Phlebotomus chinensis is a primary vector of visceral leishmaniasis; it occurs in various biotopes with a large geographical distribution, ranging from Yangtze River to northeast China. Phlebotomus sichuanensis, a species closely related to P. chinensis in high altitude regions, has a long term disputation on its taxonomic status. Both species occur in the current epidemic regions and are responsible for the transmission of leishmaniasis. Population genetic analysis will help to understand the population structure and infer the relationship for morphologically indistinguishable cryptic species. In this study, microsatellite markers were used for studying the genetic differentiation between P. chinensis and P. sichuanensis.Sandflies were collected in 6 representative localities in China in 2005-2009. Ten microsatellite loci were used to estimate population genetic diversity. The intra-population genetic diversity, genetic differentiation and effective population size were estimated.FST = -0.003-0.090) and no isolation by distance was detected. AMOVA analysis suggested that the variations were largely derived from individuals within populations and among individuals. Consistently, the analysis of ribosomal DNA second internal transcribed spacer (ITS2) sequence uncovered three types of variants, which corresponded with the three gene pools revealed by microsatellites.All 10 microsatellite loci were highly polymorphic across populations, with high allelic richness and heterozygosity. Hardy-Weinberg disequilibrium was found in 23 out of 60 (38.33%) comparisons associated with heterozygote deficits, which was likely caused by the presence of null allele and the Wahlund effect. Bayesian clustering analysis revealed three clusters. The cluster I included almost all specimens in the sample SCD collected at high altitude habitats in Sichuan. The other two clusters were shared by the remaining 5 populations, SCJ in Sichuan, GSZ in Gansu, SXL and SXX in Shaanxi and HNS in Henan. The diversity among these 5 populations was low (P. sichuanensis. The P. chinensis populations did not have a significant divergence from each another.The data suggested that the SCD population carried a distinct gene pool, which was differentiated from the other populations. The high altitude ecological habitats, distinctive ITS2 and herein divergence inferred by microsatellite loci support the species status of  Phlebotomus Rondani & Berte, Sergentomyia France & Farrot, Idiophlebotomus Quate & Fairchild, Grassomyia Theodor and Chinius Leng [Phlebotomus, P. chinensis Newstead, P. sichuanensis Leng & Yin, P. longiductus Nitzulesc, P. wuii Yang & Xiong and P. alexandri Sinton are vectors of leishmaniasis [Leishimania donovani, which has been and still is a serious threat to public health in the endemic areas in China [Phlebotomine sandflies are small insects of great medical and veterinary relevance. In China, phlebotomine sandfly fauna includes over 40 species in five genera, ius Leng ,2. In thin China ,4. Accorin China .Phlebotomus chinensis is a prevalent species with wide geographical distribution, having records in 20 provinces ranging from Yangtze River to the northeast China [P. sichuanensis, based on the study of a large number of sandfly specimens that were collected in the area of 29-33°N, 102-106°E in Sichuan province in 1976-1980 [P. chinensis collected in the type locality. Various morphometric and morphostructural characters were used for distinguishing P. sichuanensis from P. chinensis[P. sichuanensis is 2/3-8, 1/9-15, while it is 2/3-15 in P. chinensis. Phlebotomus sichuanensis is mainly distributed in the regions from 900 m to 2800 m in Gansu, Sichuan, Yunnan and Tibet [P. sichuanensis as an independent species [P. sichuanensis as a large type of P. chinensis, and synonymized P. sichuanensis to P. chinensis[. Epidemiologically, both sandflies are competent vectors of VL. Natural infection of L. donovani was detected in sandflies collected in high and low altitude regions [Leishmania in experimental feeding on Chinese hamsters infected with L. donovani[P. sichuanensis. Apparently, non-morphological, convincing and distinctive taxonomic markers are needed for solving the identity issue.st China . In 1983976-1980 . The spechinensis,6. Male P. sichuanensis, we conducted six sandfly collections in 2005-2009, where P. chinensis and P. sichuanensis occur. Among them, sample SCD was collected in habitats at high altitudes (above 2000 m), a typical locality of P. sichuanensis. Previously we have reported the sequence variation of the ITS2 and Cyt b generated from these samples [P. chinensis was clearly separated from P. longiductus, P. perfiliewi, P. pernicious, P. ariasis, P. duboscqi and P. alexandri. The partial ITS2 sequences of SCD specimens showed distinctive variation from that of P. chinensis[Molecular markers, such as mitochondrial cytochrome b (Cyt b), ND1, ND4, the second internal transcribed spacer (ITS2) of ribosomal DNA and microsatellite markers, have been widely used for sandfly studies in taxonomic discrimination and inference of phylogenetic relationship -16, as w samples . Based ochinensis.Microsatellites are highly polymorphic genetic markers that evolve much faster than mitochondrial or nuclear genes, which are particularly useful for resolving the structure of populations at a finer geographical and evolutionary scale. In this study, we conducted population genetic analysis of the same six sandfly collections reported in the paper above , based oAdlerius in China, P. chinensis, P. sichuanensis, P. longiductus and P. fengi Leng & Zhang. The distribution region of P. longiductus and P. fengi is limited to Xingjiang and Yunnan. In this study, wild adult sandflies were collected in 2005 and 2009 from six locations in the range from 104°15′N to 110°60′ N, and 33°18′E to 36°18′ E in Sichuan, Gansu, Shaanxi, Henan provinces , using the manufacturer’s protocol. Ten microsatellite loci , GA1  in the data set without prior information of the sampling locations, implemented with STRUCTURE 2.2 [K (K = 1 to 6), with a burn-in period of 1,000,000 chains and 1,000,000 Markov chains Monte Carlo replications. The method of Evanno was used to determine the most likely number of clusters [ad hoc quantity, ΔK, based on the second order rate of change of the likelihood function between successive values of K.A Bayesian approach was used to infer the number of clusters (TURE 2.2 . A modelclusters . This apFST between pairs of populations using ARLEQUIN 3.0 [Nm) between localities was estimated from pairwise FST[FST. We focused on estimates of FST performed under the infinite alleles model (IAM) because this model is considered more reliable when fewer than 20 microsatellites are used [P-values. The isolation by distance model was investigated as a potential explanation for the observed population differentiation. The significance of the regression of genetic differences on geographic distance between sample pairs was tested using a Mantel test [Genetic differentiation was estimated by calculating QUIN 3.0  and GENEQUIN 3.0 . The numrwise FST. An analare used . The sigtel test  with 100Ne) was estimated using NEESTIMATOR 1.3 [The long-term effective population size  per locus ranged from 2.3 at locus HN54 to 9.83 at locus GA76. As an exception, only one allele was detected at locus GA1 in sample GSZ (Table Rs) across 6 samples was 3.72, ranging from 3.145 in SCD to 3.849 in HNS. The average observed heterozygosity (HO) across all samples ranged from 0.236 (TG1) to 0.77 (GA109), the minimum was in SXL (0.375), the maximum in HNS (0.503). The mean expected heterozygosity (HE) was 0.619, with a range of from 0.49 (SCD) to 0.693 (HNS). Putting these statistics together, the HNS population showed the highest diversity, whereas the SCD population showed the lowest diversity.Ten microsatellite loci were genotyped for these specimens. The number of alleles (FIS), reflecting heterozygosity deficits  comparisons did not conform to Hardy-Weinberg expectations, and the deviations were associated with positive inbreeding coefficient (P < 0.01). The pair of GA10 and HN54 appeared at LD in all populations, except in the SCD population.Fisher’s exact tests were conducted for LD within each of the six populations. Out of 270 comparisons only 17 pairs (6.30%) were at LD (K = 3 clusters) . We therefore examined if there were different gene pools in these samples. The Bayesian cluster analysis divided specimens into three gene clusters (posterior probability of Bayesian clustering Ln (D) likelihood score optimal for ) Figure . Sample ) Figure . The SCDFST were estimated in a location based manner for the six samples, which is presented in Table FST value was greater and the Nm value was lower between SCD and the others than the pairwise comparisons among the other five populations. Therefore, the SCD represented a population diverged from the other five P. chinensis populations in the study. Tests of isolation by distance were performed for five populations except SCD. No statistically significant correlations were detected between genetic differentiation and geographic distances based on the Mantel test . The results suggested that geographic distance did not significantly contribute to the genetic differentiation observed in the P. chinensis populations.The gene flow and In the hierarchical AMOVA, both the “among individuals within populations” and “among individuals” variance components were considerably high (83.35%), suggesting that the total variances largely came from individual variations Table .Ne varied considerably depending on the model used. Under the heterozygote excess model, all of the Ne estimates were infinity. Under the linkage disequilibrium model, diverse Ne values were detected across populations  to 264.4 (SCJ).Estimates of long-term ns Table . The sixPhlebotomus chinensis s. l. is the major vector for VL transmission in the endemic regions except Xinjiang in China. The sandflies in these regions have two major types of ecological habitats. In the open flatland regions with an altitude <900 m, such as the vast plain area north of the Yangtze River, the sandflies are found in the indoor shelters such as human dwellings and domestic animal sheds. The transmission of VL is largely from human to human. In the mountain areas, the sandflies are largely exophilic, breeding in a variety of wild habitats, such as various caves and rodent burrows. If human dwellings are available, the sandflies feed on humans or domestic animals. The dogs are the main animal hosts of L. donovani, and VL is largely transmitted between dogs and humans. In the areas with an altitude >2000 m, usually there are no human dwellings. The sandflies feed on wild animals for breeding, and transmit Leishmania among wild animals [Phlebotomus sichuanensis[, or a large type of P. chinensis[P. chinensis and P. sichuanensis in the high altitude areas. animals ,41. Phlehuanensis,6, or a chinensis,42 were chinensis. In pastchinensis). The saP. chinensis collections. When six sample collections were compared, the differentiation between SCD and others was evident by high FST and reduced gene flow . Indeed, cluster analysis, implemented by using STRUCTURE, recognized three gene clusters in the six sandfly collections. Almost all individuals in SCD population were assigned to cluster I Figure . The dathuanensis. The morhuanensis, althougene-flow -45. FurtFST = -0.003-0.090, Nm = 2.516-6.581, Table P. chinensis populations. The small genetic differentiation in P. chinensis populations and no evidence of isolation by distance suggested that no obvious barriers limit the dispersal of sandflies in the P. chinensis populations sampled in this study.The pairwise level of genetic variation was small in the remaining five populations (Leishmania genotypes have been found in different geographic origins, such as hill, plain and desert [P. chinensis and P. sichuanensis are competent vectors [P. sichuanensis occurs in regions of above 2000 m, where Leishmania has been cycling among wild reservoir animal hosts. It is conceivable that P. sichuanensis constitutes a necessary component connecting the zoonotic VL to the human community. The current characterization of sandfly population structure and ITS2 sequences provide molecular data to develop objective and reliable methods for molecular identification of sandfly specimens. Such tools will be particularly useful to further investigate the ecology, behavior and vector capacity of P. chinensis and P. sichuanensis in the mountainous regions. This type of data will facilitate the development of appropriate measures to control sandfly vectors.Leishmaniasis has shown an increasing trend in recent years in China . Differed desert . The cur vectors ,9. The dP. sichuanensis possessing a distinct gene pool, which was differentiated from the P. chinensis populations. The molecular data support the species status of P. sichuanensis. The five P. chinensis populations did not have a significant divergence from each other. The genetic distinction of P. sichuanensis from P. chinensis warrants further study to explore potential influence on physiology, behavior, and vector competence that may be associated with different ecological habitats between the two species.The microsatellite data suggest that SCD represents a population of The authors declare that they have no competing interests.YM conceived and designed the experiments. LZ performed the experiments. YM and JX analyzed the data, wrote the manuscript. All authors read and approved the final manuscript.


Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes. We applied this approach to a complex, uniquely admixed South African population. Using genome-wide SNP data from over 764 individuals, we accurately estimate the genetic contributions from the best ancestral populations: isiXhosa The collective term for people of mixed ancestry in southern Africa is “Coloured,” and this is officially recognized in South Africa as a census term, and for self-classification. Whilst we acknowledge that some cultures may use this term in a derogatory manner, these connotations are not present in South Africa, and are certainly not intended here. The field of population genetics has experienced a resurgence in the past few years due to access to extensive single nucleotide polymorphism data. The availability of genome-wide multi-locus genotype profiles has fueled long-standing interest in analyzing patterns of genetic variations to trace the ancestry components of recently admixed human populations, to identify genes underlying ethnic difference in disease risk and shed light on both the evolutionary history and migrations of recently admixed human populations Because distinct populations exhibit substantial variation in genetic disease risk, the choice of reference populations for a multi-way admixed population may be sensitive and critical in biomedical research. Current algorithms for identifying the best proxy ancestral populations are inadequate for multi-way admixed populations, including HAPMIX To address these challenges and the uncertainty in ancestral populations we developed PROXYANC, an approach to select proxy ancestry for recently admixed populations. We implemented two novel algorithms in PROXYANC, based on population genetic differentiation and optimal quadratic programming, respectively. We demonstrated through simulation of a complex multi-way admixed population that these two algorithms can select best proxy ancestry for an admixed population, given a pool of related/unrelated or admixed reference populations. Our simulation demonstrated that our complementary algorithms perform better in selecting the best proxy-ancestry for a multi-way admixed population, compared to the f3 statistic http://www.statssa.gov.za), describes the present population of South Africa to be characterized by diversity, including groups originating from African (79%), European (9.6%) and Asian (2.5%) populations. A study conducted by Tishkoff and colleagues The South African Coloured population (SAC) has a high level of intercontinental admixture and therefore diverse ancestry Here we developed PROXYANC, a novel method to select the best ancestral populations in multi-way admixed populations. We characterized the African, European, South Asian and East Asian origins of the SAC by applying PROXYANC to a cohort of the SAC  and report the considerable refinement of the contributions of genetic ancestry components. We establish that the SAC has had substantial admixture from isiXhosa, ‡Khomani, European, Indian (Gujarati) and Chinese populations. Using the best proxy ancestral populations found by PROXYANC, we demonstrated that the ancestral allele frequency differences correlated with increased linkage disequilibrium (LD) in the SAC, indicating that increased admixture LD is present in this population, and the observed LD has its origin from admixture events. This result supports the rejection of the hypothesis of founder effects or of population bottlenecks that could have been due to the racial segregation of the past, formalized during the recent apartheid regime in South Africa.We developed the method PROXYANC, which searches for the best combination of reference populations that can minimize the genetic distance between the admixed population and all possible synthetic populations, consisting of a linear combination from reference populations . For genetic distance, the y scores  are fromy scores . The higted data . This reTo evaluate the impact of selecting the best proxy ancestral population for an admixed population in estimating admixture proportion, we ran the ADMIXTURE software on three data sets (each of which includes the simulated admixed data set): 1) the original samples from ; 2) the expanded samples from ; and 3) a separate set of putatively unrelated ancestral populations . The results from the first two panels produced the estimate of the contributions in the simulation data of the following ancestral populations; CEU:, the Human Genome Diversity Cell Line Panel K array), the International Haplotype Map (HapMap) Phase 3 M array), and samples from 6 southern African populations obtained from Pickrell et al. To select the best proxy ancestral populations using the real SAC data, we applied PROXYANC to 5 pools of reference populations implicated by both PCA and admixture analysis. We first constructed African, European, South Asian and East Asian population data sets using populations described in analysis –S8. We pry score  and -optgramming  were in gramming . This reUsing the result from PROXYANC on the SAC data, we combined the top proxy ancestral populations   and 5, iTaken together, the results above provide confidence that our inferred five ancestral components with balanced African contributions from isiXhosa and ‡Khomani populations, followed by Northern and Western European, Gujarati Indian and a smaller Chinese contribution, is closer to the true picture of ancestral contributions according to the SAC’s history. We believe that our result also has the advantage of handling sample size differences and using accurate proxy ancestral populations, and believe that both the number of SNPs  and its history of multi-faceted colonization We additionally compared the genome-wide haplotype diversity and the percentage haplotype sharing by IBD , and the result in We introduce PROXYANC, an approach to select proxy ancestry for complex multi-way admixed populations. We assessed its accuracy through a simulation of a multi-way admixed population and demonstrated the impact and sensitivity of the choice of reference panel in estimating global and local ancestry and in imputing missing genotypes. Because of increased urban development and migration, the proportion of individuals with significant recent genetic admixture is on the increase in many modern societies. However, increased population admixture influences genome heterozygosity, which in turn will affect phenotypes relevant to health. Therefore, the choice of the best proxy ancestral populations for an admixed population is critical in both the study of population genetics and in identifying genes underlying ethnic differences in genetic disease risk. Our simulation results demonstrated the usefulness of the choice of proxy ancestry for admixed populations, in contributing to the accuracy of the inferences of both local and global ancestry. Selecting an accurate proxy ancestral population for an admixed population is required for improving the power of GWAS for admixed populations. Furthermore, our simulation demonstrated that the proxy ancestral panel achieved a similar accuracy to that including all available populations in imputing missing genotypes of an admixed population. This indicates that the choice of accurate ancestral panel can help in reducing computational costs of the imputation engine for finding the best haplotype among all available populations during imputation processes.To the best of our knowledge, PROXYANC is the first approach to select the best reference ancestral panel given pools of reference ancestral panels. Our methods to select proxy ancestral populations in a multi-way admixed population have enabled us to characterize the genetic ancestry component of the uniquely admixed Coloured population of South Africa that accounts for 49% of the population of the Western Cape Province of South Africa . Previous studies of this historically complex population were hampered by the relatively small sample size and few putative ancestral populations publicly available, and especially the very low number of San individuals. In the present study we have utilized the increased number of reference populations available, and the best proxy ancestries of the SAC obtained from PROXYANC allowed us to document a contribution of the isiXhosa, ‡Khomani, European, Gujarati Indian, and Chinese genetic material to the SAC . We expected a southern Bantu-speaking group such as isiXhosa instead of a West African group such as the Yoruba to be a better proxy ancestor of the SAC. The isiXhosa as best proxy ancestor of the SAC reflects the early mixing of mainly indigenous San females with the southern Bantu groups and potentially the distinct genetic profile of southern Bantu-speaking populations after their expansion through Africa. Subsequently male settlers, mainly from the Netherlands, Britain, Germany and France, and male slaves from South Asia A higher degree of LD is expected in admixed populations, and this could at certain points of its history be influenced by population bottlenecks, or still be a result of the admixture itself. We demonstrated that the allele frequency differences between each pair of proxy ancestral populations correlated with the degree of LD in the SAC, suggesting that the admixture increased genetic diversity and that the observed LD in the SAC has its origin mainly in the admixture. This study observed a weak level of founder haplotypes identical-by-descent along the genome of the SAC, which strengthens the evidence against the argument that past legislated separation of ethnic groups in South Africa, including the SAC, caused population bottlenecks. However