Koreans are generally considered a Northeast Asian group, thought to be related to Altaic-language-speaking populations. However, recent findings have indicated that the peopling of Korea might have been more complex, involving dual origins from both southern and northern parts of East Asia. To understand the male lineage history of Korea, more data from informative genetic markers from Korea and its surrounding regions are necessary. In this study, 25 Y-chromosome single nucleotide polymorphism markers and 17 Y-chromosome short tandem repeat (Y-STR) loci were genotyped in 1,108 males from several populations in East Asia.In general, we found East Asian populations to be characterized by male haplogroup homogeneity, showing major Y-chromosomal expansions of haplogroup O-M175 lineages. Interestingly, a high frequency (31.4%) of haplogroup O2b-SRY465 (and its sublineage) is characteristic of male Koreans, whereas the haplogroup distribution elsewhere in East Asian populations is patchy. The ages of the haplogroup O2b-SRY465 lineages  and the pattern of variation within the lineages suggested an ancient origin in a nearby part of northeastern Asia, followed by an expansion in the vicinity of the Korean Peninsula. In addition, the coalescence time  for the age of haplogroup O2b1-47z, and its Y-STR diversity, suggest that this lineage probably originated in Korea. Further studies with sufficiently large sample sizes to cover the vast East Asian region and using genomewide genotyping should provide further insights.These findings are consistent with linguistic, archaeological and historical evidence, which suggest that the direct ancestors of Koreans were proto-Koreans who inhabited the northeastern region of China and the Korean Peninsula during the Neolithic  and Bronze  Ages. The Koreans are geographically a Northeast Asian group, who are thought to be most closely related to Altaic language-speaking populations. Anthropological and archaeological evidence suggests that the early Korean population was related to Mongolian ethnic groups, who inhabited the general area of the Altai Mountains and the Lake Baikal regions of southeastern Siberia . Based oHowever, like many debates on the genetic history of human populations, the origin of the Korean population remains controversial. Studies of classic genetic markers have shown that, among the East Asians, Koreans tend to have the closest genetic affinity with Mongolians ,6. TheseBased on recent studies of Y-chromosome variation, the East Asian gene pool is almost completely contained within three major Y-chromosome lineages  ,10. Eastet al. [et al. [Hammer and Horai  hypotheset al.  also suget al. ,13,14. L [et al.  suggesteThus, to understand the male lineage history of Korea, more data from such informative genetic markers from Korea and its surrounding regions are necessary. In the present study, 25 Y-chromosome single-nucleotide polymorphism (Y-SNP) markers and 17 Y-chromosome short tandem repeat (Y-STR) loci (Yfiler) were genotyped in 1,108 men from East Asian, several populations, to not only identify haplogroup O2b lineages and trace their migration history, but also to distinguish populations with different genetic backgrounds.This study was approved by the Ethics Committee and institutional review boards of Institute of Bio-Science and Technology in the Dankook University. Separate written informed consent was obtained for enrollment from all participants.et al. [et al. [In this study, we analyzed 1,108 men, representatives of several East Asian populations   using a previously described protocol . PrimersY-STRs  were amplified  and analyzed by capillary electrophoresis using a genetic analyzer  and accompanying software . Alleles were named according to the recommendations of the International Society of Forensic Genetics . The 25 FST (Y-SNP) values. The population genetic structure of the ethnic and/or regional groups was assessed by analysis of molecular variance (AMOVA) using the RST (Y-STR) values [FST and AMOVA were performed using Arlequin software  [FST values were visualized by multidimensional scaling (MDS) plot analyses . Haplotype diversity and mean number of pairwise differences of 15 Y-STR markers (excluding DYS385a/b in Yfiler) linked with the haplogroups O2b*, O2b1, O3 and C were also calculated (Arlequin 3.0 package) [http://www.fluxus-technology.com). The MJ network was constructed by weighting 99 (47z), 10 , nine (DYS393), eight , five , two (DYS389I) and one (DYS439) [http://www.mas.ncl.ac.uk/~nijw/) [The genetic differentiation between different population samples and its statistical significance were assessed via ) values . The calequin3/) . Populatpackage) . In addipackage) . Median-package)  of the h(DYS439) . Coalesc/~nijw/) , assumin/~nijw/) .This survey of East Asian Y-SNPs identified 18 haplogroups, 15 of which were present in our Korean group Table . Haplogret al. [O3-M122 was the commonest Chinese Y-chromosome haplogroup found, and its presence in Korea may originate from demic diffusion by way of south-to-north migration ,29,30. Cet al. . HaplogrHaplogroup N-M231 was present in the Korean and Mongolian groups at moderate frequencies, suggesting that the early Korean population may have shared a common origin with Mongolian ethnic groups who inhabited the general area of the Altai Mountains and Lake Baikal regions of southeastern Siberia ,33. The The geographical distribution of the O2b*-SRY465  in East Asia is shown in Figure Previous studies suggested a southeastern Asian origin for O2b-SRY465 ,13, becaAge estimates based on our Y-STR data provide further support for the initial expansion of the O2b*-SRY465 in prehistoric Korea, in accordance with the proto-Korean lineages. Based on the Korean demographic and population history, a constant population in three different BATWING models may give the best fit to our data. Thus, time to most recent common ancestor (TMRCA) for the O2b*-SRY465 lineages was 9,900 years, assuming constant population size  in part with the relatively recent O3 and C3 lineages (which include a Chinese component) explains some of the main events formulating the current Y chromosome composition of the Korean population. Thus, our findings are consistent with linguistic, archaeological and historical evidence, which suggest that the direct ancestors of Koreans were proto-Koreans who inhabited the northeastern region of China and the Korean Peninsula during the Neolithic  and Bronze  Ages.Our results support the idea that both haplogroups O2b*-SRY465 and O2b1-47z had an The authors declare that they have no competing interests.SHK, WNK and WKK conceived and designed the experiments; SHK, KCK, DJS, HJJ and KDK performed the experiments:. SHK, KCK, WNK and WKK analyzed the data;. MSH, JMS, WNK and WKK contributed reagents, materials and analysis tools; and SHK, MSH, WNK and WKK wrote the paper. All authors read and approved the final manuscript.Table S1. Thirteen Y-chromosome single-nucleotide polymorphism (Y-SNP) markers and primer information for PCR amplification.Click here for fileTable S2. SBE primers for the detection of 13 Y-chromosome single-nucleotide polymorphisms (Y-SNPs) studied.Click here for fileTable S3. Haplotypes for 25 Y-chromosome single-nucleotide polymorphisms (Y-SNPs) and 17 Y-chromosome short tandem repeat (Y-STR) loci in 1,108 males from East Asian populations.Click here for fileTable S4. FST distances from haplogroup frequencies in East Asian populations .Click here for file


S. cerevisiae strains and evaluate relationships between grape varieties and geographical location on populational structures. From the musts obtained from 288 grape samples, collected from two wine regions , 94 spontaneous fermentations were concluded and 2820 yeast isolates were obtained that belonged mainly (92%) to the species S. cerevisiae. Isolates were classified in 321 strains by the use of ten microsatellite markers. A high strain diversity (8–43 strains per fermentation) was associated with high percentage (60–100%) of fermenting samples per vineyard, whereas a lower percentage of spontaneous fermentations (0–40%) corresponded to a rather low strain diversity (1–10 strains per fermentation).We herein evaluate intraspecific genetic diversity of fermentative vineyard-associated Ho) was about two to five times lower than the expected heterozygosity (He). The inferred ancestry showed a very high degree of admixture and divergence was observed between both grape variety and geographical region. Analysis of molecular variance showed that 81–93% of the total genetic variation existed within populations, while significant differentiation within the groups could be detected. Results from AMOVA analysis and clustering of allelic frequencies agree in the distinction of genetically more dispersed populations from the larger wine region compared to the less extended region. Our data show that grape variety is a driver of populational structures, because vineyards with distinct varieties harbor genetically more differentiated S. cerevisiae populations. Conversely, S. cerevisiae strains from vineyards in close proximity (5–10 km) that contain the same grape variety tend to be less divergent. Populational similarities did not correlate with the distance between vineyards of the two wine regions. Globally, our results show that populations of S. cerevisiae in vineyards may occur locally due to multi-factorial influences, one of them being the grape variety.For the majority of the populations, observed heterozygosity ( Saccharomyces cerevisiae strains have found that the species as a whole consists of both “domesticated” and “wild” populations. Although the genomes of most S. cerevisiae strains with disparate ecological and geographic sources are mosaics, genealogical relationships from DNA sequence diversity showed that domesticated strains derived from two independent clades, corresponding to strains from winemaking and sake (Japanese rice wine). “Wild” populations are mostly associated with oak trees, nectars or insects  Recent phylogenetic analyses of et al., S. cerevisiae strains in both vineyards and wineries, numerous molecular methods were developed recently. Microsatellite analysis can be considered the method of choice for S. cerevisiae strain delimitation, allowing high-throughput and precise data generation. Besides, due to the high level of discrimination and unequivocal results, expressed as base pair number (or as repeat number), the generated data are suitable for computational population genetic analysis S. cerevisiae strains from 56 worldwide geographical origins. The genotypes clustered in subgroups, according to the strain's technological use . Macrogeographical differentiation of strains from Asia, Europe and Africa accounted for 28% of the observed genetic variation, which suggests clonal reproduction and local domestication of natural strains originating from the same geographic area. S. cerevisiae strain was based on 32 single-nucleotide polymorphism markers S. cerevisiae population structure are still poorly understood.As reviewed by Martiny S. cerevisiae strains derived from cumulative small microsatellite allele-frequency differences. Within a vineyard the strain's genetic divergence correlated with the distance between sampling points, suggesting a pattern of isolation-by-distance. However, geographical distance was not correlated with genetic proximity, pointing towards the involvement of other factors, for the differentiation of S. cerevisiae populations In our previous studies, we showed that microsatellites are informative markers for distinguishing populations from vineyards in very close geographical locations (50–100 km). Genetic differences and populational structures among S. cerevisiae strains. Grape samples of the nine most representative grape varieties were collected at the harvest time of two consecutive years in 16 vineyards from the Bairrada and Vinho Verde appellations of origin in Portugal . For populational analysis 288 samples were obtained, that concluded 94 spontaneous fermentations and 2820 yeast isolates were obtained that belonged mainly (94%) to the species S. cerevisiae, being classified in 321 strains using 10 polymorphic microsatellite markers.In this study we test the hypothesis that both geographical region and grape varieties are drivers of population structures of fermentative vineyard-associated During the harvest time of two consecutive years, grape samples of representative grape varieties were collected in 16 vineyards . In the vineyards of BAO, 132 grape samples were collected and 50 (38%) of spontaneous fermentations occurred, providing 156 S. cerevisiae strains (average: 3.1 strains per fermentation). The total yeast count  ranged between 1.0×106 and 8.0×107 cfu/ml of must. With a few exceptions, all isolates belonged to the species S. cerevisiae due to their inability to grow in a medium containing lysine as sole nitrogen source (data not shown), the amplification of S. cerevisiae specific PCR-based interdelta patterns and by the amplification of S. cerevisiae specific microsatellite loci , Arinto (C), Avesso (D), Loureiro (G), Touriga Nacional (I); BAO: Aragonês (B), Baga (E), Bical (F) Maria Gomes (H), Touriga Nacional (I)), being Touriga Nacional shared by both wine regions. In vineyards 2–10 and 12–16, one single predominating grape variety was cultivated and collected. Vineyards 1 (VAO) and 11 (BAO) were chosen as reference vineyards, containing all five grape varieties of each region. With this approach, a total of 288 grape samples were collected for spontaneous fermentations. As detailed in ite loci . No amplS. cerevisiae strains. The number of strains obtained from one vineyard in one sampling year was between 0–43 and 0–23 in the Vinho Verde and Bairrada region, respectively. Non-Saccharomyces species that are well-known for their occurrence in vineyards, were found in vineyard 11 in the samples from final stages of fermentations that were carried out using musts from the grape varieties Aragonês , Maria Gomes  and Touriga Nacional . The average duration until the beginning of fermentations  was between 3.5 and 15.7 days . The average fermentation period (corresponding to the weight loss from 2 gl−1 to 70 gl−1) was between 6.3 and 18.8 days . Fermentations with grapes from the Bairrada region started within 6 days, whereas fermentation onset of musts collected in the Vinho Verde Region was much slower (14 days). However, the average fermentation duration was identical for the musts from both regions (12 days). Grape varieties that started fermentations most rapidly  correlated, by trend, with a higher number of S. cerevisiae strains . When the percentage of spontaneous fermentations among the six samples collected from each vineyard was compared with the number of isolated S. cerevisiae strains , as well as grape variety D in vineyards 8 and 9 (VAO), which were 5–10 Km apart. These populations were also well separated from other groups. Conversely, the S. cerevisiae strains from different grape varieties in the same vineyards  were much more divergent. The grape variety Touriga Nacional (I) is cultivated in most of Portuguese winemaking regions and was therefore included as a reference in our approach. S. cerevisiae populations from these grapes obtained in vineyards 1, 10, 11 and 13 were unresembling. In summary, we can assert that populational structures prevail according to winemaking regions, whereas S. cerevisiae populations are most similar in vineyards in close vicinity (at least up to 10 km) where the same grape varieties were cultivated.The highest bootstrap support was found for Ho) was about two to five times lower than expected heterozygosity (He) for the ten loci analyzed (Ho/He>1) for six microsatellites. The average of FIS values over all loci was rather high for most groups (mean of 0.61), pointing towards inbreeding as the predominating reproductive mechanism. The pattern and degree of populational divergence in the ten nuclear microsatellites among subpopulations was estimated by FST determination over all loci by AMOVA analysis, as shown in S. cerevisiae populations were included that consisted of at least 5 isolates . The contribution of variation within the populations defined was always high, ranging from 81 to 93%. For the analysis between wine regions, vineyards and grape varieties, the assemblage of several populations was considered as a group, indicated by parenthesis in ST values ranged between 0.07 and 0.19, corresponding to a moderate (0.05–0.15) to great (0.15–0.25) genetic differentiation ST value was obtained for the comparison of vineyards 1 and 11 that contained multiple grape varieties and that are located at a distance of 180 km. This value decreased to 0.133 and 0.145 when all populations from VAO and BAO were compared, including or not the populations from vineyards 1 and 11, respectively. In agreement with the data presented in the previous section, S. cerevisiae populations were less divergent in the smaller BAO, where FST values ranged between 0.067 and 0.120, whereas the corresponding values for the larger VAO region were between 0.157 and 0.173.For the majority of the populations, observed heterozygosity  were obtained when 1CGI was compared with the more distant BAO populations , whereas lower values (FST 0.18–0.20) were found when 1CGI was checked against the closer VAO populations 2A, 3A and 7C, suggesting a geographic correlation. However, this was not observed for the majority of the remaining comparisons, where FST values ranged between 0.13–0.16, independent of the geographic distance. The lowest FST value of 0.1 was found for populations from grape varieties E in the vineyards 11 and 12, located at a distance of 5 km. However, a strict correlation between grape variety and geographic proximity cannot be assumed because populations from vineyards 2 and 3, where variety A was cultivated were more divergent (FST 0.16) than populations from distinct grape varieties in vineyards 11, 12 and 13, that were located from each other at similar distances. These data show that the grape variety can be in fact a driver of populational structures because vineyards with distinct varieties (1 and 11) harbor genetically more differentiated populations, whereas vineyards with the same grape varieties in close proximity (11 and 12) contain less divergent groups of strains.To further investigate associations between genetic differentiation and geographic distance, pair wise vineyard comparisons were performed according to their geographic distance . The genS. cerevisiae populations were distinguished by a considerable degree of admixture. Deeper divergence was observed between both geographic regions and grape varieties, being more evident in the VAO region which is in agreement with AMOVA analysis. Populations from vineyards 8 and 9, that shared a heterozygous excess (Ho/He>1) for six microsatellites loci, can be clearly distinguished. Clusters 1 and 3 were more represented in VAO populations, whereas clusters 5 and 10 were more predominant in BAO populations. Populations from multiple grape varieties in vineyards 1 and 11  or soils 2–103cells/ml must S. cerevisiae in many wine regions in France versus conventional) and floor management systems Vineyards are an important yeast ecosystem. S. cerevisiae strains correlated with the distance between sampling points, suggesting a pattern of isolation-by-distance. However, this relationship was not found for larger geographical distances, pointing towards the involvement of other factors such as the grape variety, which we evaluate within the present study. We highlight that S. cerevisiae isolates were obtained after enrichment through must fermentation and therefore may not accurately represent vineyard populations. Our experimental approach is therefore an acceptable compromise that allows for estimation of population composition, but does not provide a precise description in terms of relative strain abundance in nature.In our previous studies we showed that within a vineyard the genetic divergence of Fermented musts from the grape varieties C, D and E  showed a notable strain diversity, which seems to be correlated with the percentage of spontaneous fermentations in a vineyard. Contrarily to the view that strains compete for nutrients under stressful fermentative conditions, it was surprising to find numerous strains at the end of the fermentations, suggesting a cooperative effect that may guarantee efficient fermentation when strain diversity is rather high. The faster fermentation onset observed for several grape varieties might also be related with a more favorable nutritional composition of the grapes. Spontaneous fermentations can be considered as complex multifactorial process, where strain diversity is one variable for a rapid onset, while the grape variety appears to be also relevant.S. cerevisiae in vineyards depend on climatic factors S. cerevisiae strain abundance, elevated percentage of spontaneous fermentations and low fermentative lag time compared to the closely located (10 km) vineyard 9, where the same soil, microclimatic conditions grape variety occurred. This result is in agreement with recent research showing that phytosanitary treatment has an impact on grape associated biodiversity The occurrence and survival of S. cerevisiae strains, even within geographically close regions. The isolated S. cerevisiae strains were unique for each vineyard and were also not re-isolated in consecutive years. However, in our previous research we found strains with a wider temporal and spatial distribution S. cerevisiae populations derived mainly from gradations in allele frequencies rather than from distinctive “diagnostic” genotypes. These markers are useful for unambiguous populational analysis, but it needs to be considered that sub-strain level discrimination may occur due to their relative high mutation rate. Clonal expansion with some cycles of homothallic self-mating is considered to be the most likely reproduction in yeasts, generating the high observed homozygosity and very structured populations due to inbreeding or genome renewal IS values suggest that Portuguese yeast populations are inbred, which is in agreement with previous results obtained with strains from Chile and New Zealand, where FIS values ranged between 0.4–0.75 Microsatellite typing of the chosen loci  followedS. cerevisae populations from different vineyards and grape varieties. Results from FST analysis and clustering of allelic frequencies agree in the distinction of genetically more dispersed populations from the larger VAO compared to the BAO region. Our data indicate that the grape variety can be a driver of populational structures because populations associated with different grape varieties from vineyards 1 and 11 were genetically more divergent than populations obtained from the same grape variety in vineyards in close locations (11E–12E (5 km), 8D–9D (10 km)). Comparison of strains from variety A in the close vineyards 2 and 3 (10 km) revealed a higher FST value, but these populations were still less differentiated than the ones obtained from vineyard 1. A correlation between genetic and geographical distances was only evident when the more divergent populations from vineyard 1 were compared to other groups of strains. The higher genetic differentiation of yeasts from the experimental vineyard 1 may be attributed to the fact that it contains ten different grape varieties in larger quantities and 152 varieties of a clonal ampelographic collection, that were introduced three to four years before our study was initiated. The inferred ancestry of populations support strong admixture whereas divergence was again observed between both geographic regions and grape varieties. Interestingly population 10I from VAO seemed more related with populations from BAO when the inferred ancestry was analyzed, This is one of the few varieties that is used in all Portuguese winemaking regions and might have been introduced in the VAO together with the yeast strains as a commensal member of grapevine flora, as previously suggested by Legras Various approaches were used to determine the genetic structure of S. cerevisiae strains have been globally dispersed by humans, supporting the importance of geography in shaping S. cerevisiae's population structure S. cerevisiae in vineyards occur due to multi-factorial influences, being the grape variety one of them. These findings are in agreement with a recent report about distinctive non-Saccharomyces yeast populations occurring on different grape varieties in the same vineyard Recent studies showed that S. cerevisiae populations and the grape variety. All necessary permits were obtained for the described field studies, the owners of the vineyards agreed with the collection of grape samples and the sampling plan.The sampling plan included a total of 16 vineyards (ten in the Vinho Verde and six in the Bairrada region) as shown in −4 and 10−5) were spread on YPD plates , and 30 randomly chosen colonies were collected after incubation . The isolates obtained throughout this work were stored in glycerol  at −80°C.From each sampling point, approximately 2 kg of undamaged and healthy grapes were aseptically collected and the extracted grape juice was fermented at 20°C in small volumes (500 ml). Fermentation progress was monitored by daily weight determinations. When must weight was reduced by 70 g/l, corresponding to the consumption of about 2/3 of the sugar content, diluted samples . DNA isolation was performed as previously described Saccharomyces species. These species were identified by restriction analysis of the ribosomal internal transcribed spacer (ITS) region as previously described S. cerevisiae and fail to amplify all of the corresponding homologous loci in sibling species such as S. bayanus and S. paradoxus that can be found occasionally in winemaking environments. We therefore consider that these sibling species did not occur in our spontaneous fermentations.In a preliminary approach, all isolates were analysed by interdelta sequence typing http://genome-www.stanford.edu.saccharomyces) and the results obtained for the size of microsatellite amplicons of this strain, the number of repeats for all alleles was calculated. Allelic frequencies, observed and expected heterozygosity, FIS determinationas well as AMOVA analysis was performed by the software Arlequin 3.11 Based on the genome sequence for strain S288C  and expected (He) heterozygosity for S. cerevisiae populations from vineyards 1–15 and grape varieties A–I. The ratios between observed (Ho) and expected (He) heterozygosity are indicated by underlined bold letters (Ho/He>1) and underlined letters (0.5>Ho/He>1). For the remaining fields the ratio was <0.5.(TIF)Click here for additional data file.


