Glossina morsitans morsitans, is a significant problem in Zambia and Malawi. It is the vector for the human infective parasite Trypanosoma brucei rhodesiense, which causes human African trypanosomiasis, and various Trypanosoma species, which cause African animal trypanosomiasis. Understanding the genetic diversity and population structure of G. m. morsitans is the basis of elucidating the connectivity of the tsetse fly populations, information that is essential in implementing successful tsetse fly control activities. This study conducted a population genetic study using partial mitochondrial cytochrome oxidase gene 1 (CO1) and 10 microsatellite loci to investigate the genetic diversity and population structure of G. m. morsitans captured in the major HAT foci in Zambia and Malawi. We have included 108 and 99 G. m. morsitans samples for CO1 and microsatellite analyses respectively. Our results suggest the presence of two different genetic clusters of G. m. morsitans, existing East and West of the escarpment of the Great Rift Valley. We have also revealed genetic similarity between the G. m. morsitans in Kasungu National Park and those in the Luangwa river basin in Zambia, indicating that this population should also be included in this historical tsetse belt. Although further investigation is necessary to illustrate the whole picture in East and Southern Africa, this study has extended our knowledge of the population structure of G. m. morsitans in Southern Africa.The tsetse fly,  Glossina morsitans morsitans, an important vector of the Trypanosoma parasite. Our aim was to identify the optimal range of areas in which to implement effective tsetse fly control programs. We focused on five areas of active human African trypanosomiasis foci in Zambia and Malawi and used both mitochondrial and nuclear markers for population genetics analyses. High levels of genetic differentiation were observed between G. m. morsitans in Nkhotakota Wildlife Reserve, Malawi, and those at the other locations included in this study. Nkhotakota Wildlife Reserve lies on the eastern side of the escarpment of the Great Rift Valley at an altitude that is at the biological limit of G. m. morsitans, thereby functioning as a geographical barrier restricting gene flow from the G. m. morsitans on the western side of the escarpment. The western side of the escarpment is part of a historically-known tsetse belt that resides within the Luangwa river basin. We have demonstrated that a previously undescribed population of G. m. morsitans in Kasungu National Park, Malawi, should be included in this historical tsetse belt.Techniques from population genetics have been widely applied to assess problems in evolutionary biology, computational biology, wildlife conservation, animal breeding, etc. In this study, we used population genetics approaches to elucidate the genetic population structure of the tsetse fly  Glossina spp.) are the vector for the Trypanosoma parasites that cause human African trypanosomiasis (HAT) and African animal trypanosomiasis (AAT). Both diseases present a significant burden in terms of public health and economy in sub-Saharan Africa [Tsetse flies  of tsetse flies: G. morsitans morsitans, G. morsitans centralis, and G. pallidipes; one species from the Fusca group (subgenera Austenina Townsend); G. brevipalpis; and one species from the Palpalis group (subgenera Nemorhina Robineau-Desvoidy); G. fuscipes [G. m. morsitans and G. pallidipes are the major vectors of AAT and HAT in these countries. The prevalence of human infective T. b. rhodesiense, as assessed by the presence of the T. b. rhodesiense-specific human serum resistance-associated gene, was highest in G. m. morsitans [G. m. morsitans inhabits savanna woodlands, and its distribution has been mapped primarily by determining the abundance of mammal hosts, and the analyses of tsetse habitat using geographical information systems and remotely-sensed satellite data [G. m. morsitans populations in East and Southern Africa are distributed across Tanzania, Mozambique, Zimbabwe, Zambia and Malawi [G. m. morsitans in two of the four allopatric belts has been explored using mitochondrial and microsatellite markers, and significant differences have been identified among five populations from Zambia, Mozambique and Zimbabwe [G. m. morsitans in this region [G. m. morsitans populations from Malawi.Zambia and Malawi, along with Mozambique and Zimbabwe, lie within the “common fly belt” in Southern Africa . Tsetse fuscipes . Among torsitans . G. m. mite data ,13. The d Malawi  and consZimbabwe ,16. FurtZimbabwe . Althougs region , there hG. m. morsitans in the major HAT loci in Zambia and Malawi, which data are fundamental for vector control, we conducted a population genetics study using a 407-bp region of mitochondrial cytochrome oxidase 1 gene (CO1) with 10 microsatellite loci as genetic markers.Zambia and Malawi, two countries in South-East Africa with a significant HAT burden, report fewer than100 new cases annually , and KasG. m. morsitans were collected from three locations in Zambia, and two locations in Malawi  of template DNA, 5 μl Ampdirect Plus (Shimadzu Corp.), 0.05 μl BioTaq HS DNA Polymerase (Bioline), 0.5 μl (10 mM) primers, and 3.7 μl of water for a total volume of 10 μl. Amplification included an initial denaturation step at 95°C for 10 min, followed by 94°C for 30 s of denaturation, 30 cycles each for 30 s at 60°C for annealing, 1 min at 72°C for extension, and a final extension step at 72°C for 7 min. The PCR products were purified using ExoSAP-IT (Applied Biosystems), following the manufacturer’s protocol. Forward and reverse strands were sequenced with ABI 3130/3500xl sequencers (Applied Biosystems). The chromatograms were visually inspected, and poor-quality data were trimmed using ApE Plasmid Editor v2.0.51 . Both forward and reverse sequences were used to create a consensus sequence for each sample, and multiple sequences were aligned using online MAFFT v7 [We generated new primers  for the amplification of a 477-bp fragment of the mitochondrial CO1 gene. Reactions contained 0.25 MAFFT v7 , resultiNd); the average nucleotide diversity within locations (π); the number of haplotypes within locations (H); and haplotype diversity within locations (Hd). the summary statistics and the mismatch distribution of pairwise differences were analyzed using DnaSP v6.11.01  [D: based on the difference between expected segregating sites, and Fu’s Fs: based on the degree of excess of rare alleles), population pairwise ϕST  and the genetic diversity within and among populations evaluated by the analysis of molecular variance (AMOVA) using the haplotype frequencies distance method, were analyzed using ARLEQUIN v3.5.2.2 [The summary statistics calculated were: the average number of nucleotide differences between individuals within locations  . Neutralv3.5.2.2 ,25. BonfTo infer and visualize the evolutionary relationships of the haplotypes, we constructed a median-joining haplotype network using POPART v1.7 .μl, containing 1 μl template DNA, 0.05 μl Multiplex PCR mix 1 and 5.0 μl Multiplex PCR mix 2 , 0.2 μl (10 mM) primers, and 3.55 μl of water. Amplification included an initial denaturation step at 94°C for 1 min, followed by 94°C for 30 s of denaturation, 30 cycles each of 90 s at 57°C for annealing, 90 s at 72°C for extension, and a final extension step at 72°C for 10 min. PCR products were diluted from ×1 to ×20 according to the thickness of the band from the electrophoresis results, and four different fluorescence samples were pooled to be genotyped on an ABI 3130 sequencer. Alleles were scored using the software Peak Scanner v1.5 (Applied Biosystems) and the scored peaks were manually edited. Micro-Checker v2.2.3 was used to check for null alleles, and two loci were dropped due to the presence of null alleles [We used 12 autosomal microsatellite loci, which have been described in other studies –30. Amplgenepop file, which was used in GENEPOP v4.7 [NA), allelic size range , expected heterozygosity among polymorphic loci (HE), observed heterozygosity among polymorphic loci (HO), estimation of the inbreeding coefficients , and population pairwise FST based on number of different alleles were calculated using ARLEQUIN v3.5.2.2. The genetic diversity within and among populations were calculated by AMOVA analysis as implemented in ARLEQUIN v3.5.2.2 [MSA v4.05  was usedPOP v4.7  to test POP v4.7 . Geneticv3.5.2.2 . BonferrG. m. morsitans was determined using the Bayesian clustering method used in STRUCTURE v2.3.4 [The genetic structure of E v2.3.4 . Ten repE v2.3.4  implemenE v2.3.4 . The repE v2.3.4 , and theE v2.3.4 .Ne), including both female and male samples, was estimated for each population using the LD method in NeEstimator v2.1 [The effective population size  in these locations were generally high, ranging from 0.582 in SHKB to 0.801 in KNP. In contrast, nucleotide diversity (π) was low, ranging from 0.002 in SHKB to 0.007 in NWR. The most common haplotype, Hap_1, was found in 33 individuals (30.6%) from all sampling locations except NWR, indicating a common ancestry of the G. m. morsitans from four locations , suggesting the effects of either positive selection or population expansion in KNP  between NWR and other locations, with values ranging from 0.203 to 0.307. All comparisons between LZNP and the other locations showed significant ϕST values, ranging from 0.177 to 0.273  than the variation among populations (15.71%) , suggestto 0.273 .G. m. morsitans samples were genotyped at 10 microsatellite loci. None of the microsatellite loci pairs showed significant results of the LD tests (NA was highest in LZNP (10.1) and lowest in SHKB and KNP (8.8) in the five locations (HE was observed in SHKB (0.768), and the highest was observed in LZNP (0.835).A total of 99 LD tests . NA was ocations . The lowFST estimate among locations was 0.028 (p < 0.001). All pairwise comparisons between NWR and other locations were statistically significant (p > 0.05), with FST values after Bonferroni correction ranging from 0.024 (NWR vs. LZNP) to 0.075 (NWR vs. SHKB)  compared to the percentage of variation among populations (2.76%) and among individuals within populations (−11.39%) in the AMOVA analysis . The FSTs. SHKB) , indicatdistance .Including all five locations in the STRUCTURE analysis, the Evanno method resulted in the identification of two genetic clusters . NWR wasNe was estimated using the LD method. SHKB and KNP had 95% confidence intervals which included infinity. LZNP, MGMA, and NWR showed Ne of 121.1 (95%CI 65.0–606.2), 133.5 (95%CI 65.7–2763.0), and 32.1 (95% CI 24.2–45.5), respectively. NWR had relatively low Ne values compared to the other locations  and LZNP with NWR (FST = 0.024). The discrepancy between CO1 and microsatellite pairwise comparisons may be due to differences in the level of differentiation between mitochondrial and nuclear genomes. The mitochondrial genome is known to reach genetic-drift equilibrium earlier than the nuclear genome, due to the smaller effective population size of the mitochondrial genome. These results suggest that there is limited gene flow between G. m. morsitans in NWR from the same subspecies found in other locations, a finding that corresponds well with the estimation of G. m. morsitans distribution conducted in previous studies [Our haplotype network analysis of the CO1 sequences and microsatellite STRUCTURE analyses revealed high differentiation between ons Figs  and 3. Tded 0.03 . When we studies ,13,17. N studies ,46, whicϕST values compared with other locations Click here for additional data file.S2 FigPlots were generated using the Evanno method  implemen(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