in spite of this isolation, the original admixed population was large and a population bottleneck is therefore unlikely.The obtained best proxy ancestry for the SAC provides opportunities to examine an accurate, unbiased estimation of the ancestry at each genetic locus in this multi-way admixed population, to potentially provide crucial insights into identifying disease genes based on ethnic difference. As existing methods that infer local ancestry assume that non-admixed ancestral populations are the most suitable, it may not be advisable to use the isiXhosa, which have some Khoe-San ancestry In conclusion, this study has highlighted the importance of selecting the best proxy ancestry for potential downstream analysis in a multi-way admixed population. The investigation of admixture LD and the identification of source populations for the SAC has not only deepened our understanding of its evolutionary history, but also provide opportunities for designing a method to account for a combined genome-wide SNP case-control and admixture mapping in a multi-way admixed population such as the SAC. PROXYANC will also provide a useful tool for the investigation of other multi-way admixed populations.Approval from the Ethics Committee of the Faculty of Health Sciences, Stellenbosch University  from two suburbs of Cape Town were collected and genotyped using the Affymetrix 500h Africa . GroupinThe question we want to address is, given a pool of available continental affiliated populations, for example European or African, which population is the best European or African proxy ancestry of the admixed population under study. We assume prior knowledge of geographical potential ancestral populations.A), A if their linear combination  between genetic loci. Accounting for this assumption, we can compute the proxy ancestry score from the data of the admixed population and pair-wise reference populations. Computing the correlation between the LD in the admixed population and allele frequency differentiation in each pair of ancestral populations, the Proxy-Ancestry Score algorithm is as follows:Given Taking the Fisher’s transformation on We regress For For each reference population http://www.cbio.uct.ac.za/proxyanc).To start our simulation, we independently phased each putative ancestral population, including European (CEU), isiXhosa, ‡Khomani, East Asia (CHD) and Gujarati Indian using BEAGLE To simulate the genome of an admixed individual that can mimics the genetic make-up of a multi-way admixed population such as the SAC, we sample haplotypes from European (CEU), isiXhosa, ‡Khomani, East Asia (CHD) and Gujarati Indian with probability related to our prior estimate of the ancestral proportion from each putative ancestral population . Considering a continuous gene flow model To evaluate PROXYANC, we applied both approaches implemented in PROXYANC , we removed 2,044 out of 39,064 SNPs on chromosome 1 from the simulated data, and we imputed them using 4 different sets of reference populations, including a panel of populations  used directly in the simulation, a panel formed of initial samples from ancestral populations  used to test PROXYANC, a panel of all 20 populations listed above and a panel formed by inappropriate proxy ancestral populations, including Russian, Japanese, Palestinian, Yoruba and Ju|’hoan populations. his allowed us to assess the imputation accuracy rate using different reference panels.We applied the clustering algorithm implemented in ADMIXTURE Increased LD in a population relative to its ancestral population(s) can be due to founder events or population bottlenecks http://www.cbio.uct.ac.za/proxyanc).In order to compare the level of admixture in the SAC, we computed the proportion of IBD and the pairwise population concordance (PPC) test. For the pairwise identity-by-state (IBS) test, we ran PLINK with 10,000 permutations between populations in the same data set . We coded the SAC as cases and its proxy ancestries as controls. We calculated the empirical p-values to determine whether case/case-pairs were less similar to each other compared to control/control-pairs Figure S1Plot of proxy-ancestry scores of each population in each group of reference populations (Subjects and Methods). All the highest peaks can be observed from the five ancestral populations that contributed to the admixture in the simulated data.(TIFF)Click here for additional data file.Figure S2Plot of individuals ancestry. The first two plots are based on the reference populations used to simulate the admixed population and to assess PROXYANC , respectively. The mean and its standard deviation from both analyses yielded to CEU (20%0.0999 and 19%0.1039), CHD (8%0.0709 and 8%0.0691), Gujarati (11%0.0784 and 11%0.0839), IsiXhosa (32%0.1169 and 34%0.1545) and ‡Khomani (29%0.1201 and 27%0.1428), respectively. The bottom plot is based on populations geographically close to the best proxy ancestors of the simulation data. The admixture proportion in the plot is inconsistent to the true admixture proportions in our simulated data, 2.9% from both Russian and Palestine, 2.6% from Japanese, 2.6% from both Yoruba and Ju|’hoan and 40% and 50% from two unknown populations.(TIFF)Click here for additional data file.Figure S3Ancestral population clustering (A) and Principal Component Analysis (B) of the SAC and African populations. (A) The plot in (A) is the proportion of each individual’s ancestry. (B) The plot is of the first and the second eigenvectors in the PCA of the combined populations. For clarity, the population labels in figure (A) are ordered as Kaba, Fang, MKK, ban, XHS, XHS2, LWK, SBAN, HER, STS, ASW, SAC, SAN, BUS, KHS, KHO, HAZ, SAW, Mada, man, Brong, yor, Igbo, Fulani, YRI, Hausa, Kongo, Bulala, Bamoun, TNS, moz, MRC_S, ALG, MRC_N, EGT, LBY and SAH_occ ( SAH_occ .(TIFF)Click here for additional data file.Figure S4Ancestral population clustering (A) and Principal Component Analysis (B) of the SAC and European populations. (A) The plot in (A) is the proportion of each individual’s ancestry. (B) The plot is of the first and the second eigenvectors in the PCA of the combined populations. For clarity, the population labels in figure (A) are ordered as bas, fre, ita, CEU, SAC, sar, rus, ady and orc ( and orc .(TIFF)Click here for additional data file.Figure S5Ancestral population clustering (A) and Principal Component Analysis (B) of the SAC and South Asian populations. (A) The plot in (A) is the proportion of each individual’s ancestry. (B) The plot is of the first and the second eigenvectors in the PCA of the combined populations. For clarity, the population labels in figure (A) are ordered as pat, pim, SAC, sin, bur, haz, bal, kal, mak, bra and GIH ( and GIH .(TIFF)Click here for additional data file.Figure S6Ancestral population clustering (A) and Principal Component Analysis (B) of the SAC and East Asian populations. (A) The plot in (A) is the proportion of each individual’s ancestry. (B) The plot is of the first and the second eigenvectors in the PCA of the combined populations. For clarity, the population labels in figure (A) are ordered as yi, CHB, hez, dau, oro, SAC, dai, tuu, mia, tuj, she, yak, CHD, cam, JPT, jap and mon ( and mon .(TIFF)Click here for additional data file.Figure S7Principal Component Analysis (PCA) of the SAC and the World-wide populations . The first and the second eigenvectors in the PCA of the combined SAC and worldwide populations are shown.(TIFF)Click here for additional data file.Figure S8Principal Component Analysis of the SAC and both American and Middle-east populations, respectively. . (A) The first and the second eigenvectors in the PCA of the combined SAC and American populations. (B) The first and the second eigenvectors in the PCA of the combined SAC and Middle-east populations. Both figures in (A) and (B) show no evidence of relatedness between the SAC and populations from America and Middle-east.(TIFF)Click here for additional data file.Figure S9Plot of proxy-ancestry scores (Subjects and Methods) of each population in each group of reference populations. The highest peaks indicates the best proxy ancestry for the South African Coloured population.(TIFF)Click here for additional data file.Figure S10LD across all the autosomes in the SAC compared with proxy ancestral groups. (A–E). Plots of R-square ((TIFF)Click here for additional data file.Figure S11LD due to proxy ancestral population  admixture in the SAC. To generate these plots, we computed the LD between all pairs of markers in the SAC and the expected admixture from each pair of ancestral populations. The figure is the scatter plots of LD in the SAC and the expected admixture LD in pairs of ancestral populations.(TIFF)Click here for additional data file.Table S1Putative ancestral populations included in the fine characterization of the South African Coloureds (SAC) and simulation data.(PDF)Click here for additional data file.Table S2f3 Statistic: the signal of admixture in the simulation data  and Indian Gujarati and CEU) using pair-wise ancestral populations. The f3 statistic fails to provide clear evidence/non-evidence of population admixture based on simulated data of a 5-way admixed population.(PDF)Click here for additional data file.Table S3Comparing genetic diversity between the South African Coloured population (SAC) and the five proxy ancestral groups contributing to the SAC admixture. Mean and standard error of shared haplotype segment in cM (Hap.segment), mean and standard error of haplotype diversity measure (Hap.diversity) and proportion of IBD (Prop.IBD).(PDF)Click here for additional data file.File S1PROXYANC: (PDF)Click here for additional data file.


