Results from neutrality tests, along with observations of elevated diversity and low differentiation across populations, supported previous genus-level evidence for balancing selection at these loci. Despite being low, MHC divergence across populations was significant and may be attributed to drift effects typical of geographically separated populations experiencing little to no gene flow, or alternatively to shifting allele frequency distributions driven by spatially variable and fluctuating pathogen communities. At the DRA, zebra exhibited geographic differentiation concordant with microsatellites and reduced levels of diversity in Etosha due to highly skewed allele frequencies that could not be explained by demography, suggestive of spatially heterogeneous selection and local adaptation. This study highlights the complexity in which selection affects immune gene diversity and warrants the need for further research on the ecological mechanisms shaping patterns of adaptive variation among natural populations.Demography, migration and natural selection are predominant processes affecting the distribution of genetic variation among natural populations. Many studies use neutral genetic markers to make inferences about population history. However, the investigation of functional coding loci, which directly reflect fitness, is critical to our understanding of species' ecology and evolution. Immune genes, such as those of the Major Histocompatibility Complex (MHC), play an important role in pathogen recognition and provide a potent model system for studying selection. We contrasted diversity patterns of neutral data with MHC loci, ELA Spatiotemporal fluctuations in pathogens generate complex patterns in the distribution of gene variation among host populations. Pathogens affect hosts not only by driving changes in population size, but also by eliciting an evolutionary response in host immune genes. Stochastic demographic factors  influence, in the same way, rates of gene flow and genetic drift at all loci in an organism's genome The Major Histocompatibility Complex (MHC) is a family of genes that plays a critical role in vertebrate immune function. Class II MHC genes encode cell-surface glycoproteins, with peptide binding regions (PBRs) that are responsible for recognizing foreign antigens from extracellular pathogens (e.g. eukaryotic parasites and bacteria) and presenting them to helper T-lymphocytes to elicit an immune response. These genes typically exhibit elevated levels of polymorphism and highly divergent variants have been shown to persist over long time periods, even through the course of speciation events i) overdominant selection ii) frequency-dependent selection iii) fluctuating selection The mechanism by which pathogen-mediated balancing selection maintains diversity in MHC genes has been extensively debated in the literature Equus quagga) experience spatiotemporal variability in pathogen pressures across localities  parasites, found in the population at nearly 100% prevalence DRA and DQA PBR within zebra populations differing in parasite richness and severity  and South African National Parks, South Africa . All field sampling was conducted in accordance to the requirements and guidelines outlined. The sample collection protocol was also approved by the Animal Care and Use Committee (Protocol #R217-0510B) at the University of California, Berkeley.E. quagga populations of southern Africa: Etosha National Park, Namibia (n = 84), and Kruger National Park, South Africa (n = 89). Fecal samples were collected immediately following defecation and could be attributed to individual zebra. Sample preservation and genomic DNA extraction protocols are outlined in Kamath & Getz Blood, tissue and fecal samples were collected from two From 2000 through 2012, Etosha zebra population abundance was estimated from aerial survey data as being relatively stable, fluctuating between approximately 13,000 to 16,000 individuals . In Kruger, zebra population surveys from 1980 to 1993 similarly indicate that abundance was stable, ranging between 21,454 to 33,164 individuals per year, estimates that may only represent 60–85% of the true population size -DRA and -DQA were amplified from genomic DNA following PCR and sequencing reaction protocols described in Kamath & Getz DRA and DQA, respectively. We sequenced loci in forward and reverse directions to confirm heterozygous base positions. Sequence chromatograms were edited and aligned manually using Geneious 5.0 DRA heterozygotes was determined with the haplotype reconstruction program, PHASE v2.1 The exon 2 coding regions of the ELADQA locus is known to be highly variable and our data may represent alleles from two loci DQA sequences as ‘alleles’ despite the possibility they may come from the different loci. To identify alleles in heterozygous individuals, molecular cloning was carried out using a TOPO-TA® cloning kit with Mach 1™ T1R competent cells (Invitrogen). We minimized polymerase errors, heteroduplex and chimera formation by using a high fidelity polymerase  in the initial PCR. Amplicons were run on a 1% agarose gel and visualized using GelStar® Nucleic Acid Gel Stain  and the Dark Reader transilluminator system  which does not damage DNA and also increases the transformation efficiency during subsequent cloning procedures. Bands were excised and purified using QIAquick Gel Extraction Kits (Qiagen), ligated into pCR®4 TOPO vectors and transformed into E. coli competent cells. Following an overnight incubation at 37°C, sixteen to twenty-three positive clones were picked per individual and clones were directly sequenced using the same primers as in the initial PCR. Alleles were confirmed with at least two observations . Sequences not meeting these criteria were considered to be erroneous and not considered in subsequent analyses.The Fibrinogen beta chain gene, intron 7 (β-Fibr) appears to be evolving neutrally and has been demonstrated to be an informative marker for systematic and evolutionary studies in both birds and mammals β-Fibr with primers developed using the publicly-available horse genome and Primer3 β-Fibr10 (5′-CAGTAGTATCTGCCGTTTGG-3′) and β-Fibr11 (5′-GAGGGCGACAAATACCAAC- 3′) (The AAC- 3′) . AmplifiEquus callabus)  . Forwardn = 42) obtained from zebras in Etosha.A portion of the samples were derived from feces, and thus were expected to be subject to high genotyping error rates and allelic dropout. To account for these issues, we used a comparative genotyping protocol Fisher's exact tests for Hardy-Weinberg (H-W) equilibrium and genotypic linkage disequilibrium (LD) between pairs of loci were conducted in GENEPOP 4.0 A) and expected heterozygosity (HE) at all loci using GenAlEx 6.2 ACORR) in HP-RARE 1.1 β-Fibr, DRA, DQA) in terms of number of segregating sites . APD was calculated based on the average percentage of sequences that differ among all possible individual pair-wise comparisons, as outlined in Yuhki and O'Brien DRA and β-Fibr loci. As diversity data was not normally distributed, we used a non-parametric Kruskal-Wallis rank randomization test to test the null hypothesis of group-mean equality. Differences in variance between population samples were addressed by a Levene test based on absolute residuals of each observation to the respective population mean. A Wilcoxon sign-rank test (Z test) was performed to account for unequal variance between population samples in group-mean comparisons. In addition, we tested for differences in the distribution of DQA allele number per individual across populations through goodness-of-fit contingency analyses, with significance assessed through calculation of the Chi Square statistic (2χ). All statistical analyses were performed using JMP 4.0 (SAS Institute Inc.) software. As we found greater than two alleles in only a small number of individuals (n = 10), we also conducted all analyses excluding these individuals to confirm observed patterns in the data.Given that the eles see . HomozygF-statistics  in FSTAT v2.9 FST values derived from the nuclear intron, β-Fibr. Population divergence was further assessed by global exact tests of differentiation .Selection may affect the distribution of mutations and frequency of alleles within and among populations. Therefore, comparing the population differentiation observed at functional and neutral loci may be informative for understanding the nature of selection cs FST: . The FSFST and its family of analogs have been shown to approach zero , sometimes even among fully differentiated subpopulations D actual differentiation estimator, DestDest, we reported the harmonic mean across all loci.As the variability of a genetic marker increases, estimates of DQA locus, population allele frequencies used in FST computations are potentially biased due to overestimation of rare allele frequencies (as discussed previously). Therefore, we calculated a measure of differentiation F′ , to account for this bias in allele frequencies. This measure is derived from the similarity index F′ were estimated by applying a Taylor expansion approximation F′ were also estimated for the DRA and β-Fibr to validate comparisons of differentiation across loci.At the β-Fibr intron), and both ELA loci independently. The genetic clustering algorithm maximizes Hardy-Weinberg proportions, under a model allowing for population admixture and the assumption that alleles were correlated. We considered models that specified K = 1 through 5 genetic clusters and conducted 10 independent runs for each value of K, each totaling 1,000,000 MCMC steps . We inspected both the maximum log probability for a given model, Pr(X|K), and the rate of change in the log probability of the data between successive K values, ΔK, to determine the most probable number of genetic clusters given the dataset K using the program CLUMPP v1.1 DistructZebra population structure was further assessed using the Bayesian clustering algorithm in the program STRUCTURE v2.3 β-Fibr sequence data in Arlequin 3.5 We constructed mismatch distributions using the θ), a measure of diversity proportional to the effective population size (eN) and mutation rate (μ) such that (θ = 4eμN) and (2) the exponential growth rate parameter  relative to the neutral mutation rate representing the direction and magnitude of change in population size. A Metropolis-coupled MCMC approach was employed for each run (using one cold chain and four heated