To assess the genetic diversity of seven Yunnan indigenous goat populations , their population structures were investigated using 20 microsatellite markers.The results indicated that the genetic diversity of these goats was rich. The observed heterozygosity ranged from 0.4667 ± 0.0243 to 0.5793 ± 0.0230, and the mean number of alleles ranged from 4.80 ± 1.61 and 4.80 ± 1.64 to 6.20 ± 2.93. The population structure analysis showed that these seven goat populations were separated into two clusters, consistent with the results from phylogenetic networks, pairwise differences, and STRUCTURE analyses. We speculate that this may have been caused by natural geographical isolation, human migration and economic and cultural exchanges. We suggest removing CSRD247 and ILSTS005, two loci identified to be under positive selection in the present study, from the microsatellite evaluation system of goats.The present study may provide a scientific basis for the conservation and utilization of Yunnan indigenous goats. Currently, the abundant genetic diversity of goats has been assessed by using many different types of molecular markers, including microsatellites  and the Animal Protection Law of China . All samples were collected from venous blood. The sample supply department guaranteed that after blood collection, the blood collection site was disinfected with alcohol to ensure no infection. At the same time, the animals were observed to survive normally after 1 week without any adverse effects. The genomic DNA from 175 individual blood samples of seven Yunnan indigenous goat populations  heterozygosity, expected heterozygosity (HE), mean number of alleles (NA), and polymorphism information content (PIC) was performed with the Microsatellite Toolkit  was calculated by Fisher's exact test with Bonferroni's correction using FSTAT 2.9.3.2  were assessed with Arlequin software version 3.5.1.3  and 0.5994 (0.3387 [ILSTS029] to 0.7298 [SRCRSP9]), respectively. The average PIC across loci was 0.5436 and ranged from 0.3003 (ILSTS029) to 0.7680 (SRCRSP23) among all populations  to 22 SRCRSP23). The mean . The meaHE within the population ranged from 0.5834 ± 0.0456 in NLG to 0.6206 ± 0.0377 in ZTG. The Ho ranged from 0.4667 ± 0.0243 in WGG to 0.5793 ± 0.0230 in FQG. The NA ranged from 4.80 ± 1.61 (WGG) and 4.80 ± 1.64 (FQG) to 6.20 ± 2.93 (YLG)  that deviated from HWE, while FQG and HGG showed one marker  that deviated from HWE .FIS within the population ranged from 0.024 (p = 0.2311) in FQG to 0.214 in WGG (p = 0.0004). No population generated a p‐value for inbreeding coefficients that was significantly different from zero, indicating an adjusted nominal level (5%) of 0.00036 based on 2,800 randomizations of the p‐value for FIS  and ZTG (πX = 10.8697), and the lowest diversity was observed for YLG (πX = 10.1867) and LHG (πX = 10.1377). YLG, ZTG, NLG, and LHG had the smallest differences between them compared with those between the other three populations  when assessing the pairwise differences between populations (πXY), consistent with the results of the corrected average pairwise difference (πXY−[πX + πY]/2). In addition, according to the chi‐square test of FST, all populations showed significant divergence (p < 0.05) from each other |/s|L(K)|. From K = 2 to K = 4, seven studied populations were separated and formed two independent groups: group I, including FGQ, HGG, and WGG, and group II, including YLG, ZTG, NLG, and LHG  and ILSTS005  were found to be under positive selection in the locus selection style analysis  of all microsatellite loci across the seven Yunnan goat populations, suggesting that these markers were adequate for assessing the diversity of these populations. In addition, several markers showed a deviation from HWE, which could have been due to the small sample size or the potential occurrence of recent population genetic events  analyzed in the present study was estimated, showing that the Ho value of every population was smaller than the HE values, and 1–8 markers deviated from HWE within a population. Deviations from HWE occur when individual populations are substructured into smaller flocks within populations that are isolated from each other or improperly managed by humans due to inbreeding  and ZTG (FIS = 0.174) were higher than the values reported in a previous study , the p values for FIS in five populations  were nearly significant (p = 0.0004). These findings further suggest that these populations might be more likely to experience inbreeding.In addition, the FST observed from four populations  was generally lower than that observed between the other three breeds, indicating moderate to high genetic similarity among these breeds. The high genetic differences within the latter three populations compared to those within the four populations named above indicated a more complex genetic background of the domestication as well as less gene flow exchange between these breeds. This result was consistent with that obtained for phylogenetic network clustering.The pairwise FST and phylogenetic network described above. Particularly, from K = 2 to K = 3, three populations  were consistently separated, becoming an independent cluster. In addition, the other four goat breeds  were increasingly complex with an increasing K‐value reaching 4. A previous study reported that FQG showed the largest difference from Guishan goat and Maguan hornless goat (MGS) and the lowest genetic divergence from LHG and Yunling goat (YLG) using mtDNA variants  under positive selection. The domestic and wild animals were clustered according to their geographic locations and breeding and management histories by using microsatellites (Granevitze et al., 5In the present study, we estimated the diversity and population structure of 175 Yunnan goats from seven indigenous populations using 20 microsatellite markers. The results indicated that although these goats showed high diversity within the populations, the risk of inbreeding still existed. Second, the two‐population structures clustering from seven goats could be caused by geographical, economic, and cultural characteristics. Finally, we recommend removing CSRD247 and ILSTS005 loci from future studies on microsatellite evaluation system of goats, due to possible positive selection.None declared.YFH, GXE, and QHH, participated in the experimental design and wrote the manuscript; YJZ, MXC, YHM, LZ performed the laboratory experiment and carried out the bioinformatics data analysis; GXE have read and approved the final manuscript. Click here for additional data file.


Arabidopsis lyrata to investigate whether signatures of balancing selection can be detected based on genomic smoothing of Restriction Associated DNA sequencing (RAD-seq) data. We compared how different sampling approaches (both within and between subspecies) and different background levels of polymorphism (inbreeding or outcrossing populations) affected the ability to detect genomic regions showing key signatures of balancing selection, specifically elevated polymorphism, reduced differentiation and shifts towards intermediate allele frequencies. We then tested whether candidate genes associated with disease resistance  were detected more frequently in these regions compared to other regions of the genome.Genome scans based on outlier analyses have revolutionized detection of genes involved in adaptive processes, but reports of some forms of selection, such as balancing selection, are still limited. It is unclear whether high throughput genotyping approaches for identification of single nucleotide polymorphisms have sufficient power to detect modes of selection expected to result in reduced genetic differentiation among populations. In this study, we used R-gene analogs predicted to be under pathogen-mediated selection than regions of non-elevated polymorphism, and that many of these also showed evidence for an intermediate site-frequency spectrum based on Tajima’s D. However, we found few genomic regions that showed both elevated polymorphism and reduced FST among populations, despite strong background levels of genetic differentiation among populations. This suggests either insufficient power to detect the reduced population structure predicted for genes under balancing selection using sparsely distributed RAD markers, or that other forms of diversifying selection are more common for the R-gene analogs tested.We found that genomic regions showing elevated polymorphism contained a significantly higher density of Genome scans based on a small number of individuals sampled from a wide range of populations were sufficient to confirm the relative scarcity of signatures of balancing selection across the genome, but also identified new potential disease resistance candidates within genomic regions showing signatures of balancing selection that would be strong candidates for further sequencing efforts.The online version of this article (10.1186/s12864-018-4806-7) contains supplementary material, which is available to authorized users. High throughput sequencing and associated genotyping methods have revolutionized population genomic studies of population structure and selection and been applied to a wide range of species . Such apArabidopsis ),A. thaliana coding sequences (TAIR10.29) revealed four RAD loci annotated as NLR genes when allowing for up to 50% missing data, but only two using 0% missing data  at individual RAD loci we then identified individual outlier RAD loci with the 1% highest levels of polymorphism in the North American selfing (NA-S) group . Of these, 52 were annotated as NLR encoding genes present in our test panel , both with prior evidence for balancing selection  were shared between the analyses with 0% or < 50% missing data. Of these shared candidates, three genes were annotated as two 0 (RPS2: ) and At5ST, among populations relative to the genome-wide average, and elevated Tajima’s D relative to the genome-wide average. We used 35 outcrossing individuals of A. lyrata from 15 populations (originating from three countries) in Northern Europe (EU-N) and 32 individuals from eight outcrossing populations around the North American Great Lakes (NA-O), for which genetic structure among populations within each region is strong , but mostly due to the requirements for loci to be present in no fewer than 50% individuals in a sample group (see methods for details). Using loci present in fewer than 50% of individuals in a sampling group increased the density of loci, but also resulted in low sample sizes to estimate diversity and differentiation at individual loci, which we wanted to avoid.Balancing selection may also leave a signature of reduced genetic differentiation among populations, as well as shifts in the allele frequency spectrum towards intermediate allele frequencies , 23. Thee and/or π) for EU-N and NA-O samples separately using 300Kbp windows centred on polymorphic RAD loci. This is a broad window size, but given that there were polymorphic RAD loci on average every 11.595Kbp for NA-O samples and 13.519Kbp for EU-N samples, and Stacks estimates average window polymorphism with reduced weight on RAD loci further from the centre of the window, we are confident that the effective resolution of our windows was more localised than the total window size suggests. Generally, there was some overlap in the location of high diversity windows in the EU-N and NA-O samples  or positive