Furnestinia echeneis in reared and neighbouring wild sea bream to indicate pathogen transfer, characterized by the phenotypic plasticity of the parasite attachment apparatus and the lack of phylogenetic differentiation. The observed pattern of genetic variation inferred by nuclear DNA Internal Transcribed Spacer 1 (ITS1) and mtDNA cytochrome C oxidase 1 (COI), between parasite populations is most likely caused by a recent shared demographic history like a reduced species area in the last glacial period. In spite of such recent expansion that populations underwent, F. echeneis shows differentiation in haptor morphometry as an adaptive trait in closely related populations at the aquaculture site. This suggests that differentiation in morphology may occur relatively rapidly in this species and that adaptive forces, not the speciation process, drives this monogenean parasitation. On the other hand, the observed phylogenetic inertia suggests a low to moderate gene flow (based on FST) between parasites in cultured and wild fish, evidencing for the first time the transfer of pathogens at the aquaculture site inferred by a molecular tool.It is widely accepted that disease interactions between cultured and wild fish occur repeatedly, although reported cases have mainly relied just on the observation of similar symptoms in affected populations. Whether there is an explicit pathogen transfer between fish stocks, or each develops its own pathogen population, has been insufficiently studied and rarely supported by molecular tools. In this study, we used population dynamics and genetic structure of the monogenean  The monogenean parasite Furnestinia echeneis (Diplectanidae) once forming the monospecies genus Furnestinia based on the distinctive feature of a single adhesive organ on the opistohaptor Lamellodiscus based on the phylogenetic analysis of 18S and Internal Transcribed Spacer 1 (ITS1) rDNA Lamellodiscus, although less strongly developed. The parasite is strictly specialist for the sea bream Sparus aurata and has been recognised as a common and prevalent primary trigger in the course of secondary bacterial diseases in farmed bream in the Mediterranean Lamellodiscus elegansF. echeneis has been observed colonising its reared host As a response to an increasing demand for limited fish supply from fisheries, aquaculture has emerged as a high-throughput production of relatively cheap protein, significantly contributing to the enhancement of the global seafood offer to the market. Likewise aquaculture production estimated at around 45 million tons in 2004 has been predicted to reach 74 million tons by 2015 F. echeneis population genetic structure in reared sea bream (adult fish and newly seeded fingerlings) versus wild sea bream aggregating at the facility site, inferred from ITS1 rDNA and mtDNA cytochrome oxidase 1 (COI) markers, as well as potential differences in morphological features of the opistohaptor (lamellodisc); and b) estimate the length of time necessary for F. echeneis to colonised parasite-naïve fish (imported sea bream fingerlings) while at the same time identifying the origin of the colonising monogenean (wild vs reared adult fish).In this paper, our goals were to a) define This study was carried out in strict accordance with the recommendations of the Protocol for Work with Animal in Experiment of the Institute of Oceanography and Fisheries, Croatia and Regulation for protection of animals that are used in experiments or other scientific purposes of the Ministry of Agriculture, Fisheries and Rural Development of Croatia (NN 135/06). The study was approved by the Animal Ethics Committee of the Institute of Oceanography and Fisheries by a written permit (06/2009). Fish were sampled from the cages by hook and line and immediately exposed to excessive anesthesia by Eugenol®. When no opercular or fin movements were observed, fish were transferred to ice containers and transported to the laboratory. The same procedure was followed for wild fish, except that samples were collected by spear gun.Sparus aurata) (N = 32) age +1, were sampled during summer months in 2010 from a single cage of a central Adriatic finfish facilities (Maslinova N 45°18′ E 16°27′). Monogeneans isolated from this sample were afterwards designated as population 1 - pop1. The average sea bream total weight was 119.82 g (±35.64 SD) and total length 19.82 cm (±9.13 SD). Wild sea bream (N = 22) were caught by hook and line or a spear gun at the same facility site, in close vicinity of sampled cage and measured 335.53 g (±146.03 SD) and 28.01 cm (±5.32 SD). Monogeneans isolated from this sample were afterwards designated as population 2 - pop2.Cage reared sea bream . Fish were killed by the overexposure of essential clove oil (Eugenol®) in concentration over 100 ppm. Parasitological examination was performed as previously described F. echeneis individuals  were identified based on In the Gulf of Lion , Mediterranean Sea, wild sea bream (N = 20) were caught by spear gun and measured 257.42 g (±63.23 SD) and 23.21 cm (±6.67 SD). Monogeneans isolated from this sample were afterwards designated as population 3 - pop3. In June 2010, imported sea bream fingerlings , were sampled at the arrival in the finfish facility  till infection with monogenean F. echeneis individuals. First, to test whether or not the global morphometry of monogenean individuals differs between hosts, a principal component analysis (PCA) was conducted using all variables measured on the haptor. Also, each landmark value was compared between two types of host i.e. wild and reared seabream, using the Mann-Whitney test. Second, to define possible morphotypes, the Euclidian standardized morphometric distance between individuals of F. echeneis was computed using all measurements made on the haptor, and a clustering analysis was carried out, using the unweighted pair group method using arithmetic average (UPGMA) on all morphometric distances after standardization. Finally, linear discriminant analysis (LDA) was performed to verify the presence of pre-defined morphotypes.Morphometry measurements were performed according to For phylogenetic analysis, genomic DNA was isolated using the QIAGEN DNeasy Blood and Tissue Kit (Qiagen). Quantity and purity of isolated DNA and amplified fragments afterwards was checked by bio-photometer (Eppendorf). Each specimen DNA was used twice; for COI and ITS1 amplification, respectively. CGT CGT GCC TGG GA 3′ and reverse primer 5′ GTA CAT AGA CAT CAC ACC AAG GT 3′. A mitochondrial DNA locus, COI (cytochrome C oxidase I) was amplified by PCR using 0.8 µM of each primers: forward primer 5′ GAG CTA AGT AAA AAT CAA GAA CC 3′ and reverse primer 5′ TCT ATC TAA CAC TGA GGC TG 3′, amplifying ∼300 bp of F. echeneis COI. The rest of the reaction mix for both markers consisted of DreamTaq buffer (Fermentas), 2 mM of MgCl2, 2 mM of each dNTP, 1.25 U of DreamTaq DNA polymerase (Fermentas) and 3 ng/µl of template. For both fragments the amplification profile consisted of initial denaturation for 3 min at 95°C, 35 cycles of denaturation for 30 sec each at 95°C, annealing at 56°C for 30 sec, elongation for 60 sec at 72°C with final extension of 10 min at 72°C. Products were loaded on a 1% agarose gel and visualized by adding SYBR Safe (1%) directly in the gel.A ∼900 bp fragment of Internal Transcribed Spacer 1 (ITS1) with partial 18S and 5.8S ribosomal DNA, was amplified using 0.8 µM of each primers: forward primer 5′ CAThttp://molevol.cmima.csic.es/castresana/Gblocks.html).PCR products were purified using QIAquick PCR Purification Kit (Qiagen) and sequenced on an ABI 3100 automatic DNA sequencer (Applied Biosystems), using the ABI PRISM BigDye Terminator Cycle Sequencing Kit, in both directions. Sequences were aligned by Clustal X, implemented in the MEGA 5 software, using default parameters, and trimmed using GBlocks tool , bootstrap t-test was used, while differences among prevalences were tested by unconditional tests, both incorporated within QP3.0.Nucleotide sequences of COI and ITS1 genes were compiled and aligned with Clustal X 1.83 A substitution model for both genes and the gamma distribution shape parameter for the rate of heterogeneity among sites were determined using Modeltest 3.07 ST and statistical significances were tested with 10000 permutations. The number of migrants per generation (Nm) between localities, AMOVA and FST calculations were performed in Arlequin 3.5. The null hypothesis of population panmixia was also tested in Arlequin 3.5 using an exact test of the differentiation of haplotypes among populations.For evaluation of hypothesized patterns of spatial genetic structure, a hierarchical analysis of molecular variance (AMOVA) was used to partition variance components attributable to population variance and to individuals within the populations, where 10000 permutations were performed to test the significance of pairwise population comparison. Pairwise genetic differentiation between populations was estimated using the fixation index FTajima’s D Mismatch distributions Maximum likelihood (ML) analyses were performed on molecular data sets, which included concatenated sequences from both genes. The ML heuristic searches were performed in PAUP* v4.0b10 http://tree.bio.ed.ac.uk/software/figtree/).Concatenated phylogenetic tree was constructed from the tree output file produced in the maximum likelihood analysis and visualized using FigTree (http://www.fluxes-engineering com/sharenet.htm).Finally, to illustrate haplotype distribution among sampled groups, a median-joining network F. echeneis in the wild sea bream population (N = 22) was 71.1% (95% confidence limits 69.32–79.51), intensity 3.24 (bootstrap 95% confidence limits 2.82–3.63) and abundance 2.24 (bootstrap 95% confidence limits 1.85–2.92) parasite per fish. In cage-reared +1 year old sea bream (N = 32), prevalence was 73.2% (95% confidence limits 61.54–78.12), intensity 3.95 (bootstrap 95% confidence limits 3.48–4.35) and abundance 2.73 (bootstrap 95% confidence limits 2.09–3.24) parasites per fish. In imported fingerlings (N = 104), F. echeneis oncomiracidia were observed on the 10th day after seeding in semi offshore cages, with prevalence of 20% (95% confidence limits 18.17–23.33), intensity 1.54 (bootstrap 95% confidence limits 1.32–1.78) and abundance of 0.2 (bootstrap 95% confidence limits 0.18–0.23) parasites per fish.The prevalence of 2 = 359.99, p  = 0.05), with exponent of the negative binomial k  = 0.828 (reared fish); 1.021 (wild fish); 0.07 (fingerlings), indicating non-random contact of Furnestina and sea bream.The smallest infected sea bream (fingerling) measured 7.5 cm and 6.28 g, while the largest one measured 32 cm and 448.15 g, respectively. Monogeneans were aggregated across host populations (right biased), and most sea breams harboured low numbers of parasites. The greatest number of parasites (N  = 14) has been harboured by a male of 23 cm and 219.87 g. Fitting the negative binomial distribution as a theoretical model to the observed data following the maximum-likelihood method, observed and expected frequencies did not differ significantly (χP<0.05).Comparing prevalence, abundance and intensity values between fish categories, no difference was observed between wild and +1 year old reared sea bream, while a significant difference between adult fish categories and fingerlings was noticed . The