We have examined genetic diversity at fifteen autosomal microsatellite loci in seven predominant populations of Orissa to decipher whether populations inhabiting the same geographic region can be differentiated on the basis of language or ancestry. The studied populations have diverse historical accounts of their origin, belong to two major ethnic groups and different linguistic families. Caucasoid caste populations are speakers of Indo-European language and comprise Brahmins, Khandayat, Karan and Gope, while the three Australoid tribal populations include two Austric speakers: Juang and Saora and a Dravidian speaking population, Paroja. These divergent groups provide a varied substratum for understanding variation of genetic patterns in a geographical area resulting from differential admixture between migrants groups and aboriginals, and the influence of this admixture on population stratification.ST = 0.010), the contemporary caste and tribal groups formed distinct clusters in both Principal-Component plot and Neighbor-Joining tree. In the phylogenetic tree, the Orissa Brahmins showed close affinity to populations of North India, while Khandayat and Gope clustered with the tribal groups, suggesting a possibility of their origin from indigenous people.The allele distribution pattern showed uniformity in the studied groups with approximately 81% genetic variability within populations. The coefficient of gene differentiation was found to be significantly higher in tribes (0.014) than caste groups (0.004). Genetic variance between the groups was 0.34% in both ethnic and linguistic clusters and statistically significant only in the ethnic apportionment. Although the populations were genetically close (FThe extent of genetic differentiation in the contemporary caste and tribal groups of Orissa is highly significant and constitutes two distinct genetic clusters. Based on our observations, we suggest that since genetic distances and coefficient of gene differentiation were fairly small, the studied populations are indeed genetically similar and that the genetic structure of populations in a geographical region is primarily influenced by their ancestry and not by socio-cultural hierarchy or language. The scenario of genetic structure, however, might be different for other regions of the subcontinent where populations have more similar ethnic and linguistic backgrounds and there might be variations in the patterns of genomic and socio-cultural affinities in different geographical regions. Human society in a geographic area develops when colonizing populations bring along with them different languages, cultures and technological advancements over a period of time. As more populations migrate to settle in the same area, they are either eliminated, subjugated or absorbed . In Indith – 5th century B.C. from southeast Asian countries of Java, Sumatra, Brunei and Indonesia [This study aims to understand the genetic diversity of populations of Orissa and examines the role of language and genetic origin on structure of populations inhabiting the same geographic region and evaluates some of the suggested population histories from a molecular perspective. Orissa is a coastal state in the southeast region of India, which is occupied by population groups having varied ethnicity, belonging to different strata of the hierarchical caste system and speaking languages belonging to different linguistic families. Its strategic geographic location between Northern plains and peninsular Southern India and cultures assimilated during the 4ndonesia  have enrndonesia . Other tndonesia . Of thesndonesia ,11,12. Hndonesia .Microsatellites or short tandem repeats (STRs) are most extensively used for elucidating the genetic diversity and evolution of human populations because of their abundance and prevalence in the genome, high level of polymorphism and amenability to automation -23. HighIn this study, we have examined variation at 15 autosomal STR loci in a sample of 404 individuals from Orissa  on the seven populations of Orissa have been previously reported ,31. ExceST was calculated separately for caste groups and tribes. The coefficient of gene differentiation was found to be significantly higher in tribes (0.014) than caste groups (0.004). Combining all seven populations yielded an FST of 1%, demonstrating low level of population differentiation within Orissa. All values of FST were significantly different from zero (p < 0.05). Analysis of molecular variance (AMOVA) presented in Table To quantify the amount of genetic diversity that exists among populations, Fibes 0.01 than casBecause the amount of genetic variance between groups was found to be low, we also used clustering algorithm implemented in STRUCTURE analysis Figure  to exploThe inter-population genetic relationship among Brahmins, Khandayat, Karan, Gope, Juang, Saora and Paroja was determined using principal component analysis. The plot Figure  of princThe Neighbour-Joining (NJ) tree Figure  gives a India is a remarkable representation of a large segmented society that harbours rich genetic diversity within its human populations and offers myriads of attributes to study the various factors influencing demographics of human populations. It is of particular interest to study patterns of genetic affinities among endogamous groups inhabiting small geographical regions within the subcontinent because of their diverse origins and interethnic admixtures.We have typed a set of fifteen polymorphic autosomal microsatellite markers in linguistically and socially divergent populations with different histories of origin to elucidate the genetic diversities and affinities among them and to understand the role of genetic origin and language on the genetic structure of populations living in geographic contiguity. The most distinctive feature of our study was the clear delineation between castes and tribes, as was evident from both multivariate and phylogenetic analyses Figure , 2b and The significantly low coefficient of differentiation among the seven populations , along with the number of alleles shared between them, confirms admixture and suggests an increased genetic affinity among populations residing in geographic proximity irrespective of their socio-cultural affiliation ,38,39. Tet al 1998, where populations studied from widely separated geographic areas were found to exhibit closer genomic affinities with their geographic neighbors than with those sharing similar social ranks. It also substantiates the suggested origin of Khandayat from skilled individuals drawn from peasantry and aboriginals