Tajima’s D  within geographic regions that overlapped with smoothed windows of significantly elevated diversity in one or both sample groups. For the EU-N group, just five smoothed windows of significantly elevated diversity  showed FST values in the bottom 5% of windows  and At3g44630 .Fig. 6PST values) across both EU-N countries , another two were annotated as At1g63870 , and the final two were both annotated as At5g43470 . For NA-O samples, there were 182 overlapping windows of high diversity and FST (5.17Mbp in length) containing 791 genes, of which five were annotated as NLR encoding genes , two as At3g44400 .Interestingly, a high proportion of windows of significantly elevated diversity overlapped with windows of high genetic differentiation  and a fFinally, we identified smoothed windows showing significantly elevated diversity that overlapped with 120 Kbp sliding windows showing elevated Tajima’s D. To minimise the confounding effects of demographic history across countries, we identified the windows with the 5% highest values of Tajima’s D for each Northern European country separately  and for all NA-O samples combined. The average value across all SNPs for Northern European countries was consistently positive  was identified in all three Scandinavian (EU-N) countries, although to our knowledge no functional resistance allele has been described in A. thaliana  that also show elevated polymorphism and high Tajima’s D in A. thaliana . NLRs were again significantly overrepresented in windows of elevated diversity . In total 1847 windows showed significantly elevated HST between the two subspecies was 0.278  we confirmed previously observed patterns of genetic diversity and genetic structure across the subspecies of A. lyrata, but also revealed finer-scale spatial genetic structure within countries using only several individuals per population; (2) genomic regions showing elevated polymorphism contained a significantly higher number of disease resistance genes than other genomic windows; and (3) relatively few genomic regions showed both elevated diversity and reduced genetic differentiation among sample groups, a key signature distinguishing balancing from other forms of selection.In this study we demonstrate that high throughput genotyping of a small number of individuals across a large number of populations can identify signatures of different forms of selection. Specifically, we identified genome-wide signatures of balancing and diversifying selection within and between two subspecies of A. lyrata with the origin of diversity in Central Europe [A. l. lyrata populations around the Great Lakes than observed using microsatellites  similarly found evidence for high diversity and reduced FST at the stickleback Major Histocompatibility locus, a locus known to show signatures of balancing selection in a wide range of taxa. Using smoothing over multiple RAD loci can minimise the risk of identifying high diversity genomic regions based on an incorrectly assembled individual locus and thus increase the power to distinguish outliers. Additionally, given the importance of accurately calling SNPs for assessing variation in diversity, we used a 10× minimum coverage per locus for calling heterozygotes and used the rxstacks module from the Stacks pipeline (http://catchenlab.life.illinois.edu/stacks/comp-v1/rxstacks.php) to exclude and, where possible, correct likely sequencing errors from our RAD dataset. Finally, our study demonstrates the power of this smoothing approach even with relatively sparse marker density.Consistent with other studies, our results suggest that outlier analyses based on genomic smoothing are preferable to using single RAD loci when looking for genes showing elevated polymorphism. For example, using RAD-seq data and the Nucleotide binding site-leucine rich repeat proteins (NLRs), are a major class of Resistance Gene Analogs (RGA) known to be good at generating allelic diversity, and such diversity is important for recognizing a diverse pool of potential pathogen effectors [A. thaliana and around two-thirds of known R-genes in A. thaliana have a matching gene in A. lyrata. We found, as predicted, that the density of NLR loci in A. lyrata was significantly higher in genomic regions of elevated allelic diversity than other regions of the genome and that this result was consistent across different sample groups of A. lyrata  and in the same cluster as WRR4 (At1g56510) [. WRR4 confers broad spectrum resistance to the oomycete rust pathogen Albugo candida was in a genomic region of elevated diversity in all outcrossing groups in our study, and also shows elevated diversity in both A. thaliana [Capsella sp. [A. l. lyrata from the Great Lakes region when compared to average nucleotide diversity across a conservative set of RAD loci present in all individuals [R-genes thought to be influenced by balancing selection were only present in genomic regions of significantly elevated diversity in one of the population groups; for example, two genes recognising Pseudomonas bacteria in the NA-O samples, RPM1 [RPS2 [An advantage of our broad sampling of ups Fig. . Furtherdopsidis , 67, andsistance , 68. Int1g56510) . WRR4 co4 At1g565 and in tella sp. . This loes, RPM1 , 70 and M1 [RPS2 , 71. ThiM1 [RPS2 . NeverthST. In any case, the relatively high density of individual markers, particularly in the more variable outcrossing sample groups (on average every 11.6Kbp or 13.5Kbp), means that our resolution with respect to individual genes was relatively high. For example, even for the NA-S samples, individual high diversity individual RAD loci could be identified in the vicinity (+/− 2500 bp) of annotated R-genes . Howevemator ØW . Thus, bST could represent the random fixation of diverged NLR alleles in the different subspecies by genetic drift, or selection maintaining diverged alleles in different geographic locations. Selection by distinct pathogen communities in different geographic locations could result in increased differentiation between geographic regions or populations, and also elevate diversity across sample groups at these loci [Puccinia graminis [RPP8, showed elevated polymorphism, FST and Tajima’s D across EU-N countries , as welgraminis . Howevergraminis . Here, wmorphism , 75 and morphism , 76. HowRPP8 homolog and a paralog of WRR4 were present in such regions, along with genes annotated as part of the RPP7 and RPP1 gene clusters . For example, a  cluster ), show ethaliana . Further rubella . Thus, a rubella . Our strA. lyrata. Our smoothed outlier analyses based on relaxed filtering of missing data demonstrated that high throughput genotyping approaches, such as RAD-seq, retain power to detect genes in regions of the genome showing signatures of different types of selection. We identified genomic regions of elevated polymorphism containing disease resistance candidates known to be influenced by balancing selection in A. thaliana. Furthermore, within regions showing classical signatures of balancing selection , we identified novel candidate disease resistance genes, which have not been previously described as balanced polymorphisms in other taxa. Interestingly, we identified relatively few signatures of classical balancing selection, specifically genomic regions showing both high diversity and reduced differentiation. While this could result from a lack of power to detect reduced FST with RAD markers, the high average differentiation between and within A. lyrata subspecies instead suggests that this mode of selection could be relatively rare, even for a priori candidates such as disease resistance loci. In fact, candidate disease resistance loci in A. lyrata were mostly located in regions showing both elevated polymorphism and elevated differentiation, suggesting that diversifying selection may play a more important role than expected in pathogen resistance evolution across broad geographic ranges. Overall, our study provides insight into the relative frequency of signatures of balancing and diversifying selection across the genome, but also identifies candidate genes that could be targeted with whole gene sequencing to further investigate these alternative modes of selection.By sampling a small number of individuals within populations across multiple spatial scales, we confirmed and extended previous predictions about both broad- and fine-scale phylogeographic differentiation in Arabidopsis lyrata ssp. lyrata Seeds collected from individual plants were sampled at 12 sites  across the North American Great Lakes region in the summer of 2011 . DNA was extracted following the protocol of the Qiagen DNeasy plant mini kit , from dried leaf tissue, disrupted using a Fastprep machine and Fastprep lysing matrix A tubes . DNA extractions from multiple leaves of an individual were pooled to obtain a minimum of 2 μg per individual (at least 10 ng/ul). DNA quantification and quality checks were performed using a Nanodrop ND1000 spectrophotometer and 2% agarose gel electrophoresis. Final quantifications were performed using high-sensitivity double-stranded DNA assay kits for the Qubit 2.0 Fluorometer .Pst1, which is not sensitive to methylation, and was predicted to produce 64,056 RAD loci across the 207 Mbp A. lyrata genome. Each individual was tagged using barcodes differing by at least 2 bp. Three Pst1 libraries for the 49 North American individually barcoded samples were optimized and sequenced using one lane of an Illumina HiSeq 2000 sequencer. The process was then repeated for the 42 European samples.DNA from the 91 individuals was sent to Edinburgh Genomics  for 100 bp paired-end Restriction Associated DNA sequencing. DNA was digested using Stacks program process_radtags [. A window that is 15% of the size of the read length is moved across each read and removes the read if the average quality score within the window drops below a minimum phred score of 10. The reads were trimmed to 92 bp to remove the ID tags. Using fastQC to inspect read quality after the above-described read filtering revealed that average read quality score showed a clear peak at 38 in all samples, and that the median base quality rarely falls below a quality score of 32 . Therefore, the reads were of high quality for use in further analyses.Raw 100 bp reads were demultiplexed using the individual barcodes. FastQC  was used to check read quality and to count total reads per individual. Reads were filtered to remove those with uncalled bases and those of low quality using the flags –c and –q in the _radtags . A windoA. lyrata ssp. lyrata reference genome [A. lyrata, ~ 197Mbp in length, using default parameter conditions . The reference-aligned reads were then processed by Stacks v1.32 [rxstacks to reduce the potential for sequencing errors to inflate diversity estimates. Specifically, this module removed a small number of assembled RAD loci (on average 167 per sample) with highly negative log-likelihoods that likely represent sequencing errors and removes erroneous SNP calls  were recovered in the catalog of all loci in all individuals. However, many of these loci are not present in all individuals. Approximately 51.7% (European samples) or 60.6% (North American samples) loci were assembled per individual , reducing to 40.7 and 42.5% after removing those loci with fewer than 10 reads per locus. The majority of loci were removed at the Nucleotide diversity was estimated as the average number of nucleotide differences for all pairwise comparisons of sequences within a regional group, averaged across RAD loci and divided by the length of the RAD