contribution of median ventral bar (mvb) and lateral dorsal bar (ldb) to variances between groups was negligible.According to the elemental projection plot , it can F-factor in LDA ≥7.00) in discrimination between the groups are c’, b’, and f. The discriminant function 1 accounts for 60.42% of total variance. A bivariate plot of CV1 versus CV2, shown in The LDA classification was performed in order to test for three pre-defined morphotype groups based on their morphological similarity. Using the log-transformed variables, the LDA correctly classified 100% of the cases. Variables having the greatest statistical significance (F. echeneis populations from different geographic origins were obtained and deposited in GenBank (JX089988-JX090041 for COI locus and JX090045-JX090099 for ITS1 locus). The length of the COI and ITS1 fragments used in the analysis was 279 bp (n = 66) and 969 bp (n = 55), respectively. In total, 20 variable sites were observed and 17 haplotypes were detected for COI fragment while for ITS1 fragment, 19 variable sites and 9 haplotypes were detected  and gene flow (Nm) among population are shown in ST values were generally high, showing significant genetic structure in the range investigated (FST(COI)  = 0.60, P<0.001; FST(ITS1)  = 0.29, P<0.001). Pairwise FST values among Adriatic and Mediterranean populations were high and significant, whilst among wild and reared Adriatic populations FST values were low and not significant, leading to much higher Nm estimated values in comparison to the Adriatic-Mediterranean values   was shalF. echeneis was investigated using mismatch distribution. For both genes, the goodness of fit test showed that no mismatch distributions for sample localities deviated significantly (P>0.05) from predicted values under the sudden expansion model of The demographic history of S test are presented in S test, which is based on the distribution of haplotypes, also showed negative values for Adriatic and overall populations, indicating an excess of rare haplotypes over what would be expected under neutrality. Following this test, the hypothesis of neutral evolution was rejected for all populations except for the western Mediterranean population (pop3).The results of Tajima’s D test and Fu’s FFurnestinia echeneis population dynamics between wild and reared fish are the same, indicating that the same ecological traits work simultaneously on both sides of the net barrier. In the wild environment fish would not show such elevated values of parasite population, since host interactions, food availability and other ecological factors are far less pronounced than for agglomerated enclosed fish hosts in aquaculture, where parasite proliferation is supported by high density, stress, and organic load. However, since farming facilities are known to represent fish aggregating devices (FAD), similar ecological factors within cages can be drawn to fish populations aggregating in their vicinity, resulting in the same dynamic values for F. echeneis in this case. Although we have not assessed Furnestinia dynamic through 1-year sampling, only in its most proliferative period (summer months), the same values have been observed in previous study F. echeneis infecting Mediterranean and Adriatic sea bream, we have evidenced the existence of genetically highly structured populations. Such genetic structuring of all three studied F. echeneis populations could be attributed to parasite ecological characteristics as wide distributional range (Adriatic vs. Gulf of Lion), the fragmented nature of the habitat or/and low expected rate of long distance dispersal ST value. To our knowledge, this is the first molecular evidence of pathogen transfer between fish in aquaculture and in the wild. Genetic differentiation of sea louse Lepeophtheirus salmonis infecting farmed and wild salmon has been previously studied using allozyme polymorphism and RAPD Analysing population genetic structure of the monogenean Furnestinia molecular diversity indices showed to be similar between the populations for the two analysed loci, although in both cases monogeneans from reared fish showed higher diversity indices that might have been expected due to their potential isolation in the cages. Haplotype diversity lay in the range 0.60–1 (COI), which is high in comparison to many other parasite species. Similar high haplotype diversity values have been reported in another monogenean species, Mazocraeoides gonialosae  F. echeneis based on Tajima’s D and Fu tests. A positive value would have indicated a bias towards intermediate frequency alleles, while a negative value would have indicated a bias towards rare alleles, the latter being a landmark of recent population expansion. This further suggests a relatively recent colonisation event of the Adriatic host. In consequence, Mediterranean and Adriatic Furnestinia populations showed incongruence in their expansion time, the former having more ancient population expansion pattern. Alternatively, negative values of Tajima and Fu’s tests could have been the outcome of balancing selection at a nearby locus, although studies demonstrating direct or indirect selection (through hitchhiking) on the mitochondrial genome in natural populations are rare to point a general rule Furnestinia populations fits with the widely observed pattern of population expansion in organisms across taxa following the last glacial period, which ended around 12,500 years ago.Recent population expansion is suggested for the Adriatic populations of F. echeneis experienced a transfer from wild to aquaculture fish, and as an hermaphroditic, specialist and fast-reproducing parasite with direct life-cycle, it generated a high diversity of haplotypes and discrete populations within Adriatic area. Haplotypes divergence  is in accordance with previous data for monogenean species: Haliotrema aurigae (0.17–0.7%), Euryhaliotrematoides grandis (0.17–7.99%), Polylabroides (0.12–1.89%) and Microcotyle (0.14–2.56%) Furnestinia populations.Furnestinia haplotypes parasitising adult reared sea bream. Furthermore, the haplotype network suggests that the most recent haplotypes belong to monogeneans isolated from fingerlings, and are divergent from the most abundant haplotype 1. This supports the hypothesis that pathogen transfer from adult caged fish to fingerlings has more probability to occur than the one from wild aggregating fish, emphasising the importance of widely neglected zootechnical measure that culturing sites, with sea currents taken in consideration, have to be designed in order to separate reared fish in different age categories. Differences in Furnestinia abundances between reared sea bream adults and fingerlings is attributed solely to the short period of fingerling sampling (e.g. as soon as the parasite has been established on the gills the sampling was stopped), and given enough time, Furnestinia would equalise its abundances in adult and fingerling hosts.Colonization of the monogenean-free fingerlings that originated from a biosecurity hatchery systems, by oncomiracidia, has been evidenced to occur relatively fast (10th day after transfer in cages) and in all cases, oncomiracidian haplotypes were shared with Furnestinia population is that it does not show evidence of neutral evolution Lamellodiscus, it is not unusual that the description of new species is documented as morphological variants of previously described species Lamellodiscus species, unlike Furnestinia, previous authors suggested that morphometric differences would indicate radiation and further speciation. However, in Furnestinia populations, shared by two closely sympatric fish populations, longer haptoral components in parasites from reared fish may represent a rapid adaptation to the local environment where excessive gill mucus production Ergasilus sieboldi, mucus cells encircling the parasite were significantly more abundant in infected than uninfected tissue Furnestinia infecting reared sea bream compared to wild fish. Such phenotypic plasticity in monogenean sclerotized parts, unsubstantiated with genetic differentiation between parasite population in reared and wild fish, could be also induced by other environmental factors like temperature Another characteristic of the Furnestinia populations are most likely caused by a recent demographic history in the form of a reduced species area in the last glacial period. In spite of such recent expansion, this monogenean shows differentiation in haptor morphometry in closely related populations at the aquaculture site, suggesting that differentiation in morphology and potentially in other traits may occur relatively rapidly in F. echeneis and that adaptive forces, not the speciation process, drives this monogenean parasitation. On the other hand, the observed phylogenetic structure suggests a free gene flow between parasites in cultured and wild fish, providing evidence for the transfer of pathogens at the aquaculture site inferred by a molecular tool.In conclusion, observed patterns of genetic variation within and between Figure S1Morphometric variables (landmarks) measured on the sclerified parts of the opisthohaptor of Furnestinia echeneis individuals: a, a’ - total length of dorsal and ventral hook; b, b’ - point length of dorsal and ventral hook; c, c’ - blade opening of dorsal and ventral hook; d - distance between grip and hilt; e - grip length; f - hilt length; mvb - median ventral bar; ldb - lateral dorsal bar.(TIF)Click here for additional data file.Figure S2Mismatch distribution of cytochrome c oxidase I (COI) haplotypes of Furnestinia echeneis sampled from Adriatic wild sea bream (a), Adriatic cage sea bream (b) and western Mediterranean wild sea bream (c).(TIF)Click here for additional data file.Figure S3Mismatch distribution of internal transcribed spacer 1 (ITS1) haplotypes of Furnestinia echeneis sampled from Adriatic wild sea bream (a), Adriatic cage sea bream (b) and western Mediterranean wild sea bream (c).(TIF)Click here for additional data file.Materials S1Furnestinia echeneis samples, with geographic area of sampling, source, host category and allocated GenBank accession numbers.(DOC)Click here for additional data file.Results S1Number of COI haplotypes obtained in each population and changes in base composition.(DOC)Click here for additional data file.Results S2Number of ITS1 haplotypes obtained in each population with changes in base composition.(DOC)Click here for additional data file.Results S3Sampling localities, hosts and descriptive statistics of genetic diversity of Furnestinia echeneis, based on COI sequence data.(DOC)Click here for additional data file.Results S4Sampling localities, hosts and descriptive statistics of genetic diversity of Furnestinia echeneis, based on ITS1 sequence data.(DOC)Click here for additional data file.Results S5Analysis of molecular variance (AMOVA) for Furnestinia echeneis populations, based on mitochondrial COI and ITS1  sequences data.(DOC)Click here for additional data file.Results S6Tajima's D, Fu's Fs statistics, corresponding P values and mismatch distribution parameter estimates for Furnestinia echeneis based on COI sequence data.(DOC)Click here for additional data file.Results S7Tajima's D, Fu's Fs statistics, corresponding P values and mismatch distribution parameter estimates for Furnestinia echeneis based on ITS1 sequence data.(DOC)Click here for additional data file.