Dichroplus elongatus which is an agricultural pest of crops and forage grasses of great economic significance in Argentina. We use Direct Amplification of Minisatellite Regions (DAMD) and partial sequences of the cytochrome oxydase 1 (COI) mitochondrial gene to investigate intraspecific structure, demographic history and gene flow patterns in twenty Argentinean populations of this species belonging to different geographic and biogeographic regions. DAMD data suggest that, although genetic drift and migration occur within and between populations, measurable relatedness among neighbouring populations declines with distance and dispersal over distances greater than 200 km is not typical, whereas effective gene flow may occur for populations separated by less than 100 km. Landscape analysis was useful to detect genetic discontinuities associated with environmental heterogeneity reflecting the changing agroecosystem. The COI results indicate the existence of strong genetic differentiation between two groups of populations located at both margins of the Paraná River which became separated during climate oscillations of the Middle Pleistocene, suggesting a significant restriction in effective dispersion mediated by females and large scale geographic differentiation. The number of migrants between populations estimated through mitochondrial and DAMD markers suggest that gene flow is low prompting a non-homogeneous spatial structure and justifying the variation through space. Moreover, the genetic analysis of both markers allows us to conclude that males appear to disperse more than females, reducing the chance of the genetic loss associated with recent anthropogenic fragmentation of the D. elongatus studied range.Many grasshopper species are considered of agronomical importance because they cause damage to pastures and crops. Comprehension of pest population dynamics requires a clear understanding of the genetic diversity and spatial structure of populations. In this study we report on patterns of genetic variation in the South American grasshopper  The evolutionary potential of a species depends mainly on the genetic variation of their populations, which is the consequence of a balance between evolutionary and demographic processes generating either heterogeneity or homogeneity among local populations. The amount of genetic variation within and among natural populations is mainly explained by several historical and contemporary processes, including genetic drift, effective migration, natural selection, fragmentation and range expansion et al.et al. Since Jeffreys Population genetic structure is not always mirrored in the geographical proximity of individuals. Therefore, identifying populations a priori can lead to errors due to potential biases caused by unidentified migrants and cryptic spatial structure One persistent challenge in the analysis of population genetic data is the need to account for the spatial arrangement of samples and populations. Spatial genetic structure is defined as the non-random distribution of genetic variation among individuals within populations. Unlike traditional genetic studies, landscape genetics incorporates tests to analyse the existence of probable landscape heterogeneity on gene flow and hence on genetic variation patterns Mitochondrial DNA (mtDNA) data have been extensively used to understand the spatial distribution of genetic lineages within species allowing the historical factor with the highest effect on the lineages spatial patterns to be identified Mitochondrial and nuclear markers differ in their mode of inheritance and in the rate of evolution. Mitochondrial sequences tend to have faster evolution with respect to nuclear sequences Many grasshopper species behave as opportunist species, which are able to increase their population size and geographical distribution, in response to the expansion of cultivated areas. Most of them are considered of economic importance because of the damages they cause to crops and pastures Dichroplus elongatus provides a helpful biological model to analyse the structure of populations that vary in their historical frequency in relation to control management strategies and the extent of demographic fluctuation because of their great biotic potential. D. elongatus is a South American grasshopper with a wide geographic distribution which has been reported as a dominant or codominant species in most grasshoppers outbreaks which have occurred in the last years The grasshopper Previous studies have revealed strong genetic structure at chromosome level. Population cytogenetic studies demonstrated that the persistence of B chromosomes in natural populations from Argentina may be explained mainly in a selective scenario. The maintenance on supernumerary chromosomes is the result of trade-offs among opposite selective effects and interactions with their mitotic instability D.elongatus samples using molecular neutral markers can gain insight into these aspects.The efficiency of using the estimates of genetic diversity in the management of agronomically important species depends on the efficiency of detecting the population structure and identification of the origin of migrants D. elongatus belonging to different geographic and biogeographic regions.Our general goal is to analyse genetic variation in populations of this grasshopper species by DAMD, in order to generate a large number of characters needed for genomic scans, and by sequences of mitochondrial DNA. Our particular aims are to obtain complementary information to improve our understanding of the processes underlying the spatial and temporal dimensions of genetic variation and thereby reach a better idea of intraspecific structure, demographic history and gene flow patterns in 20 Argentinean populations of Dichroplus elongatus (Orthoptera: Acrididae) was collected from 20 natural populations across three biogeographic regions , followed by 35 cycles with annealing temperatures of 46°C for INS and 47°C for M13 (60 s). We also used a 72°C extension cycle (90 s) and a 94°C denaturing cycle (60 s). Reaction mixtures (50 µl) contained 1X reaction buffer, 50 µM MgCl2, 200 µM dNTPs, 2 µM primer, 50 U/µl Taq polymerase (Invitrogen), and 200 ng DNA. PCR products (6 µl) were fractionated on 6% polyacrylamide gels for 3 h at 55 W, and the DNA bands were visualised by silver nitrate staining . Bands ranging from 300 to 1,000 bp were scored for the further analysis.Total genomic DNA was isolated according to the method of Marchant 5′- GGAGGATTTGGAAATTGATTAGTTCC-3′ and D11 mtDNA 5′- ACTGTAAATATATGATGAGCTCA-3′. Each PCR was carried out in a total volume of 50 µl. PCRs contained 50 mM Cl2Mg, 50 µM dNTPs, 10 µM of each primer, 50 U/µl Taq polymerase (Invitrogen), 10 X buffer and 100 ng DNA template. The following temperature profile was used for the PCR: 94°C for 3 min, followed by 10 amplification cycles with an annealing temperature at 46°C for 1 min and 25 amplification cycles at 51°C for 40 s. Each cycle was preceded by a denaturalisation cycle at 94°C for 10 s and followed by an elongation cycle at 68° for 1 min. The final extension was conducted at 68°C for 10 min. After visualisation on a 1% agarose gel with a 100 bp ladder, PCR products were purified and sequenced on an ABI PrismTM Sequencer 31309l Genetic Analyzer  by the Macrogen INC., Seoul, Korea Sequencing Service.The polymerase chain reaction (PCR) was used to amplify a 526-base pair (bp) fragment of the mitochondrial gene cytochrome oxidase I (COI) in a total of 169 adult males using specific primers from The DAMD bands were scored as presence (1) or absence (0) and only those that were well defined in all populations were taken into account to generate the DAMD matrix dataset.Independence of DAMD fragments were tested by means of the Fisher’s exact test with the Markov chain method considering 1000 iterations per batch and using GENEPOP software v4.0 ISF = 0) and by assuming ISF = 0.23 estimated previously through isoenzymatic analysis in Sequeira et al. AFLPsurv software PPL) at the 5% level and expected heterozygosity (HE) following Lynch and Milligan loci using the Bayesian method developed by Zhivotovsky The genetic variability was estimated under two different conditions: by supposing Hardy- Weinberg equilibrium (I) In addition, the Shannon information index  simulations. Results were examined under three probable models: i) full model (f≠0 and Bθ≠0); ii) f = 0 model (f = 0 and Bθ≠0); iii) theta  = 0 model (f≠0 and Bθ = 0). Then, we compared models using the Deviant Information Criterion (DIC) We also estimated population differentiation implementing a Bayesian approach for dominant markers without assuming Hardy-Weinberg equilibrium using HICKORY version 1.0.4. Genetic structuring of the samples was investigated in parallel using 2 Bayesian population assignment methods implemented in STRUCTURE 2.1 BAPS considers populations instead of individuals as sampling units and establishes populations with different allelic frequencies instead of partitioning individuals based on Hardy-Weinberg equilibrium. Under the spatial model, the population structure is estimated supposing as a priori information that the structure within a certain sampling area depends on the adjacent areas. Under the option “spatial clustering”, the population landscape is scattered into a “coloured Voronoi tesselation” Nei’s genetic distances P) of observed r values though 1000 permutations. The 95% confidence intervals around each r value were estimated by bootstrapping. The correlation coefficient was plotted as a function of distance to produce spatial genetic correlograms.We analysed the relationship between population pairwise genetic similarity and geographic distances based on the spatial autocorrelation multivariate approach development by x- and y-axes represent latitude and longitude whereas z-axis represents genetic distances). Genetic structure across the landscape was inferred from measured genetic distances using an inverse distance weighted interpolation across a uniform grid laid over the entire sampling area. A grid size of 60×60 was selected , with a distance weighting parameter (α) of 1.We also performed Mantel tests Sequences were aligned using CLUSTAL 1.81 The haplotypes were identified and characterised using the GENEALEX version 6.0 software hπGenetic variation was estimated using haplotype diversity Networks enhance haplotype relationships rather than conventional phylogenetic trees when recent multifurcations occur, the level of haplotype divergence is low and/or ancestral and derived haplotypes coexist STF (using haplotypes frequencies) and STΦ  were conducted to assess population structure patterns with the ARLEQUIN version 3.5 software STΦ and STF indices.AMOVA based on We used distributions of the number of pair-wise mutational differences among individuals – or mismatch distributions – to explore demographic patterns of populations with DNAsp version 5.0 software DFWe also test spatial or demographic expansion estimating Tajima’s We used a Bayesian approach implemented in BEAST software (version 1.4.8) We examine two different models of rates variation among branches: the strict clock and the uncorrelated lognormal-distributed relaxed molecular clock analyzing ESS values in TRACER Mitochondrial rates have been proposed for arthropods to be in the range of 1.5–3.96% pairwise divergence per million years Therefore, we selected an uncorrelated lognormal relaxed molecular-clock model using Bayesian skyline tree prior in BEAST with the average number of substitutions per site