Glossina fuscipes fuscipes is the primary vector of trypanosomiasis in humans and livestock in Uganda. The Lake Victoria basin has been targeted for tsetse eradication using a rolling carpet initiative, from west to east, with four operational blocks (3 in Uganda and 1 in Kenya), under a Pan-African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). We screened tsetse flies from the three Ugandan PATTEC blocks for genetic diversity at 15 microsatellite loci from continental and offshore populations to provide empirical data to support this initiative.E and NC).We collected tsetse samples from 11 sites across the Lake Victoria basin in Uganda. We performed genetic analyses on 409 of the collected tsetse flies and added data collected for 278 individuals in a previous study. The flies were screened across 15 microsatellite loci and the resulting data were used to assess the temporal stability of populations, to analyze patterns of genetic exchange and structuring, to estimate dispersal rates and evaluate the sex bias in dispersal, as well as to estimate demographic parameters (NWe found that tsetse populations in this region were stable over 4-16 generations and belong to 4 genetic clusters. Two genetic clusters (1 and 2) corresponded approximately to PATTEC blocks 1 and 2, while the other two (3 and 4) fell within PATTEC block 3. Island populations grouped into the same genetic clusters as neighboring mainland sites, suggesting presence of gene flow between these sites. There was no evidence of the stretch of water separating islands from the mainland forming a significant barrier to dispersal. Dispersal rates ranged from 2.5 km per generation in cluster 1 to 14 km per generation in clusters 3 and 4. We found evidence of male-biased dispersal. Few breeders are successfully dispersing over large distances. Effective population size estimates were low , while census size estimates ranged from 1200 (cluster 1) to 4100 (clusters 3 and 4). We present here a novel technique that adapts an existing census size estimation method to sampling without replacement, the scheme used in sampling tsetse flies.Our study suggests that different control strategies should be implemented for the three PATTEC blocks and that, given the high potential for re-invasion from island sites, mainland and offshore sites in each block should be targeted at the same time. Glossina) is a major vector of trypanosomiasis throughout sub-Saharan Africa, causing extensive morbidity and mortality in humans and livestock [The tsetse fly  by first reducing populations using area-wide approaches , followed by massive release of sterile males to ensure eradication [Glossina fuscipes fuscipes (Gff). A program , which ended in 2004, reduced tsetse populations by 75% to 90% in the mainland sites of the target area, but the program did not include islands [In 2001, the Organization for African Unity (OAU) launched a new initiative, the Pan-African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) to eradicate the tsetse flies from a vast area of sub-Saharan Africa  because of previous success of tsetse eradication on islands in Equatorial Guinea [The PATTEC plan, unlike FITCA, includes islands and intends to eradicate  to east . The baspatterns ,23. Blocl Guinea  and Zanzl Guinea .Gff populations within and between the three Ugandan PATTEC blocks. We used these data to estimate effective population size (NE), to evaluate temporal stability over 4-16 generations, and to measure genetic exchange and dispersal rates within and between blocks. In view of the finding that high levels of genetic exchange occur among continental Ugandan populations of Gff separated by distances smaller than 100 km [Gff island populations for eradication trials.We used genetic variation at 15 microsatellite DNA loci to examine the genetic differentiation of Gff at 3 continental localities across the Lake Victoria basin in Uganda , and locus GmmD15, because it was monomorphic in all of the 11 sites we sampled. Thus, we only used 15 loci for all subsequent genetic analyses.DNA was extracted from tsetse legs using the PrepGEM Insect DNA extraction kit  as per the protocol provided by the manufacturer. We collected genotypic data across 18 microsatellite loci  and comparisons (LD) using the Benjamini-Hochberg method [O), expected heterozygosity (HE) and the inbreeding coefficient (FIS) were calculated using the program Genalex 6.41[Genepop to perform Fisher’s exact test on both microsatellite alleles and genotypes.We used nepop 4.1 to test nepop 4.1 was usednepop 4.1 Markov cg method  with a falex 6.41. In ordeStructure 2.3.3[Gff populations in the Lake Victoria basin , has been shown to perform better than the Bayesian clustering approach when hierarchical and clinal structure is present in the data [adegenet package [We used the model-based Bayesian clustering method implemented in ure 2.3.3 to deterthe data . We used package  in R [39ST values [ST values were obtained using the program Arlequin 3.5[ST describes the genetic structure produced by non-random distribution of individuals among subpopulations relative to the total population. However, our sample may contain multiple hierarchical levels of genetic differentiation, such as genetic clusters of populations with further partitioning within clusters, including potential genetic structure arising from isolation of island from mainland populations. In order to determine the contribution of different hierarchical levels to the observed genetic structure, we estimated hierarchical F-statistics using the method described in Yang [hierfstat[In order to quantify the genetic heterogeneity of Lake Victoria populations, we computed pairwise FT values  among saequin 3.5 and thei in Yang   and dispersal were evaluated using Rousset’s procedure  within gGeneclass 2.0[Flock 2.0[k partitions . In the first approach, we used the software class 2.0 to compuclass 2.0,51. In tFlock 2.0 to assigE) that could be introduced by migration, which influences linkage disequilibrium as well as temporal methods of NE estimation [E was computed using Waples and Do’s LD method implemented in the program LDNe[E: 1) a Bayesian algorithm based on coalescence and implemented in the program TM3[MLNE. Census size (NC) was computed via a sequential Bayesian method [C  aogram TM3 implemenn method  adapted n method  using ann method . This men method ,58 to esO and HE values in KG  and the highest in OK , while mean allelic richness across the 15 loci ranged from 2.87 in MA to 5.40 in BU . After applying the Benjamini-Hochberg false discovery rate procedure [We observed the lowest Hrocedure  to the mST values between different sampling seasons revealed temporal homogeneity, i.e. temporal samples from the same sites were not significantly genetically differentiated. The smallest difference was observed between BU seasonal samples  and highest in BY . This was consistent with the similarity in allele frequencies between seasons observed in Additional file We examined the temporal stability of the samples for which temporal collections were available. Pairwise FStructure identified four distinct genetic clusters , while significantly different, is much lower than among other clusters. The extent of gene flow between clusters 3 and 4 is also evident from posterior probabilities of assignment obtained from Structure ) values against geographic distance to evaluate the occurrence of isolation by distance (IBD) within these groups , Wright’s neighborhood size (WN) and migration rate (m), using both 1D and 2D stepping-stone models (Table 2 (2D: 6.2 km2 and 12.9 km2), and neighborhood size  were similar to each other. These estimates were higher for group 3 samples . Migration rate estimates per generation were also higher in group 3 (0.033) than the other two genetic groups  and 0.025 in group 2).We calculated per generation dispersal (σ), dispersal surface  estimates computed using both a linkage disequilibrium method (LDNe) and two temporal methods (a likelihood approach implemented in MLNE and a Bayesian approach implemented in TM3). Table C).Estimates of population size were computed for each genetic group. Table E and NC were estimated for a dataset consisting of 12, 4, and 16 generations of flies from groups 1, 2 and 3, respectively. For the temporal methods only the first and the last samplings were used for NE estimation, as the increased sampling interval might decrease the bias caused by overlapping generations and age structure [LDNe and temporal methods were very similar (Table ST between EB and other populations in the region was 0.07-0.09). We used NE estimates obtained via the LD method to calculate dispersal. NC was much higher in group 3  in group 3; this ratio was higher in group 2 (0.101) and highest in group 1 (0.121).Ntructure . With thGff populations are genetically stable over multiple seasons. Recent work on mainland sites in Uganda on the same species corroborates this result [Gff abundance [E values , especially if migration alleviates the effects of drift. Seasonal fluctuations in population size could also be a reflection of the low efficiency of trapping devices used to monitor fly populations [Gff is susceptible to high temperatures [G. tachinoides in northern Nigeria, which, like Gff, belongs to the palpalis group [The genetic data we collected for 14 sampling sites  could be facilitated by the presence of suitable na camara-76. Thesna camara,77,78.Gff[G. p. gambiensis, however, Solano et al.