Culex tritaeniorhynchus (Giles) (Diptera: Culicidae), collected from Bellary, Cuddalore, Pune, and the Microbial Containment Complex laboratory culture in India were analyzed for morphological and allozyme variation. Multivariate analysis based on eight morphological characteristics and three morphometric indices was used to investigate the morphological variations among the four populations. Principal component analysis of the data suggested that siphon, saddle, and anal gills related variables were most important. Discriminant factor analysis of morphological data revealed that the four populations form significantly different clusters which can be differentiated from each other based on siphon, saddle, and pectin teeth related variables. Allozyme electrophoresis of the four populations revealed that the mean heterozygosity per locus value had high variation, ranging from 0.0879 to 1.794. Fst values between 0 and 0.519 suggested genetic differentiation within these populations. Fis values ranged from 0 to 1 with most of the values closer to 1. The allelic frequencies and Nei's genetic identity values showed that genetic differences between populations were small, but significant. Some of the morphological and allozyme variations in the Cx. tritaeniorhynchus populations could be partly attributed to the environmental conditions. The findings suggested that transition of morphological characters and allozyme variations in Cx. tritaeniorhynchus populations seem to be consequences of influence and selection by the environmental conditions. These results indicated that populations of Cx. tritaeniorhynchus in non-endemic areas of Japanese encephalitis (JE) virus infection have higher adaptability as compared to endemic areas of JE infection.Four populations of  Culex tritaeniorhynchus (Giles) (Diptera: Culicidae) has emerged as an important vector of Japanese encephalitis (JE) virus in east, southeast, and south Asia . The change in the pattern of JE virus transmission in some parts of India from epidemic to endemic is partly correlated with the establishment of Cx. tritaeniorhynchus in these areas. The ability of Cx. tritaeniorhynchus to transmit and spread JE across India has become a topic of concern. Understanding the role of Cx. tritaeniorhynchus as a zoonotic and epizootic vector of JE is of primary importance in the understanding the JE epidemiology. Differences in transmission and vector competence of Cx. tritaeniorhynchus for JE provide reasons for investigation of variations in the populations of this species. However, in spite of its epidemiological importance in JE transmission, few studies have been done on Cx. tritaeniorhynchus. Neither the evolutionary history nor the population dynamics of this species is well understood. Investigation of different levels of genetic and morphological variation among the populations of Cx. tritaeniorhynchus will be important in designing vector control strategies. Considering repeated cases of JE infection, comparison of population variations in Cx. tritaeniorhynchus of endemic versus non-endemic areas of JE infection will be important in designing improved vector control measures. The present study attempted to address some of the above concerns by studying morphological and genetic differences between four populations of Cx. tritaeniorhynchus belonging to JE endemic and non-endemic areas.uth Asia . While CCx. tritaeniorhynchus provides insights into how past and contemporary species were influenced by evolutionary forces  laboratory culture in Pune were chosen as study sitesbecause Bellary, Cuddalore and Gorakhpur are endemic and because Pune is non-endemic to JE infection. In the MCC laboratory culture, c nature ; howeverc nature .Cx. tritaeniorhynchus. Multilocus enzyme electrophoresis was used as a preliminary tool to evaluate isoenzymic, genetic, and population variability in Cx. tritaeniorhynchus. The importance of the study to evaluate levels of genetic diversity of Cx. tritaeniorhynchus populations across India was also discussed.In this study, the question of whether the four populations differ from each other in morphological and/or genetic structure was addressed. It was hypothesized that there is no significant difference between the morphology and isoenzyme profiles of JE endemic populations  and JE non-endemic (Pune) populations. Discriminant factor analysis (DFA) and principle component analysis (PCA) were performed in order to select an aggregate of morphological characters which collectively differentiated the four populations of Cx. tritaeniorhynchus were sampled from four populations  at the National Institute of Virology (NIV) in Pune for the last 12 years. The population was self-mating and fed on blood meal. The colony was not supplemented with field collections and was kept in a separate room to avoid contamination between laboratory colonies. Colonies of each population were also maintained at NIV Pune. Individuals of n et al. . VoucherEight morphological characters and three ratios were scored for morphological analysis of fourth-instar larvae . Siphon M Tris-Borate, trace of bromophenol blue as a tracking dye at pH 6.8) on ice for one minute. Supernatants were collected by centrifugation at 10000g, 4° C for 5 min. Electrophoresis was carried out on a 7 cm long, 1 mm thick, 12.5% non-denaturating Polyacrylamide gel at 5° C with a constant current of 20mA (Biorad electrophoresis system) until the tracking dye (bromophenol blue) reached the bottom of the gel (approx. 90–120 min). Staining was carried out for seven different allozymes . The data was analyzed using multivariate statistics. Multivariate analysis offered the advantage of taking into account all the variables in a single analysis, thus making it possible to assess variation in the morphological characters of larvae from different collection sites. Principal component analysis (PCA) was done to create uncorrelated principal components from the original variables. Factor scores estimated the actual values of individual observations for the factors, and correlation between variables and factors was called factor loading. The first two principal factors, which explained maximum variation in the data, were analyzed to understand the variation in the morphology of different individuals. Discriminant factor analysis (DFA) was done to find the variables which were most useful for discriminating between individuals of different populations.One factor ANOVA was performed to evaluate the morphological differences in the four populations of In DFA, to find out whether the clusters were significantly different from each other, Pillai's trace statistics  were perA), the effective number of alleles per locus (A0), percentage of polymorphic loci (P), and mean heterozygosity per locus (H) with respect to the Hardy-Weinberg expectation  (k - 1)] were obtained, with k(k - 1)/2 degrees of freedom, where n was the sample size and k was the number of alleles  Fst(k - 1)] was used, with (k - 1) (s - 1) degrees of freedom, where s was the number of populations  homozygotes for the most common allele, (ii) heterozygotes for the most common allele, and (iii) other genotypes. Departures from Hardy-Weinberg were only considered significant if both χ2 tests were significant. The gene frequency data were analyzed using BOTTLENECK software (HE) was higher than the expected equilibrium gene diversity (Heq), which was calculated from the observed number of alleles for each locus in each population under the assumption of mutation-drift equilibrium and the infinite allele model  pecten teeth, width of anal gills, comb scale, and width of siphon were not significantly different, while remaining characters were significantly different even after Benferroni correction. Between populations of JE non-endemic areas, six characters — namely width of siphon, siphon saddle ratio, width of anal gills, pecten teeth, anal gill index and denticles on apical pecten tooth — were not significantly different, while the remaining characters were significantly different. When data for JE endemic and non-endemic region populations were pooled separately, the comparison showed that five characters — namely pecten teeth, denticles on apical pecten tooth, length of saddle, width of anal gills, and comb scales — did not differ significantly.1) explained 33.10% of the total variability, while the second factor (F2) explained 13.25% of the total variability; together the first two factors explained 46.35% of the total variability. Characters such as length of siphon, siphon index, siphon/saddle ratio, length of anal gills, and anal gill index showed high magnitude on F1. Length of siphon, width of siphon, length of saddle, length of anal gills, and denticle on apical pecten teeth showed high magnitude on F2. F1 was significantly different in all four populations of Cx. tritaeniorhynchus, whereas F2 was significantly different in Bellary and Pune populations. DFA could distinguish four significant clusters for Cuddalore, Bellary, Pashan and the MCC laboratory population   . Characten teeth .Cx. tritaeniorhynchus  in the MCC laboratory population were weak, showing low esterase activity. Bellary, Cuddalore, and Pune populations showed prominent β-EST-1 activity. Bellary and Cuddalore populations shared monomorphic ADH and were considered to be encoded by a single monomorphic loci whereas, Pune and the MCC laboratory populations showed polymorphism in ADH with presence of ADHa and ADHb alleles. Two alleles, GLCa and GLCb, were detected in all populations of Cx. tritaeniorhynchus. GPDa and GPDb alleles were detected in Bellary, Cuddalore, and the MCC laboratory, whereas the Pune population was monomorphic. SOD-3 loci were absent in the Cuddalore and Pune populations. SOD-3 was monomorphic in the Bellary population and SOD-3a and SOD-3b were present only in the MCC laboratory population. Isoenzyme profiles differed significantly between endemic and non-endemic populations. While enzymes like ADH and esterase were monomorphic in the case of endemic populations, they were polymorphic in non-endemic populations.Allozyme electrophoresis resulted in clear and consistent staining for 7 enzymes encoded by13 putative loci: ADH, α-Amy, G6PDH1, G6PDH2, G6PDH3, GPD, GLC, β-EST-1, β-EST-2, β-EST-3, SOD1, SOD2, and SOD3. All enzymes migrated anodally. A total of 18 alleles were detected from the four populations of rhynchus . The allCx. tritaeniorhynchus. Mean number of alleles per locus were 1.2, 1.2, 1.3, and 1.4 for the Bellary, Cuddalore, Pune and MCC laboratory populations, respectively. Percentages of polymorphic loci were 20%, 20%, 30%, and 40%, respectively, and themean heterozygosity per locus was 0.0879, 0.0905, 