chains). Acceptance rates fell between 5 and 40%, probability density functions were inspected for unimodality, and effective sample size (ESS) were confirmed to be >200 using Tracer v1.5 Historical changes in zebra population sizes were characterized with a coalescent-based model in LAMARC v2.1.5 β-FibrPast population dynamics were inferred using intron data with the Bayesian Skyline Plot (BSP) model in BEAST v1.6 Fobs) with the expected homozygosity (Fexp), based on a random sample of the same size consisting of the same number of alleles, simulated under the assumption of neutrality. Tajima's DFSD and FS are analogous to the E-W test, but because they are based on sequence data can also reflect historical selective pressures or demographic changes. FS measures the probability of observing a certain number of alleles given the average pair-wise sequence divergence (θ), whereas Tajima's statistic contrasts the observed θ to that which would be expected under neutrality given the number of segregating sites (S). Negative values for both statistics imply population expansion or purifying selection, and positive values suggest either a population bottleneck or balancing selection. To tease apart signatures of demography and selection, we contrasted neutrality test results to those performed on β-Fibr. In addition, allele frequency distributions at neutral and functional loci were statistically compared across populations with contingency analyses in JMP 4.0 (SAS Institute Inc.).Hypothesis testing was conducted to check for significant departures from neutrality at ELA loci using approaches that reflect both recent and historical processes. All tests were conducted in Arlequin 3.5 ω = dN/dS) at coding genes  using maximum likelihood models of codon-substitution in the CODEML subroutine of PAML 6 (Kimura 2 parameter with 6 gamma-distributed rate categories) nucleotide substitution model as determined by jModelTest To characterize molecular-level evidence of selection, we estimated rates of non-synonymous to synonymous mutations  were incorporated  to evaluate the ancestral state of E. quagga haplotypes.We inferred phylogenetic relationships among sequence haplotypes by constructing a median-joining haplotype network E. quagga were highly polymorphic, with a mean of 9.0 alleles per locus (range: 3–15) in the Etosha zebra population and 7.1 alleles per locus (range: 3–12) in Kruger  between Hmb1 and Htg14 in Etosha, but not in Kruger. In addition, results from exact tests by locus and population indicated significant (p<0.001) heterozygote deficiency at Hms7 and Htg15, in Etosha only. We note that these observations may be due to the presence of null alleles. However, mean null allele frequency (NAF) by locus was estimated to be low   were recovered in Etosha and Kruger zebra populations. Twenty-one DQA alleles   were also found. Population patterns of allelic richness were analogous with and without the correction applied for unequal sample sizes.Ten novel alleles were discovered at the DQA locus, there was on average 1.56 (range: 1.31–1.80) and 1.77 (range: 1.46–2.07) alleles per individual in the Etosha and Kruger zebra populations, respectively. Less that 15% of samples cloned were found to have more than two alleles, and therefore the majority of our DQA data is likely derived from one locus. There was no evidence for significant differences in copy number frequency distributions across populations  were high when contrasted to β-Fibr intron data  and allele frequency-based (EH) indices  . In contrast, DRA differentiation was not significantly different from FST estimates observed at microsatellite loci . Analyses of β-Fibr genetic structuring indicated substantially higher differentiation across populations  and supported the observation that low differentiation at ELA loci may be indicative of balancing selection acting on these genes. These results were corroborated by estimates of the FST analog, F′ (Dest) followed a similar pattern to that indicated by the patterns of FST across loci  and highest ΔK, with individuals from Etosha clustering separately from those in Kruger . The model of sudden population growth was rejected in Kruger, but with marginal significance . As significance is borderline for both populations, mismatch results are inconclusive. However, in both Etosha and Kruger the population expansion model could not be rejected as indicated by relatively low, non-significant estimates of the Harpending's raggedness index .Mismatch distribution analyses of the neutral intron indicated a weak signature of population expansion in the Etosha zebra population, as the null model could not be rejected  generations−1. Although positive, the magnitude of g is extremely small and may indicate populations that are in the process of stabilization. The most probable estimate of the diversity measure, θ, was identical across populations, estimated to be 99.3 (84.8–100.2) and 99.3 (83.0–100.1) in Etosha and Kruger, respectively. Bayesian skyline plots, based on an independent dataset, confirmed that these zebra populations are both large, and have similarly experienced stability in the recent past  in Etosha was 0.302 (0.253–0.549) generationsent past .D and Fu's FS tests for departures from neutrality were not significant (p>0.05) at all loci and populations (Fobs) than would be expected under a neutral model, supporting the hypothesis that balancing selection is occurring at ELA loci. However, when multi-locus genotypes are excluded at the DQA, these results become non-significant. Significance of E-W tests, but not D or FS, implies that selection at these loci is possibly a relatively recent phenomenon.Tajima's ulations . Althougβ-Fibr by population. The most outstanding observation was that DRA allele frequencies were evenly distributed in Kruger, but skewed in Etosha . In particular, the DRA*03 allele was predominant in Etosha, representing approximately 44% of all alleles observed which could potentially be driving the decreased diversity found at this locus. Contingency analyses also suggested significantly different allele frequency distributions at the DQA locus . DQA distributions differed in the large number of rare and private alleles found in each population . β-Fibr allele frequency distributions were also significantly different  between populations, with Kruger exhibiting a more skewed distribution  comparing models of invariable versus variable evolutionary rates across codon sites (M3 vs. M0) and models of positive selection to neutral evolution (M7 vs. M8) were significant (p<0.05) in both populations. While estimates of ω across the DQA gene region were close to 1 in both populations , approximately 40% of codon sites were determined to be under significant positive selection (ω = 2.52).Molecular-based analyses revealed no evidence for positive selection or variable rates of selection at the molecular level of the ulations . In contβ-Fibr allele from E. callabus differed by one mutational step from the most frequent allele observed in E. quagga (β-Fibr*01). At the DRA, four E. callabus alleles were ancestral to the Eqbu-DRA*10 and Eqbu-DRA*11 alleles in E. quagga. However, one allele was shared between the two species (Eqbu-DRA*08 = Eqca-DRA*04). At the DQA, there were large mutational differences observed between alleles, and E. callabus alleles were found distributed throughout the network.Phylogenetic median-joining haplotype networks of ELA loci showed a lack of geographical allele structuring by population . The β-FE. quagga populations. Our results suggested that selection is acting variably across MHC genes and populations in zebra.This study juxtaposed MHC with neutral data to disentangle the co-occurring effects of selection and neutral evolutionary processes  on the distribution of immunogenetic variation across g) from this study that indicated effective population trajectories are similar in Etosha and Kruger zebra and suggested historically stabilized populations with the possibility of low, positive growth. Given census estimates, we expected neutral genetic diversity to be higher in Kruger due to a population size that is approximately twice as large as Etosha. In contrast, we found the opposing pattern, with neutral diversity being higher in Etosha. This discrepancy could be due to sampling artifacts from differences in survey approaches and observer bias across parks, or it is possible there is subdivision within the Kruger zebra population and our genetic data represent only a portion of this population. To date, however, there has been no genetic study in zebra documenting the degree of population mixing throughout Kruger.Demography and migration dynamics may confound our ability to detect selection. We used neutral data to elucidate population history and extricate the role of these processes in shaping immune gene variation. Population size estimates from plains zebra in Kruger (1980–1993) FST = 0.04). This finding is in agreement with a recent phylogeographic study on five subspecies of E. quagga that showed zebra population structuring is among the lowest of 17 different savannah-adapted ungulate species in Africa  β-Fibr intron , however, was higher than that based on microsatellites (FST = 0.04). This discrepancy between nuclear markers suggests further inquiry into the possibility that our assumption of the neutrality at the β-Fibr intron has been violated. Alternatively, the differences observed between structure as inferred from microsatellite and intron loci may be due to differences in the mutational modes and rates of these markers At microsatellite loci, genetic differentiation across zebra populations was relatively low  mirrored FST results in comparisons of ELA loci with the β-Fibr intron, suggesting that the pattern may also be upheld. Furthermore, STRUCTURE results using neutral data revealed clustering of individuals by population, in contrast to the lack of geographic clustering observed at both ELA loci.Under balancing selection, due to similar pathogen regimes across populations, we would expect low population differentiation at MHC loci relative to neutral loci due to theoretically greater effective migration rates DRA locus was comparable to estimates at microsatellite loci. A similar observation was made at the DRA locus among domestic donkey (E. asinus) populations i) local adaptation, (ii) weak selection acting on