across the tree averaged to be 0.0115 per million years and unconstrained rates for individual branches.We use the Bayesian Skyline Plot method (BSP) implemented in the BEAST version 1.4.8 software to visualize the dynamics of the population size fluctuation over time considering GTR substitution model with invariant sites, a constant growth rate for the skyline model and a chain length of 40000000. To test whether our results were influenced by population structure and non-random sampling we conducted extensive experiments using a wide range of different parameter settings. To identify the influence of the number of coalescence groups, analyses were repeated with 4, 6, and 10 groups and the models were compared. Finally, it is assumed that the control region in insects evolves essentially neutrally and that therefore signals of non-neutrality should be associated with population size changes rather than with signals of selection.Estimates and credible intervals for each parameters and demographic reconstruction were analysed with the software TRACER v.1.1.4 Asymmetric migration rates between pairwise studied populations were estimated from haplotypes using Bayesian Markov Chain Monte Carlo (MCMC) coalescent modelling implemented in LAMARC version 2.1.3 D. elongatus using M13 and INS primers detected a total of 155 informative DNA fragments, 152 of which were polymorphic. No linkage disequilibrium was detected between DAMD markers.The analysis of DAMD profiles in ISF = 0) in twenty Argentinean populations (PPL) varied from 100% in RAU, COE, GUA, MCA, STO, YAP, RCO and HCM to 96.8% in SCA, and the mean expected heterozygosity (EH) ranged from 0.449% in HCM to 0.395% in the sample of SCA. Similarly, YAP (0.601), RAU (0.582) and RCO (0.581) populations had a higher Shannon’s index (I), and SCA population (0.488) had a lower Shannon’s index (I). The population with the lowest diversity values was SCA, whereas the highest variability was concentrated in populations of Las Yungas and in the north of Espinal biogeographic region.The DAMD variation was quantified . Positive correlations were found between I and the minimum temperature . Whereas EH was positively correlated with minimum temperature and mean temperature .Spearman partial correlation analysis showed that both ISF value estimated through isoenzymatic studies  revealed very similar results (data not shown).The results assuming inbreeding and considering the previously PT = 0,132; P = 0.001), whereas about 12% of the variation was due to differences among populations within regions . A low proportion of the variation (1%) could be attributed to regional differences , which, even though significant, indicated a low structure at the biogeographic level.A hierarchical AMOVA conducted over the 20 populations of the three biogeographic regions indicated that approximately 87% of the DAMD variation arose from genotypic variation within populations , and the west Region, containing populations distributed west of Paraná River . Similar results were obtained when AMOVA was carried out considering east and west regions showing little variation (1%) at the regional level, whereas significant variation was found among (11%) and within (88%) population levels (data not shown).ST sample comparisons and gene flow estimations (Nem) between populations are summarised in em >1), they were insufficient to prevent genetic differentiation.Pairwise Fem = 2.34; YAP, Nem = 2.22; MCA, Nem = 2.08). The lowest value of mean gene flow was detected for SCA (Nem = 1.23). Pairwise comparisons showed the highest Nem values among populations of Las Yungas  and GUA-COE (Nem = 3.5) from Pampeana.The highest values of mean gene flow were found in populations located at the northern edge of the studied distribution  and 6 clusters in Espinal  with and without geographic information, respectively.Results from STRUCTURE under the admixture ancestry model with correlated allele frequencies identified 18 genetic groups in the data set. The software identified HCM + RCO and GUA + COE as two genetic clusters  D. AlthoBAPS analysis attributed 11% of the overall variance to differentiation among populations  and 89% to variation within populations , whereas the biogeographic regions could not be differentiated. Comparable results were obtained when hierarchical analysis was carried out contemplating eastern and western populations separated by the Parana River (data not shown).An AMOVA with the genetic groups of populations obtained in the Neighbour-joining analysis at the population level based on Nei genetic distances  showed tr = 0.071, P = 0.0009). In Pampeana and Espinal , there was evidence of isolation by distances (IBD). These results suggest that the population of D. elongatus in the studied region may have reached equilibrium between genetic drift and migration.Mantel tests detected a pattern of isolation by distance (IBD), revealing a significant positive relationship between pairwise genetic and geographical distances for the entire study region  and 100 km  with an X - intercept at 127.7 km , but significantly negative values for distances up to 200 km, with an X- intercept at 187.7 km  was sequenced in each of 170 individuals collected from 19 populations in three biogeographic regions, resulting in 39 polymorphic sites and 32 different haplotypes . All difThe most common and widespread haplotype (DE-14) consisted of 66 individuals and was detected in 15 out of 19 analysed populations . The second most frequently observed variant (DE-24) was found in 26 individuals appearing in 9 populations  .The Pampeana and Espinal biogeographic regions shared 6 haplotypes, whereas no haplotyes were shared between Las Yungas and the remaining biogeographic regions. In Pampeana, 14 private haplotypes were identified, 5 of which occurred in a single individual (singletons). In Espinal, 10 private haplotypes were detected, 6 of which were singletons. Populations with a higher degree of private haplotypes were CAR (four private haplotypes) and MOC and RCO (both with three private haplotypes). When populations were grouped according to their geographic position with respect to Paraná River, we demonstrated that the east and west regions only shared 3 haplotypes. The most frequent haplotypes (DE-14 and DE-24) and DE-08 were present in GUA and CAÑ. In the east region, 10 private haplotypes were detected, 5 of which occurred in a single individual, whereas in the west region, 15 private haplotypes were detected, 5 of which were singletons.h) and nucleotide diversity (π) ranged from 0 to 0.917 and 0 to 0.017, respectively. YAP and GUA showed the highest haplotype diversity, whereas CON and FLO showed the lowest values of haplotype diversity. The highest values of nucleotide diversity were detected in MOC, GUA and SCA, and CON and FLO showed the lowest values .Haplotype diversity was found to be positively and significantly correlated with maximum annual temperature  were exclusively from the east edge of the studied area (populations between STO and GUA), whereas haplotype DE-12 was distributed exclusively from VET to FLO (southern region of the distribution).CT, differences among populations within regions accounted for 19%  of the total variation, while 76% of the variance could be attributed to within-population variability .The AMOVA that accounted for frequencies and divergence between haplotypes revealed that only 5% of the genetic variance was found among biogeographic regions ST statistics showed a higher level of variation among biogeographic regions (6.7%)  and lower levels of differentiation among populations within biogeographic regions (18.5%) and within populations (74.7%) . The FST statistics values were generally lower, suggesting the importance of haplotype divergence in the population structure pattern.The parallel analysis using FCTF = 0.151, P = 0.0001) of the total variation, while only 12.7%  of the variance could be attributed to variation among populations within regions and 71.5% could be attributed to within-population variability . The same pattern was found for the analysis using STΦ statistics. Differences among regions accounted for the 11.8%  of the variance, while 14.8% of the variation was attributed to differences among populations within regions  and 73.4% to differences within populations .Differences were also found when considering east and west regions separated by Paraná River. A higher level of genetic differentiation was evident among regions when the geographic groups were taken into account for the AMOVA analysis. Differences among east and west regions accounted for 15.8% . These results were confirmed by the observed mismatch distributions, which closely matched those expected under a model of sudden expansion. The mismatch distribution plot for the east region was smooth and unimodal, indicating a population expansion, whereas the multimodal pattern of the west region mismatch distributions may suggest strong population subdivision and a stable population size  A and B.P = 0.013 and 0.028 respectively) and Fu’s Fs values . The mismatch distribution for YAP was clearly unimodal and closely matched the expected distributions under the expansion model, whereas COB and RAU showed bimodal distributions, suggesting that expansion events were not detected with this analysis (data not shown).At the population level, COB and RAU have negative and significant Tajima’s D  of the east and west regions are shown in MRCA for the east region was approximately 0.66 Myr (660000 years) in the late Pleistocene glacial cycles . The mean Bayesian TMRCA for the west region was 0.74 Myr (740000 years) . All sampled populations coalesce at approximately 740000 years, indicating that the west region is the most ancestral.The estimated TIndividual population sizes were traced back to the origin of each population as inferred by BSP analysis. YAP Bayesian skyline plot showed a population size growth event at approximately 260.000 years ago, followed by a relatively stable population size (data not shown).MRCA values for each population dated back to the late Pleistocene, with mean values between 0.09–0.739 Myr , suggesting a very recent colonisation. GUA showed a similar TMRCA  to the entire east region, indicating that this population is the most ancestral of the eastern region.T.739 Myr . CON hadLAMARC analysis showed low values of historical gene flow, ranging from 10−5 to 2.91. The coalescent model revealed asymmetrical migration rates from southwest to northeast. The highest migration rates were detected among nearby populations located in the east region  to the eastern populations, but no migration in the reverse direction, indicating a possible colonisation route for this species .Dichroplus elongatus, a widely distributed South American grasshopper, is considered to be an agricultural pest of crops and forage grasses of great economic importance D. elongatus using Direct Amplification of Minisatellite Regions (DAMD) and a 527 bp fragment of COI mtDNA sequences demonstrated higher levels of intraspecific variation comparable with other orthoptera taxa D. elongatus showed that genetic variability was characterised by a decrease in PLP, EH and I as a function of latitude and temperature. The low level of DAMD variability detected in southern populations could be related to the fragility of the populations due to the extension of agroecosystems in the southernmost studied area. Populations at high latitude in the studied area include the southernmost analysed populations of Pampeana region and the westernmost studied