0.0950, and 0.1794, respectively. Effective numbers of alleles per locus were 1.187, 1.1986, 1.1941, and 1.359, respectively. F statistics for 10 loci  which was found to be higher than the expected heterozygosity at mutation equilibrium drift (Heq) (ft (Heq) . For theCx. tritaeniorhynchus and two outliers, Cx. pseudovishnui and Cx. vishnui  in the Cuddalore population as compared to the remaining Cx. tritaeniorhynchus (9–10) populations studied. Siphon index of the Cuddalore population (13–14) was also greater than Culex bankensis (4–5), Cx. pseudovishnui (6–10), and Cx. vishnui (6–8). The Bellary and Cuddalore populations had shorter anal gill lengths as compared to the Pune and MCC laboratory-reared populations. The causes of morphological differences between populations are often quite difficult to explain. Phenotype is under the double control of environmental conditions and genotype, but morphological changes can be rapid when different environmental conditions occur (Klepaker 1993). The transition of siphon length and anal gill length in Cuddalore from the rest of the populations is hypothesized to be a consequence of selection due to environmental conditions.The effects of geographical and environmental events on morphological and genetic structure of local populations of rhynchus . Principrhynchus . Length Cx.tritaeniorhynchus in the MCC laboratory population was higher – 0.96(±0.091), and these identities were markedly higher than the value of 0.85, suggested by Avise (Cx. tritaeniorhynchus showed higher homogeneity between the four populations, with Fis values ranging from 0.61 to 1 (Cx. tritaeniorhynchus populations, there were single groups in the dendrogram. In concordance with high levels of heterozygosity, the BOTTLENECK test results (Heterozygocity was an important parameter in determining the genetic variability. At the population level, genetic diversity of ulations  was simiulations . The higby Avise  as the l.61 to 1  and Nei  results  indicate results , which iCulex family have a notorious reputation for developing resistance to insecticides, including organophosphates, carbamates, and pyrethroids (Cx. tritaeniorhynchus. Pune is non-endemic to JE but has long history of malaria vector control programs. It is possible that Cx. tritaeniorhynchus has been exposed to chemicals used for vector control and, hence, has acquired the high esterase activity. These observations clearly indicate that in the future different control measures will be required to reduce the Cx. tritaeniorhynchus populations.Insecticide resistance complicates the role of mosquitoes in pathogen transmission because it limits the option for vector control. Members of ethroids . All theCx. tritaeniorhynchus revealed that the Pune population has more adaptation possibilities than the other two field populations. Due to urbanization, environmental conditions such as pollution, water quality, and air quality in Pune are different than in Bellary and Cuddalore. These environmental conditions might be playing a crucial role in the adaptability of the Pune population.Allelic frequency is one of the elements important in characterizing a population's genetic state. The higher the number of alleles per locus, the higher the adaptation possibility of a population. The allelic frequency analyses carried out in three field populations of Cx. tritaeniorhynchus populations. Better knowledge of population structures may benefit existing JE control strategies. Adaptability, genetic differentiation, heterozygosity, genetic identity, and bottleneck effects provide insights into population structure. In endemic areas of JE infection, little genetic differentiation was observed, whereas in non-endemic areas moderate genetic differentiation was observed. Adaptability was higher in non-endemic areas compared to endemic areas of JE infection. Excess of heterozygosity relative to allele number was observed in more loci of non-endemic areas compared to endemic areas of JE infection. These results clearly indicate that populations of Cx. tritaeniorhynchus in non-endemic areas have higher adaptability compared to endemic areas of JE infection. In Neighbor joining cluster analysis, populations of endemic JE infection areas showed high morphological and genetic similarity. Additional studies on genetic makeup and population dynamics will help in designing better vector control and antiviral strategies.Comparison of non-endemic versus endemic areas of JE infection will help in better understanding the structure of The null hypothesis, that there is no significant difference between morphometry and isoenzyme profile, was rejected. JE endemic and JE non-endemic populations differed significantly in characters related to siphon and anal gills. Isoenzyme profiles differed significantly between JE endemic and JE non-endemic populations. While enzymes like ADH and esterase were monomorphic in the case of JE endemic populations, they were polymorphic in JE non-endemic populations.Cx. tritaeniorhynchus populations. It is important to point out that this is the first study to use multivariate analysis of morphological characters and allozyme analysis to resolve the population differences of Cx. tritaeniorhynchus in India. Results from this study illustrate the complexity of population variation in the mosquito Cx. tritaeniorhynchus. The allelic frequencies, F statistics, and Nei's genetic identity values showed that genetic differences between populations were small, but significant. The detected morphological and phenotypic variation may be related to differential environmental conditions such as temperature, food availability, and water quality. It is also known that in small populations, selection can often operate to influence the characters. The same characters, however, show that the environment confers adaptive morphological changes on organisms giving false morphological variations, suggesting the presence of stable variants. Efforts in correlating vector competence and its selection vis-à-vis morphological and genetic variation will be of great importance. It would be interesting to test whether microsatellites, which are known to give a closer estimation of heterozygosity at large-scale levels than allozymes, would be more useful in resolving the population structure of Cx. tritaeniorhynchus.In conclusion, the traditional multivariate morphometry employed during the present study demonstrated its usefulness in distinguishing


Peromyscus maniculatus) converge within the state of Oregon. Populations of these mice diverge morphologically across an east–west axis, and they diverge in mitochondrial DNA haplotypes across a north–south axis. In this study, we investigate these geographically contrasting patterns of differentiation in the context of ecological and evolutionary definitions (paradigms) of populations. We investigate these patterns using a new and geographically expansive sample that integrates data on morphology, mitochondrial DNA, and nuclear DNA. We found no evidence of nuclear genetic differentiation between the morphologically and mitochondrially distinct populations, thus indicating the occurrence of gene flow across Oregon. Under the evolutionary paradigm, Oregon populations can be considered a single population, whereas morphological and mitochondrial differentiations do not indicate distinct populations. In contrast, under the ecological paradigm morphological differentiation indicates distinct populations based on the low likelihood of demographic interactions between geographically distant individuals. The two sympatric but mitochondrially distinct haplogroups form a single population under the ecological paradigm. Hence, we find that the difference between evolutionary and ecological paradigms is the time-scale of interest, and we believe that the more chronologically inclusive evolutionary paradigm may be preferable except in cases where only a single generation is of interest.Despite current interest in population genetics, a concrete definition of a “population” remains elusive. Multiple ecologically and evolutionarily based definitions of population are in current use, which focus, respectively, on demographic and genetic interactions. Accurate population delimitation is crucial for not only evolutionary and ecological population biology, but also for conservation of threatened populations. Along the Pacific Coast of North America, two contrasting patterns of geographic variation in deer mice ( Populations are the fundamental unit of evolution, the scale at which the microevolutionary forces of natural selection, genetic drift, gene flow, and mutation act. Population delimitation is the analytical process by which researchers attempt to define boundaries between distinct populations. The current emphasis of conservation biology on conserving “evolutionarily significant units”  relies oIn the ecological paradigm, the cohesive forces are largely demographic, and emphasis is on co-occurrence in space and time so that individuals have an opportunity to interact demographically . In the evolutionary paradigm, the cohesive forces are primarily genetic, and emphasis is on reproductive interactions between individuals.Peromyscus maniculatus (deer mice) in western North America, within the state of Oregon. We investigate these mice with methods that have commonly been used to delimit populations: analyses of mitochondrial DNA (mtDNA) and morphological differentiation. We then further compare our findings to results from nuclear DNA analyses, which are becoming more common for investigating population delimitation.Here, we investigate the applicability of these paradigms to populations of P. maniculatus represent an interesting conundrum for population delimitation. Evidence from field surveys and classical taxonomy indicates that the morphologies of Oregon P. maniculatus populations diverge across a west–east axis , which may indicate a misleading degree of population connectivity or isolation. Mitochondrial DNA may indicate population isolation despite interbreeding between populations because of the maternal inheritance of mtDNA, especially in species with male-biased dispersal such as iculatus . In contIn this study, we test the validity of population designations based on morphological and mtDNA data under the above ecological and evolutionary “population” paradigms. We conduct replicate sampling transects across both the morphological and mtDNA axes of differentiation. We present statistically rigorous morphological data from populations to determine the validity of the previously reported west–east/forest-sagebrush axis of morphological differentiation. We provide new mtDNA data along the new sampling