the MHC locus, or (iii) an artifact of using genetic markers evolving under different mutational modes and rates DRA relative to the β-Fibr locus, akin to our observations at the DQA locus, indicates that a difference in the mutation model may be responsible for the discrepancy. But, the lack of a similar observation at the DQA may alternatively suggest that local adaptation is occurring at this locus. We note, however, that our inferences regarding demography based on a single locus must also be taken with caution.Differentiation at the FST and global exact tests. The evolutionary process of genetic drift may be affecting ELA differentiation, albeit weakly, by stochastically shifting allele frequency distributions within populations. This is parsimonious with an expectation of little to no recent gene flow between these two populations, as they are contained in parks and separated by more than 2,000 km of a human-dominated matrix. An alternative explanation (to that of genetic drift) is that variable pathogen pressures across the localities and over time may be driving distributional shifts in ELA allele frequencies across populations.Despite being low, ELA population differentiation remained significant, as indicated by pair-wise E. quagga population in Etosha exhibited higher genetic diversity than Kruger at all neutral loci. This pattern was fairly consistent, regardless of the diversity index evaluated. In contrast, DQA population diversity patterns are generally similar across populations. It is possible that balancing selection may be preserving similar levels of DQA diversity due to equivalently high pathogen diversity across populations. Interestingly, DRA genetic diversity across populations is strikingly incongruent with that observed at neutral loci, revealing depressed variability in Etosha. Allele frequency distributions showed that the paucity of diversity at this locus in Etosha is driven by the presence of one predominant allele. In contrast, Kruger zebra possessed many of the same alleles, but frequencies were relatively evenly distributed. Opposing DRA and neutral diversity patterns across populations provides evidence for geographically heterogeneous selection at the DRA. Pathogen-mediated selective pressure may differentially affect these two loci because of differences in their functional role (i.e. differences in the specific pathogens that these antigens are capable of recognizing).The DRA patterns across populations, with respect to neutral data, highlights the possibility that zebra in Etosha may be subject to local selective pressure by pathogens at this locus. Matthee et al.Specifically, the marked difference in Besides intestinal parasites, zebra in Etosha are also known to be severely affected by anthrax, a lethal infectious bacterial disease D and Fu's FS tests were unable to reject the hypothesis of neutral evolution; However, we recognize that the ability of these tests to detect selection depends on the nature of the mutational process and the duration, strength and timing of selection D and FS test statistics were generally consistent with positive selection at ELA genes and opposed values observed at the intron, indicating a putative weak selection signal. As these statistics reflect selection operating to change the site frequency spectrum, accumulation of such mutations may require long time periods extending beyond the history of a population. Whereas, the significant E-W tests recovered here support the conclusion that relatively recent balancing selection plays an important role in shaping allele frequency distributions within zebra populations. At the DQA locus, molecular selection analyses also suggested significant heterogeneity across the gene region and positive selection at approximately 40% of codon sites. Thus, while balancing selection is likely maintaining diversity at these genes, it is also possible that selection signatures have been obscured over time by fluctuating selective pressures due to changing pathogen communities or demographic events.Tajima's et al.Simulations by Ejsmond dN/dS ratios and MHC gene phylogenies) have provided genus-level evidence for balancing selection acting on both the DRA and DQA loci in equids i) elevated ELA diversity over neutral diversity within populations, (ii) low genetic structure across populations relative to that observed at neutral loci, (iii) significant rejection of the null hypothesis of neutrality based on the assumption of mutation-drift equilibrium, and (iv) evidence for heterogeneous rates of evolution across codon sites, with significant positive selection occurring at specific sites (only at the DQA). These combined findings provide convincing evidence for balancing selection operating on ELA genes in zebra. However, the somewhat differing patterns observed at the DRA across populations also suggest that there may be heterogeneous selection pressures and local adaptation operating at this locus.The hypothesis that balancing selection preserves MHC diversity is well accepted and supported in the literature DRA locus— two findings which are compatible when considering different time and spatial scales. These results highlight the importance of integrating neutral and adaptive data over different scales to uncover the relative effects of demography and selection in shaping functional diversity. Future ecological studies are warranted that investigate the link between host immunogenetic diversity and pathogen community structure to better understand the mechanisms underlying adaptation.MHC studies in natural populations are critical for understanding adaptation and evolutionary potential, as variation in these genes reflect biologically relevant processes significant to fitness. Patterns of MHC variation are shaped by a complex interplay of selective and demographic factors, which may be challenging to disentangle, but possible to achieve through the amalgamation of multiple lines of evidence. Our data suggest that selection on MHC genes may vary spatially, and also differ by locus. Balancing selection over evolutionary time scales may act cumulatively to retain MHC diversity, but this selection signature may be obscured due to fluctuating and diverse pathogen communities. We found evidence for balancing selection at MHC genes in zebra populations, but we also conclude heterogeneous selection may be acting across populations at the Protocol S1Polymerase Chain Reaction protocols for neutral loci. PCR reagents and cycling conditions used to amplify the β-Fibrinogen, intron 7 and microsatellite loci: Aht21, Asb23, Cor014, Hmb1, Hms7, Htg7, Htg9, Htg14, Htg15, Lex20, Lex33, Lex52, Ucdeq505, Um011, and Vhl47.(DOC)Click here for additional data file.Figure S1Flowchart of comparative microsatellite genotyping approach. This approach involves comparing two to three initial replicate PCRs, with heterozygotes confirmed in two PCRs and homozygotes in three PCRs. If a disagreement is found  additional PCRs were performed until each allele is observed a minimum of two times. In the event that no consensus was found, an individual was either scored as having a missing genotype or given a half-locus genotype, by assigning one allele as missing data. In summary, a minimum of 2 PCRs is required to confirm a heterozygote genotype and 3 PCRs for a homozygote, with a maximum of up to 7 PCRs conducted. Adapted from Hansen et al.(TIF)Click here for additional data file.Figure S2Frequency distribution of ELA-DQA copy number.DQA copy number frequency distribution in individuals from Etosha (black) versus Kruger (gray). One to four alleles were observed in each individual. Contingency goodness-of-fit analyses revealed no significant difference between population frequency distributions .(TIF)Click here for additional data file.Figure S3ELA-DQA allele frequency distributions, including alleles from multi-locus genotypes. Alleles are presented in descending order and by population, with Etosha in black and Kruger in gray.(TIF)Click here for additional data file.Table S1Populations sampled and individuals successfully genotyped at each locus. Loci investigated include microsatellites (μsats), β-Fibrinogen intron 7 (β-Fibr), ELA-DRA exon 2 (DRA), and ELA-DQA exon 2 (DQA). The number of confirmed alleles found in each population is reported, with that for μsats reported as the mean (standard error) of 15 loci. Over both populations, typing success ranged from 41–71% per locus.(DOC)Click here for additional data file.Table S2Description of microsatellite loci. Includes total number of alleles, observed size range in base pairs (bp), fluorescent label used for genotyping analyses, annealing temperature used in polymerase chain reaction (PCR), and the reference study in which it was initially discovered in E. callabus.(DOC)Click here for additional data file.Table S3Microsatellite diversity by locus and population. For each population, diversity by locus and total mean diversity are reported. Diversity is described in terms of number of alleles (A), observed heterozygosity (HO), and expected heterozygosity (HE). Sample sizes (N) are reported for each locus and population. Significant departures from Hardy-Weinberg equilibrium are indicated in boldface.(DOC)Click here for additional data file.Table S4Microsatellite null allele frequency and genotyping error rates. Null allele frequency (NAF) was estimated by population and locus. Total genotyping error rates, broken down by allelic dropout and false allele generation, were determined by paired genotyping of blood and fecal samples from individual zebra captures. All rates marked as “0” represent values of 0.000.(DOC)Click here for additional data file.Table S5Results from clustering analyses in STRUCTURE. Analyses were conducted over 10 runs of K = 1 to 5, combining all neutral data (13 microsatellites and the β-Fibr intron) and, separately, at each ELA locus. The mean posterior log probability (Mean L(K)), standard deviation (SD L(K)), mean difference between successive likelihood values of K (L′(K)), absolute value of the difference between successive values of L′(K) (|L″(K)|), and second order rate of change of the likelihood function with respect to K (ΔK) are reported. The best-fit models are highlighted in bold, and were selected based on mean posterior probabilities and following the approach described by Evanno et al.(DOC)Click here for additional data file.