[Within clusters, island populations were not genetically differentiated from the mainland ones  were quite concordant among the linkage and temporal methods, ranging from 33 to 121 in group 2, 157 to 212 in group 1 and 240 to 310 in group 3. The NC estimated for group 3 was much higher than the NC estimates for groups 1 and 2. Despite the large difference in NC estimates, the NE estimates were similarly low in all three groups. The NE/NC ratio was, therefore, lowest in group 3 .Population size estimates were calculated for three groups, which we defined as genetically distinct units using multiple analyses. The effective population size estimates  were similar between the 1D and 2D IBD models. These distances were approximately 14–15 km for flies in group 3 and lower in the other two groups, ranging from 2.5 to 4.5 km (Table 2) within groups 1, 2 and 3 were 6.2, 12.9 and 200.1 km2, respectively. Similarly, migration rates per generation (m) within the three units ranged from 0.01 in group 1 to 0.03 in group 3. Flies in group 3 cover greater distances and disperse over a wider surface area per generation, suggesting that conditions for movement are more favorable in this region, possibly due to environmental factors.Regression of linearized FGff based on mark-release-recapture (MRR) studies, which are about 14.2 km per generation given the movement estimate of 338 m/day [G. palpalis gambiensis and G. tachinoides[morsitans group [Gff suggest that the dispersal capacity of flies is reduced in these areas, probably due to habitat loss and control efforts. The reduction in dispersal capacity has had an effect on genetic cohesiveness in the region and led to the differentiation into distinct genetic groups.These genetically derived dispersal distances and migration rates are very similar to estimates of dispersal rates for 38 m/day . Our genchinoides,86. MRR ns group , suggestSuppression should be followed by eradication in all three groups. While eradication would be harder to implement in group 3 because of the comparatively larger population size, larger dispersal distance and surface per generation, even the best suppression efforts would be much more difficult to maintain over time. Thus, the better option would be for an eradication campaign to follow an initial suppression phase post-haste, much more rapidly in group 3 than the other two groups.The dispersal of flies across our study area showed evidence of sex bias. While male-biased dispersal in group 3 was only supported by mAIc, evidence for male-biased dispersal was stronger in groups 1 and 2. The finding of male-biased dispersal is very valuable for sterile insect technique (SIT) vector control efforts. The release of sterile male flies, as the better dispersing sex, holds the promise of sterile individuals being able to efficiently compete with wild breeders.2 = 200 km2), as well as a very large census size and the potential for the NE/NC ratio to increase in the case of population size reduction, all suggest that suppression alone is not likely to produce desirable results in the long run and that it should be coupled with eradication. Additionally, following the initial suppression phase, eradication would have to ensue faster for group 3 than the other two groups in order to overcome the comparatively higher dispersal capacity of flies and prevent re-infestation. The high dispersal rate in group 3 is a strong argument against the Buvuma islands being a suitable location to evaluate eradication protocols, and that the Ssese islands are a better target for this purpose, provided mainland sites are also included. The finding of male-biased dispersal of tsetse populations in this region ensures that eradication efforts involving SIT are likely to be successful.The findings of this study have reaffirmed the importance of gathering genetic data prior to implementing area-wide tsetse vector control operations. The high levels of genetic mixing between islands and mainland sites suggest that these sites should be treated at the same time. The boundaries of the PATTEC blocks need to be modified to reflect the genetic composition of fly populations . Fly populations from the two westernmost groups (1 and 2) are relatively isolated from flies in group 3, suggesting that suppression followed by eradication measures can be effective in these regions, but only if area-wide approaches include both island and mainland sites. For group 3, high levels of gene flow, which translate to a large dispersal surface  across 15 loci are shown for the group of BU and OK samples , and BV, BY, BZ and LI samples grouped together .Click here for fileTable S1. Fisher’s exact differentiation test . For each site or group of sites (BU-OK and BV-BY-BZ-LI), tsetse collected at different sampling times  were tested for differences in allelic frequencies (genic differentiation) and genotypic frequencies. P (genic) and P (genotypic) – probability of non-differentiation.Click here for fileTable S2. Pairwise FST values.  FST values were computed for 4 clusters, averaged across 15 loci based on Weir and Cockerham [ockerham . FST valClick here for fileTable S3. Pairwise FST values.  FST values were computed for 14 sampling sites, averaged across 15 loci based on Weir and Cockerham [ockerham . FST valClick here for file


GSTA and GSTM subfamilies, located on different chromosomes.Extensive genome-wide analyses of many human populations, using microarrays containing hundreds of thousands of single-nucleotide polymorphisms, have provided us with abundant information about global genomic diversity. However, these data can also be used to analyze local variability in individual genomic regions. In this study, we analyzed the variability in two genomic regions carrying the genes of the GSTA and GSTM gene clusters showed similarities in their allelic and haplotype diversities. These patterns were similar in three Russian populations and the CEU population of European origin. There were statistically significant differences in all the haploblocks of both the GSTM and GSTA regions when the Russian populations were compared with populations from China and Japan. Most haploblocks also differed between the Russians and Nigerians from Yoruba, but, some of them had similar allelic frequencies. Special attention was paid to SNP rs4986947 from the intron of the GSTA4 gene, which is represented in apes by an A nucleotide. In the Asian and African samples, it was represented only by a G allele, and both allelic variants (G/A) occurred in the Russian and European populations.Analysis of the polymorphisms in GSTA and GSTM gene regions, and that African subpopulations were involved differently in the formation of the European and Asian human lineages.The results obtained suggest the presence of common features in the evolutionary histories of the  The results of genome-wide analyses of different populations can be used to study the patterns of DNA diversity in particular genomic regions containing specific genes or gene clusters. One interesting and functionally significant genetic system includes the glutathione-S-transferase (GST) genes that encode the different GSTs.GST polymorphisms had been studied , and these were not sufficient to infer the genetic relationships of populations. It may be especially relevant that particular genes of some GST families are located close to each other, forming clusters in the genome[GSTA and GSTM genes, located on different chromosomes, in three groups of Russians from the western (Tver), eastern (Murom), and southern (Kursk) regions of the European part of Russia. The analyses were based on both the comparison of allelic variation in individual SNPs and the haplotype diversity across the GST clusters. The genotypes were obtained from a genome-wide analysis of SNPs[The GSTs are one of the key groups of detoxification enzymes. The chemistry of the reactions catalyzed by these enzymes is based predominantly on the conjugation of glutathione to the electrophilic centers of various substances, which leads to a loss of toxicity and the formation of more hydrophilic products. The important noncatalytic functions of the GSTs include their capacity to sequester carcinogens, their involvement in the intracellular transport of a wide spectrum of hydrophobic ligands, and their modulation of signaling pathways,2. Like e genome. However of SNPs, perform of SNPs. The datDNA samples were isolated from blood samples obtained with the informed consent of Russian donors from western (Andreapol district of the Tver region), eastern (Murom district of the Vladimir region), and southern locations (Kursk and Oktyabrsky districts of the Kursk region) in the European part of Russia. Their ethnicity was determined by interview. All individuals were unrelated and represented the native ethnic groups in the regions studied . The DNA was isolated from peripheral leukocytes with standard techniques, using proteinase K treatment and phenol–chloroform extraction.GSTM and GSTA gene clusters are located. The sample sizes of the populations taken from the HapMap Project were: 165 individuals from CEU, 86 from CHB, 84 from JPT, and 166 from YRI.All the DNA samples were genotyped at the Estonian Biocentre , using the Illumina Human CNV370-Duo (Tver and Murom samples) and Human 660W-Quad chips (Kursk samples), according to the manufacturer’s instructions. In total, 288 Russian samples were genotyped (96 samples per population). Because the microarrays differed in the numbers of SNPs tested, the number of SNPs examined was standardized to obtain a set of loci that was consistent across all the populations analyzed. The set of loci was chosen by considering the chromosomal regions in which the ST)[D')[D' and its confidence interval. Linearized pairwise FST[P < 0.05.The allele frequencies, their Hardy–Weinberg equilibrium status, and the SNP-based Wright’s fixation index (FST) were calST). The paiST)[D') was estiST)[D'). The haprwise FST values wGSTA cluster, which is located at p12.1 of