transects to expand the geographic sampling of admixture between northern and southern mtDNA haplotypes within Oregon. We then explore whether morphological and mtDNA differentiation corresponds to nuclear DNA differentiation. Next, we use these nuclear genetic data to test for genetic connectivity across Oregon populations to determine whether separate “evolutionary” populations exist. Finally, we interpret the results under the both population paradigms to determine whether the populations delimited under each paradigm are congruent.P. maniculatus from six localities across Oregon  for a total n = 503 and used jModelTest to estimate the most likely model of sequence evolution and the model parameters for each locus using the Akaike information criterion. We evaluated seven models of evolution and four parameters  per model . We used these models and parameter values to perform maximum-likelihood based phylogenetic inference with PHYML 3.0 . Each run used six substitution categories and included a proportion of invariant sites and a Γ-distribution of rate variation. For each locus, each run consisted of 20 million generations, saving every 20,000th tree, with the first 250 saved trees discarded as a “burn-in.” Each run consisted of four chains with default priors other than the branch length prior, which we set to an unconstrained value of 0.50 because of the short branches expected in this population study. For each run, we used AWTY  using the vegan package  in R. Wek = 9) to correspond to the number of loci genotyped for this analysis. We tested each PCoA axis for statistical significance by comparison to the broken-stick distribution.To test whether the nuclear microsatellite data were differentiated in concurrence with the morphological data, we ordinated the triangular molecular genetic distance matrix generated by GENALEX using Principal Co-ordinate Analysis (PCoA) in vegan. We set the number of axes to nine  for each k across the 10 runs. We then calculated the ΔLn P(D) between each adjacent value of K to find where ΔLn P(D) was maximized to indicate the most likely number of populations in the sample .To estimate the number of populations present among the six localities we sampled, we analyzed the microsatellite data from all individuals with the program STRUCTURE 2.3.3 . We performed 10 runs each for In our geographically expanded sample of mice from Oregon, we again found strong mtDNA divergence  accordinThe locality-based phylogeny inferred from *BEAST did not reveal significant geographic genetic structure among samples from each of the six localities. Nodal posterior probabilities for genetic relationships between localities were quite low (0.1737–0.3482), and the tree as a whole was unresolved .P < 0.001). None of the remaining principal component axes were significantly explanatory. Greater PC1 values were correlated with larger measurements of all 19 traits, indicating that PC1 values corresponded to overall size of an individual. However, the range of loadings on PC1 varied greatly across traits , indicating that the size increase in forest populations was allometric rather than isometric in nature and that PC1 values thus reflect variation in body proportions to some degree. The five measurements with the strongest loadings on PC1 were total length (−0.316), humerus length (−0.302), tail length (−0.299), weight (−0.296), and body length (−0.267).Mice from forest and sagebrush-steppe localities were significantly different in overall morphology , supportr = −0.03, P = 0.827).Unlike the PCA for morphological data, the PCoA for microsatellite data found that individuals across the entire state of Oregon (both forest and shrub-steppe habitats) had very similar nuclear microsatellite variation . The micm were significantly different from zero with the exception of migration from Curry into Lincoln and Curry into Wasco Counties in the nuclear sequence analysis  (between k = 4 and k = 5) . The waterfall diagram for the individual run with the highest Ln Likelihood  also did not indicate any population structure corresponding to sampling locality.The STRUCTURE analysis supported the presence of either one or two genetic populations among the six localities sampled. The magnitude of ΔLn P(D) was greatest between d k = 5) . WaterfaIn terms of population delimitation, individuals of both mitochondrial clades were found at the same localities, and thus they have the opportunity to interact demographically. Thus, under the ecological paradigm of Waples and Gaggiotti (2009), mice of both clades form a single population. Based on the nuclear DNA data, mice of both clades are likely interbreeding and thus form a single population under the evolutionary paradigm of Waples and Gaggiotti (2009). We thus conclude that in this case designating mice with distinct mtDNA haplotypes as separate populations is inaccurate.K metric  to evaluate the STRUCTURE results under the hypothesis of a single genetic pool (K = 1), which was supported by the *BEAST and PCoA analyses. Nevertheless, the two clusters supported by the ΔK metric were relatively undifferentiated in terms of FST, and this could represent stochastic variation present within a single genetic cluster. Additionally, membership in these two clusters corresponded to neither mtDNA haplogroup nor to locality.The mtDNA divergence observed here is consistent with the divergence we originally identified . HoweverThe geographically expanded sampling of the current study reveals that the admixture zone between Pacific Northwest and Californian mtDNA haplotypes may be more geographically complex than the north–south gradient described by P. maniculatus populations, supports the general pattern of genetic homogeneity suggested by The locality-based phylogeny of nuclear DNA data was unresolved, indicating that mice from these six localities are not genetically distinct. This finding is concordant with the large amounts of interpopulation gene flow indicated by the LAMARC analysis. As an alternative to using microsatellite data to infer population relationships as in The morphological and nuclear genetic patterns of differentiation that we observed are discordant . The morOne conclusion would be that these mice simply have a plastic phenotypic response to their local environment and that they could represent a single population. On the other hand, these mice may be undergoing divergent natural selection that results in a pattern of habitat-associated local adaptation. Our results show that forest mice are morphologically differentiated from sagebrush-steppe mice despite substantial gene flow between populations associated with different habitat types, suggesting that gene flow is being balanced by some other evolutionary phenomenon, perhaps divergent natural selection. The pattern of morphological differentiation between Oregon forest and sagebrush-steppe mice is similar to a pattern of morphological differentiation between forest and grassland mice observed in other North American deer mouse populations. In these other populations, mice that live in forested habitats are larger, longer-tailed, and have longer hind feet than mice that live in adjacent nonforested habitat . These at = 12.28, df = 165, P < 0.001), longer tails , and longer hind feet  than interior sagebrush-steppe mice. Coastal forest mice also had longer tails relative to body length than interior mice . In contrast to Horner's (1954) study, the nonforest mice sampled here had longer feet relative to body size than forest mice . Interestingly, forest and sagebrush-steppe populations had statistically indistinguishable numbers of presacral vertebrae  despite a large difference in number of tail  vertebrae . This increase in body segmentation limited to a specific body structure suggests potential evolution of developmental regulatory genes in forest mice  over the chronological and spatial span of interaction. Ecological population paradigms emphasize co-occurrence in space and time to provide an opportunity for demographic interaction. Evolutionary population paradigms emphasize genetic interactions between individuals that can take place many generations after an individual is deceased through the mating of descendant offspring, allowing genetic continuity over large geographic distances. Delimiting populations under an ecological population paradigm allows a priori population delimitation based solely on geographic location of individuals. In contrast, delimiting populations under an evolutionary paradigm requires (in the absence of direct observation of reproduction) genetic analysis in order to identify genetic relatedness between individuals produced by past reproductive interactions between their ancestors, allowing post facto population delimitation. In the current study, mice from forest and sagebrush-steppe environments form separate ecological populations because of their geographic separation but constitute a single evolutionary population based on their genetic cohesion. This finding highlights the difficulty of using an ecological paradigm to delimit populations of species with geographically broad, continuous distributions such as P. maniculatus compose a single population. Specifically, the genes of any individual could eventually mix with the genes of any other Oregon P. maniculatus over an evolutionary time frame (perhaps over centuries). However, over an ecological time frame (perhaps over tens of years) this type of reproductive interaction would be unlikely. Thus, if ecological and evolutionary population paradigms are to be reconciled as a single concrete population definition, we will likely have to specify the time scale over which interactions between individuals must occur. For the time being, deciding whether to apply an ecological or evolutionary population paradigm to a research problem should rest with the researcher (Waples and Gaggiotti 2005). Population delimitation based on an evolutionary paradigm allows researchers to integrate genetic evidence of past reproductive interactions between ancestors, resulting in a chronologically expansive body of evidence that may better reflect long-term patterns of population cohesion. Population delimitation based on an ecological paradigm will likely be the more conservative than delimitation based on an evolutionary paradigm simply because of the small spatial and chronological scale over which demographic interactions can take place. More research is necessary on whether genetic methods can reliably reflect demographic interactions (In this study, we were interested primarily in the evolution of the populations we studied, and based on our genetic evidence we conclude that Oregon ractions , and as