Plasmodium falciparum populations in Africa where most infections occur.Malaria parasite population genetic structure varies among areas of differing endemicity, but this has not been systematically studied across P. falciparum microsatellite loci were genotyped in 268 infections from eight locations in four West African countries , spanning a highly endemic forested region in the south to a low endemic Sahelian region in the north. Analysis was performed on proportions of mixed genotype infections, genotypic diversity among isolates, multilocus standardized index of association, and inter-population differentiation.Ten polymorphic FST values < 0.03), and an overall test for isolation by distance was not significant.Each location had similar levels of pairwise genotypic diversity among isolates, although there were many more mixed parasite genotype infections in the south. Apart from a few isolates that were virtually identical, the multilocus index of association was not significant in any population. Genetic differentiation between populations was low (most pairwise Although proportions of mixed genotype infections varied with endemicity as expected, population genetic structure was similar across the diverse sites. Very substantial reduction in transmission would be needed to cause fragmented or epidemic sub-structure in this region. Plasmodium falciparum causes an annual burden of hundreds of millions of episodes of clinical malaria, and between approximately 0.5 and 1.5 million deaths, mostly in endemic populations of sub-Saharan Africa [1 − ∑p2, where n is the number of isolates analyzed and p represents the frequency of each different allele at a locus. He has a potential range from 0  to 1 .For each locus in each individual isolate, the predominant allele  or the only allele  was counted for population genetic analyses. Summary indices including numbers of alleles, allelic diversity within each population, and allele frequencies per locus per population were calculated using FSTAT Version 2.9.3.2 (updated from ). AlleliIAS) was calculated, based on genotypic profiles of the majority allele at each locus in each infection, using the LIAN version 3.5 Web interface [IAS = 1/L-1(VD/ VE-1), where L is the number of loci used, and the variance (VD) in pairwise numbers of mismatched alleles between isolates was compared with that expected under linkage equilibrium (VE) by simulation of data by 10000 iterations under the null hypothesis of VD = VE by Monte Carlo random sampling [For isolates that were fully genotyped at all 10 loci, analysis of multi-locus genotypic profiles of the isolate was performed, considering the majority allele at each locus in the case of mixed genotype infections. Pairwise comparisons among all isolates within each population were performed using Splitstree  to genernterface . This insampling .FST) computed with FSTAT, and a test for isolation by distance was performed from the pairwise genetic distances and geographical distances between populations, using a Mantel test of matrix correlation  [The level of genetic differentiation between the populations was calculated using fixation indices (program) .TA42) to 24 (for locus Polyα). For each of the 268 isolates, the genotype profile is listed in Additional file TA42 which was genotyped in 76.9% of isolates)  from the distribution of allele frequencies, and was similar across all the sites, with averaged values across the loci between 0.72 (for Richard Toll) and 0.80 (for Caio) , and tended to be higher at sites in the south Figure . In partIAS) test, significant values were detected in five of the populations .Most isolates had complete genotype data for all loci, and in these the multilocus profiles were examined, considering the majority allele at each of the ten loci. Almost all isolates differed from each other at most loci, and for each population the median number of loci with matching alleles in pairwise comparisons was only two out of 10 Figure . Howeverns Table , but aftnt Table . As manyfections . Here, tFST values were low, ranging from not significantly greater than zero for many population pairs, through to FST = 0.065 (P = 0.048) between Richard Toll and Caio . However, the northernmost site at Richard Toll tended to be more divergent from the rest of the populations  were at very low frequencies  [Across a marked gradient in transmission intensity among West African locations sampled here, the parasite populations show remarkably similar population genetic structure. There was a high allelic diversity for the ten ountries ,33. Althountries  and a hiountries , a much mission) .P. falciparum genotypes detected per infection varied among the populations studied, with highly mixed infections at each of the sites in Guinea which experience high transmission for much of the year, in contrast with sites having limited seasonal transmission further north in the region. This substantial difference is likely to be due to differences in endemicity as predicted, rather than confounding due to differences in sampling. Samples from five of the sites were from clinical cases presenting to health facilities, and those from the remaining three sites were from community sampling of asymptomatic individuals, but the latter sites were in the middle of the range geographically and in terms of proportions of mixed genotype infections, so this did not cause the observed north–south contrast in values. Review of comparisons elsewhere between asymptomatic and symptomatic infections also shows no consistent overall difference in proportions of mixed genotype infections [As expected, the mean numbers of fections -40.P. falciparum isolates are sometimes seen as multi-locus genotypes persist through a number of self-fertilisation and transmission cycles. This has allowed comparisons of identical versus non-identical pairs of clones for estimation of phenotype heritability in a manner analogous to a conventional twin-pair study [The multi-locus index of association analysis initially indicated non-random patterns in several populations, but this was shown to be entirely due to only one or a few pairs of virtually identical isolates. In South American and Southeast Asian populations of low endemicity, identical ir study ,42. In Air study . It has ir study , and occir study . Such idAs was seen here, it has elsewhere been shown that inclusion of a very small number of closely related parasite genotypes can generate a significantly non-random multi-locus index of association, even when there is no linkage disequilibrium among the loci in the population generally . Such ocP. falciparum, with most pairwise FST values being less than 0.03. This is considerably less than the differentiation among local sites within non-African countries that are less endemic, including Malaysia [FST values exceeding 0.10 between sites separated by similar distances. It is instead consistent with previous sampling from more widely separated African populations, which has shown FST values of less than 0.05 for a similar set of microsatellite loci [Over the sampled range of up to ~ 1200 kilometers between sites in West Africa, this microsatellite analysis found very low levels of genetic differentiation between the local populations of Malaysia , Papua NMalaysia , the PhiMalaysia , and BraMalaysia , with FSite loci ,16. Despite loci . In compP. falciparum populations has been clearly shown, providing a framework for future genomic-scale studies. Comprehensive analysis of genome sequence variation should allow finer differences in population structure to be detected [Despite studying only ten polymorphic loci and sampling a very limited number of isolates from some of the sites, marked variation in proportions of multiple clone infections and relatively similar genetic structure of detected , includiP. falciparum in West Africa showed there were more mixed parasite genotype infections in highly endemic forested areas in the south than in drier areas with lower transmission in the north, although each location showed similar levels of allelic diversity and pairwise genotypic diversity among isolates. Apart from a few exceptional pairs of isolates that were virtually identical, there was no significant multilocus index of association in any population, genetic differentiation between locations was low, and an overall test for isolation by distance was not significant. Substantial future reduction in transmission would be needed before fragmented or epidemic sub-structure in parasite populations is likely to be seen in this region. Given the high levels of recombination and minimal reproductive isolation of parasite populations in this region, genome-wide studies may detect differential signatures of selection against a background of neutral variation that is relatively spatially homogeneous.This analysis of ten microsatellite loci in The authors declare that they have no competing interests.VAM and DJC designed the experiments. VAM performed the experiments. VAM and DJC analysed the data. VAM, KML, ADA, JS, DCN, AA-N, and DJC provided materials and tools. VAM and DJC wrote the paper. All authors read and approved the final manuscript.Table S1. Alleles scored in each of the 268P. falciparumisolates genotyped at 10 microsatellite loci. Microsatellite alleles detected in isolates from the eight sampled populations, with highlighting showing predominant allele calls in the mixed genotypes.Click here for fileTable S2. Allele frequencies at 10 microsatellite loci in each of the eight population samples ofPlasmodium falciparum. Data on frequency of each allele scored for each microsatellite locus in each of the eight populations sampled.Click here for file