chromosome 6 over a 250-kbp area. The polymorphisms are presented according to their locations in relation to the genes. Based on the threshold value for the pairwise linkage disequilibrium between the SNPs (D' > 0.7)[GSTA cluster. All the haploblocks were identical in all the populations studied. Figure Figure ' > 0.7), six bloGSTA cluster in the Russian populations and in the HapMap populations. A comparative analysis showed no differences in the distributions of the SNP variants in the Russian populations, and similar allelic frequencies were found in the CEU population. However, the allelic distributions in the three remaining HapMap populations differed considerably from those in the populations of European descent.Table ST) to quantitatively assess the levels of interpopulation frequency variation. Figure ST values. The diagram shows that the Russian populations form a single cluster, with the CEU population close to them. However, the African YRI population and Asian CHB and JPT populations are situated at a considerable distance from them.We also calculated the fixation indices  presented in Table P were set for each block using the Bonferroni correction for multiple testing. The data generated showed no marked differences in the haplotype frequencies across the Russian populations and the CEU population. However, a comparison of the haplotype frequencies in the Russian populations with those in the Chinese, Japanese, and Nigerian populations indicated significant difference between them. Most P values were considerably lower than the specified levels. The exceptions were block #5 and, to a certain degree, blocks #1 and #4, where the pairwise P values for the pairs of Russian and Nigerian populations were higher than values specified for these blocks.The comparison of the populations was based on the haplotype frequencies calculated for each block. The calculated probabilities  and Africa (YRI). The two-dimensional plot of FST-based distances was similar to the plot obtained for the GSTA cluster (data for the GSTM cluster are not shown).The GSTM cluster. As in the GSTA cluster, the numbers of haplotypes observed in the blocks differed. When we considered the P values for the pairwise comparisons , who share a common ethnic origin, were similar. No marked differences were also established between the three Russian populations and the CEU population, which clearly reflects their common European ancestry. In this context, it was interesting to find some similarity between the Russian samples and the Yoruba population from Nigeria in the haplotype frequencies of some blocks (mainly block #5 of the GSTA cluster and block #1 of the GSTM cluster). Because the European populations differed significantly from the populations of China and Japan in the haplotype spectra of all blocks in both clusters, we propose that these similarities can be attributable to some particular features of these haploblocks in the microevolutionary history of the populations. At the same time, the Russian and Nigerian populations differed significantly in the remaining haploblocks of both gene clusters.Although genes of GSTA cluster, located in the intron of the GSTA4 gene. In apes, this SNP site carries an A nucleotide[Another interesting finding that warrants particular attention is SNP rs4986947 from block #6 of the cleotide. In the cleotide. By contcleotide. These mcleotide. In addicleotide. These qGSTA and GSTM subfamilies. By using a haplotype-based approach, we have demonstrated a similarity in the patterns of allelic diversity between the GSTA and GSTM gene clusters in all populations studied. This leads us to propose that the evolutionary histories of these clusters share many features and mark the same events in the evolutionary trajectories of the main human groups.In summary, we have reported the results of a study of SNPs in two genomic regions carrying the genes of the The authors declare no competing interests.INF carried out the polymorphism typing, performed the statistical analysis and drafted the manuscript. AVK participated in the study design, helped with the statistical analysis and manuscript drafting. SAL conceived of the study, participated in its coordination and helped to draft the manuscript. All authors read and approved the final manuscript.


Vireo atricapilla) suffered a substantial contraction of breeding habitat and population size during much of the 20th century. In a previous study, we reported significant differentiation between remnant populations, but failed to recover a strong genetic signal of bottlenecks. In this study, we used a combination of historical and contemporary sampling from Oklahoma and Texas to (i) determine whether population structure and genetic diversity have changed over time and (ii) evaluate alternate demographic hypotheses using approximate Bayesian computation (ABC). We found lower genetic diversity and increased differentiation in contemporary samples compared to historical samples, indicating nontrivial impacts of fragmentation. ABC analysis suggests a bottleneck having occurred in the early part of the 20th century, resulting in a magnitude decline in effective population size. Genetic monitoring with temporally spaced samples, such as used in this study, can be highly informative for assessing the genetic impacts of anthropogenic fragmentation on threatened or endangered species, as well as revealing the dynamics of small populations over time.Anthropogenic alterations in the natural environment can be a potent evolutionary force. For species that have specific habitat requirements, habitat loss can result in substantial genetic effects, potentially impeding future adaptability and evolution. The endangered black-capped vireo ( Among the challenges to understanding evolution at the population level is unveiling demographic history using genetic data. Although ‘snapshots’ of genetic patterns based on single samples can be extremely informative, the ability to divulge historical population processes that shaped current patterns of genetic variation is limited . This caThis need to understand the potential evolutionary outcomes of past demography is nowhere as crucial, perhaps, as in cases where the genetic impacts of anthropogenic actions need to be assessed – as is often the need in conservation studies. For species existing in small populations and those of conservation concern, it may be necessary to unravel demographic history to evaluate whether genetic sustainability is of concern , and to Vireo atricapilla) – an endangered bird species.One avenue for circumventing the above limitations is to use archived specimens and molecular techniques sufficiently sensitive for working with limited or degraded DNA . Such saMolothrus ater), associated with increasing habitat edges, are considered as important influences. Severe parasitism by cowbirds is considered to be a relatively recent problem – having increased together with fragmentation – although it is reasonable to expect that some parasitism has always existed.The black-capped vireo is a neotropical songbird that breeds in the early-successional oak-juniper savanna ranging from south-central Texas through southern Oklahoma (USA). This species is reported to have suffered substantial losses in both its breeding and wintering habitat because of agriculture and urbanization over the past 50 years . At the Recently, we reported that many populations of black-capped vireos showed more structure than might be expected, based on the vagility of these birds . There wNev) to understand the impact of drift on remnant populations.Little is known about the demographic history of this species, and especially about past genetic diversity and population sizes. In this study, we (i) compare diversity indices and population structure from historical and contemporary populations, (ii) use approximate Bayesian computation models to explore the demographic history – especially with regard to the amplitude and timing of putative population size changes and (iii) estimate long-term effective population size (We focused on the availability of multiple samples collected from 1899 to 1915 at locations from areas corresponding with the contemporary samples collected during 2005–2008. We chose this period because (i) few samples existed in collections either before or after this time from multiple locations and (ii) the sampling straddles the most likely period of habitat and population decline. Three locations  represenContemporary samples were collected in 2004–2006, with additional samples collected in 2007 and 2008. Methodology of sample collection is similar to the one described by 3 patch of skin removed from the toe-pads of museum specimens using sterile surgical razors and then placed in a sterile microcentrifuge tube  using GENETIX (AR), which controls for biases in allelic diversity arising from unequal sample sizes  to test the hypothesis that the sample medians do not between differ time points. For historical comparisons, where we have three time points, we used a Kruskal–Wallis test , blocked by locus, to compare HEXP and AR among sampling periods.To estimate changes in genetic diversity between a) historical and contemporary samples or b) between pairs of samples within the contemporary period, we used a Wilcoxon signed-rank test . This nonparametric analysis uses estimates of FST (Θ of Weir and Cockerham) among the 1905–1910 historical samples from Kerr, Bexar and Oklahoma populations in GENETIX. FST estimates were obtained using 3000 permutation resampling to control for possible variation because of differences in sample sizes. We performed identical analyses on the corresponding three contemporary populations for comparison. We used a Wilcoxon