogeographic structure among localities in Europe, with at least two refugial areas contributing to the current genetic structure of gypsy moth. The near panmictic status of haplotype LD4 also present in Georgia suggests that more complex forces have taken role in shaping of the contemporary phylogeographic pattern of gypsy moth, and one of likely explanations could be a man-aided dispersal. Such hypotheses have already been drawn on larger scale studies . Howeverescribed . In factescribed ,58, the


Anopheles gambiae s.l. complex species to pyrethroids. The voltage-dependent sodium channel (Vgsc) gene is the main target of pyrethroids and DDT. In Benin, the frequency of the resistant allele (L1014F) of this gene varies along the north-south transect. Monitoring the evolution of resistance is necessary to better appreciate the genetic structure of vector populations in localities subject to the intensive use of chemicals associated with other control initiatives. The purpose of this study was to map the distribution of pyrethroid insecticide resistance alleles of the Kdr gene in malaria vectors in different regions and ecological facies in order to identify the evolutionary forces that might be the basis of anopheline population dynamics.Several studies have reported the strong resistance of Anopheles gambiae s.l. populations and resistance mechanisms were performed using adult mosquitoes obtained from larvae collected in the four agroecological zones in southern Benin. Genomic DNA extraction was performed on whole mosquitoes.The characterization of Anopheles gambiae s.l. complex and the identification of genotypes related to pyrethroid resistance as the Kdr gene amino acid position 1014 in sodium channel. Molecular speciation and genotyping of Kdr resistant alleles (1014) were done using PCR.The extracted genomic DNA from them were used for the molecular identification of species in p value of the allelic frequency was determined using the binomial test function in R version 3.3.3. The Hardy-Weinberg equilibrium was checked for each population with Genetics software version 1.3.8.1. The observed heterozygosity and the expected heterozygosity as well as the fixation index and genetic differentiation index within and between populations were calculated using Genepop software version 4.2.Genepop software version 4.2 was used to calculate allelic and genotypic frequencies in each agroecological zone. The Anopheles coluzzii was the major species in all agroecological zones while Anopheles gambiae was scarcely represented. Regardless of the species, resistant homozygote individuals (L1014F/L1014F) were dominant in all agroecological zones, showing a strong selection of the resistant allele (L1014F). All populations showed a deficit of heterozygosity. No genetic differentiation was observed between the different populations of the two species. For Anopheles coluzzii, there was a small differentiation among the populations of the central cotton and bar-lands zones. The genetic differentiation was modest among the population of the fisheries zone (Fst = 0.1295). The genetic differentiation was very high in the population of Anopheles gambiae of the bar-lands zone (Fst = 0.2408).During the study period, Anopheles gambiae s.s. populations in all agroecological zones of southern Benin. It would be desirable to orientate vector control efforts towards the use of insecticides other than pyrethroids and DDT or combinations of insecticides with different modes of action.This study revealed that the use of insecticides in Benin for years has altered the genetic structure of  Anopheles gambiae s.s., Anopheles funestus, and Anopheles arabiensis species are the most frequent malaria vectors in sub-Saharan Africa , and large when it is between . This differentiation is very large if the Fst value is greater than 0.25.Several analytical approaches were used to establish the genetic structure of populations. The genetic constitution of each population was determined by calculating the allelic and genotypic frequencies of the am (W&C)  and Robeam (W&C)  formulasby Hartl . GeneticAnopheles gambiae complex identified. In all agroecological zones, Anopheles coluzzii was the major species. The analysis of the results revealed that whatever is the agroecological zone, Anopheles coluzzii was the major species. The proportion of Anopheles gambiae was low in most agroecological zones except for the bar-lands zone. In the depression zone, Anopheles coluzzii accounted for 75% of the species while the proportion of Anopheles gambiae was 25%. No hybrid (Anopheles coluzzii/Anopheles coluzzii) was found in this zone. In the bar-lands zone, 59.64% of Anopheles coluzzii were found against 38.91% for Anopheles gambiae. Hybrids accounted for only 1.45% in this zone. Considering the cotton zone of the center, we obtained 82.86% of Anopheles coluzzii and 17.14% of Anopheles gambiae. In the fishery zone, data revealed 93.89% of Anopheles coluzzii, 5.28% of Anopheles