populations of Espinal. All of the studied high-latitude populations belong to geographic provinces that are subject to intense agricultural exploitation . Grasshopper control through agropesticides may explain the reduction in population size and the consequent loss of genetic diversity in these populations.DAMD analysis in The DAMD population structure estimated by AMOVA showed that the distribution of the variation is not associated with the biogeographic or geographic region of origin and that the main genetic differentiation lies within populations. Accordingly, the Bayesian analyses of genetic differentiation showed that the “full model” better explains the detected variation, indicating genetic differentiation among populations and some local inbreeding. However, the model that implies differentiation between populations and lack of local inbreeding also managed a good fit, which suggests that local inbreeding is low.BAPS and STRUCTURE software efficiently identified the number of clusters or ideal populations. BAPS demonstrated the existence of at least 16 ideal populations, i.e., genetically differentiated clusters. The software recognises sampled populations in Las Yungas (RCO and HCM) and two populations of Pampeana (COE and GUA) as an ideal population and identifies a cluster consisting of two nearby populations of Espinal and a distant Pampeana population . STRUCTURE software identified 18 ideal populations suggesting two clusters, one of which brings together RCO-HCM and another cluster grouping COE-GUA. The a posteriori probability for K = 16 introduced only minor differences and identified an additional cluster formed by STO, YAP and CAÑ.The analysis of DAMD population structure using Bayesian cluster approaches through BAPS considering the option of “admixture of genomes” gives additional information. HCM, RCO, STO and YAP populations contain more individuals with a mixture of ancestries suggesting the importance of gene flow in the observed differentiation. Estimates of gene flow between pairs of populations support these results, as they showed increased gene flow between populations grouped by the probabilistic assignment of individuals (HCM-RCO) (COE-GUA).This result confirms the level of DAMD differentiation between populations detected by AMOVA, Bayesian analysis of differentiation and the phenogram, suggesting a significant constraint on gene flow, even among nearby populations, or a low level of shared polymorphisms. The analysis of the assignment of individuals through Mioscirtus peccary in the Iberian Peninsula identified only 8 clusters Locusta migratoria. Analysis of 24 populations in Europe, China and Madagascar identified 7 ideal populations D. elongatus in Argentina.The strong signal of detected population structure is not common in species of Orthoptera. A microsatellite loci analysis of 24 populations of D. elongatus was genetically highly diverse, but also that the DAMD variation among populations was geographically associated. The autocorrelation results are in agreement with the Mantel test results. Both approaches demonstrated a significant increase in genotypic distances among populations with growing geographic distance. Analysis of variation in DAMD loci on a large scale by use of Mantel test showed IBD when considering the entire studied area, or the separate biogeographic regions of Pampeana and Espinal (data not shown). Genetic differentiation tends to increase with increased geographic distance, but that relationship explains only 12% of the variation. The remaining variation is due to variability within populations. Spatial autocorrelation analysis showed a high correlation among individuals at the smallest distances. We have detected a consistent pattern of fine-scale genetic structure with positive autocorrelation for populations separated by less than 100 km, whereas populations separated by more than 200 km showed greater genetic differences than expected from a random distribution. The autocorrelation and Mantel test results indicate that proximate populations are genetically more alike than more distant ones.The spatial genetic structure analysis not only demonstrated that D. elongatus DAMD loci. Our results suggest that although migration and genetic drift occur among adjacent populations, measurable relatedness among neighbouring populations declines with distance, and dispersal over distances greater than 200 km is not typical, whereas effective gene flow may occur for populations separated by less than 100 km. Thus, besides local endogamy, restrictions in gene flow in D. elongatus may lead to a non-homogenous spatial structure and justify the variation through space. In general, the DAMD pairwise gene flow estimates of neighbour populations are relatively low (1<Ne.m<2), supporting the importance of restrictions in gene flow in the signals of autocorrelations.Positive autocorrelation signals may also be due to spatial patterns shaped by natural selection, but only at selected or linked loci D. elongates, the genetic landscape shape plot shows a strong restriction in gene flow between populations from regions that would have been more disturbed by anthropogenic activities . Road edges and grassy margins are common features in most agricultural landscapes The environmental characteristics typifying the different habitats that shape the conditions of a landscape can either limit or promote the movement of individuals in populations and so the extent of genetic connectivity D. elongatus identified 32 haplotypes and demonstrated large values of nucleotide (0.002–0.017) and haplotype (0.524–0.917) diversity, but no geographic pattern was detected. Most populations share one or both of the most frequent haplotypes (DE-14 and DE-24). The presence of shared haplotypes in most populations may be explained by one of two scenarios: restricted gene flow among local populations or the predominance of ancestral haplotypes The analysis of mtDNA sequence of LAMARC studies support the second scenario. However, the magnitude of estimated gene flow between pairwise populations according to mtDNA data was different from some of the estimates based on FST values using DAMD data. The results from LAMARC analysis demonstrated that there was some directional bias in dispersal, especially between local populations of D. elongatus in different geographic regions. mtDNA  suggested a marked directionality of gene flow from western to eastern populations and at a minor level from south to north, suggesting a directional movement of females towards the north-eastern populations.The limited gene flow among populations indicated by minisatellite analysis and The relationship between haplotype and nucleotide diversity may be explained by different demographic frameworks h>0.5) and nucleotide (π>0.5%) diversity are high, the population is stable with a relatively long evolutionary history. Populations of STO, MCA, MOC, COE, GUA, CAR, PUI, VET, SCA and RLS meet this condition, suggesting apparent population stability.When values of haplotype  and high nucleotide diversity. These results may reflect the divergence level of both populations.When π and h values are low, the population might have undergone a reduction in population size or a recent colonisation event that generated few mitochondrial lineages. CON, FLO and RCO are characterised by low values in both indices, reflecting that these populations may have experienced a reduction in population size in the past. The estimated TMRCA showed that CON and FLO are the youngest populations , suggesting that low genetic diversity may reflect anthropogenic pressure.When both D. elongatus exhibited a higher degree of variation with respect to other grasshopper species. In Mioscirtus wagneri, the analysis of 16S and COII partial sequences in 24 natural populations of Iberian Peninsula showed values of haplotype (0–0.68) and nucleotide diversity (0–0.0006) that were substantially lower than those observed in the present study Oxya hyla intricate, which is a rice pest in southeast Asia, showed moderate values of genetic diversity  The mtDNA diversity analysis reveals that STΦ and STF statistics showed some differences. The AMOVA based on STΦ revealed greater differentiation among populations (14.8%) than the AMOVA based on haplotype frequencies (STF) (12.7%), indicating the relative importance of the divergence between haplotypes in the pattern of observed population differentiation. AMOVA analysis also indicated that ∼70% of the variation could be explained by differences within populations, while only ∼15% of the variation was attributed to differences among populations within regions. A large component of the variation (∼12%) was observed among geographic regions (east and west sides of Paraná River). Pairwise comparisons based on the frequency of haplotypes and the distances between them (STΦ) indicated that CON is the most differentiated population from the others. The high genetic differentiation detected between populations located on both margins of the Paraná River suggests significant restrictions in gene flow mediated by females and substantial large scale geographical differentiation.AMOVA results based on Phylogenetic inference based on the haplotype network displayed a “star-like” shape with DE-24 being the most probable ancestral haplotype. This structure reveals a shallow geographic structure.The present results are indicative of significant genetic differentiation of mtDNA lineages among the eastern and western populations, although these regions do not appear to display a strong phylogeographic signal.Different populations exhibit different histories, and even it is wrong to assume that ancestral or refugial populations have stable population histories Pleistocene era was characterised by cyclic climatic oscillations between warm and cold periods affecting population isolation in many species through recurrent glaciations D. elongatus populations from the studied area of Argentina originated 740000 years ago during Middle Pleistocene (781000–126000 years before pesent). Moreover, our TMRCA analysis indicates that populations located west of Paraná River  are the most ancient; however, populations located at east of Paraná River showed higher values of genetic diversity, suggesting secondary contact.The analysis based on the molecular clock model for COI haplotypes supports the hypothesis that the LAMARC analysis in Middle Pleistocene. Further oscillations in water levels of the Paraná River during Upper-Middle Pleistocene transition, may also explain a secondary contact among both regions across the River in west-east direction. In agreement, the pairwise mismatch analysis in eastern region fitted into a pattern of population undergoing expansion, supporting an extremely dynamic history of eastern populations.Paleo-taxonomic approaches suggested that environmental conditions should be some different in west and east regions of Paraná River during Pleistocene. The west region must have been more cold and arid environmental conditions, with a manifest predominance of open environments whereas west region of Paraná River must have been associated to more benign conditions, i.e., warm and humid MRCA), which points to GUA as the most ancient population of the eastern region.The migration rate analysis showed that one of the most likely routes of colonisation of the eastern region was through the area containing the CAM and CAÑ populations, which was formed by a slightly elevated block during Middle Pleistocene According to the BSP, after a phase of constant