signed-rank test (paired by locus) to see whether the degree of differentiation among historical samples was different from that of contemporary samples, for the three population pairs. Pairwise differentiation values for each locus were the replicates in the statistical comparison. Using FST to infer differentiation in cases where intra-population diversity is high can be problematic  may have taken place and to estimate the historical and present population sizes. Coalescent inference methods can utilize genetic summary statistics to extract evolutionary histories , and theblematic .Ne and timing of the putative decline for the whole species and (ii) incorporating divergence events among sample sites in the coalescent genealogies would exclude gene flow between lineages, which we know to be incorrect.The ABC approach can be briefly summarized as follows: First, coalescent population gene genealogies are simulated from a uniform prior distribution for each parameter of interest. Priors are defined based on what is known from the species biology, or based on estimates for similar species. Then, genealogy and parameter space is explored through Markov chain Monte Carlo (MCMC) algorithms with a range of uniform priors, producing a large reference table of summary statistics from which genetic data are simulated. Second, a rejection algorithm using We coded 11 potential scenarios to explore demographic history and to detect bottlenecks from our two temporal samples, and a total of 11 million data sets were simulated. A summary of scenarios evaluated and priors used are presented in Ne in our sampled populations. For microsatellite data, the temporal method is reported to be more precise when samples are taken several generations apart than point estimates , where it is assumed that migrants originate from an infinitely large population. This was important because, despite our finding of population differentiation, FST values indicate that the study populations experience gene flow  population by combining samples from the other two remaining populations. While the assumption (infinitely large source) is typical for many idealized populations, in reality few species satisfy this assumption. Although historical populations may not have been infinite, they may have represented a panmictic population, without significant population structure. Hence, we avoided using contemporary populations as the source population as gene flow from differentiated populations may produce biased estimates , we assumed three potentially different generation lengths  to evaluate the effects that T may have on estimates of Ne. There is some variation among sexes (Concurrent estimation of stimates . Temporang sexes  regardinNe assuming closed populations using three approaches: (i) the moment estimator of Ne (MtNe) based on equations 15 and 18 from Ne) implemented in the program CoNe  and heterozygosity (HEXP) among the 1905, 1910 and 1915 samples from Kerr  being generally higher than FST and GST for both the historical and contemporary periods.Based on rom Kerr . In contulations . We alsoulations , with pontiation , despitet90 to N8 [200:1000] at t0  generations ago  for the Bexar and Oklahoma samples based on two sampling periods (1910–2005) were approximately 38  and 31 , respectively (The MLectively . For KerNe) produced the smallest estimates, coalescent estimator (CoNe) produced the largest estimates, and the likelihood estimator  produced estimates intermediate to the other two methods  for the historical population, and 872  for the modern population samples.Results from ONeSAMP gave HEXP followed a similar pattern as AR, although the proportional change was smaller in the former. Our observation of lower heterozygosity in contemporary relative to the historical populations indicates that inbreeding or genetic drift had occurred , drastic demographic changes appear unlikely during 1900–1915. Allelic richness was higher in the historical samples compared to the contemporary samples, indicating a population contraction. Nine alleles were not detected in the contemporary samples compared to historical samples. No reciprocal condition of unique alleles in contemporary populations was detected. Allelic richness is considered more sensitive to population bottlenecks than is heterozygosity . Estimatoccurred , b, proboccurred  as it taoccurred . AlthougThis historical divergence between Texas and Oklahoma populations may represent a long established discontinuity in vireo habitat that pre-dated urbanization of the mid-20th century. Historical vireo distributions in Texas and Oklahoma are separated by approximately 400 km  of unsuiThe Origin of Species (1859) is particularly prescient and relevant to our study: ‘Climate plays an important part in determining the average numbers of a species, and periodical seasons of extreme cold or drought, I believe to be the most effective of all checks. I estimated that the winter of 1854–1855 destroyed four-fifths of the birds in my own grounds; and this is a tremendous destruction, when we remember that 10% is an extraordinarily severe mortality from epidemics with man. The action of climate seems at first sight to be quite independent of the struggle for existence; but in so far as climate chiefly acts in reducing food, it brings on the most severe struggle between the individuals, whether of the same or of distinct species, which subsist on the same kind of food’.Coalescent approaches have become useful tools for uncovering important demographic events in the history of populations . In our While pulses of freakish climate change can undoubtedly spike mortality, the genetic and evolutionary consequences of drawn-out climate change will need to be investigated – especially when such changes are also occurring concurrently with anthropogenic habitat changes. It has been argued that the severity of the 1930s Dust Bowl was exacerbated by human land use changes over the preceding 50 years , which iNe approach assuming migration produced smaller estimates and wider confidence intervals compared to other estimators that assumed closed populations. It is important to note that the MLNe joint estimator assumes that rates of migrants are from an infinitely large population, gene flow remains constant over the sampling interval, or there is no significant subdivision among source populations. We now know from analysis of structure that these assumptions are not satisfied. However, most natural populations do not persist with constant migration rates over time (Ne. This offers an informative contrast with the approaches assuming closed populations. Bias has been a major concern with estimation of Ne based on temporal variance. However, these biases are expected to be less problematic with larger sample size, multiple sampling points, increasing number of variable loci and increasing the interval between samples. Ne from Kerr, for which population we have the best sample representation. ONeSAMP results also confirmed the trend that we observed with the ABC analysis, although actual estimates were higher for both the historical and contemporary samples.The MLver time . NonetheOverall, our results from the various approaches discussed here, such as decreases in allelic diversity, heterozygosity within populations, increased differentiation among populations and evidence for a demographic bottleneck based on coalescent simulations, suggest that a population decline of considerable effect has occurred between the historical and contemporary period. Furthermore, these demographic changes coincide with documented environmental and habitat changes that have occurred over the last century. Based on these results, a strong case can be made for the need to improve genetic connectivity between remnant populations, if adverse genetic consequences or loss of adaptive potential are to be prevented. Further, the steep trajectory of genetic decline indicates that this species may have a diminished buffering capacity against continued onslaughts on their habitat.Our work presented here provides a broadly applicable approach to address questions about population genetic change in cases where determining anthropogenic impacts may be valuable to future management. While use of archived genetic material is by no means novel, advances in molecular and computational methods make the use of limited archived tissue viable and especially valuable from a conservation perspective. We recently applied this approach successfully in revealing potentially critical details about the recent demography of another endangered species, the golden-cheeked warbler . This woHere, we were able to trace the genetic consequences of demographic change based on changes in allele frequencies over time, and by modeling alternative evolutionary scenarios. The ability to infer demographic history allows us to view genetic change in the context of habitat loss and fragmentation, and prognosticate on how this genetic change may impact the future persistence of populations.Black-capped vireo populations are rebounding from their low census numbers following intensive cowbird control and active management of habitat, including prescribed burns, to suit their habitat requirements . As a teAlthough the northern range of the species has contracted, it is believed that the breeding range extends southward farther than previously thought . Our stuOther similar studies  have shoQuerying the past with ancient or archived DNA provides information that helps resolve details of the otherwise hazy evolutionary past of populations or species. Inferences from such analyses allow us to evaluate which events of the past may be most consequential for the evolutionary future of populations.