gambiae, and 0.83% of hybrids. Careful analysis considering the sampled localities revealed that, exceptionally in Bohicon and Klouékanmè which belongs to the bar-lands zone, Anopheles gambiae was in majority. Only a few hybrid forms have been found in some localities .Table L1014F mutation of the Kdr gene was analyzed in the different species identified in all agroecological zones. The genetic structure results are summarized in Table 1014F/1014F) were mostly represented in all agroecological zones. In Anopheles gambiae, the frequency of resistant homozygous individuals was 85.71% in the zone of the depression, 92.52% in the bar-lands zone, 83.33% in the central cotton zone, and 100% in the fisheries zone. Heterozygous individuals of genotype 1014 L/1014F were scarcely represented including 14.29% in the zone of the depression, 4.67% in the bar-lands zone, 16.67% in the central cotton zone, and none in the fisheries zone. Susceptible homozygote individuals (1014 L/1014 L) were only found in the bar-lands zone with a frequency of 2.81%. The frequency of the L1014F resistant allele was strongly represented Anopheles gambiae populations with a mean frequency exceeding 90% across all four agroecological zones. The HWE was respected in the Anopheles gambiae populations of the zone of the depression and of the central cotton zone . This equilibrium was not observed in the populations of the bar-lands zone . A strong selection of resistant homozygote individuals was recorded in the fisheries zone.The Anopheles coluzzii species, resistant homozygote individuals (1014F/1014F) exhibited relatively high frequencies in the different agroecological zones studied. In the zone of the depression, 85.72% of individuals had this genotype. This frequency was 78.05% in the bar-lands zone, 82.76% in the central cotton zone, and 79.59% in the fisheries zone. Heterozygous individuals (1014 L/1014F) showed variable frequencies depending on the agroecological zone. There were 4.762% heterozygous individuals in the zone of the depression, 15.24% in the bar-lands zone, 12.07% in the central cotton zone, and 16.86% in the fisheries zone. Homozygote susceptible individuals (1014 L/1014 L) exhibited low frequencies in all agroecological zones. There were 9.52% in the zone of the depression, 6.71% in the bar-lands zone, 5.17% in the central cotton zone, and 3.55% in the fisheries zone. All Anopheles coluzzii populations in the study areas showed high frequencies for the resistance allele 1014F. It was 88.09% in the zone of the depression, 85.67% in the bar-lands zone, 88.79% in the central cotton zone, and 88.018% in the fisheries zone. None of these populations respected the Hardy-Weinberg equilibrium .In Ho), the heterozygosity expected (He), and the fixation index (Fis) in Anopheles coluzzii and Anopheles gambiae across the different agroecological zones. Heterozygosity observed was lower than expected heterozygosity in all Anopheles coluzzii populations, suggesting a deficit of heterozygosity (Fis > 0). Similarly, this heterozygosity deficit was observed in Anopheles gambiae populations collected from the bar-lands zone. An excess of heterozygosity (Fis < 0) was observed in Anopheles gambiae populations collected from the central cotton zone. However, in the few populations where panmixia was observed, heterozygosity was balanced: there was neither deficit nor excess.Table Anopheles populations for both Anopheles coluzzii and Anopheles gambiae (Table Fsc = 0). In Anopheles coluzzii, low genetic differentiation was observed in the bar-lands and the central cotton zones (Fst < 0.05), while a moderate differentiation was observed in the fisheries zone (Fst = 0.13). In Anopheles gambiae, the genetic differentiation was very large (Fst = 0.2408) in the bar-lands zone.Genetic differentiations were calculated within and between different ae Table . For botAnopheles coluzzii and Anopheles gambiae are represented in all agroecological zones. Several studies have shown [Anopheles coluzzii is mostly found in fisheries zones where availability of water favors the development of permanent breeding sites. Studies in Ghana have shown that Anopheles coluzzii prefers to lay eggs in permanent settlements [Anopheles gambiae occurs in large numbers can be explained by the sampling period characterized by the existence of favorable ecological conditions.The molecular identification of the different species revealed that ve shown , 40 thattlements , 42. TheAnopheles coluzzii and Anopheles gambiae are distinct species whose biological separation is not nearly complete. Coetzee et al. [Anopheles gambiae and Anopheles coluzzii are two distinct species. Nevertheless, in the agroecological zones studied, Anopheles coluzzii and Anopheles gambiae live in sympatry. This remark reflects an adaptation of these two species to different breeding sites and ecology. Several studies have proved the sympatric life between the different species of Anopheles gambiae complex and even with