population size, the eastern and western regions appear to have experienced a demographic expansion, beginning approximately 150000 and 250000 years before present, respectively. Paleoenvironmental studies of the landscape in these regions during Late Pleistocene, but before Last Glacial Maximum (LGM), suggest the existence of suitable environmental conditions characterised by a slight humidity elevation and grassland vegetation Even though, Pleistocene climatic changes affect patterns of intraspecific diversity D. elongatus has provided answers to multiple questions about the population structure and dispersal abilities of these species. There are differences among AMOVAs based on minisatellite loci and AMOVAs based on mtDNA sequences, showing male-biased gene flow. Additionally, different populations of D. elongatus have reproductive and morphological differences, including male sexual selection favouring larger individuals and phenotypic variation as a result of local adaptation to season length and number of generations along a latitudinal gradient The use of biparental (DAMD) and uniparental (mtDNA) inheritance markers in D elongatus. Although climatic events of the Pleistocene have had a marked effect on the historical distribution and intra-specific divergence of D. elongatus, the extreme human land use and recent insecticide approaches used to control pest expansion could affect the intraspecific variation of this species. The dispersing males of D. elongatus may contribute to diminish the chances of genetic loss associated with recent anthropogenic activities in the extended Argentinean agro ecosystem. However in D.elongatus the male biased dispersal may be insufficient to prevent some level on local inbreeding detected through nuclear markers. Further studies examining genetic population structure over time and space are essential to analyse the effect of programmes for combating this grasshopper species.Our results show that the complex demographic history, effective migration, contemporary anthropogenic pressures and landscape heterogeneity could determine the genetic structure among populations of Appendix S1Variable sites defining the 32 haplotypes recovered from the 19 populations of D. elongatus studied.(DOC)Click here for additional data file.


Tai people are widely distributed in Thailand, Laos and southwestern China and are a large population of Southeast Asia. Although most anthropologists and historians agree that modern Tai people are from southwestern China and northern Thailand, the place from which they historically migrated remains controversial. Three popular hypotheses have been proposed: northern origin hypothesis, southern origin hypothesis or an indigenous origin. We compared the genetic relationships between the Tai in China and their “siblings” to test different hypotheses by analyzing 10 autosomal microsatellites. The genetic data of 916 samples from 19 populations were analyzed in this survey. The autosomal STR data from 15 of the 19 populations came from our previous study . 194 samples from four additional populations were genotyped in this study: Han (Yunnan), Dai (Dehong), Dai (Yuxi) and Mongolian. The results of genetic distance comparisons, genetic structure analyses and admixture analyses all indicate that populations from northern origin hypothesis have large genetic distances and are clearly differentiated from the Tai. The simulation-based ABC analysis also indicates this. The posterior probability of the northern origin hypothesis is just 0.04 [95%CI: (0.01–0.06)]. Conversely, genetic relationships were very close between the Tai and populations from southern origin or an indigenous origin hypothesis. Simulation-based ABC analyses were also used to distinguish the southern origin hypothesis from the indigenous origin hypothesis. The results indicate that the posterior probability of the southern origin hypothesis  is greater than that of the indigenous origin hypothesis . Therefore, we propose that the genetic evidence does not support the hypothesis of northern origin. Our genetic data indicate that the southern origin hypothesis has higher probability than the other two hypotheses statistically, suggesting that the Tai people most likely originated from southern China. Tai people are a subgroup of Tai language speakers who are widely distributed in Southeast Asia and the Yunnan Province of Southwest China. Tai people are the largest ethnic group in Thailand, but this ethnic group is called different names in other countries. They are called Dai in China, Shan in Burma and Lao in Laos. Although different names are used in different countries or in different literature, most researchers agree that these Tai speakers share a recent common origin Even though most researchers agree that Tai people share a recent common origin, the source of the Tai migration remains controversial. There are several popular hypotheses for the place from which the Tai people came, and these hypotheses can generally be summarized into two types: an indigenous origin hypothesis th and early 20th centuries th century B. C. Dodd also suggested that Tai people and Mongolians share a recent common origin th century by Davies Yue” people who were indigenous people in the south of ancient China. According to their theory, Tai people and the other Tai-Kadai-speaking ethnic groups in southern China, such as the Zhuang and the Mulao, have a recent common ancestor. Consistent with this hypothesis, today’s Chinese Dai and other Tai-speaking people in other countries migrated from southern China approximately 1,000 or 2,000 years ago. In 1900, the British scholar Scott suggested that Tai people were indigenous people of southwestern China and have evolved into an independent ethnic group The theory that the Tai originated from northern China was introduced in the late 19Yue” people, with other Tai-Kadai speakers who lived in southern China, such as the Zhuang and the Mulao. Thus, we refer to the Zhuang and the Mulao as the “southern origin of the Tai”. Finally, the Austro-Asiatic speakers, such as the Wa and the Bulang, were thought to share a recent common ancestor with Tai people in the indigenous origin hypothesis In addition to archeological, linguistic and historical investigations, genetic methods are also very useful for inferring some demographic events, such as population migrations, admixture and the relationships of different populations. The various theories of the origin of the Tai people were mostly derived from historical, cultural and archeological evidence but lack biological support. In this study, we use genetic methods to explore which hypothesis about the origin of the Tai is most likely correct. Nineteen ethnic groups were analyzed. Three Dai populations  that speak Tibeto-Burman, were chosen to test the reliability of our method based on analyses of genetic variation. There is evidence that Tibeto-Burman speakers and Han people share a recent common ancestor Microsatellites are highly informative loci that are found across the human genome that can provide generally reliable relationships among closely related populations HE) HE results and HWE test results of the four populations that were genotyped in this study are shown in HE was 0.666 (D3S1285 of the Mongolian population), and the highest HE was 0.898 (D3S1263 of the Yunnan (Han) population). All 10 of the markers were highly diverse in these four populations. The genotypic data of these 10 markers in 19 populations were listed in All of the 19 populations, which included 916 samples, were analyzed. Four of the populations were genotyped in this study, and the data from the other 15 populations is from Lin’s study Most loci were consistent with HWE in the four populations that were genotyped in this study. After a Bonferroni correction for multiple tests, only two cases, D3S1278 and D3s1292 in the Han (Yunnan) population, remained significant at an α = 0.000125 significance level. This may be caused by the deficiency of heterozygotes, which could be attributed to a null allele.Because all of the 10 markers were located on chromosome 3, although the distances between them were very far , analyses of linkage disequilibrium between adjacent loci were performed to ascertain that these loci were not linked. In all of the 19 populations, no significant linkage disequilibrium was identified between these loci after a Bonferroni correction was performed. Linkage disequilibrium beyond adjacent loci was not tested because the high recombination fraction between loci made linkage disequilibrium unlikely.FSTFST comparisons between all 19 of the populations are shown in the lower triangle of P values are shown in the upper triangle. The values of pairwise FST ranged from 0.003 to 0.071. The differences, indicated by FST, between most of the populations were significant, even when the significance level was set at 0.0003 (after a Bonferroni correction). The FST value was very small and not significant among the Dongxiang, Sala and Han (Gansu) populations. The FST value between the Zhuang and the Mulam was also small and not significant. All of the FST values between the Mongolian population and the three Dai populations were greater than the FST value between the Zhuang and the three Dai populations.The fixation index FST values among them. The Mongolian, Dongxiang and Sala populations were pooled as the NT (Northern origin of the Tai). The Zhuang and the Mulao populations were pooled as the ST (Southern origin of the Tai). The Wa and Bulang populations were pooled as the NAT (Native origin of the Tai). The three Dai populations were pooled as the Tai of China (TC).According to the three hypotheses of the origin of the Tai, we pooled populations that are located in each of the hypothetical origins of the Tai and calculated the FST value between the TC and the NT was 0.0183; the FST value between the TC and the ST was 0.0055; the FST value between the TC and the NAT was 0.0052. The differences that are indicated by the pairwise FST among these four pooled populations were significant (P<0.0001). The genetic distance between the TC and the NT was nearly three times as large as the distances between the TC and the other two pooled populations (the ST and the NAT).The CD) AD) DST) FST* distance FST. The results are shown in FST analyses. The genetic differentiation was high between the Tai and populations from the northern origin hypothesis. Conversely, genetic differentiation was low among populations from the southern origin hypothesis or populations from the indigenous hypothesis and the Tai. In most of the PCA analyses, the Han  clustered together and were near the populations from northern China. The Han (Guangdong) was near the populations of southern China.In order to avoid deviations which may be caused by the difference of the distance calculation methods and catch the common features of populations’ relationships which were revealed by different genetic distances, four other genetic distances were calculated. Those are Cavalli-Sforza's chord measure (rMAX = 0.66±0.05 (K = 9) in our analyses indicates that more information is given with the LOCPRIOR model than without it. The results for K = 2 to 6 are shown in K = 5. According to the guidelines in the STRUCTURE manual K = 5 is the most appropriate value.Population structure was also investigated using STRUCTURE 2.3 under the LOCPRIOR model K = 5, the five different genetic components had similar proportions in the three Tai populations. Simultaneously, similar proportions could also be found in populations from