The present-day Brazilian population is a consequence of the admixture of various peoples of very different origins, namely, Amerindians, Europeans and Africans. The proportion of each genetic contribution is known to be very heterogeneous throughout the country. The aim of the present study was to compare the male lineages present in two distinct Brazilian populations, as well as to evaluate the African contribution to their male genetic substrate. Thus, two Brazilian population samples from Manaus (State of Amazon) and Ribeirão Preto (State of São Paulo) and three African samples from Guinea Bissau, Angola and Mozambique were typed for a set of nine Y chromosome specific STRs. The data were compared with those from African, Amerindian and European populations. By using Y-STR haplotype information, low genetic distances were found between the Manaus and Ribeirão Preto populations, as well as between these and others from Iberia. Likewise, no significant distances were observed between any of the African samples from Angola, Mozambique and Guinea Bissau. Highly significant Rst values were found between both Brazilian samples and all the African and Amerindian populations. The absence of a significant Sub-Saharan African male component resulting from the slave trade, and the low frequency in Amerindian ancestry Y-lineages in the Manaus and Ribeirão Preto population samples are in accordance with the accentuated gender asymmetry in admixture processes that has been systematically reported in colonial South American populations. Between the 16th and 19th centuries, about 4 million Sub-Saharan African slaves arrived in Brazil  and the other from Ribeirão Preto (State of São Paulo). Three African populations, from Guinea Bissau, Angola and Mozambique were also included in the study, since they represent the ancestral populations of most Africans that arrived in Brazil during the period of the slave trade. The five populations were genetically characterized for Y chromosome specific STR loci by typing 9 markers , whereas the Brazilian samples were typed for five SNP markers . In order to evaluate the possible male contributions to our samples, a comparison was made between our data and those already available for Brazilian, Amerindian, African and European populations.The Y-chromosomal minimal haploptype was defined by 9 Y- STRs  in unrelated individuals from Manaus (N = 42), Ribeirão Preto (N = 65), Guinea Bissau (N = 32), Angola (N = 48) and Mozambique (N = 36). The samples from Brazil, Guinea Bissau and Mozambique were collected in district hospitals. The Brazilian samples were composed of individuals from the cities Manaus and Ribeirão Preto. The African samples from Guinea Bissau and Mozambique consisted of individuals living in the regions of Bissau and Maputo, respectively. The samples from Angola were collected in the northern region of the country, and included individuals from the villages of N'Dalatando and Lucala, in Kwanza province, and from the province of Uíge. Blood samples were obtained with written informed consent.PowerPlexY PCR Amplification Kit (Promega), with primers and amplification conditions according to manufacturer's instructions. As regards the others from Guinea Bissau, Angola and Mozambique, the STRs DYS19, DYS389 I, DYS389 II, DYS390 and DYS393 were amplified as described by For samples from Manaus and Ribeirão Preto, the minimal haplotype was typed using a ST genetic distances were visualized in two-dimensional space by using the Multi DimensionalScaling (MDS) method included in the StatSoft, Inc. (2007) STATISTICA data analysis software system, version 8.0.Both haplotype diversity, according to The haplotype results obtained for the STRs  are provided as Supplementary Material (Tables S1 to S5). Haplotype diversity was estimated in all studied populations . A compaIn the sample from Manaus, all individuals presented different haplotypes (42 unique ones) with overall haplotype diversity of 1.000 ± 0.0052. In Ribeirão Preto, 58 different haplotypes were observed, 54 of which unique. In Ribeirão Preto, the most common haplotypes represented in more than one individual  correspond to or are just a few steps apart from, the most frequent haplotype in all Iberian populations . The same was observed when comparing these two populations with other urban and/or admixed South American . Among other American populations, a significant differentiation was found between Manaus or Ribeirão Preto, and African descendents from Rio de Janeiro  and South Amerindians .The population samples from Manaus, Ribeirão Preto, Guinea Bissau, Mozambique and Angola were compared with different populations  than those observed between the Brazilian and European samples. Highly significant RST values were found when comparing the Manaus and Ribeirão Preto with all the African populations .Within the African group, although p-values were not significant (p > 0.01), higher RST genetic distances, based on Y-STR data  plot of pairwise RSTR data , it is pFive SNPs were typed in the Manaus and Ribeirão Preto samples, in order to trace the origin of the Y-chromosomes in the current population. In each population sample, a single chromosome belonged to the most frequent Sub-Saharan African haplogroups by carrying the M2 mutation (Tables S1 and S2). In Ribeirão Preto, a second African lineage could be found, which lacks the M213 and SRY10831 mutations, therefore being classified in paragroup A*. One out of 65 samples from Ribeirão Preto and 4 out of 42 from Manaus carried both the M213 and M3 mutations that characterize Amerindian haplogroups. The remaining samples, were classified in F* (except Q3), E1b1b1 - M35 or Y* .Based on the SNP results, we concluded that Europe is the main source of paternal lineages existing in the present-day population of Ribeirão Preto (95.4%), with African and Amerindian lineages only representing 3.1% and 1.5% of the chromosomes, respectively. In Manaus, the origin of most chromosomes can also be traced to Europe (88.1%), although a higher Amerindian component was found (9.5%). Only a single African-ancestry chromosome (2.4%) was detected in the sample from Manaus.e.g. et. al. 2004; ST = 0.18) to the Toba Amerindian sample and any of the Iberian samples. Nevertheless, from the SNP results it can be inferred that, although genetic distance analysis based on STR profiles allowed to identify the main European contribution to the Brazilian samples, it was not able to detect minor contributions. In fact, the almost 10% Amerindian contribution to the Manaus sample was insufficient to produce significant genetic distance values between Manaus and both Ribeirão Preto or Iberian populations.Many studies have been carried out to characterize the genetic diversity of Brazilian populations aiming to better understand colonization processes and the demographic history of its native populations .Y chromosome haplotype distribution in the Ribeirão Preto population sample (N = 65). Y chromosome haplotype distribution in the Guinea Bissau population sample (N = 32). Y chromosome haplotype distribution in the Angola population sample (N = 48).Y chromosome haplotype distribution in the Mozambique population sample (N = 36).This material is available as part of the online article from http://www.scielo.br/gmb.