sequence (92 bp), equivalent to the nucleotide diversity estimate of Nei (1987) . ExpecteWe then used those loci present in all 91 individuals to determine the degree of genetic structuring within and between regions. RaxML v8  was usedStacks were converted to alleles in Genepop format using the haplotypes.tsv Stacks file and a custom R script by Mark Ravinet (https://github.com/markravinet/haplotype_to_genepop). Using the R packages “adegenet” [ade4” [N = 37, using polymorphic loci present in all of those individuals), among populations within the three different Scandinavian countries , and across all North American Great Lakes samples (N = 49). For North American samples we also compared patterns of genetic structure inferred using RAD loci to genetic structure inferred using eight microsatellites  rather than SNPs for these analyses. RAD haplotypes identified by degenet” , 82 and ” [ade4”  locus alal. 2010 ).ST (Weir & Cockerham) values were estimated using the R program “diveRsity” [earth.dist function in the “fossil” package [MRM function in package “ecodist”; [Finally, we used RAD loci present in all individuals to estimate IBD relationships for regions with sufficient sampling of populations, specifically all eight North American outcrossing populations and the five populations in each of Norway, Sweden and Iceland. Pairwise FveRsity” , and geo package . Finallycodist”;  was usedWe used several complementary approaches to examine genome-wide patterns of polymorphism and divergence and help detect signatures of balancing selection, focusing analyses on three different subsets of samples from the two subspecies. The following sets of samples were defined:NA-S: We tested whether excesses of heterozygosity and diversity in genes under balancing selection can be detected against an overall low background level of polymorphism using individuals from five selfing populations of A. l. lyrata  using two sets of outcrossing populations sharing a recent demographic history and similar geographic coverage (area and distance among samples). For A. l. petraea we used samples from three Northern European countries . We also tested the consequence of this relaxed filtering (< 50% missing data vs 0% missing data) for the detection of candidate loci using the NA-S samples.He are calculated by the program Stacks, whereas Ho was estimated from Stacks output. Specifically, observed heterozygosity (Ho) was estimated as the proportion of heterozygous individuals at a RAD locus out of the total number of individuals genotyped at that locus. Nucleotide diversity (π) was estimated as the average number of nucleotide differences for all pairwise comparisons of sequences within the set of samples, divided by the length of the RAD sequence (92 bp), which is equivalent to the estimate of Nei (1987). Expected heterozygosity  was also estimated  for more direct comparison with Ho.For estimating observed heterozygosity, nucleotide diversity and expected heterozygosity, we used variation in RAD haplotypes (linked set of variants within each 92 bp RAD locus) rather than considering individual SNPs at RAD loci. This strategy was used because highly polymorphic genes might be expected to have multiple SNPs within a 100 bp region, so allelic diversity may be particularly high and would be missed just by using a SNP-based approach. Both π and Stacks [He, as described in Hohenlohe et al. (2010). Each smoothed window is defined by the value σ, where a window 6σ in length is centred on a polymorphic RAD locus. The width of the window was set for different sampling groups to encompass on average 30 RAD loci. The average diversity measure of RAD loci within this window is then weighted by distance to the RAD locus (3σ in each direction), so RAD loci in the centre of the window more strongly influence overall window polymorphism. Since observed heterozygosity would not be as meaningful across genes (i.e. because it is a binary rather than a quantitative trait), only π and He were compared using the smoothing approach. Bootstrap resampling  was used to test for windows showing significantly higher diversity than the genome-wide average , they were considered as a single genomic region of significantly elevated diversity for annotation. The number and ID of genes in regions of elevated diversity were then compared among the different sample groups  to look for shared candidate loci.To detect genomic regions showing high diversity, we adopted a smoothing algorithm implemented in Stacks  to generribed in ). WindowA. lyrata genes annotated as associated with disease resistance. This set included all annotated Nucleotide Binding Site-Leucine Rich Repeat (NLR) genes, plus some additional loci  were extracted from a downloaded gff file (A. lyrata_107_v1.0_gene_details.gff from Phytozome v107).To test the relative ability of each of the above strategies to detect regions under balancing selection, we focused on a test panel of We also looked for evidence of balancing selection  within this set of NLR genes in Brassicaceae species. In total 17 of these genes represented clear a priori candidates for being under balancing selection , 87–90, p-value indicated the proportion of simulated differences that were greater than the observed difference. For comparison to the NLR genes, we used a set of Leucine Rich Receptor- Receptor-like kinases (LRR-RLKs), which are not expected to be at higher frequency in regions of elevated diversity [A. thaliana [A. lyrata genes annotated as these loci, resulting in 253 genes present in the A. lyrata genome assembly.We used a randomisation test to test the prediction that the density of NLR loci is higher in windows of significantly elevated diversity than outside these windows. The randomisation test estimated whether the average number of NLR genes per smoothed diversity window (+/− 1 x σ either side of each polymorphic locus) was significantly greater in windows of significantly elevated diversity compared to windows of non-significantly elevated diversity. Windows were labelled as “high diversity” or “not high diversity”, then this label was randomly permuted (without replacement) and the difference in density of NLR genes between the two categories recalculated. This was repeated 1000 times to produce a null distribution of differences to which the observed difference is compared. The iversity . We usedthaliana  and thenHe and Ho  samples, we looked for candidate genes in regions of significantly elevated diversity (both nucleotide diversity and expected heterozygosity), initially based on single outliers and then based on smoothing across multiple RAD loci. The single outlier approach involved identifying loci with the highest 1% values of π, He to identify high diversity genomic regions, but also used evidence for balancing selection based on reduced population differentiation (FST) and an intermediate site frequency spectrum (Tajima’s D). These analyses were based on RAD loci present in a minimum of 50% of individuals in a sample group (< 50% missing data). For the weighted smoothing analysis, window size was adjusted to contain about 30 RAD loci, using a σ value of 60Kbp for both EU-N and NA-O sample groups . Regions of significantly elevated diversity were identified in both groups separately and annotated NLR genes identified.For North American outcrossing and Northern European samples we focused on elevated π and ST) or an intermediate site frequency spectrum  within each of the NA-O and EU-N sample sets. FST was calculated in Stacks using RAD haplotypes and AMOVA-based FST estimates [ST was estimated within smoothed windows of identical size to the smoothed diversity estimates. We calculated pairwise FST among sample groups clearly separated in the RaXML tree, specifically among the three EU-N countries and among three clusters of the NA-O populations  whose genomic position overlapped with regions of significantly elevated diversity were identified.We then identified genomic regions of elevated diversity that also overlapped with windows of reduced population differentiation  in a sliding window analysis using the R package “PopGenome” [A. lyrata NLR genes in these overlapping regions. As D can be inflated by hidden genetic structure, these analyses were performed separately for each EU-N country in turn  and all NA-O samples together. NA-O samples were pooled as population divergence within the Great Lakes region was comparable to that observed within each Scandinavian country  and there was no option to weight loci based on distance to the centre of the window.Tajima’s D could not be calculated using pGenome” . Windowstry Fig. . In contA. lyrata subspecies. Windows of significantly elevated diversity across all outcrossing (All-O) samples and FST between subspecies were identified as described above, but using a reduced window size of 50Kbp due to the higher RAD marker density across this sample set. Overlap between elevated diversity and reduced FST windows were then examined for the presence of A. lyrata NLR genes.Finally, we compared populations of the strongly diverged Additional file 1:Tables S1-S7 and supplementary Figures S1-S12. (DOCX 26587 kb)Contains supplementary methods and results, in addition to supplementary


Aedes albopictus is an invasive mosquito species that has spread globally and can transmit several arboviruses, including dengue, chikungunya and yellow fever. The species was first reported in Brazil in 1986 and since then has been found in 24 of the 27 Brazilian states, often in peri-urban environments close to highly urbanized areas. To date, population genetics of this important mosquito in areas in the city of São Paulo has not been investigated. In this study, we used 12 microsatellite loci to investigate the microgeographic population genetics of Ae. albopictus, which is present throughout the city of São Paulo. All the analyses revealed structuring of the populations studied, divided into two groups with restricted gene flow between them and without evidence of isolation by distance. We propose two hypotheses to explain the results: (i) low dispersal capability—limited gene flow between populations is due to the low dispersal capability inherent to Ae. albopictus; and (ii) multiple introductions—the structure identified here results from multiple introductions, which led to different dispersal patterns within the city and more genetic heterogeneity. The ability of Ae. albopictus to invade new areas and expand may explain why these mosquito populations appear to be well established and thriving in the city of São Paulo. There are currently more humans living in urban areas than ever in the history of civilization . As a coInhabiting urban areas is challenging for most species. However, invasive species are more likely to thrive in such environments than native species . FurtherAedes (Stegomyia) albopictus (Skuse), an aggressive species well adapted to urban environments. This mosquito can breed in artificial containers  and blood feed on human hosts, completing its entire life cycle in urban environments [Mosquito species that have adapted to urban environments can not only be a source of nuisance but also transmit diseases, as in the case of ronments –9.Aedes albopictus is native to Asia and has spread to all continents except Antarctica, most likely because of its close relationship with humans [Ae. albopictus to colonize new areas by being inadvertently dispersed in used tires imported from other countries [h humans ,11. As th humans ,13. Thisountries ,15. The ountries –18 and rountries –21.Aedes