the southern origin hypothesis  and populations from the indigenous hypothesis . A clear distinction was observed between the Tai and populations from the northern origin hypothesis . In particular, the genetic component represented by orange  of the NT to the TC was −0.08±0.21 (mean±S.D.), and the estimated mY of the NAT to the TC was 1.08±0.21. This indicates that the NT postulated as the parents of the TC have made very little genetic contribution to the TC. According to the southern origin hypothesis, the Mulam and the Zhuang were pooled (ST) as the southern parent of the TC. The mY of the ST to the TC was 0.35±0.12, and the mY of the NAT to the TC was 0.65±0.12. Thus, the ST contributed approximately 35% of the genes to the gene pool of the TC, and the other 65% of the genes in the gene pool of the TC came from the NAT populations. Based on these results, the southern origin hypothesis appears more reasonable than the northern origin hypothesis when the gene flow after Tai migrated to southwestern China was considered.Because gene exchange between the Tai and native populations in southwestern China (Wa and Bulang) possibly existed after the Tai people migrated to southwestern China, it is necessary to evaluate the genetic influence of the Wa and the Bulang on the Tai people when examining both the northern and southern origin hypotheses. Admixture analyses of multi-parental populations were performed using the Admix 2.0 program The above analyses indicate that there is a large genetic distance between the NT and the Tai; therefore, the northern origin hypothesis is not supported by our genetic data. However, we still cannot distinguish whether the southern origin hypothesis or the native origin hypothesis is closer to the actual situation. These three hypotheses were simulated, and their posterior probabilities were calculated using DIY-ABC v1.0.4.46b After generating 1.5 million simulated datasets (0.5 million for each scenario), the posterior probability of each scenario was evaluated using polychotomous logistic regression Following the recommendations of Robert et al. Chu, which was located in what is today the Hubei Province of China. The largest wave of immigration to Yunnan occurred early in the Ming Dynasty in 1389 A. D. Approximately 3 million Han people, most of whom came from Nanjing (Jiangsu Province today), and a few from Shanxi and Hebei Provinces, were sent to Yunnan by the emperor of the Ming Dynasty. Thus, they all came from northern China. In Midu County, Yunnan Province, where we collected the samples representing the Han (Yunnan) population, the Han people consider themselves “pure Han people”. According to the county annals of Midu, they were the first migrants, following the army, and came from Jiangsu Province (North of the Yangtze River) in the Ming Dynasty. Actually, most of the Han people in Central Yunnan came from northern China. The spoken languages serve as further evidence indicating that the Han in Yunnan came from northern China. Today, the languages used by most Yunnan Han people belong to the northern dialect of Chinese.Genetic data from living human populations can be used to reconstruct their evolutionary histories and to investigate certain demographic events. Our study aimed to determine the origin of modern Tai-speaking people using genetic variation analyses. To ensure that our methods were applicable, we introduced the Han (Yunnan) into our study, the origin of which is well documented by ancient historical records. At approximately 200 B. C., tens of thousands of migrants entered Yunnan from the kingdom of FST values between the Yunnan Han and the other two northern Han populations (Shangdong and Gansu) were very small (0.006 and 0.008). Furthermore, there were no statistically significant differences between them after Bonferroni correction (P>0.0003). Conversely, the pairwise FST value between the Yunnan Han and the Guandong Han, which is a typical southern Han population, was 0.018, and the difference was significant. The PCA results based on different genetic distances also indicate that the Han (Yunnan) have a closer genetic relationship to the northern Han than the southern Han. Using the southern Han population for comparison, STRUCTURE analysis also revealed more consistent proportions of genetic components in the Han (Yunnan) and other northern Han populations. Consequently, for a relatively short time, the genetic variation of the Han (Yunnan) was mainly determined by their origin, and the Han (Yunnan) and the Han in northern China still have a similar genetic makeup, although they are separated by large geographic distances. The consistency between the historical records and our genetic analyses also shows that our microsatellite-based methods can be used to correctly trace population origins. Thus, we used these methods to test the hypotheses of the origin of the Tai.The results of our genetic analyses are consistent with these historical records. The pairwise FST and PCA results. In particular, the Mongolian population, which was considered “near in blood with Tai people” by Dodd mY. This indicates that the NT did not genetically contribute to the gene pool of the TC. After immigration, a gene pool may primarily be affected by genetic drift, mutation or gene flow. Within such a relatively short period, approximately 2,000–3,000 years, it is difficult to believe that random genetic drift, mutation or gene flow from native populations (Wa and Bulang) could generate such significant differences between the Tai and populations from the northern origin hypothesis . The simulation-based ABC analysis also indicates this. The posterior probability of the northern origin hypothesis was only 0.04 [95%CI: (0.01–0.06)]. Furthermore, certain populations that are separated by small geographic distances from populations from the indigenous hypothesis (Wa and Bulang), such as Hani and Han (Yunnan), do not share a similar genetic makeup with them. Therefore, we propose that the hypothesis of a northern China origin is unlikely.Three main hypotheses about the origin of Tai-speaking people were proposed based on archaeological and anthropological data: the indigenous origin hypothesis Other reports have also shown that Tai-speaking people have large genetic distances from Mongolian populations. Yao et al. (2002) examined hypervariable segment I (HVSI) of mtDNA from several Chinese populations, including Tai-speaking people and Mongolian populations. The phylogenetic trees they constructed showed that Tai-speaking people (including Chinese Dai and Thai in Thailand) and Zhuang clustered on the tree, whereas the Mongolian population was located distantly from these populations. PCA results also showed that Mongolian people have a large genetic distance with Tai-speaking people FST analysis and PCA comparisons indicate that the genetic differences among these populations are small. Furthermore, the clustering analysis from STRUCTURE also indicates that these populations are genetically similar. We also found that the mean number of different alleles per locus in the ST (12.1±1.7) was slightly larger than in the Tai (11.4±0.1) and in the NAT (10.5±1.03), but this difference was not statistically significant . To find the most likely model of the Tai origin, we inferred the possibilities of the three hypotheses of the Tai origin using the ABC approach We excluded the northern origin hypothesis, but it is difficult to separate the southern origin hypothesis from the indigenous hypothesis. Populations from the southern origin hypothesis (Zhuang and Mulao) and those from the indigenous hypothesis (Wa and Bulang) are very closely related. The results of pairwise Finally, in our study, we only selected Tai populations found within China, which is based on an inference agreed upon by most anthropologists and historians: modern Tai-speaking people have a recent common origin The autosomal STR data of 15 populations came from our previous study The DNA was obtained from immortalized B lymphocyte cell lines in our ethnic cell bank. Written informed consent was given for the establishment of cell lines and for subsequent genotyping studies. This study was approved by the Ethics Committee at the Chinese Academy of Medical Sciences and Peking Union Medical College. The DNA was extracted using a DNA Miniprep Kit .To compare our results to the published STR data PCR reactions contained 0.2 µmol/L of primer mix, 200 µmol/L of each deoxynucleotide triphosphate (dNTP), 1×PCR Buffer, 0.1 U Transtart DNA polymerase  and 20 ng of genomic DNA in a total volume of 25 µL. Amplification reactions were performed using a Perkin Elmer GeneAmp PCR System 9600 thermal cycler , and cycling conditions were as follows: initial denaturation at 94°C for 5 min, followed by 10 cycles of 94°C for 30 s, 55°C for 30 s and 72°C for 30 s, 25 cycles of 89°C for 30 s, 55°C for 30 s and 72°C for 30 s and a final extension at 72°C for 20 min. The amplified products were detected with an ABI3730 genetic analyzer . The data files were generated by ABI PRISM GeneScan Analysis software .HE values FST values Arlequin version 3.11 CD) were computed using PHYLIP AD distance DST) FST* distance FST and the four types of distances above using GenAlEx Genetic distances based on Cavalli-Sforza's chord measure (FST<0.02) r value is reported. An r value lower than 1 indicates that the sampling location in the model is effective K) from 2 to 9, using an MCMC chain with a burn-in length of 80,000 iterations, followed by 80,000 iterations under the LOCPRIOR model. Most of the parameters were set to their default values as advised in the user’s manual. Following the suggestion of Falush et al. K was identified using the value of the average logarithmic probabilities across runs returned by STRUCTURE 2.3. The outputs from STRUCTURE were graphically modified by DISTRUCT Population structure was investigated using STRUCTURE 2.3 mY based on the average coalescence times between pairs of genes was evaluated by Admix 2.0. −4 per generation Estimation of the admixture coefficient The simulation-based ABC analysis was performed using DIY-ABC v1.0.4.46b −4 and 10−3Regarding the parameters for the microsatellite markers, each locus was assumed to follow a generalized stepwise mutation model (GSM) We evaluated the power of our methodology to discriminate between scenarios by analyzing test data sets simulated with identical numbers of loci and individuals as in our actual data set. Five hundred of such test data sets were simulated under each competing scenario, using parameter values drawn from the same prior distribution of those used in the ABC analyses. The posterior probabilities of each competing scenario were estimated for each simulated test data set and were used to compute type I and II errors in the choice of scenario by considering that the chosen scenario is the one with the highest probability value. We produced a total of 1,500 test data sets for the set of three competing scenarios that were analyzed to infer the evolutionary history of the Tai.Table S1Standard diversity indices. The allele frequencies, expected heterozygosities (HE) and Hardy-Weinberg Equilibrium (HWE) tests of the four new ethnic groups for the 10 microsatellites.(XLS)Click here for additional data file.Table S2Genotypic data of 19 populations. The genotypic data of 10 microsatellite markers in 19 populations.(XLS)Click here for additional data file.Table S3FST of 19 populations. The pairwise FST values and their significance among the 19 populations.(XLS)Click here for additional data file.