An accurate estimate of the divergence time between Native Americans is important for understanding the initial entry and early dispersion of human beings in the New World. Current methods for estimating the genetic divergence time of populations could seriously depart from a linear relationship with the true divergence for multiple populations of a different population size and significant population expansion. Here, to address this problem, we propose a novel measure to estimate the genetic divergence time of populations. Computer simulation revealed that the new measure maintained an excellent linear correlation with the population divergence time in complicated multi-population scenarios with population expansion. Utilizing the new measure and microsatellite data of 21 Native American populations, we investigated the genetic divergences of the Native American populations. The results indicated that genetic divergences between North American populations are greater than that between Central and South American populations. None of the divergences, however, were large enough to constitute convincing evidence supporting the two-wave or multi-wave migration model for the initial entry of human beings into America. The genetic affinity of the Native American populations was further explored using Neighbor-Net and the genetic divergences suggested that these populations could be categorized into four genetic groups living in four different ecologic zones. The divergence of the population groups suggests that the early dispersion of human beings in America was a multi-step procedure. Further, the divergences suggest the rapid dispersion of Native Americans in Central and South Americas after a long standstill period in North America. The genetic history of human populations, especially their colonization and migration, contains essential information for understanding the genetic structure of human populations as well as the genome landscape of human individuals. America is the continent most recently colonized by human beings. While mysteries about colonization in Eurasia and migration in Africa were partially clarified by genetic studies Migration models regarding the initial entry into America is one of the essential topics in genetic studies of Native Americans. Different migration models were proposed over the past few decades for the peopling of America when both archaeologic and genetic evidence suggested that populations related to Asians were the first successful colonizers to reach America during the last glacial maximum around 20 thousand years (kyr) before the present (BP) or even earlier The history of population dispersion after the initial colonization of Native Americans is less discussed while the debates on the origins and the time of the first Americans receives the most attention of geneticists. Coastal routes of early American migrations have been proposed in both mtDNA and STR studies. Wang et al. suggested least-cost paths in a coastal migration scenario including both Pacific and Atlantic coastal routes An understanding of the colonization and migration of Native Americans will depend on a good understanding of the genetic relationship of Native American populations. The genetic distance, a measurement of population divergence, is frequently applied to explore genetic affinity of human populations because the genetic distance has a linear relationship with the divergence time of pairwise populations in simple genetic scenarios Microsatellites (or STR), one commonly used genetic marker, can be fitted well by a molecular clock, and can therefore provide a reliable estimate of the time of population divergence whereas even a large-scale single-nucleotide polymorphism (SNP) dataset cannot A novel method was developed in this study to measure the genetic divergence of populations in complicated multi-population scenarios (see Methods for details). We addressed the performance of the novel method in two separate evaluations using simulated STR data.In the initial evaluation, performance of the novel method was examined for different sample sizes using 50 simulated STR datasets that were generated for a four-population demographic model . The resNe, see Methods for details). Five pairwise divergences among six observed populations (excluding the reference population) were estimated and the estimates were plotted against pre-given divergences using box plots  and effective population size  of the ancestral population (Popab) is the sum of the newborn populations’ Ne at divergence time t . Therefore, we have the equations below:To present the relationship of coalescent time of lineages and the populations’ divergence time in a Wright-Fisher model with two populations , we assua)EEE–(4) can be used to estimate demographic parameters (including population divergence time) when the expected coalescent times of two lineages within or between populations are available from Equation (1).aN, bN, and ABt) in a two-population model can be calculated (r) and expectations of the coalescent times (a)EEE(ξ) are known. In most studies however, the population growth rate is not known. To solve this problem, we introduced a reference population c with a known divergence time  simultaneously (results not shown).Using Equations (2)–(4), three of the four demographic parameters  was used as a robust estimate of the divergence ABt and distribution of the serial values supplied information about the reliability of the indicators. In other words, a four-population model  could be applied to estimate population divergence when multiple populations were involved.It is trivial to develop a model to include all populations when there are more than 20 Native American populations involved in our study. Therefore, we aimed to propose an explicit method that could be easily applied in scenarios with many populations. Model M3 could be transformed into a universal four-population model when we reassigned symbols  to the four populations see  because Following the same principles as that of Equations (2)–(4), we constructed a system of equations for the aforementioned four-population model . The sysDemographic parameters for 21 Native American populations were estimated in a two-stage procedure in this report. First, we estimated the population demographic parameters for all four-population combinations, including the Asian population reference and three other Native American populations. After that, the median of all the estimated divergences between each pair of Native American populations was used as a robust estimation of divergences between the paired populations.−4We evaluated the aforementioned method in two separate assessments using simulated STR data. The simulated STR data were produced from simulated sequences from MS using a strict stepwise mutation model ABt, ABCt, and ABCDt, respectively. The population growth rate was set to 0.001 in the simulations. The evaluation was carried out with a different sample size  and different locus number  on a total of 50 independent simulated data sets. Estimation bias was cautiously addressed using medians of 50 estimates and overall means of the medians. The 95% CI of the medians was used to assess the reliability of the estimates for each different sample size and locus number . Wang et al. excluded the relatives to reform data sets N379 and N354 −4 per generation for the involved tetra-repeat loci Expected coalescent times of pairwise lineages within or between populations were calculated using Equation (1) in this study. We used a mean mutation rate μ = 6.4×10Using Zhivotovsy’s methods, the empirical value of divergence time between Native Americans and Siberians (Tundra Nentsi population) was estimated to be 1536 generations with the upper bound 3721 generations Pairwise divergences of populations were estimated using the aforementioned multi-population method. For each population pair, we obtained 19 divergence values (estimation) in all, corresponding to calculations with different interference populations (Population X in model M3). A median of 19 results was used as the final estimate for divergence. The first and third quartiles of the 19 results supplied information for reliability of the final result. Neighbor-Net was constructed on the basis of the estimated divergences to present the genetic relation of the Native American populations. The Neighbor-Net caught more details than the tree-based presentation To further eliminate the uncertainty of the estimations, we divided the 21 populations into 4 population groups according to their genetic affinity and geographic locations. Divergence of the population groups was defined as the mean divergences of between-group population pairs. We constructed a UPGMA tree for the divergences of groups to present a historical pattern of sequential colonial events in the geographic regions.Text S1Effects of genetic admixture on the novel method.(PDF)Click here for additional data file.Text S2A system of equations based on the four-population model.(PDF)Click here for additional data file.