The Qinghai-Tibetan Plateau (QTP) is one of the most extensive habitats for alpine plants in the world. Climatic oscillations during the Quaternary ice age had a dramatic effect on species ranges on the QTP and the adjacent areas. However, how the distribution ranges of aquatic plant species shifted on the QTP in response to Quaternary climatic changes remains almost unknown.Hippuris vulgaris from the QTP and adjacent areas. Our sampling included 385 individuals from 47 natural populations of H. vulgaris. Using sequences from four chloroplast DNA (cpDNA) non-coding regions, we distinguished eight different cpDNA haplotypes. From the cpDNA variation in H. vulgaris, we found a very high level of population differentiation (GST = 0.819) but the phylogeographical structure remained obscure . Phylogenetic analyses revealed two main cpDNA haplotype lineages. The split between these two haplotype groups can be dated back to the mid-to-late Pleistocene (ca. 0.480 Myr). Mismatch distribution analyses showed that each of these had experienced a recent range expansion. These two expansions (ca. 0.12 and 0.17 Myr) might have begun from the different refugees before the Last Glacial Maximum (LGM).We studied the phylogeography and demographic history of the widespread aquatic herb This study initiates a research on the phylogeography of aquatic herbs in the QTP and for the first time sheds light on the response of an alpine aquatic seed plant species in the QTP to Quaternary climate oscillations. Profound climatic oscillations during the Quaternary ice age of the past ∼2 million years have left imprints on modern-day biota by effecting species' distributions, evolution and extinction 6 km2The Qinghai-Tibetan Plateau (QTP) located in western China is the highest and largest plateau on earth, with an average altitude of approximately 4,500 m and an area of 2.5×10ca.1,816 seed plant species in more than 339 genera, with ca.33 genera being endemic It is estimated that the present-day alpine flora of the QTP  numbers ca.133 aquatic herbaceous seed plants species in 63 genera and 29 families Puccinellia degeensis, P. multiflora, Carex sagaensis, C. muliensis) are endemic to the QTP and adjacent areas In the QTP and adjacent areas, the large number of high altitude lakes, ponds, streams, rivers and wetlands Hippuris vulgaris (Hippuridaceae), a species with a worldwide distribution, in the QTP and adjacent areas. In China, the species is mainly distributed in the Southwest, Northeast and Northwestern regions Hippuris vulgaris is a major and widespread component of aquatic vegetation in the QTP and adjacent areas. It can be found at altitudes of up to 5,000 m and is a highly cold tolerant species ycf6-psbM, trnT-trnL, the rps16 intron and atpI-atpH) between 385 individuals from 47 populations from the QTP and adjacent areas. Our objectives were: (1) to elucidate the intraspecific divergence of H. vulgaris in relation to the Quaternary climatic fluctuations, and, (2) to infer historical population range expansion of this aquatic plant on the QTP.In this study, we assessed the phylogeographical pattern of an aquatic perennial herb, This study was conducted in accordance with all People's Republic of China laws. No specific permits were required for the described field studies. No specific permissions were required for access to the locations described in this study. The location is not privately owned and neither is it protected in any way. This study species is also not protected by any law.H. vulgaris was collected from populations across the QTP and neighboring areas, from the southeast (the HDM) to the northeast (Qinghai province) to the north (Xinjiang province)  . The samH. vulgaris, polymorphism was observed in four regions, ycf6-psbM trnT-trnL rps16 intron atpI-atpH 2, and 50 mM KCl], 1 mM of each primer, 2 U Taq Polymerase , and 60 ng of DNA template. Amplification of genomic DNA was carried out on a PTC-100™ thermocycler . It was commenced with 5 min at 94°C and annealing at 60°C for 5 min, followed by 30 cycles of 1 min at 94°C, 2 min annealing at 50–60°C (depending on the kinds of primers), and 2 min extension at 72 °C, and a final extension cycle of 10 min at 72°C.Total genomic DNA was isolated from 0.5 g of silica-dried leaf tissue following the CTAB method The size of PCR products was determined electrophoretically on 1.5% (W/V) agarose gels run at 100 V in 0.5×TBE (Tris-boric acid-EDTA) and visualized by staining with ethidium bromide. All PCR products were purified from agarose gel using the TIANquick Midi Purification Kit following the protocols provided by the manufacturer . The purified PCR products were sequenced using the ABI Prism BigDye terminator cycle sequencing ready reaction kit  and performed on an ABI 3730 automated sequencer .ycf6-psbM, trnT-trnL, the rps16 intron, and atpI-atpH. For a comparison, the cpDNA haplotypes were also determined from the substitutions only. Phylogenetic analyses of cpDNA haplotype sequences were performed by the neighbor-joining (NJ) method. The NJ tree was constructed according to Kimura's two-parameter model CpDNA sequences were aligned by the program Clustal W h) and nucleotide diversity (pi) for each population and for the entire species were calculated using ARLEQUIN ver. 3.1 HS), total gene diversity (HT), proportion of total diversity caused by differences between populations (GST), and the number of substitution types (NST) were estimated from cpDNA haplotypes following the methods described by Pons and Petit http://www.pierroton.inra.fr/genetics/labo/Software/Permut/; 1000 permutations test). A comparison was made between GST and NST using the U-statistic, which is approximated by a Gaussian variable taking into account the covariance between GST and NST. GST depends only on the haplotype frequency, whereas NST takes into account differences between haplotypes. If NST is significantly higher than GST, closely related haplotypes occur more often in the same populations than less closely related haplotypes, indicating the presence of phylogeographical structure To measure levels of genetic variation, haplotype diversity (K) of groups of geographically adjacent populations that maximizes FCT, i.e., differences among groups of populations. The most likely number of groups (K) was determined by repeatedly running SAMOVA with 2–10 groups and choosing those partitions with a maximum FCT value, as suggested by Dupanloup et al. K, the configuration with the largest FCT value after the 100 repetitions was retained as the best grouping of populations. Hierarchical analysis of molecular variance  using SAMOVA v. 1.0 e AMOVA;  was alsoF statistic (FST) between populations was calculated using the program ARLEQUIN ver. 3.1 FST values and the geographical distances was performed using ARLEQUIN ver. 3.1 The T, in number of generations) since expansion began using T  = τ/2uu is the neutral mutation rate for the entire sequence per generation. The value for u was calculated as u = µkg, where µ is the substitution rate in substitutions per site per year (s/s/y), k is the average sequence length of the DNA region under study (each indel was treated as one mutation) and g is the generation time in years (i.e. the average age at which reproduction first occurs). Rate-constancy of cpDNA haplotype evolution in H. vulgaris was evaluated by relative rate tests in MEGA 3 −9 substitutions per site per year (s/s/y) H. vulgaris was assumed to be one year .To infer the historic demographic expansion events within each inferred haplotype clade, we carried out mismatch distribution analyses in ARLEQUIN ver. 3.1 H. vulgaris lineages using BEAST v 1.5.4 −9 s/s/y A Bayesian approach was used to estimate the divergent times for different ycf6-psbM, trnT-trnL, the rps16 intron and atpI-atpH were 515, 427, 513, and 651 bp in length, respectively. The total length of combined alignments was 2,106 bp. A total of eight polymorphic sites (four substitutions and four indels) of the combined four cpDNA non-coding regions resulted in the resolution of eight haplotypes (A–H) across the 385 individuals (47 populations) of H. vulgaris sampled  and within populations, ranging from 0.0000 to 0.2167, the QHH population has the highest pi value (data not shown). Within-population gene diversity (HS) was 0.111 and total gene diversity (HT) was 0.615. Parameters of VS and VT were 0.071 and 0.484, separately. From the 47 populations sampled, 35 were fixed for a single chlorotype and only 12 populations were polymorphic with two or three haplotypes  indicating no phylogeographic structure. In the SAMOVA analyses, FCT values increased progressively as the value of K was increased from 2 to 10, which did not allow us to unambiguously identify the number K of groups of populations. The Mantel test revealed no significant correlation between genetic and geographical distances of cpDNA haplotypes  over all populations.H. vulgari , which further supported that HPG I and HPG II had experienced rapid expansions. The expansions for HPG I and HPG II were estimated to have been at 0.12 and 0.17 Myr  and the HRag for each of the two groups was not significantly different from that expected under the population expansion model . Lack of