albopictus was established in Brazil in 1986 and since then has spread to most of the country, where it is often found in suburban areas with higher vegetation coverage [Ae. albopictus domiciliation in a densely populated slum in Rio de Janeiro. The presence of the species in such an environment could indicate its increased adaptation to areas undergoing anthropogenic changes in Brazil [coverage ,23. Howen Brazil .Aedes albopictus is a competent vector for several arboviruses, including dengue (DENV), chikungunya (CHIKV), Zika (ZIKV) and yellow fever (YFV) [er (YFV) –30, and er (YFV) .Ae. albopictus in the state of Bahia, Brazil, in an active ZIKV transmission zone [Even though the species is not implicated in dengue transmission in Brazil, the DENV-1 serotype has been isolated from its larvae . In addiion zone . It is aion zone ,34.Aedes aegypti, Aedes fluviatilis, Culex nigripalpus, and Culex quinquefasciatus in the city of São Paulo, Brazil [Ae. albopictus in São Paulo could lead to a better understanding of how anthropogenic changes to the environment in developing countries such as Brazil are modulating the population structure of this species and the implications of this for vector-borne disease transmission patterns [Urbanization processes are often responsible for driving the genetic diversity within urban populations of mosquitoes ,6. This , Brazil –38. São , Brazil . Thus, ipatterns ,40.Ae. albopictus have been carried out as this species continues to spread worldwide [Ae. albopictus in Manaus, Brazil, found that populations of this species have undergone a recent expansion following a founder effect [Population genetic studies of orldwide ,40–43. Ar effect . Moreover effect .Ae. albopictus in São Paulo [Ae. albopictus throughout the city of São Paulo.Microsatellite markers are highly polymorphic genetic markers widely used in mosquito population genetics studies –48. Prevão Paulo , we hypoAedes albopictus samples were collected from 10 urban parks  in different areas of the city of São Paulo  following the manufacturer’s protocol. Twelve microsatellite primers labeled with a fluorescent dye  and 1μL (~1ng) of purified DNA were used in the PCR reactions, which were performed as described before  in an E6HO), expected heterozygosity (HE), deviations from Hardy-Weinberg equilibrium (HWE) and inbreeding coefficient (FIS) were calculated with the diveRsity v3.4.0 package in R [http://genepop.curtin.edu.au/) [To assess the validity of the microsatellite markers, the number of alleles per locus per population, observed heterozygosity  , and HP-edu.au/)  was usedFST), the same software was used to estimate values of FST unbiased by the presence of null alleles. Mantel test was used to compare both FST values (biased and unbiased) with ade4 package in R [Null-allele frequency was assessed for each locus for each population using FreeNA . In ordeage in R ,58 usingFST (fixation index) and the heterozygosity-based estimator G”ST for measure population structure of all populations, as proposed by Meirmans and Hedrick [FST values was generated using EDENetworks (v2.18) [FST/(1-FST)) and geographic distance in kilometers was calculated with ade4 package in R [To compute pairwise values of  Hedrick , the div Hedrick  (v3.4.0) (v2.18) . Analysi (v2.18)  to detecage in R ,58 usingA Bayesian model-based clustering analysis in STRUCTURE (v2.3.3) was used to infer population structure . SimulatFST and G”ST) for all populations. A cross-validation analysis was performed in Adegenet using 30 replicates to determine the number of PCs to be retained in the DAPC, the analysis suggested 60 as the number of PCs associated with the lowest root mean squared error.Discriminant analysis of principal components (DAPC) was used to further assess genetic structure between populations. DAPC was implemented in R using Adegenet package ,64 for tHE (expected heterozygosity) greater than HO (observed heterozygosity) in 89% of the conducted tests, indicating deviations from the HWE. Average FIS (inbreeding coefficient) was 0.57072 (P<0.05). However, these results could have been produced by chance, as after Bonferroni correction no loci were linked together across the tested populations.Hardy-Weinberg equilibrium (HWE) tests conducted for each locus in each population showed  0.57072 . After 6FST values biased and unbiased by the presence of null alleles .Allelic richness ranged from 1 (NBC) to 13.34 (BMX), and average private allelic richness was low, varying from 0.12 (SHG) to 1.95 (BMX) . EstimatFST) and the heterozygosity-based estimator (G”ST) revealed similar results , indicating a high degree of structuring. The lowest FST values were observed between samples collected at GRP, IND, SHG, PRV, and IBI and ranged from 0.0047 to 0.0396, suggesting that these populations are very similar to each other and different from the others. The same was observed for G”ST, which ranged from 0.0525 to 0.1494 for the same populations. Although the values of G”ST were higher than those of FST, the relationship between Ae. albopictus populations were similar for both estimators.Pairwise estimates of the fixation index ) and geographic distance (P = 0.5933).AMOVA showed that 90.80% of the variance was estimated to be within populations . Mantel distance , indicatThe results of the Bayesian cluster analysis and subsequent application of the Evanno method were used to identify the most likely number of genetic groups, which was two according to the ΔK estimator . The anaFST and G”ST, and the genetic network.DAPC explained 94% of the variance in the data, which was capable of partitioning the genetic variation in K = 2 and K = 3 similarly to STRUCTURE analysis . The relAedes albopictus, a highly anthropophilic species whose dispersal around the world is known to have been mediated by humans [Ae. albopictus [Ae. albopictus at the microscale level, considering the distribution of populations of this species in a city.y humans , has a vy humans ,65. Althbopictus ,66,67, tbopictus . The preFST and G”ST estimators revealed the same relationships between the populations, indicating a high level of structuring between the two groups. DAPC and STRUCTURE analysis revealed high genetic diversity between the two population groups and high similarities within the groups. Furthermore, no evidence of IBD was found for the populations, indicating that the source of genetic variation detected could be other than geographic distance.Our findings suggest all analyses showing the same genetic structuring pattern between the populations: two distinct groups of populations with limited gene flow between them. Both the Ae. albopictus populations, suggesting that the genetic variation between populations probably occurs at a low hierarchical level. Similar results were previously found for native and invasive Ae. albopictus [Ae. albopictus populations [Our findings also revealed high levels of homozygosis, high values estimated by the inbreeding coefficient, deviations from the HWE and high molecular variability within the bopictus ,68, indibopictus . Previouulations ,66.Ae. albopictus populations are probably undergoing in the city of São Paulo. Processes of population expansion following founder effects are particularly important since they are known for leading to deviations in the HWE. Moreover, although the null alleles probabilities for some loci were considered high (>40%), it did not influence the final results, and removing loci with high probabilities did not enhance the results. The presence of null alleles is common in studies using microsatellite markers and are not believed to invalidate the results [Ae. fluviatilis and Ae. aegypti collected in the same region [The deviations from HWE found in this study were consistent with the pressures  results ,69,70. Se region ,36. Moree region ,68,71. Te region .Ae. albopictus [Ae. albopictus populations worldwide showed the Brazilian populations to be a monophyletic group. The authors suggested that the samples analyzed were derived from a single Ae. albopictus invasion by a native population from South-East Asia [Therefore, we believe that there are two hypotheses to explain the pattern of genetic structure in the populations studied here. The first one of the probable causes of the genetic structuring is the limited gene flow between populations due to the low dispersal capability inherent to bopictus . A studyast Asia . HoweverAe. albopictus populations may have been chaotic and that this may have played a role in maintaining genetic diversity in invasive populations around the world [Ae. albopictus probably occurred. Under this hypothesis, the population structure found in this study is due to multiple introductions of Ae. albopictus in the city of São Paulo, leading to different dispersal patterns within the city and more genetic heterogeneity. Manni et al. [Previous studies have suggested that the dispersal pattern of he world . Our seci et al. , postulaAe. albopictus, substantially impacting its population dynamics and genetic diversity patterns [Ae. albopictus. In our opinion, the two hypotheses suggested here could be explored by future studies by focusing on broader geographic scales and also employing longitudinal experimental designs. This approach would make it possible to identify trends of founder effect and population expansion, and movement and subsequent colonization of new areas by Ae. albopictus.There are several mechanisms able to increase or decrease the genetic variation in a given population . Invadinpatterns . At thisAe. albopictus populations have reduced gene flow between densely urbanized areas and rural areas [Ae. aegypti in the city of São Paulo [Ae. fluviatilis and Cx. nigripalpus [Previous studies suggested that al areas ,45. A sião Paulo . Howeverripalpus ,38. ThisAe. aegypti had been eradicated from Brazil, it reinfested the country in the 1970s [Ae. albopictus as this mosquito was first recorded in Brazil in 1986 and approximately 30 years later had spread to 24 of the 27 Brazilian states [Although the invasive mosquito he 1970s ,76. The he 1970s ,77, and he 1970s . The samn states .Aedes albopictus, which is widespread in Brazil, probably entered the country through the port of Espírito Santo and was then passively dispersed in cargo transported on highways, as it was first reported on the Rio-São Paulo highway in 1986 [Ae. albopictus to invade new areas and expand explains why these mosquito populations appear to be well established and thriving in the city of São Paulo. Human movements throughout the city and the lack of large-scale mosquito control measures in Brazil have probably favored the dispersal and establishment of this species in the city. These factors, together with the epidemiological importance of this mosquito, highlight the need for further studies of the population genetics of this species in Brazil focusing on broader geographic scales and longitudinal experimental designs. Aedes albopictus populations are genetically diverse and can diverge in their ecology and behavior, affecting their resistance to insecticides and vector capacity, among other factors. in 1986 ,22. Alth in 1986 ,24. The S1 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableHO (Observed heterozygosity), HE (Expected heterozygosity), HWE (Hardy-Weinberg Equilibrium) and FIS (Inbreeding Coefficient).N , A , Ar (Allele richness), Pr , (DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 TableAbove the diagonal: geographic distances between populations in kilometers.(DOCX)Click here for additional data file.