Haemonchus contortus (order Strongylida) is a common parasitic nematode infecting small ruminants and causing significant economic losses worldwide. Knowledge of genetic variation within and among H. contortus populations can provide a foundation for understanding transmission patterns, the spread of drug resistance alleles and might assist in the control of haemonchosis.H. contortus individual adult worms were collected from seven different geographical regions in China. The second internal transcribed spacer (ITS-2) of the nuclear ribosomal DNA and mitochondrial nicotinamide dehydrogenase subunit 4 gene (nad4) were amplified by polymerase chain reaction (PCR) and sequenced directly. The sequence variations and population genetic diversities were determined.152 nad4) among the 152 worms, with nucleotide diversities of 2.6% and 0.027, respectively, consistent with previous reports from other countries, including Australia, Brazil, Germany, Italy, Malaysia, Sweden, the USA and Yemen. Population genetic analyses revealed that 92.4% of nucleotide variation was partitioned within populations; there was no genetic differentiation but a high gene flow among Chinese populations; some degree of genetic differentiation was inferred between some specimens from China and those from other countries.Nucleotide sequence analyses revealed 18 genotypes (ITS-2) and 142 haplotypes (H. contortus in China. The results revealed high within-population variations, low genetic differentiation and high gene flow among different populations of H. contortus in China. The present results could have implications for studying the epidemiology and ecology of H. contortus in China.This is the first study of genetic variation within  Haemonchus contortus is a trichostrongyloid nematode and one of the major pathogens affecting small ruminants worldwide [orldwide . The aduorldwide . The bloorldwide , consequorldwide .H. contortus in the USA have shown that this species exhibits high within population variation and low genetic differentiation within continuous geographical regions, likely ascribing to high gene flow influenced by host movement [H. contortus within Brazil and Italy [Population genetic studies of movement ,6. Howevmovement . Other rnd Italy ,9.H. contortus have been conducted in a wide range of geographical regions of the world, including Australia, Brazil, Europe, Malaysia, and the USA [H. contortus in China, in spite of its endemic status and economic impact in this country [H. contortus from southwest, central and northeastern regions of China, employing the second internal transcribed spacer (ITS-2) of nuclear ribosomal DNA and the mitochondrial nicotinamide dehydrogenase subunit 4 (nad4) gene as markers.Population genetic studies of  the USA ,7-12. Ho country ,14. TherH. contortus were collected from the abomasa of slaughtered sheep or goats from seven geographical locations in tropical to subtropical climate zones and six provinces of China  were washed extensively in physiological saline, stored in 70% ethanol and then sent to the College of Veterinary Medicine, Huazhong Agricultural University, Wuhan. Upon arrival, individual worms were identified morphologically, according to Lichtenfels et al. (1994) [In total, 152 individual adult specimens of Total genomic DNA was isolated from individual worms using sodium dodecyl-sulfate/proteinase K treatment , followenad4 gene was amplified by PCR using primer1-F (5′-GGATTTGGTCAGCAAATTGAA-3′) and primer2-R (5′-GCCTGCAAATGAATTAACA-3′) [2, 250 μM each of dNTP, 100 pmol of each primer and 1 U Taq polymerase (TaKaRa) under the following conditions: initial denaturation at 94°C for 5 min, followed by 30 cycles of denaturation at 94°C for 30 s, annealing at 55°C for 30 s and extension at 72°C for 1 min, with a final extension of 72°C for 5 min.ITS-2 (~350 bp) was amplified using the conserved primers: NC1 (5′-ACGTCTGGTTCAGGGTTGTT-3′) and NC2 (5′-TTAGTTTCTTTTCCTCCGCT-3′) . A regioAACA-3′) . PCR (25All PCR products were examined on agarose gels (1.5%) to verify that they represented single bands, column-purified  and then sequenced directly  in an automated sequencer  using appropriate forward and reverse primers (in separate reactions). Forward and reverse sequences were merged, consensus sequences determined and then deposited in the GenBank database.nad4) using the program Clustal W within MEGA v.5.0 [Sequences were aligned over a consensus length (231 bp for ITS-2 and 412 bp for GA v.5.0 . PairwisGA v.5.0 .http://sing.ei.uvigo.es/ALTER/) was used to define haplotype sequences. The diversity indices (Fst and Nst) were calculated using the program DnaSP5.1 [D[nad4 sequences from previous studies [The phylogenetic analysis was conducted using the neighbour-joining (NJ), maximum parsimony (MP) and maximum likelihood (ML) methods, respectively, based on the Tamura -Nei model . ConfideDnaSP5.1  to evaluaSP5.1 [D and Fu’saSP5.1 [D were alsaSP5.1 [D. To estiaSP5.1 [D. For thiaSP5.1 [D was draw studies ,10 were H. contortus , revealing the nucleotide identities of 96.1 to 98.2%. The alignment of all 18 ITS-2 sequences with the reference sequence X78803 revealed six substitutions at the nucleotide positions  were defined (Table nad4). Among 142 unique haplotypes, 73 parsimony informative sites were identified. Nucleotide diversities ranged from 0.0178 to 0.0369, and the haplotype diversity ranged from 0.993 to 1.000 for the seven distinct populations of H. contortus  as the outgroup. The tree revealed a relatively continuous variation in genetic distance among haplotypes . Extending the analyses, to discern the relationships among 142 haplotypes, a parsimony network was constructed  [nad4 sequences, chosen randomly from the Chinese sample set and from each of the four other H. contortus populations representing other countries  were included  , ten nadd Figure . The thrnad4 haplotypes from Chinese samples across the parsimony network  was computed among populations. With the introduction of three-levels in the analysis, it was shown that 92.4% of the variance was distributed within populations and only 7.6% among populations  detected in H. contortus populations in various countries, such as Germany and Sweden/Kenya [nad4, the nucleotide diversities within each of the seven H. contortus populations in China ranged from 0.018 to 0.037, with an average nucleotide diversity of 0.027  and those from SZ, YD, GX, YN and SX (goat)  of genetic diversity was partitioned within populations of H. contortus from China, with no clear phylo-geographic structuring (with the exception of a subset of seven specimens from Yunnan), suggesting a high gene flow without clear geographical barriers among populations from different provinces. This proposal was supported by evidence of low pairwise Fst values between Chinese populations. The greatest nucleotide diversity within the H. contortus population from Yunnan, and the highest Fst values between this population and other Chinese populations, might relate to the fact that this province is particularly mountainous throughout, possibly preventing dispersal and gene flow.The genetic analysis of the H. contortus from China and the USA indicated a high genetic differentiation and less gene flow between these populations from two distinct continents. In contrast, the lowest genetic differentiation of Chinese specimens from those from Malaysia was reflected in the lowest pairwise Fst value. These results support a previous proposal that the global population genetic structure of H. contortus is characterized by no or low genetic differentiation between specimens from abutting geographical regions or within continents with limited barriers to gene flow, but significant genetic differentiation on a global scale (across continents) with substantial barriers to gene flow [On the other hand, on a global scale, the highest Fst value between ene flow .nad4 within populations of H. contortus to a large effective population size (Ne), high biotic potential, rapid, direct life-cycle and a high mutation rate in this polymorphic nematode [H. contortus infection are relatively high. An appraisal of key studies published in Chinese [H. contortus exists in at least 30 of the 32 provinces in China, and is the dominant intestinal parasitic nematode of sheep and goats, with prevalences ranging from 6.5% to 100% and infection intensities of at least 20–8000 worms per host. The movement of livestock throughout China is also common. Since 1978, the livestock industry has undergone an enormous transformation. By the end of 1996, the total numbers of goats and sheep reached 303 million head, and the number has increased by 78.5% since that time, with a high demand on the red meat market for lamb [H. contortus in China appear to be similar to those in other countries and studies.Previous studies have attributed a high degree of sequence diversity in the nematode ,9,29, wh Chinese -34 showsfor lamb . Taken tH. contortus relies largely on anthelmintics [H. contortus in China. Nonetheless, there are a small number of studies [H. contortus populations in China. As the level of gene flow among populations of H. contortus parasitizing goats and sheep in China was shown here to be very high, there is substantial opportunity for rare resistance alleles to spread, indicating an urgent need to conduct a nationwide investigation of drug resistance in H. contortus. Such a focus will inform the scientific and non-scientific communities about the prevalence and intensity of resistance, and should underpin future control efforts in China.As there is no commercial vaccine against haemonchosis in China, like elsewhere, the control of lmintics . Here, tlmintics . In spitlmintics , no prec studies -39 reporH. contortus in China. The results revealed high within-population variation, low population genetic differentiation and high gene flow of H. contortus in China. The results also indicated that on a global scale, there is no or a low level of genetic differentiation among H. contortus populations from the same continent, and significantly higher levels of genetic differentiation among those from different continents. These findings have important implications for studying the molecular epidemiology and controlling the spread of anthelmintic resistance against H. contortus in China.In conclusion, this is the first study of genetic variation within AMOVA: Analysis of molecular variance; ITS-2: The second internal transcribed spacer of ribosomal DNA; L3s: The third-stage larvae; MJ: Median joining; ML: Maximum likelihood; MP: Maximum parsimony; nad4: Mitochondrial nicotinamide dehydrogenase subunit 4 gene; Ne: A large effective population size; NJ: Neighbour-joining; PCR: Polymerase chain reaction.The authors declare that they have no competing interests.MH conceived the project. MB, WH, FZ, GZ, CW, XY, YZ, JZ, RF collected samples. FY and FL carried out laboratory work. FY performed the data analyses. FY and MH interpreted the data. FY, RBG and MH wrote the manuscript. All authors read and approved the final manuscript.Alignment of the 18 unique ITS-2 sequence types representing 152 individual adults of Haemonchus contortus from seven different geographical locations in China. The accession number for each sequence is given in Table Click here for fileThe neighbor-joining (NJ) tree displaying the relationship among the 142 nad4 sequence types representing 152 individual adults of Haemonchus contortus from seven different geographical locations in China. Each terminal branch represents one sequence. Each individual sequence is labeled according to geographical origin of the worm from which it was derived. Bootstrap values of >50% are indicated above or below the branches. Haemonchus placei (accession no. AF70785) was used as the outgroup.Click here for file


Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae) is one of the most destructive insect pests of cruciferous plants worldwide. Biological, ecological and genetic studies have indicated that this moth is migratory in many regions around the world. Although outbreaks of this pest occur annually in China and cause heavy damage, little is known concerning its migration. To better understand its migration pattern, we investigated the population genetic structure and demographic history of the diamondback moth by analyzing 27 geographical populations across China using four mitochondrial genes and nine microsatellite loci. The results showed that high haplotype diversity and low nucleotide diversity occurred in the diamondback moth populations, a finding that is typical for migratory species. No genetic differentiation among all populations and no correlation between genetic and geographical distance were found. However, pairwise analysis of the mitochondrial genes has indicated that populations from the southern region were more differentiated than those from the northern region. Gene flow analysis revealed that the effective number of migrants per generation into populations of the northern region is very high, whereas that into populations of the southern region is quite low. Neutrality testing, mismatch distribution and Bayesian Skyline Plot analyses based on mitochondrial genes all revealed that deviation from Hardy-Weinberg equilibrium and sudden expansion of the effective population size were present in populations from the northern region but not in those from the southern region. In conclusion, all our analyses strongly demonstrated that the diamondback moth migrates within China from the southern to northern regions with rare effective migration in the reverse direction. Our research provides a successful example of using population genetic approaches to resolve the seasonal migration of insects.The diamondback moth  Many animals undergo seasonal migration to escape deteriorating habits, colonize new resources, avoid predation, competition and parasitism and benefit reproduction However, migration usually homogenizes the genetic differentiation among populations Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae) is one of the most destructive insect pests that affects cruciferous plants worldwide The diamondback moth Population genetic approaches have been previously used to reveal the migration of the diamondback moth. All studies have detected no genetic differentiation within the populations of Australia and New Zealand In China, where the climate ranges from temperate to subtropical to tropical, diamondback moth outbreaks occur yearly and cause heavy damage. Although Ma and Chen Mythimna separata (Lepidoptera: Noctuidae) Spodoptera exigua (Lepidoptera: Noctuidae) Loxostege sticticalis  Helicoverpa armigera (Lepidoptera: Noctuidae) Nilaparvata lugens (Hemiptera: Delphacidae) In the present study, we investigated the population genetic structure and demographic history of the diamondback moth across China by intense sampling, using both mitochondrial genes and microsatellite loci. The aim was to (1) apply genetic approaches to resolve the migration pattern of this insect without much background information and (2) reveal the migration pattern of the diamondback moth in China. If the migration of the diamondback moth is confirmed, the details of its life cycle and overwinter abilities in northern China should be reconsidered, and new controlling strategies based on forecasting systems could be developed for regional management of this insect pest. Additionally, the sampling and analysis methods used here would be a potential model to reveal the migration of other insects, such as the oriental armyworm cox1, trnD, atp8, atp6 and nad5, from the 27 populations of the diamondback moth showed different genetic variation. We observed 205, 2, 12, 60 and 93 haplotypes in the cox1, trnD, atp8, atp6 and nad5 genes, respectively, in the 794 individuals (GenBank Accession numbers: KC154863-KC155245). The cox1 alignment had the highest variable and parsimony-informative sites, haplotype (h) and nucleotide (π) diversity, followed by the nad5, atp6 and atp8 alignments, suggesting that these genes possess a large amount of genetic diversity. By contrast, trnD demonstrated low values of the diversity parameters , 350 haplotypes were observed in 794 individuals. Among the 350 haplotypes, 246 were unique to one individual, 56 were unique to individuals from the same population, and 48 were shared by individuals from different populations. There were 272 (13.0%) variable characters, of which 156 (7.4%) were parsimony informative. The haplotype (h) and nucleotide (π) diversity were 0.9814 and 0.0024, respectively.When the genes Based on the combined genes, all 27 populations showed high haplotype diversity and low nucleotide diversity. However, a relatively low value of the haplotype diversity was observed in the JSLY (0.5030), GXLZ (0.7330), JSNJ (0.7520) and FJQZ (0.7540) populations .All microsatellite loci showed high levels of variation. The number of alleles ranged from 77 to 135, and the observed heterozygosity ranged from 0.17 to 0.90 in the 27 populations. There was no significant genotypic disequilibrium among the nine loci. Tests for Hardy-Weinberg equilibrium within populations and loci showed significant deviation .STF difference based on mitochondrial genes showed significant differentiation in 521 of the 702 population pairs  based on microsatellite data also showed no differentiation among populations. Our analyses indicated that no geographical differentiation exists among populations in China.Next, we tested the division of the 27 populations into different geographical groups. The SAMOVA results based on mitochondrial genes showed that the  2 to 16 . When th 2 to 16 . The gloP = 0.036496) and 0.0975 for microsatellite data (P = 0.1584)  , indicatcox1 gene (372 bp) worldwide, 10 of the 15 haplotypes from Korea, one from Australia and one of seven from Canada were identical to haplotypes from China. The phylogenetic analysis also divided the haplotypes worldwide into two groups  to 662.8 (from FJLY to LNSY) , the numbers of migrants into northern populations were high, ranging from 9.8 to 36.6 for each population. By contrast, the numbers of effective migrants into southern populations were lower than 4.8 for each population, except HNDZ and GXBS  . When thand GXBS . When thSeveral haplotypes were dominant and evenly distributed among the different regions of China , whereascox1, atp8, atp6 and nad5. We then calculated Tajima’s D for each of the 27 populations using the combined genes and found that ‘it was not significantly negative in all populations from southern China except the populations HNDZ (p = 0.0140), GDGZ (p = 0.003) and FJLY (p = 0.0160), whereas Tajima’s D was statistically negative in all populations from northern China. Similar tendencies were found using Fu’s F statistics , and four populations from the southern regions , indicating that a sudden demographic expansion occurred in these populations .The effective population size estimated for each population showed that an obvious expansion occurred in populations from the northern regions (except HBCL and QHXN) and GXBS from the southern regions, whereas a decrease or no variation of effective population size was observed in populations from the middle and southern regions .cox1 sequence cox1 gene sequence was used for analysis of Chinese and Korea populations, the haplotype diversity became high In the diamondback moth, low mitochondrial DNA diversity among Australian populations were found based on a 257-bp h) with low nucleotide diversity (π) in the populations of the diamondback moth from China. A similar situation was previously found in many species, with a high migration rate and small effective population size Our study revealed high haplotype diversity . The gut was removed prior to DNA extraction.cox1 and nad5 and full-length sequences of atp8, atp6 and trnD, were used as molecular markers for the current study according to the types of the mitochondrial protein-coding genes and previous studies cox1-cox2 and 54°C for the regions of atp8-atp6 and nad5, and 1 min at 72°C, and a subsequent final extension for 10 min at 72°C. PCR components were added as recommended by the manufacturer of Takara LA Taq . Amplified products were purified and sequenced directly from both strands using the ABI 3730xl DNA Analyzer by Sanboyuanzhi Biotechnology Co., Ltd .To choose the gene region for the population genetic study and design the primers for amplification, we sequenced the complete mitochondrial genome of the diamondback moth as the reference sequence (GenBank accession No. JF911819). Three segments from mitochondrial genomes, including a partial sequence of Two sets of microsatellite primers have been reported for the diamondback moth S), haplotype diversity (h), nucleotide diversity (π) and the average number of pairwise differences (P) were calculated using the ARLEQUIN suite, version 3.5 Sequencing results determined from both strands were assembled using the SEQMAN program within the LASERGENE suite version 7.1.2 . Sequences of the five genes were aligned independently using CLUSTALW STF and genetic distances were calculated using MICROSATELLITE ANALYSER (MSA) version 4.0.5 The microsatellite data determined from GENEMAPPER were first checked for stuttering, large allele dropout and null alleles using MICRO-CHECKER version 2.2.3 STF values between each pair of the 27 populations were calculated using the ARLEQUIN suite, version 3.5 SCF), among groups (CTF) and within populations (STF) were compared among different group numbers within each dataset. For microsatellite data, population differentiation was investigated using the Bayesian clustering approach implemented in the program STRUCTURE, version 2.3.3 K). We performed 35 independent runs for each K (from 1 to 20) to confirm consistency across runs. The most accurate number of groups (K) was visually examined when plotting K against ΔK and using the Evanno method in the online program STRUCTURE HARVESTER For mitochondrial genes, the pairwise STF/(1-STF)] and the logarithms of geographical distance (ln Km) between all the sampling sites were constructed. These matrices were analyzed for their degree of correlation using a Mantel test To establish whether any isolation-by-distance effect occurred, matrices of genetic distance data [eNµ, where μ is the mutation rate per site per generation) and the mutation-scaled migration rate  were calculated using Bayesian search strategies and the software MIGRATE, version 3.2.16 emxN is θM . The parameters used in the calculations are as follows: long-chains = 1, long-inc = 20, long-sample = 1000000, burn-in = 1000000, heating = YES: 1: , heated-swap = YES and replicate = YES: 5. Four runs of MIGRATE analysis were conducted to verify the consistency in our results. For each run, we changed the random number seed and starting values for θ and M. In the first run, θ and M were estimated from STF values and in the subsequent runs. In the subsequent runs, Bayesian estimates of θ and M from the previous run were used. The estimated θ, M and θM from the final run are reported here.To test whether there was asymmetric dispersal between populations, the mutation-scaled population size  in the software MRBAYES, version 3.2 http://tree.bio.ed.ac.uk/software/figtree/). For the NJ method, the LogDet (Tamura-Kumar) model was used for analysis. The species Leucoptera malifoliella (Lepidoptera: Yponomeutoidea: Lyonetiidae) was selected as outgroup, because this is the evolutionary nearest species to the diamondback moth with sequenced mitochondrial genome sequence The phylogenetic relationship among the 350 haplotypes from the combined genes of cox1, atp6, nad5 gene and the combined genes were inferred using the median-joining algorithm cox1 gene and the combined genes The haplotype network of each The demographic history of each population was examined. Background selection using Tajima’s D http://tree.bio.ed.ac.uk/software/tracer/). When the two runs were converging on the same distribution, one of them was used for Bayesian Skyline Reconstruction analysis. Otherwise, additional runs were performed with increased generations until two of them were converging.Bayesian Skyline Plot implemented in the software BEAST, version 1.7.2 Figure S1The values of fixation indices among populations within groups (SCF), among groups (CTF) and within populations (STF) when the 27 populations are divided into 2 to 20 geographical groups, calculated using SAMOVA based on the combined mitochondrial genes of cox1, atp8, atp6 and nad5.(PDF)Click here for additional data file.Figure S2The haplotype network of the gene cox1. The area of a circle is proportional to the number of observed individuals. Colors within the nodes indicate the following: red, southern China; green, middle regions of China; blue, northern China.(PDF)Click here for additional data file.Figure S3The haplotype network of the gene atp6. The area of a circle is proportional to the number of observed individuals. Colors within the nodes indicate the following: red, southern China; green, middle regions of China; blue, northern China.(PDF)Click here for additional data file.Figure S4The haplotype network of the gene nad5. The area of a circle is proportional to the number of observed individuals. Colors within the nodes indicate the following: red, southern China; green, middle regions of China; blue, northern China.(PDF)Click here for additional data file.Figure S5Mismatch distribution of the combined genes of cox1, atp8, atp6 and nad5 in the 27 populations of the Plutella xylostella from China using the ARLEQUIN suite, version 3.5(PDF)Click here for additional data file.Figure S6Bayesian Skyline Plot of the 27 populations of the Plutella xylostella from China based on the combined genes of cox1, atp8, atp6 and nad5.(PDF)Click here for additional data file.Table S1Genetic diversity of the five mitochondrial genes and demographic analysis of the 27 Plutella xylostella populations as one group.(DOCX)Click here for additional data file.Table S2Summary statistics of the nine microsatellite loci examined in the 27 populations of the Plutella xylostella.(DOCX)Click here for additional data file.Table S3Estimates (M and θ) of the migration among 27 Plutella xylostella populations from China based on combined genes.(DOC)Click here for additional data file.Table S4The number of the dominant haplotypes in the 27 populations. Hap4, Hap31 and Hap8 are the three most dominant haplotypes in the combined genes, and Hap4, Hap2 and Hap2 are the most dominant haplotypes in the genes cox1, atp6 and nad5, respectively.(DOCX)Click here for additional data file.Table S5Mitochondrial genes and their amplification conditions used in this study.(DOCX)Click here for additional data file.Table S6Microsatellite loci used in this study.(DOCX)Click here for additional data file.