Phenotypically defined, biotypes frequently remain evolutionarily indistinct, resulting in ineffective application of virulence control measures and shorter durability of resistant cultivars. Here, we utilize an evolutionary framework to discern the genetic relationship between biotypes of the soybean aphid . The soybean aphid is invasive in North America and is among the most destructive pests of commercial soybean on the continent. Attempts to breed host-plant-resistant soybean have been hampered by the emergence of virulent aphid biotypes that are unaffected by the plant's resistance mechanism(s). Comparative population genetic analysis of virulent and avirulent  biotypes found populations to be genetically indistinguishable across biotype and geographic distance, with high rates of interpopulation immigration and admixture. The lack of genetic distinction between biotypes coupled with elevated genotypic diversity within all populations suggested virulence has a nongenetic-based or includes a gene complex that is widely distributed throughout soybean aphid populations, which undergo regular dispersal and unimpeded sexual recombination.Adaptive evolution of pest insects in response to the introduction of resistant cultivars is well documented and commonly results in virulent ( The recThe genetic and environmental mechanisms of pest virulence to resistant cultivars are often ill defined. Within crop resistance literature, virulent pests are most commonly organized within the pseudo-taxonomic category of biotype, an intraspecies taxon defined by a shared differentiating phenotype  is a significant hemipteran pest of soybean (Glycine max L.) native to East Asia   genes have been described, Rag1 – Rag5 , biotype 2 (virulent only to Rag1 soybean), and biotype 3 (virulent to Rag2 while remaining mostly avirulent to Rag1 soybean), and biotype 4  . Currently, five A. glycines could be the result of any of the five described categories with patterns of genetic variability matching those listed in Although much effort has been made to elucidate the mechanism and chromosomal location of aphid resistance within soybean  and susceptible variety SD-01 76R  aphids collected in the field on Rag1 expressing plants were assumed to be virulent and defined as biotype 2. Any aphids collected on susceptible soybean could be biotype 1 (avirulent to Rag1) or biotype 2 and therefore required further characterization using the detached leaf assay as outlined by Michel et al.  across an eight-day period of August 27 through September 2, 2012. These dates were selected as they coincide with peak aphid infestation in Ohio and overlap with northwestern cluster collection days. Furthermore, these dates were after known soybean aphid dispersal events that homogenize population structure, allowing us to avoid confounding geographic population structure associated with temporal factors  was an exception, with three rows of soybean (per treatment) grown in a separate plot, not adjacent to conventionally grown soybean fields. At all locations, aphids were collected on a single day  per manufacturer's instructions. A total of 18 single nucleotide polymorphisms  and the Simpson's diversity (D) and evenness score (V) were calculated to estimate the abundance and diversity of clones within and between the sampled populations. Additionally, all shared MLGs within a sampled population were assessed for origin of identity using GenClone's PSEX statistic. PSEX estimates the probability that individuals with a shared MLG were a product of sexual reproduction, as opposed to clonal propagation.While the sampling scheme was designed to avoid the sampling of clones, clonal identification was still required as to not bias the data set toward over-represented lineages , were calculated via GENEPOP  between populations with Bonferroni-corrected P-values. Principal coordinate analysis (PCA) was performed using a Nei's pairwise distance matrix in GenAlEx v. 6.41. Population assignment was estimated using both the Paetkau assignment method  than the populations within the western cluster . Locus 42701 inflated FST values between the geographic clusters and was removed from the analysis. Loci 5109 and 2654 were not geographically or biotypically associated but were nonetheless removed from the data set to avoid confounding the patterns of divergence inherent within the remaining neutral markers. Among the remaining loci, limited linkage disequilibrium was detected between six loci, but was found to have no significant effect on statistical analyses or results.LOSITAN analysis revealed one locus under directional selection (42701) and two loci undergoing balancing selection (5109 and 2654) . The dirRag1 plants compared to susceptible plants due to the virulent biotype's restricted gene pool. However, clonal lineage assessment revealed multilocus genotype (MLG) diversity to be high both within and between biotype populations. Of the 662 sampled individuals, there were 575 distinct MLGs, of which 524  were singletons . Of the shared MLGs , the majority were shared between individuals of the same biotype and collection site, while a minority were shared across biotype or site. PSEX values for members of shared MLGs were significant (P < 0.05), indicative of clonal origin for shared genotypes. The most common shared MLG consisted of 18 biotype 2 individuals from the Df site. This population was also the least diverse genotypically, with 22 of its 48 sampled members (45.8%) belonging to a shared MLG. In contrast, biotype 2 from the Fu site had the greatest diversity of MLGs with only one aphid (1.8%) having a shared MLG.Analyzing the clonal diversity among biotypes can provide an indication of the prevalence of virulence in a population. If virulence is rare, then we would expect a small diversity of genotypes to be found on D: biotype 1 = 0.994, biotype 2 = 0.974, Wilcoxon: P > 0.2, n = 7, W = 12; V) was also not significantly different between biotypes , averaging 0.566 for biotype 1, and 0.501 for biotype 2. These diversity measures remained nonsignificant when populations were compared across micro-, meso-, and macrogeographic distances  = 2.32, P > 0.2; Meso F = 0.919, P > 0.2; Macro F = 1.381 P > 0.2).Elevated genotypic diversity in many populations resulted in uninformative results for some MLG diversity statistics, as was seen in previous analyses of soybean aphid populations . Similarly, no differences in HO or FIS were observed when grouped by eastern and western clusters; however, there was significant difference in expected heterozygosity  between the clusters due to a relatively high proportion of homozygotes in both biotype populations from the Wd site.Hardy–Weinberg disequilibrium was observed at several loci, with deviation occurring at 85 of a total possible 210 cases (40.5%). Total loci in disequilibrium per population averaged 6.07 (range 3–11). These results are greater than those observed in previous research . However, significant differences were found when populations were compared among and between meso- and macrogeographic distance, with Df showing significant difference from Fu  and W1-4 sites .Population pairwise of 0.013 . No popuk = 1. Both the STRUCTURE and Peaktau analyses suggest little genetic differentiation between populations according to biotype or geographic location.If genetic variation in soybean aphid populations was associated with either biotypes or geography, then the PCA would have reflected nonrandom clustering respective of either of these two factors A,B. InstIn this study, we applied a population genetic framework to investigate the genetic relationship among virulent and avirulent insect biotypes. Utilizing the Diehl and Bush categories of biotype evolution, we have constructed a five part hypothetical framework along with predictive responses for each category . The lacPopulation genetic analysis of soybean aphid biotypes 1 and 2 showed that there is no significant differentiation between populations segregated by biotype or geographic location, but rather was consistent with genetic homogeneity across the landscape , Fig. 2.ST value in the study was not among the most geographically distant sites, but between the biotype populations in Df . The unusually large genetic differentiation between these populations was not due to genotyping error, systematic artifacts, or sampling bias. Rather, the source of the deviation was likely environmental, due to the unique growing conditions at this collection site. Unlike the other populations where the sampled plants were embedded in larger production fields, the sampled plants in Df were instead grown in separate rows, relatively isolated from nearby suitable A. glycines habitat. Additionally, Defiance County experienced an unusually dry and warm July, with mean high temperatures consistently >32°C. At this temperature, soybean aphids are known to suffer elevated mortality at the first instar   nongenetic polymorphism, (ii) polymorphic or polygenic variation within populations, (iii), geographic races, (iv) host races, and (v) species . These cNongenetic sources include the presence of phenotypic plasticity; phenotypes are environmentally dependent provided enough genetic variation is present in the population to produce a large phenotypic range . In this case, genetic variation between biotypes is expected to be minimal  and 5, tBuchnera aphidicola and two facultative species: Wolbachia and Arsenophonus  able to overcome the deficient amino acid content. B. aphidicola upregulated different proteins when their potato aphid (Macrosiphum euphorbiae) host was reared on diverse resistant cultivars . Future studies are needed to understand the interaction between the soybean aphid and its various endosymbionts.Facultative endosymbionts are associated with a number of traits in aphids including nutrition, heat resistance, parasitoid immunity, and host-plant transitions  were found to locate phloem faster and feed longer than individuals previously unexposed to the resistant plant, implying adaptive plasticity ’ by Diehl and Bush . The epiA. glycines ecology and functional genetics provides challenges to understanding biotype evolution. Furthermore, as the use of resistant soybean increases, we may see more dramatic shifts in virulence frequency not revealed through this study using a single collection year. Future research investigating the role of endosymbionts, phenotypic plasticity, gene complexes, and their synergistic interaction with host plants and environmental variables is required to isolate the specific mechanism of virulence. Understanding the evolutionary and ecological mechanisms of insect adaptation to resistant hosts will be instrumental in the development of resilient insect resistance management programs.Population genetic analysis of soybean aphid biotypes has uncovered no significant genetic differentiation across either geographic space or biotypic designation. Biotypic virulence appears to be associated with a nongenetic source or genetic mechanism combined with uninhibited gene flow, dispersal, and sexual recombination. Environmental variables are known to affect both soybean resistance and aphid physiology, suggesting that biotypic virulence may be the result of phenotypic plasticity through multitrophic interactions. However, the current lack of information regarding North American