Pulsatilla cernua, a continental‐grassland relict, were investigated using variations in chloroplast DNA (cpDNA) and microsatellites of nuclear DNA. In the analyses of three cpDNA regions, 17 haplotypes were found in 24 populations of P. cernua from Japan, Korea, and Russia. Although the route and time of migration between the continent of Asia and Japan could not be well resolved, the cpDNA haplotype network suggests the existence of several ancient lineages in Japan and a recent secondary migration from Japan to the continent. Microsatellite analyses did not indicate genetic structure among the Japanese populations, indicating the existence of gene flow across the distribution area until recently. These results indicate that the present fragmentation of P. cernua in Japan may reflect a rapid, recent reduction from a previously large, continuous distribution.The genetic diversity and structure of  GlThe Japanese Archipelago extends along a 3,000 km line from the northeast to the southwest, covering a wide range of climatic zones, from subarctic to subtropical. The distribution ranges of most plants in the Japanese Archipelago have repeatedly shifted following climatic changes during the Quaternary  and cool temperate species .In the Japanese flora, there is a group of temperate grassland plants that are distributed in northeastern China, Far East Russia, the Korean Peninsula, and Japan. Koizumi   named tToday, natural temperate grasslands in Japan are restricted to places influenced by periodic disturbances, such as fires, floods, and volcanic eruptions. The outlines of their distribution at present occupy a rather large area in Japan, but most Mansen plants are found only in a few small isolated populations. Warming temperatures after the last glacial period probably caused habitat fragmentation due to encroaching forests Suka, .Pulsatilla cernua (Thunb.) Bercht. et C. Presl., a Mansen plant  were selected for further analysis , or 1 min at 58°C (trnH‐trnK), and 3 min at 72°C, followed by 5 min at 72°C, using a DNA thermal cycler . The PCR products were purified with the Illustra Enzymatic PCR and Sequencing Clean‐up Kit  to remove excess primers and dNTPs. Purified DNA fragments were used as templates for sequencing reactions, using the ABI Big Dye Terminator Cycle Sequencing Kit (Applied Biosystems), and were sequenced by an ABI automated sequencer. The obtained sequences were aligned using CLC Main Workbench 7.6.4 (Qiagen) and MEGA 6 , which amplified constantly and were polymorphic, were chosen for further analysis  of 2.3.2AN), total number of alleles (AT), observed (OH) and expected (EH) heterozygosities   were used for the microsatellite analyses. Although eight individuals per population is a comparatively low sample size to estimate genetic structure, the mean number of alleles  simulation. STRUCTURE was run 10 times for K = 1 to K = 24 clusters, and the length of the burn‐in was set to 100,000, followed by 300,000 MCMC iterations. The most likely K value was determined by calculating ∆K  using DnaSP v6 , western Japan (pops. 12–20), Korea (pop. 21), and Russia (pops. 22–24), principal component analysis (PCA) was applied to microsatellite data. The significance of differences in genetic diversity between eastern Japan (pops. 1–11) and western Japan (pops. 12–20), and between Japan (pops. 1–20) and Russia (pops. 22–24) was evaluated by the 2.3.4We calculated the correlation coefficient between genetic distance and geographic distance for all the populations based on microsatellite data. The correlation coefficient was also calculated for the populations excluding the Russian populations, to avoid the influence of geographic barrier that is formed by the Sea of Japan. Geographic distance was transformed to Ln(1+GGD)). The Mantel permutation procedure Mantel,  was adop2.3.5We calculated the correlation coefficient between genetic diversity and geographic latitude/longitude for Japanese populations based on microsatellite data.33.1P. cernua. Four haplotypes  were found in multiple populations . Thus, the six loci were sufficiently independent to apply Bayesian clustering using the admixture, instead of the linkage model , nor between the populations of Japan and Russia .The 3.3K = 2. Based on K = 2, we recognized two groups: red and green .STRUCTURE analyses showed that the most likely number of clusters using Bayesian cluster analysis was Figure 3.4stF) between populations is ranged from 0.040 to 0.442 with an average 0.158 (Table R2 = 0.126 (p = 0.0001) and for the populations excluding the Russian populations was R2 = 0.095 (p = 0.0001).Figure 3.5AN , latitude and AT , latitude and EH , longitude and AN (R2 = 0.0936), longitude and AT (R2 = 0.0828), and longitude and EH . However, all of the correlations were not significant.Figure 44.1AN was 1.52 (range: 1.2–2.1), and the mean EH was 0.256 (range: 0.092–0.458) for the six microsatellite loci from the 24 populations (Table P. patens (L.) Mill., a widely distributed circumboreal species, exhibited higher genetic diversity: AN = 3.74 and EH = 0.541  H. Ohashi & H. Nakai (Caryophyllaceae)   in the Japanese Red Data Book  and larger populations than A. palustris . In P. cernua, we found more than a few hundred plants in several populations, but they had lower genetic diversity than the other abovementioned species: populations 3 , 7 , and 9 . Although population size is very important to consider genetic diversity, data on population size were not available in this study.The mean K = 2. However, there was no significant difference between the two groups based on the haplotype sequences . The result of PCA analysis on microsatellite also did not support two groups  indicates gene flow between them. It may suggest haplotype polymorphism within a population.Haplotype A was located at the center of the haplotype network, while the other Japanese haplotypes were radially arranged, with distances of 1–7 mutations  were found in three populations of Primorsky, but they were distantly related to each other. Although these haplotypes were located at derived positions from haplotype A in the network Figure b, the exHaplotype E, recorded from the population of Cheju Island, Korea, has a linear relationship with haplotypes A and D in the network Figure b. It cou4.3In general, the Mansen plants, namely continental‐grassland relicts in Japan, are considered to have originated in the temperate grasslands on the continent and migrated to Japan, eastward via the Korean Peninsula, under the cold and dry climate of the glacial age Hotta, . The hapP. cernua in Japan, so that multiple distribution range shifts before the last glacial period must be taken into consideration. To elucidate the migration route and the range fluctuation of P. cernua, a Mansen plant, it is necessary to do further investigation using more genetic markers and samples from the continent.In Japan, the large distribution area of haplotype A and the existence of its satellite haplotypes  imply that the rapid expansion of haplotype A happened rather recently, followed by diversification of the satellites. It is congruent with the consideration that grassland expanded on the Japanese archipelago most largely in the last glacier period Suka, . In addiNone declared.A.S. conceived the ideas; A.T., A.E.K, Z.V.K., N.F., and A.S. made fieldworks and collected the data; and A.S., A.T., and H.I. analyzed the data; and A.S. led the writing.


Aedes albopictus, is one of the 100 worst invasive species in the world and the vector for several arboviruses including dengue, Zika and chikungunya viruses. Understanding the population spatial genetic structure, migration, and gene flow of vector species is critical to effectively preventing and controlling vector-borne diseases. Little is known about the population structure and genetic differentiation of native Ae. albopictus in China. The aim of this study was to examine the patterns of the spatial genetic structures of native Ae. albopictus populations, and their relationship to dengue incidence, on a large geographical scale.The Asian tiger mosquito, Ae. albopictus mosquitoes were collected by human landing catch (HLC) or human-bait sweep-net collections in 34 localities across China. Thirteen microsatellite markers were used to examine the patterns of genetic diversity, population structure, and gene flow among native Ae. albopictus populations. The correlation between population genetic indices and dengue incidence was also examined.During 2016–2018, adult female FST) revealed highly polymorphic markers, high genetic diversity, and low population genetic differentiation. In addition, Bayesian analysis of population structure showed two distinct genetic groups in southern-western and eastern-central-northern China. The Mantel test indicated a positive correlation between genetic distance and geographical distance . STRUCTURE analysis, PCoA and GLS interpolation analysis indicated that Ae. albopictus populations in China were regionally clustered. Gene flow and relatedness estimates were generally high between populations. We observed no correlation between population genetic indices of microsatellite loci in Ae. albopictus populations and dengue incidence.A total of 153 distinct alleles were identified at the 13 microsatellite loci in the tested populations. All loci were polymorphic, with the number of distinct alleles ranging from eight to sixteen. Genetic parameters such as PIC, heterozygosity, allelic richness and fixation index (Ae. albopictus. This may represent a potential risk of rapid spread of mosquito-borne diseases. The spatial genetic structure, coupled with the association between genetic indices and dengue incidence, may have important implications for understanding the epidemiology, prevention, and control of vector-borne diseases.Strong gene flow probably assisted by human activities inhibited population differentiation and promoted genetic diversity among populations of  Aedes (Stegomyia) albopictus  originated in Southeast Asia and spread to several islands in the Pacific and the Indian Oceans during the 17th and 18th centuries [Ae. albopictus [s Skuse, 894 origienturies , the USAenturies , 4, Fijienturies  and Nigeenturies . Global Ae. albopictus poses serious public health concerns for arbovirus-related disease outbreaks. In China, dengue has been a threat for 40 years, since the first reported outbreak in 1978 [Aedes albopictus and Ae. aegypti are two important vector species responsible for dengue transmission in China. Aedes albopictus is the most predominant species and has been found in nearly one third of China [Ae. aegypti is limited to small areas of southern China, including Hainan, Guangdong, Guangxi and Yunnan provinces [Ae. aegypti was found only in two sites  of the 26 mosquito surveillance sites in China. The relative proportion of Ae. albopictus to Ae. aegypti was > 20:1 in the two sites during 2005–2015, while the proportion of Ae. albopictus to Ae. aegypti was approximately 1:2 in 2014 in Jinghong city, Yunnan Province [Aedes albopictus has been reported to be the sole mosquito vector for dengue transmission in Guangzhou, with no presence of Ae. aegypti identified over the past three decades [Ae. albopictus has contributed to the reemergence and wide spread of dengue [As a vector of over 20 arboviruses  and one  in 1978 . Local d in 1978 . Aedes aof China . This sprovinces , 16. Li rovinces  reportedProvince . Aedes af dengue . Vector f dengue .Ae. albopictus [Ae. albopictus have been isolated previously, and there are more than 50 microsatellites applied in population genetic studies of Ae. albopictus [Ae. albopictus population genetics.Molecular markers can provide abundant information that is critical to studying the sources and routes of vector invasions , 23. As bopictus , 26, 27.bopictus . Althougbopictus –30. In oAe. albopictus populations in China?; (ii) What are the patterns of colonization and dispersal (or gene flow) of Ae. albopictus in China?; (iii) Is there any association between genetic diversity indices and local dengue incidence? To address these questions, extensive mosquito samplings and a set of thirteen microsatellite loci were used in the study. The data gained from this study could provide useful information for understanding the epidemiology, prevention, and control of vector-borne diseases.The present study was designed to address the following questions: (i) What is the level of genetic diversity and population differentiation in and between Ae. albopictus mosquitoes were collected by human landing catch (HLC) or human-bait sweep-net collections in 34 locations in 19 provinces across northern and southern China, including Hainan Island  of the Public Health Science Data Center managed by the Chinese Center for Disease Control and Prevention. The 19 provinces include those with frequent dengue fever outbreaks in the past 30 years, including Guangdong, Guangxi, Yunnan, Zhejiang