Plasmodium falciparum despite the fact that morbidity has been reduced in recent years. Parasite populations in that region show interesting characteristics such as chloroquine susceptibility and low mortality rates. Genetic structure and diversity of P. falciparum populations in the Honduras-Nicaragua border were analysed in this study.The Caribbean coast of Central America remains an area of malaria transmission caused by P. falciparum isolates from endemic areas of Honduras (n = 77) and Nicaragua (n = 33), mostly from the border region called the Moskitia. Several analyses concerning the genetic diversity, linkage disequilibrium, population structure, molecular variance, and haplotype clustering were conducted.Seven neutral microsatellite loci were analysed in 110 P. falciparum populations from Honduras and Nicaragua. Expected heterozigosity (He) results were similarly low for both populations. A moderate differentiation was revealed by the FST index between both populations, and two putative clusters were defined through a structure analysis. The main cluster grouped most of samples from Honduras and Nicaragua, while the second cluster was smaller and included all the samples from the Siuna community in Nicaragua. This result could partially explain the stronger linkage disequilibrium (LD) in the parasite population from that country. These findings are congruent with the decreasing rates of malaria endemicity in Central America.There was a low level of genetic diversity in  Plasmodium falciparum and the remaining cases are caused by Plasmodium vivax . Thanks to the tremendous efforts of national and international organizations, a reduction of more than 75% of incidence rates has been confirmed in six countries of this region between 2000 and 2011. The achievements are even greater for Costa Rica and El Salvador, which are now considered in the malaria pre-elimination phase [In the region of the Americas, malaria still occurs in 21 countries with about 30% of inhabitants at some risk of infection and 8% at high risk. During 2011, the largest number of cases occurred in countries that share the Amazon rainforest, such as Brazil, Colombia, Peru, and Venezuela, while in the Mesoamerica subregion malaria cases are concentrated in Honduras, Guatemala and Nicaragua, in descending order of importance [P. falciparum in Central America is limited to the coastal areas of the Caribbean, such as the Bay Islands in Honduras and the region called “Moskitia”. Moskitia is a territory shared by Honduras and Nicaragua  [One of the most notable epidemiological characteristic of ine (CQ) ,4, whichine (CQ) ,6. CQ suPlasmodium populations in a particular ecosystem [Plasmodium species have been reported worldwide in order to better understand the biology of the parasite [P. falciparum populations. Consensus patterns of population structure have been found depending on the transmission rate in different regions [Genetic diversity indexes can be used as indicative of the adaptation and fitness of cosystem . Extensiparasite -9 and thparasite . Those sparasite ,12, and parasite -16. Mult regions ,18. In g regions . Highly  regions .P. falciparum using neutral microsatellites or simple sequence repeats (SSR) have been reported from South America. Most of the results confirm that limited genetic diversity, significant LD, and gene flow are common for Brazil, Peru, Colombia, and Bolivia parasite populations [P. falciparum are available, and mostly from Honduras. However, genetic analyses of populations of this parasite based on neutral microsatellites in Central America have not been reported so far. Taking into account recent changes in the demography and epidemiology of malaria in this region, in this work the population structure and genetic diversity of P. falciparum was assessed in 11 municipalities from Honduras and Nicaragua using seven SSR neutral markers.In the Americas, population analyses of ulations ,17,20-23ulations , drug reulations ,25 and gulations ,26 of P.One-hundred and ten human blood samples from Honduras and Nicaragua areas with endemic malaria falciparum transmission were analysed. Eighty-three (75.45%) of those samples were taken from patients living in the Moskitia region. Seventy-seven samples were collected from seven municipalities of Honduras, and 33 from four municipalities of Nicaragua Figure . Twelve P. falciparum infections were carried out by experienced microscopists, and molecular confirmation of the species was obtained through PCR amplification of the 18Sr gene according to Singh et al. [P. falciparum isolates from sub-Saharan Africa and five universally known reference clones  were included in this study as an outgroup and amplification controls.All patients showed symptoms typical of malaria at the time of enrolment. Filter paper was used to collect one drop of blood from each patient for malaria surveillance purposes. Diagnosis of h et al. . Three PP. falciparum-positive filter paper blood spots was extracted using a Chelex-based method [Plasmodium parasites are haploid organisms during most of their life cycle, except for a brief period after fertilization inside the gut of the female Anopheles, each allele obtained in the pherogram would represent a different clone of the parasite and in single clone infections, one allele would be expected per locus in each samples. In those cases when a secondary peak was observed in the chromatogram, the height of the secondary peak was measured. If the height of the minor peak was lower than 30% of the predominant peak they were considered as single clone infections [DNA from d method . The fold method , C2M34 , allelic richness (Rs), expected heterozigosity (He), allele frequencies and the number of haplotypes (h). Three of these parameters  were used to indicate the level of polymorphism in the loci and determine the diversity of the populations. He was calculated as n is the number of isolates and ρi is the frequency of ith allele.Genetic diversity parameters were calculated for the entire population and for two subpopulations (Honduras and Nicaragua) independently using ARLEQUIN version 3.5 software  by deterA is strongly dependent on sample size and different number of isolates were analysed in the two countries (77 in Honduras vs 33 in Nicaragua), it was necessary to normalize the data. For that, the allelic richness (Rs) was calculated using FSTAT version 2.9.3 software, fixed as the smallest number of individuals typed for a locus in a sample.Since FST, which is a pair-wise distance measurement used to calculate the average F statistics over all loci according to the number of different alleles between haplotypes [The ARLEQUIN software was also used to estimate population differentiation using the Wright’s pair-wise fixation index plotypes .VD / Ve - 1)/(n - 1) assuming a null hypothesis of complete linkage equilibrium  was measured using the Standardized Index of Association (sion 3.5 . IAS wasK) relying on the allele frequencies at each locus, assuming that within populations, the loci are at Hardy-Weinberg equilibrium, and linkage equilibrium [K, five independent replicates were run for 100,000 steps, after a burn-in period of 10,000 steps, and the mean log likelihoods in each run were compared. The most likely number of populations was calculated by the higher number in the rate of change for K (ΔK) [P. falciparum subpopulations was confirmed by analysis of molecular variance (AMOVA) [To establish the structure of the populations according to geographic origin, Structure version 2.3.3 software was used. This software assigns probable individual haplotypes to multiple clusters (ilibrium . An admir K (ΔK) . The str (AMOVA) . Similar (AMOVA) .P. falciparum isolates from 11 communities located in Honduras and Nicaragua, mostly from the Moskitia region across the border between both countries . For 16 (14.5%) isolates allelic data were obtained for 6 loci; and the remaining 6 (5.5%) isolates failed to amplify 2 loci. Most of the isolates analysed (99.6%), revealed one single peak in the chromatogram but three isolates from Honduras showed two peaks for one locus each. A full description of allele sizes, missing data and mixed-clone infections is given as Additional file t test. Normalized allelic richness (RS) showed a similar pattern, ranging from 1.83 to 4.08 in Honduras, and from 1 to 3.98 in Nicaragua.Number and frequencies of SSR alleles were calculated Table . Allele vs Nicaragua) ranged from zero (for TA109 locus) to three (Poly-α). In general terms, the number of alleles per locus tends to be higher in areas of high endemicity, and lower in areas of low or moderate endemicity [The number of exclusive alleles observed in only one of the two countries . He was similar for both populations in Honduras (0.35 ± 0.18), and Nicaragua (0.38 ± 0.28) .The small variation in allele numbers between countries was further evaluated by expected heterozigosity  [He values revealed to be lower than those found in other countries with higher endemicity, such as: Vietnam (0.52-0.91), three West African countries (0.78-0.96) [Low estimates of expected heterozygosities found for Central American 14-0.62) ,45, and 14-0.62) . He valu78-0.96) , NigeriaST coefficient was estimated for both subpopulations using seven microsatellite loci. FST is based on the differences in allele frequencies in each population. The number of isolates used to calculate FST between Honduras and Nicaragua was 77 and 33, respectively. Values close to zero suggest no frequency differences, and values similar to 1.0 indicate completely fixed differences without shared alleles. FST index measuring Honduras-Nicaragua inter-population variance in allele frequencies was 0.14. A qualitative interpretation of FST values has been suggested [P. falciparum populations in Malaysia through a deep sequencing approach [The Fuggested , where vapproach . These aK), and measures the probability that individual parasites belong to each of these K populations [ΔK = 23.19)  with the highest malaria incidence in Nicaragua, its human population is ethnically different from the inhabitants of the neighbor region of Moskitia and belong to different language cultures. This social difference and the almost inexistent access roads between municipalities could indicate historical separation of human communities and, as a consequence, barriers for gene flow and parasite migration, as suggested by similar studies in other regions [In order to find out the reason for the moderate differentiation between subpopulations, a clustering approach was undertaken using the Structure software. This Software uses a Bayesian analysis to infer the most likely number of populations (ulations . This an regions .h) analysis defined 25 haplotypes in the whole population , and only 14% of variation was explained by comparing subpopulations, suggesting a relative free gene flow across the region. This variation of 14% is consistent with the FST index between populations described before. Similar results were reported for South American parasite populations, where most of the diversity was also found within locations [ST = 0.56) between both populations, where 55.64% of the variance was explained between populations and 44.36% within populations.Furthermore, an analysis of molecular variance (AMOVA) was used to assess the population structure of ocations . In addivice versa [Existence of multilocus linkage disequilibrium (LD) was calculated for the entire population as a whole, and separately for each subpopulation using the standardized index of association , however this was not the case for Nicaraguan isolates including 11 isolates from Siuna. LD was considerably reduced from 0.2623 to 0.0886 when only unique haplotypes from Nicaragua were analyzed. This result reinforces the hypothesis that only a small population of parasites from Nicaragua behaves as a residual focus in an area of declining endemicity.A second LD test was also performed but including unique haplotypes for each population only Table . In the P. falciparum were determined in Honduras and Nicaragua using seven SSR neutral loci. This approach is an important tool to better understand the epidemiologic factors that need to be focused in order to control infections and to anticipate emergence of drug resistance. Honduras and Nicaragua are two of the few remaining countries in the world where P. falciparum and P. vivax are still susceptible to CQ and sulphadoxine-pyrimethamine [P. falciparum populations between Honduras and Nicaragua when neutral markers are analysed. In consequence, those results could contribute to the untangling of the reasons for drug susceptibility and the potential for drug-resistant mutation emergence in Central America during malaria control and elimination stages.Genetic diversity indexes and population structure of ethamine ,4. This ethamine ,42,50. TPlasmodium falciparum strain collected in Indochina/Laos; HB3: Plasmodium falciparum strain collected in Honduras; 7G8: Plasmodium falciparum strain collected in Brazil; K1: Plasmodium falciparum strain collected in Thailand; 3D7: Plasmodium falciparum clone from NF54, which was isolated from a patient who lived near the airport in Amsterdam, the Netherlands. The origin of the infection is unknown.Dd2: The authors declare that they have no competing interests.GF and NL carried out the DNA extraction and performed molecular experiments. GF, NL and IH drafted the manuscript and all authors read and edited the manuscript. RM, AM, and AS participated in sample collection and microscopic analyses coordination. GF, NL, and IH conceived the study and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.Microsatellite allele sizes for Plasmodium falciparum populations from Honduras, Nicaragua and reference clones.Click here for file