significant phylogeographical structure in H. vulgaris from the QTP and adjacent areas may result mainly from the occurrence of widespread haplotypes, i.e., haplotypes A and D, across the sampled regions. As a widespread, clonal and wind-pollinated herbaceous plant species, H. vulgaris populations were expected to be less differentiated For the aquatic herb 2H. vulgaris, which therefore promoted its intraspecific divergence.In this study, the divergence times for all the haplotypes were estimated to be less than 0.5 Myr. The genetic divergence between the two intraspecific lineages of the species occurred at 0.48 Myr, corresponding to the mid-to-late Pleistocene H. vulgaris populations expanded as a consequence of this retreat. The widespread haplotypes A and D in each lineage probably originated from the recent expansions during the last interglacial period. Hippuris vulgaris is a clonal aquatic herb; vegetative reproduction of this species is by rhizomes, which is potentially a mode of long distance colonization. The simple haplotype composition (many populations were composed of a single haplotype) might be attributed to founder effects. Most of the haplotypes at tip positions were unique to their particular population. Haplotypes A and D may represent the ancestral genotypes and probably produced other mutational derivatives following recent expansions For each of the intraspecific lineages, our mismatch distribution analyses showed a unimodal distribution, suggesting a recent range expansion had occurred. Both the observed variance (SSD) and the HRag for each of the two groups was also not significantly different from that expected under the population expansion model. In addition, the haplotype network analysis revealed two “star-like” clusters originating from the ancestral haplotypes A and D, respectively, which also supports range expansion. These two expansions were dated to be 0.12 and 0.17 Myr, respectively, which fell within the interglacial stage between the Penultimate Glaciation and the Last Glaciation H. vulgaris survival in refugia in the interior QTP, because this region possesses a similar cpDNA haplotype diversity and haplotype uniqueness as the HDM region. Plant species survival throughout the Quaternary on the QTP has also been reported in several previous studies The two independent range expansions could have begun from different refugee populations. The phylogeographical pattern of cpDNA haplotypes demonstrates two “star-like” clusters that were the result of haplotypes being linked to a central haplotype, but this relatively simple pattern can be explained by populations preserved in refugia that have experienced population expansion after glaciations Pedicularis longifloraLepisorus clathratusH. vulgaris had colonized through this wide arid region in Northern China, which would have acted as a barrier to dispersal. It was possible that H. vulgaris had colonized the northwest region of China through other routes, e.g., from the western or eastern edge of the Tarim basin, but this hypothesis still needs further study, with more samples around the Tarim basin included.In three adjacent populations  of the QTP, only two haplotypes were found. One is the widespread haplotype A and another is the narrow distributed and newly generated haplotype B, which is shared only by HBH and RT populations. Long distance colonization throughout the QTP and northward to the Northwest region of China might be a possible reason for the occurrence of these two haplotypes in northern region of the QTP, which is consistent with previous findings in other plants, e.g., H. vulgaris, we revealed two independent range expansions in response to the Quaternary climatic oscillations on the QTP and adjacent areas. These two expansions might have begun from different refuge populations from before the LGM, which suggested that the H. vulgaris had survived the LGM and/or previous glaciers since its origins. These findings also partly support the assumption that there was “no massive ice-sheet on the QTP” H. vulgaris were basically similar to the results obtained for several terrestrial herbs H. vulgaris remains a future research question.In conclusion, from the phylogeographic analyses of Table S1Hippuris vulgaris.GenBank accession numbers for each of the four non-coding regions of each chloroplast haplotype (A-H) identified in (DOC)Click here for additional data file.


Anopheles baimaii is a primary vector of human malaria in the forest settings of Southeast Asia including the north-eastern region of India. Here, the genetic population structure and the basic population genetic parameters of An. baimaii in north-east India were estimated using DNA sequences of the mitochondrial cytochrome oxidase sub unit II (COII) gene.Anopheles baimaii were collected from 26 geo-referenced locations across the seven north-east Indian states and the COII gene was sequenced from 176 individuals across these sites. Fifty-seven COII sequences of An. baimaii from six locations in Bangladesh, Myanmar and Thailand from a previous study were added to this dataset. Altogether, 233 sequences were grouped into eight population groups, to facilitate analyses of genetic diversity, population structure and population history.An. baimaii with the start of expansion estimated to be ~0.243 million years before present (MYBP) in north-east India. The populations of An. baimaii from north-east India had the highest haplotype and nucleotide diversity with all other populations having a subset of this diversity, likely as the result of range expansion from north-east India. The north-east Indian populations were genetically distinct from those in Bangladesh, Myanmar and Thailand, indicating that mountains, such as the Arakan mountain range between north-east India and Myanmar, are a significant barrier to gene flow. Within north-east India, there was no genetic differentiation among populations with the exception of the Central 2 population in the Barail hills area that was significantly differentiated from other populations.A star-shaped median joining haplotype network, unimodal mismatch distribution and significantly negative neutrality tests indicated population expansion in An. baimaii that, historically, were able to disperse through continuous forest habitats in the north-east India. Additional markers and analytical approaches are required to determine if recent deforestation is now preventing ongoing gene flow. Until such information is acquired, An. baimaii in north-east India should be treated as a single unit for the implementation of vector control measures.The high genetic distinctiveness of the Central 2 population in the Barail hills area of the north-east India should be confirmed and its epidemiological significance further investigated. The lack of genetic population structure in the other north-east Indian populations likely reflects large population sizes of  Anopheles dirus, Anopheles minimus and Anopheles fluviatilis complexes are the principal malaria vectors in this region. A member of the Dirus complex, Anopheles baimaii, (formerly An. dirus species D) is the main vector in forested and forest-fringe areas throughout NE India  with corresponding geographic distances among populations calculated using the software Geographic Distance Matrix Generator version 1.2.3 [Analysis of molecular variance (AMOVA) for the optimal groups was carried out in Arlequin 3.1. AMOVA takes into account the number of molecular differences between haplotypes in an analysis-of-variance framework equivalent to F-statistics. Pairwise Fce model ,38, a Maon 1.2.3 .Spatial structuring within NE India was assessed using the Spatial Analysis of Shared Alleles (SAShA) method . This meet al [A rarefaction method, as commonly used in ecological studies to estimate species diversity, was modified according to Colwell et al  to estimet al  was usedAn. baimaii in NE India has undergone expansion, a mismatch distribution was calculated in Arlequin 3.1 and compared with the expectations of the sudden expansion model. The time of expansion was estimated under the sudden expansion model assuming the mutation rate of 1.15 × 10-8/site/year as used by Morgan et al [A haplotype network was constructed using the median joining (MJ) algorithm  in NETWOan et al .To test the null model of neutral mutation and constant population size Tajima's D  and Fu'sAn. baimaii from 26 sites in NE India were sequenced for 636 bp of the COII gene. No pseudogenes were present as evidenced by the absence of stop codons, the prevalence of synonymous substitutions, low pair-wise divergence and unambiguous electropherograms. All haplotype sequences from NE India have been deposited in GenBank (accession numbers GeneBank:HQ202747 to HQ202801 and GeneBank:HQ650203 to HQ650217). To this dataset 57 COII sequences from one population in Bangladesh (n = 6), two populations in Myanmar (n = 14)and three populations in Thailand (n = 37) were added from a previous study [A total of 176 individuals of FCT values decreased from k = 2 to k = 24 indicating an overall lack of genetically distinct population groups. However, the highest value of FCT was for k = 2 , in which population 14  was separated from all other