and Hainan, as well as provinces with dengue outbreaks in recent years, including Hubei, Hunan, Guizhou and Jiangxi. Other provinces have imported cases, including Shanxi, Shandong and Liaoning. The collected specimens were identified morphologically to Ae. albopictus, and samples were stored in 70% ethanol. Total genomic DNA was individually extracted using the Insect DNA Kit , following the manufacturer’s protocol.In each location, 8–12 households or collection points at 400–3000 m apart were selected randomly for adult mosquito collections to minimize sibling bias. Approximately 30 Aedes albopictus cryptic species identification was performed by DNA sequencing of the mitochondrial gene cytochrome c oxidase subunit 1 (cox1) for the samples collected in Guangxi Province, where the cryptic species have been detected previously [Wolbachia infection status of individual mosquitoes was examined by PCR amplification of Wolbachia ribosomal DNA using a previously published method [eviously . The Wold method .A set of thirteen microsatellite markers was used to examine the patterns of genetic diversity, population structure, and gene flow among the native mosquito populations. These markers, which were developed in previous studies, included 3 dinucleotide and 10 trinucleotide loci , 32. TheAe. albopictus populations. The coefficient of relationship, r ≥ 0.25 for LRM and r ≥ 0.5 for QGM was used to define a full sibling relationship , and a value of 0.125 < r < 0.25 for LRM and 0.25 < r < 0.5 for QGM indicates a half sibling (one shared parent). In order to reduce the siblings bias within population for analysis of genetic structure, we selected only one individual from each putative full-sibling group within any population.Pairwise genetic relatedness between individuals was examined by LRM estimator  and QGM Na), effective number of alleles (Ne), inbreeding coefficient (FIS), fixation index (FST), observed heterozygosity (Ho) and expected heterozygosity (He) using GenAlEx v.6.5 [Nm = (1/FST − 1)/4 [Na) for each population was calculated with a rarefaction method using Allelic Diversity Analyzer (version 1.0) [r) as well as R-squared were estimated using GenAlEx v.6.5.Genetic variation within each locality was estimated in terms of the average number of alleles (Ex v.6.5 . The numT − 1)/4 . PolymorT − 1)/4 . The posT − 1)/4 . To deteion 1.0) . Deviatiion 1.0) , 42. Anaion 1.0) . To deteion 1.0) , 45. Genion 1.0) . Resultsion 1.0) . A ManteGeographical population structure was evaluated using the Bayesian clustering method in STRUCTURE v.2.3 , which iP < 0.05 was set for all statistical tests, and the sequential Bonferroni correction [Dengue incidence was calculated as the number of cases per 100,000,000 people. Due to the high variation in the number of cases, the data were rescaled with a log-transformation using the equation Ln (µ), where µ is the number of cases per 100,000,000 people. Pearson’s correlation coefficient was used to analyze the correlation between dengue incidence after transformation and genetic indices, including allelic richness, private allelic richness, effective alleles, Shannon’s information index, observed heterozygosity and inbreeding coefficient. The correlation analysis was performed using SPSS version 22. A significance level at rrection  was usedAe. albopictus cryptic species was detected in the samples collected from Guangxi Province. The cox1 haplotype was identical with the sequences on GenBank . All the samples showed positive infection of Wolbachia with type A and/or type B. The majority of samples (> 93%) were infected with type A and type B together, only a few samples were infected with type A (5.1%) or type B (1.6%)  of the 34 Ae. albopictus populations with the highest proportion of kinship between Beijing and Shenyang. There were 559 pairs (0.107%) of half siblings and 68 pairs (0.013%) of full siblings among individual within populations, and 5882 pairs (1.125%) of half siblings and 82 pairs (0.016%) of full siblings among individuals between populations  to sixteen (ALB-TRI-6) with an average of 11.769 per locus (Table P < 0.05), where 146 of these significant departures indicated heterozygosity deficits  to 9.000 (LS), with an average of 6.912, and the allelic richness ranged from 4.327 (SY) to 7.561 (LS), with an average of 5.995  to 0.775 , and the He values for each locus ranged from 0.456  to 0.824 (ALB-TRI-6)  to 0.690 (SZ), and the He values for each location ranged from 0.619 (SY) to 0.763 (LS)  FST values showing significant genetic differentiation and one losing the significance after Bonferroni correction  between the genetic distance (estimated as FST/(1 − FST)) and geographical distance (estimated as Ln (km)) between populations  and private allelic richness  showed a positive correlation with dengue incidence after log-transformations. However, the significance was lost after the Bonferroni correction for multiple testing . Shannon’s information index , effective alleles , observed heterozygosity  and inbreeding coefficient  showed no statistically significant correlation to dengue incidence after log transformations.In order to explore the association between genetic structure and vector-borne disease, we conducted Pearsonʼs correlation analysis of six genetic indices and annual dengue incidence from 2011 to 2015 in different provinces  gene of 140 Ae. albopictus from 14 populations in southern China, and Zhang et al. [cox1 of 119 Ae. albopictus from 17 populations in China. The results of these studies showed low genetic diversity and shallow genetic differentiation between some of the study populations. In the present study we included many new study sites and populations, such as those in the northern , western , and central areas , etc. The 34 collecting sites were widely distributed, providing comprehensive information on the population structure of Ae. albopictus throughout China. The correlation of average allele richness and sample size showed that when sample size < 15, allele richness increased rapidly as sample size increased, whereas it increased only slightly when sample size > 25. The number of samples in most populations was within the optimum range (25–30) [Ae. albopictus. The period in which the climate is suitable for mosquito survival is longer in southern subtropical areas than in northern areas. The relatively low temperatures and dry climate in the north may not be suitable for mosquito survival, reproduction, and dispersal, resulting in lower allele richness and population diversity in northern populations [Few studies have reported the population structure and genetic diversity of ing size , 55. Foring size  sequence (25–30) . The meaulations , 58.A major drawback of using microsatellite markers in population genetic studies is the potential impact of null alleles, such as reducing population genetic diversity and increasing genetic differentiation among populations , 60. MicFST-values in all pairwise populations were not high, but most were significantly different, indicating genetic differentiation between populations. The low genetic distance and pairwise FST may be related to the fact that most of the study sites are central cities in their provinces and transportation between them is convenient. Jinghong, a busy tourist destination close to the Southeast Asian countries, connects to many cities via highways and airways but has no trains or high-speed rail, which explains the relatively high pairwise FST between Jinghong and other cities. Low FST-values with no significant difference may be attributed to the close distance, convenient transportation, high traffic, and similar environmental conditions between populations [Ae. albopictus, and most populations in China have been stable for a long time [Nm > 1 indicates that a population is sufficient to prevent the occurrence of genetic differentiation [Ae. albopictus across the country. Extensive mosquito dispersal, probably aided by human transportation between these regions, also helps explain the low differentiation and the possible clustering between different regions.Our results showed that ulations . China iong time . Nm > 1 ntiation . Our resAe. aegypti populations [An. darlingi populations, and the conventional approaches based on microsatellites may underestimate overall genetic distances in closely related vector populations [FST or the degree of differentiation in the present study may be smaller for microsatellites than if SNPs have been used. Therefore, we might overestimate the gene flow between populations through the analysis of microsatellites. Mitochondrial DNA has been widely used for the study of molecular taxonomy, phylogenetic relationships and population genetics in mosquitoes [An. sinensis populations [An. arabiensis populations [c oxidase subunit 1 (cox1) gene to analyze population genetics of Ae. albopictus in southern China. We also have collected Ae. albopictus population from a different village in Wuzhou, but we did not find any individual belonging to a cryptic species by cox1 sequencing. One of the possible reasons might be due to location-specific or seasonal abundance features of the cryptic species.There is some limitation for microsatellites compared to SNPs, the third generation DNA markers. Weaker separation between populations was usually obtained with microsatellites compared to SNPs. A total of 934 SNPs showed stronger power in distinguishing closely related individuals at a small spatial scale than 8 microsatellites in ulations . A totalulations . The paisquitoes –77. Howeulations . No geneulations . Guo et ulations  discoverAedes aegypti population from French Polynesia was more susceptible to infection and had higher ability to transmit DENV-1 than Ae. aegypti population from New Caledonia in the same experimental environment [Ae. albopictus population in China. The other one might be that dengue incidence is associated with other genetic indices or other genetic markers rather than the six indices from 13 microsatellites in this study. One genetic index, the inbreeding coefficient (FIS) might be expected to show significant positive correlation to dengue incidence, due to the vertical transmission of dengue virus to mosquito offspring [Ae. aegypti mosquitoes from some different areas [Ae. aegypti mosquitoes, and in subsequent generations it was found to be steady until at least the 7th generation through the inbreeding of each generation [Ae. aegypti populations [Wolbachia existing in Ae. albopictus, not in Ae. aegypti naturally, has a blocking effect on the vertical transmission of dengue virus [Wolbachia inhibiting dengue virus is unclear, the cytoplasmic incompatibility (CI) induced by Wolbachia can reduce the mosquito populations [Wolbachia can induce density-dependent inhibition to dengue virus in mosquito cells [Wolbachia have been applied in the control of mosquitoes and mosquito-borne diseases [The spread of dengue fever has been affected not only by the climate  , 81, butironment . The genironment . The sixffspring , 87. Thint areas –90. The neration . We infeulations . Howeverue virus , 93. Altulations , and Wolto cells . At presdiseases , 97. TheAe. albopictus but also the correlation of genetic indices with dengue incidence. Our results may have implications for predicting future dengue outbreaks and understanding the epidemiology, prevention and control of vector-borne diseases. Strong gene flow probably assisted by human activities inhibited population differentiation and promoted genetic diversity among Ae. albopictus populations. This may represent a potential risk of rapid spread of mosquito-borne diseases. The data collected in this study, combined with other related factors such as climate, rainfall and human activities, will be valuable for vector control efforts as well as epidemiological prediction and modeling of the incidence and spread of vector-borne diseases.This study reported not only the spatial genetic structure of Additional file 1: Table S1. The Wolbachia infection status in populations.Additional file 2: Table S2. The pairwise genetic relatedness between individuals.Additional file 3: Table S3. Analysis of Hardy–Weinberg equilibrium.Additional file 4: Table S4. Analysis of linkage disequilibrium.Additional file 5: Table S5. Genetic indices of 34 populations.Additional file 6: Figure S1. Average allele richness of microsatellite loci in 34 populations.Additional file 7: Figure S2. Scatter plots of Log probability of the data (Left) and Delta K (Right) for Ae. albopictus populations. Delta K plots are based on the rate of change in the log probability of the data between successive K values. a All populations. b 18 populations in southern and western areas. c 16 populations in central, eastern, central northern, and northern areas.Additional file 8: Table S6.FST and Nm between 34 populations.Additional file 9: Table S7. Genetic distance and geographical distance between 34 populations.