other kinds of mosquitoes [Hybrid forms were only observed in three localities of the studied agroecological zones . These results confirmed that e et al.  have shosquitoes –44.Kdr gene is strongly selected in all agroecological zones. The high allelic frequency observed in these zones has several origins including farming practices that require extensive use of several classes of pesticides to effectively control insect pests [The resistant allele of the ct pests , widesprct pests , and manct pests  showed tct pests  and otheThe genetic structure of most of the anopheline populations analyzed is panmixia except for the central cotton zone and the zone of the depression. It has been shown in population genetics that the causes of such a Hardy-Weinberg equilibrium shift may be the Wahlund effect, consanguinity, genetic drift, selection against heterozygotes, or their combination. Based on cultural practices in Benin, one is tempted to think of a selection of the resistant allele in a high insecticide-use environment, even if the other factors are not to be neglected. The observed HWE in the abovementioned zones may be related to the relatively small numbers of mosquitoes used for data analysis, sampling period or punctual migration of individuals favoring gene flow, and random crosses between individuals. The heterozygote deficiency is widely observed within all populations. This observation can be translated by the effect of insecticides on mosquitoes that would eliminate susceptible individuals in different populations and leaving the first resistant, which in turn through preferential mating and consanguinity will transmit almost exclusively the allele of resistance to their descendants and consequently ensure the expansion of this genetic mutation within populations. No genetic differentiation was observed between the different agroecological zones regardless of the species considered. The lack of genetic differentiation observed between the different agroecological zones is linked to the strong selection of resistant individuals in these areas and, to some extent, the resolving power of the type of marker used.Anopheles coluzzii. This phenomenon is due to an apparent homogeneity of biotic and abiotic factors that can create genetic differentiation between individuals within this population. The moderate genetic differentiation observed in the fisheries zone could be due to a variability of various factors capable of exerting insecticidal pressures and the effect of human actions on Anopheles populations in the different localities of this zone. The permanent availability of breeding sites could also reduce the phenomenon of migration in this region by promoting a certain genetic structuring of Anopheles populations. In the fisheries zone, the presence of market gardening sites in Cotonou coupled with a strong domestic use of pesticides contributes to a strong selection of the resistance allele [Anopheles populations. The high genetic differentiation observed in Anopheles gambiae in the bar-lands zone is believed to be related to the highly heterogeneous geographical distribution of this species.Nevertheless, within each agroecological zone, some genetic differentiations were observed. Genetic differentiation was low in the central cotton zone and the zone of the depression in e allele . The varAnopheles collected from the bar-lands zone must be adapted to the ecology of their environment. The variability of selection pressures associated with the low representativeness of Anopheles gambiae in the different localities of this zone could partly explain the great genetic differentiation observed. The generalized heterozygote deficit observed in the Anopheles populations reflects the existence of a characteristic consanguinity within each species. It would be desirable to deepen this study using more advanced methodological and analytical approaches such as sequencing to better assess genetic differentiation between different populations.The Anopheles gambiae s.s. in Benin.The study of vectors’ population genetic structure is required before the implementation of any insecticides or chemicals based control intervention. Indeed, the selection of an individual resistance allele is often due to the large use of chemicals over the years , 47. An Anopheles gambiae and Anopheles coluzzii species using the Kdr gene in four agroecological zones of Benin. The resistance allele was strongly selected in almost all agroecological zones for both species. A panmixia gap was observed in all agroecological zones studied with a heterozygosity deficit in most populations. The low within and between individual genetic differentiations reflected the strong selection of the resistant allele in these Anopheles populations. It would be desirable to further study the molecular diversity of malaria vectors by using more resolute markers to better establish the fine genetic structure of their populations.This study established the genetic structure of