populations, indicating that population 14 is substantially genetically distinct. There appears to be some genetic distinctiveness of some of the NE Indian populations as they separated one by one from k = 3 to k = 7 respectively . The two most genetically distinct populations, 14 and 15, are adjacent to one another and not differentiated from each other  but there was no discernable spatial pattern among the other genetically distinct populations. From k = 8 onwards FSC was negative indicating no further discernable differentiation among populations within the large group of remaining populations. Up to k = 16 the six populations from Bangladesh, Myanmar and Thailand always grouped together further highlighting the distinction between them and the NE Indian populations.In the SAMOVA analysis, the ST among the eight population groups revealed some population structuring at a large spatial scale with the Bangladesh, Myanmar and Thai populations being significantly differentiated from two, three and four of the five NE Indian populations, respectively  and differentiated from all other NE Indian groups with the exception of the West NE Indian population group (p = 0.07).Since SAMOVA was unable to detect obvious population clusters, in order to detect any subtle levels of genetic differentiation using larger sample sizes, samples from all 32 locations were grouped based on their geographical proximity into eight population groups: five population groups from NE India and one population each from Bangladesh, Myanmar and Thailand Figure . AnalysiWhen lineage diversity is high, as here, it can be hard to detect differentiation since populations tend to comprise alleles from genetically divergent lineages. Since there was some indication from the SAMOVA of genetic distinctiveness within the NE Indian region the Spatial Analysis of Shared Alleles (SAShA) method  was usedAn. baimaii are presented in Table An. baimaii with overall values of haplotype diversity (hd) of 0.950 ± 0.012, nucleotide diversity of 0.0057 ± 0.0003 and θs of 0.0091 ± 0.0037. Within NE India the genetically distinct Central 2 population group was similarly genetically diverse to most other groupings but the Central 1 population had markedly lower values of the genetic diversity indices.The genetic diversity and θ estimates for the eight populations of p = 0.27 and SSD 0.026; p = 0.30). It should be noted that all these tests do not distinguish demographic expansion from a selective sweep of mtDNA, which is an expansion of a population of molecules carrying a favoured mutation. The start time of population expansion under the sudden expansion model was estimated using the same mutation rate as in earlier studies to enable a direct comparison with previous estimates for a single NE Indian population of An. baimaii [Anopheles, the estimated expansion time should be considered as very approximate. It was found that An. baimaii in the NE India expanded approximately 0.243 million years before present (MYBP) (95% CI 0.11-0.39) is in broad agreement with the earlier estimates from a single population of about 0.30 MYBP.The neutrality test statistics Table  were fou baimaii ,20. HoweAn. baimaii using the PCR-based identification method (see Methods) of Walton et al [The median joining haplotype network has an overall star-like topology Figure . There aon et al  based onAn. baimaii in NE India with sampling spanning all seven states. In agreement with earlier studies it was found that An. baimaii in NE India had substantially higher molecular diversity (i.e. θs and nucleotide diversity) than populations in Bangladesh, Thailand and Myanmar. This is in accord with NE India being the origin of all extant populations of this species [This is the first extensive study of  species . A furth species  and refs species . The the species ,53 as hi species .An. baimaii throughout NE India but, as shown by the haplotype network  but not on a smaller spatial scale (i.e. within NE India) consistent with isolation by distance on a regional scale. However, as there are relatively few sample sites outside of NE India, the possibility that the apparent isolation by distance is due, at least in part, to successive geographical barriers to gene flow cannot be excluded. For example, the Shan Plateau and Tenasserim mountain range with altitudes of up to 1,000 metres that separate Thailand and Myanmar are a likely barrier to dispersal. This is concordant with the observation of no isolation by distance observed within NE India despite the considerable distances involved and the lack of high mountains between the sample sites. Similarly, a previous study using nuclear loci  found noWithin NE India, the population groups sampled appeared to be somewhat geographically isolated, with a lack of suitable intervening habitat . Despite this, very little genetic structure was apparent, counter to the original hypothesis stated. Instead, the very high genetic diversity and lack of structuring  indicate large effective population sizes and genetic homogeneity. Given the low sample size of the Central 2 population group  further sample collection and genetic analysis should be done to confirm its genetic distinctiveness. However, the high levels of significance found here indicate that Central 2 really is genetically distinct. In addition, there were also some other indications of isolation among the NE Indian populations: the splitting off of several NE Indian populations from k = 2 to k = 7; and the low genetic diversity of the Central 1 population that indicates it has undergone a genetic bottleneck and became isolated.An. baimaii populations throughout NE India and that the slight signals of genetic isolation result from recent human-mediated forest fragmentation.Forests in NE India were until recently contiguous with lowland semi-evergreen forests throughout the Bramaputra valley merging into sub-Himalayan light alluvial semi-evergreen and secondary wet mixed forests in the hilly regions . Large sAn. baimaii and malaria transmitted by it is a challenging task in areas of its influence, due to its predominant exophagic and exclusive exophilic behaviour, along with its efficient vectorial capacity. Lack of genetic structure and presence of genetic homogeneity, as observed here, may be the likely reasons for its universally efficient vectorial status in this part of India. Use of insecticide treated nets (ITNs) in combination with repellents have been found very effective in controlling malaria transmitted by An. baimaii in the north-east India [An. baimaii in this region is susceptible to DDT  and pyrthroids (used in ITNs) [Control of st India . At presin ITNs) , but in Anopheles baimaii populations from NE India are more genetically diverse and genetically distinct from An. baimaii in the rest of Southeast Asia; the latter likely as a result of high elevations being a barrier to gene flow. Therefore it should not be assumed that biological features recorded for An. baimaii in one region of Southeast Asia necessarily apply to An. baimaii in another region. For example, it was noted that some populations in Myanmar differ with respect to larval habitat choice, breeding in wells in villages rather than in groundwater in the forest [An. baimaii such as breeding, biting and resting behaviours, response to insecticides, and malaria transmission, appear to be uniform throughout much of the region [An. baimaii are needed in the Barail hill range of the NE India to determine if the genetic distinctiveness of the Central 2 population corresponds to any changes in biological traits that affect malaria transmission or vector control. It is important to note that in the Central 2 population areas An. baimaii occurs sympatrically with the closely related, recently reported species × of the An. dirus complex [e forest ,60. Withe region ,16,61, c complex . FurtherThe findings of this study highlight the difficulty of detecting recent structuring in populations when there are very high population sizes and high genetic diversity, as multiple divergent lineages occur in all locations and there will be a substantial time lag before haplotype frequencies vary between populations. The extent of ongoing  gene flow is needed for vector control but determining this will be challenging. It will require the use of multiple markers combined with innovative analytical approaches to provide the power needed to distinguish ongoing gene flow from the potential confounding effects of demographic history.The authors declare that they have no competing interests.This study forms part of the PhD thesis work of DKS. DKS collected mosquitoes, performed the data analysis and drafted the manuscript. DKS and SMO'L performed molecular analyses including PCR and DNA sequencing of the COII gene fragment. AP helped in the field collections, data analysis and in preparation of manuscript. DRB, NPS and SS helped in mosquito collections. KD and KB performed the molecular identification work. PKM and GUA helped in drafting of the manuscript. AP, JM and CW participated in the design of the study, data analysis, draft of manuscript, general supervision of the research group and fund acquisitions. All authors read and approved the final documents.