Diatraea saccharalis, is one of the most important pests of sugarcane and maize crops in the Western Hemisphere. The pest is widespread throughout South and Central America, the Caribbean region and the southern United States. One of the most intriguing features of D. saccharalis population dynamics is the high rate of range expansion reported in recent years. To shed light on the history of colonization of D. saccharalis, we investigated the genetic structure and diversity in American populations using single nucleotide polymorphism (SNPs) markers throughout the genome and sequences of the mitochondrial gene cytochrome oxidase (COI). Our primary goal was to propose possible dispersal routes from the putative center of origin that can explain the spatial pattern of genetic diversity. Our findings showed a clear correspondence between genetic structure and the geographical distributions of this pest insect on the American continents. The clustering analyses indicated three distinct groups: one composed of Brazilian populations, a second group composed of populations from El Salvador, Mexico, Texas and Louisiana and a third group composed of the Florida population. The predicted time of divergence predates the agriculture expansion period, but the pattern of distribution of haplotype diversity suggests that human-mediated movement was most likely the factor responsible for the widespread distribution in the Americas. The study of the early history of D. saccharalis promotes a better understanding of range expansion, the history of invasion, and demographic patterns of pest populations in the Americas.The sugarcane borer moth,  The ability to move from deteriorated environments to more resourceful ones is a fundamental component of the insects’ life history and has a significant impact on agricultural ecosystems . As coloDiatraea saccharalis (Fabricius) (Lepidoptera: Crambidae) is one of the most critical sugarcane and maize pests in the Western Hemisphere  showed a similar trend; that is, the highest values of genetic diversity were found in Brazil and Argentina whereas the lowest values were found in the U.S. and El Salvador (O) and expected heterozygosity (HE) across all populations were 0.12 and 0.16, respectively. The Brazilian population of Jaboticabal-Sugarcane showed the highest observed and expected values (HO = HE = 0.24) (O = 0.03 and HE = 0.08).Overall diversity indexes [i.e., number of alleles (A), allelic richness  . The low0 and HE might indicate that most loci are in Hardy-Weinberg equilibrium, which means that the frequency of the alleles tended to remain unchanged over the generations. On the other hand, differences in observed and expected heterozygosity might indicate critical demographic changes.The observed values for heterozygosity were less than the expected values in all but the three Brazilian locations . Particularly large differences between observed and expected heterozygosity were observed in populations from Argentina and El Salvador . Similar values for HD. saccharalis, which was also reflected in the inbreeding coefficient (FIS). The average inbreeding coefficient across populations was 0.27, ranging from -0.009 (Piracicaba-Maize) to 0.727 (El Pais-Sugarcane). Departure from the Hardy-Weinberg equilibrium (HWE), as shown previously, and heterozygote deficiency (FIS), can be related to different causes. Limited dispersal, well-structured populations, and the evidence for strong positive selection are all factors that point to a more locally confined population dynamic.Overall fewer heterozygotes than expected were found in populations of ST revealed strong genetic structure between the northern  and the southern  parts of the American continents . In contrast, an overall low degree of differentiation was found among the Brazilian populations , which can be explained by the short geographical distance and therefore higher gene flow among sampled sites. Alternatively, the differences in genetic structure found in Brazil and the U.S. may be the result of a different pattern of colonization of the two geographical regions. This hypothesis will be developed further in the following paragraphs.The values of pairwise Fntinents . The higD. saccharalis samples into four clusters according to the country of origin  indicating a second event of differentiation  in the region . An inteD. saccharalis may have been influenced by human-mediated movements of maize  indicating a shared route of colonization and gene flow.The dispersal history of izations ,61. Apprizations –64. Thesizations –67. D. sD. saccharalis dispersal [Archaeological evidence demonstrates that maize dispersal occurred through the South American lowlands and the Andean region, suggesting two major routes for ispersal –70. AnalD. saccharalis Argentinian populations, a pattern of sub-structure was found as well. While samples from the Pampa region  and the Dry Pampas  grouped together and showed resemblance to the Brazilian populations, populations from remote parts of the northwest Chaco Serrano  were genetically differentiated. Together, this suggests that populations from the Pampas and the Dry Pampas might be associated with D. saccharalis dispersal routes through lowlands, while Jujuy might have a more ancient origin associated with maize dispersal through the Andean region. However, future studies are necessary to confirm this hypothesis.Regarding the th and 16th centuries. The Caribbean region was a crossing point at the beginning of European colonization of America, and served to exchange people and food between the Old and the New World [D. saccharalis by sea routes, northwards to the United States of America, specifically Florida, as well as southwards to Brazil, specifically to the São Paulo state region. The support for this hypothesis comes from the strong genetic structure within the U.S. that could indicate that the Florida population was colonized by an ancestral population probably from the Caribbean region. Alternatively, gradual range expansion of D. saccharalis through the Caribbean region could have reached Florida, where the founding population remained relatively isolated throughout the years. More studies including samples from the Caribbean region would be necessary to corroborate this hypothesis.In recent years, the long-distance movement of goods including sugarcane by maritime routes were of great importance and may explain some of the genetic structure found within the region (ew World . This neST between São Paulo and Buenos Aires was 0.02).In Brazil, two genetic clusters were derived from the nuclear markers , which cD. saccharalis dispersion in Brazil countryside, which has been a recent development. This relatively recent introduction of D. saccharalis in the Brazilian Cerrado, followed by its population expansion may explain the lower allelic richness observed in populations from central Brazil compared to populations collected in the states of São Paulo, where the gene pool was more diverse. Due to its high commercial value during the last decade, sugarcane had a considerable agricultural expansion in areas of the Cerrado. Interesting, however, is that the oldest mitochondrial haplotype was present only in MT (Hap8) and was not shared with any other locations indicating a second route of colonization, and is probably associated with the earlier lowland colonization from the Amazon region. In summary, the combination of haplotypes present in the Cerrado is likely the result of the sugarcane expansion from the east  and perhaps an earlier pre-sugarcane expansion associated with the movement of maize along the rivers by native populations. More efforts should be made to characterize D. saccharalis populations from northern parts of Brazil to test this hypothesis.The transportation of plants across states seems to be the most critical pathway for Diatraea saccharalis is a successful invasive species that colonized habitats with very distinct environmental conditions across the Americas. Likely, multiple introductions of populations over a long time period explain the complex process of colonization of new areas. After an initial period of differentiation that separates different lineages, human migration and trade was likely a major factor in explaining the spread of D. saccharalis populations throughout the Americas. Diatraea saccharalis used maize as the early vehicle for dispersal whereas sugarcane was used in a second historical moment. More information about the genetic background of the Caribbean and South America populations, mainly from Venezuela and Argentina, is needed to support our hypotheses and investigate the lowland and Andean routes of dispersal.S1 FigLoci plotted in the red area are candidates for being under positive selection while loci plotted in the yellow area are candidates for being under balancing selection.(TIF)Click here for additional data file.S2 FigBootstrap replication values of 1,000 were used, and the number at each node represents the percentage of bootstrap support for each cluster. Data present three distinct clusters separated by geographical locations.(TIF)Click here for additional data file.S3 Fig(TIFF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Tablep = 0.000). The analysis involved 16 haplotype sequences.The null hypothesis of equal evolutionary rate throughout the tree was rejected at a 5% significant level ((DOCX)Click here for additional data file.S4 TableBold indicates non-significant P-values (P > 0.05).(DOCX)Click here for additional data file.