of the region [Among the caste groups, Orissa Brahmin showed close affinity to the other upper caste populations of North India rather than to its geographic neighbors. The affinity between Bihar Brahmin and Orissa Brahmin was supported with moderate bootstrap values in the phylogenetic tree Figure , which ce region . BecauseOur study on linguistically distinct but geographically contiguous populations of Orissa using autosomal microsatellite markers reveals a significant amount genetic homogeneity in them. AMOVA results suggest that linguistic differences probably play a negligible role in the present day scenario in restricting gene flow between these populations. The middle-order caste groups shared genetic affinity with the local people of the area, while the Brahmins were similar to those from northern regions. Tribal populations, on the other hand, because of their long-term isolation and mating patterns, were well differentiated from the upper caste groups. This paper provides evidence that for populations living in geographic contiguity, ancestry is the governing factor in fine-tuning of genetic differentiation.Blood samples were collected from randomly chosen consenting volunteers, distributed across 17° -48' and 22° -34' North latitude and 81° -24' and 87° -29' East longitude of Orissa . STR loci analyzed in the study included thirteen tetranucleotides D3S1358, THO1, D21S11, D18S51, D5S818, D13S317, D7S820, D16S539, CSF1PO, vWA, D8S1179, TPOX, FGA and two pentanuleotides, PentaD and PentaE.ST estimates, genetic distance and the analysis of molecular variance [A distance measure [The genetic structure of the populations was analyzed at two hierarchical levels – within populations and among populations. The intrapopulation variability was estimated by analyzing the number of alleles and most common allele at individual loci and by estimating the average gene diversity  across tvariance  were calvariance . Genetic measure , and wer measure . The deg measure  assumingSS carried out laboratory experiments, statistical analysis and drafted the manuscript and VKK conceptualized the paper, provided important intellectual inputs in intrepretation of data and preparation of the manuscript. Both authors read and approved the final manuscript.


Nicotiana attenuata, is found primarily in large ephemeral populations  after fires in sagebrush and pinyon-juniper ecosystems and in small persistent populations (for many growing seasons) in isolated washes typically along roadsides throughout the Great Basin Desert of the SW USA. This distribution pattern is due to its unusual germination behavior. Ephemeral populations are produced by the germination of dormant seeds from long-lived seed banks which are stimulated to germinate by a combination of unidentified positive cues found in wood smoke and the removal of inhibitors leached from the unburned litter of the dominant vegetation. Persistent populations may result where these inhibitors do not exist, as in washes or along disturbed roadsides. To determine if this germination behavior has influenced population structure, we conducted an AFLP , ISSR  and ISSR+ AFLP  analysis on plants originating from seed collected from populations growing in 11 wash and burns over 11 years from the SW USA.The native annual tobacco, Genetic variance as measured by both ISSR and AFLP markers was low among sites and comparatively higher within populations. Cluster analysis of the Utah samples with samples collected from Arizona, California, and Oregon as out-groups also did not reveal patterns. AMOVA analysis of the combined AFLP and ISSR data sets yielded significantly low genetic differentiation among sites (Φct), moderate among populations within sites (Φsc) and higher genetic differentiation within populations (Φst).We conclude that the seed dormancy of this post-fire annual and its resulting age structure in conjunction with natural selection processes are responsible for significantly low among sites and comparatively high within-population genetic variation observed in this species. Nicotiana attenuata Torr. ex Watson (Solanaceae) (synonymous with N. torreyana Nelson and Macbr.) is an annual native to the Great Basin Desert of California, Nevada, Idaho, and Utah (USA) [N. attenuata seeds are stimulated to germinate by unidentified factors in wood smoke [N. attenuata produce seeds that vary in their genetically-determined primary dormancy [ah (USA) -3 and prah (USA) ,4-9. Posah (USA)  can accood smoke  which leN. attenuata are self-compatible and outcrossing does not significantly affect seed production, seed mass or viability [This well-characterized germination behavior likely affects the genetic structure of this potential annual. Genetic structure of a population results from mutations, gene flow , drift, and selection, all acting in the context of an organism's life history traits . Geneticiability  indicatiN. attenuata plants from wash and burn populations in the SW Utah  Are plants growing in burn and wash populations genetically distinct? 2) Are plants growing in the same washes genetically similar through different years? 3) What is the genetic makeup of plants found growing across large burns and geographically adjacent populations? While genetic diversity among the various Nicotiana species has been studied with RAPD [Nicotiana species.Specifically, we compare plants growing from seeds collected from 11 large populations after fires, from small populations in 10 washes, from plants in transects across 5 large burns, and from plants growing in specific areas over 10 years during which a small wash population erupted into a large burn population as a result of a fire and returned to become a small wash population. By analyzing the genetic diversity across these ith RAPD  and AFLPith RAPD  markers,ith RAPD , this isprinciple co-ordinate (PCO) analyses. The Jaccard similarity index [unweighted pair group method average (UPGMA) dendrogram revealed a lack of distinct spatial or temporal structure and had brush- or star-structures with nodal bootstrap values of less than 60% (data not shown). The samples collected from the greatest spatial distances, namely California, Oregon and Arizona, did not form separate clusters from any of the Utah populations. A cluster analysis of 10 wash and 5 burn populations all grown from seed collected in 1999  and plants from Pahcoon, the highest (0.2043 ± 0.0027) (Table A Bayesian approach  was usedest 0.204 ± 0.0027p < 0.05) revealed highly significant differences at p < 0.001. AFLP and ISSR data was combined for an AMOVA analysis of all analyzed Utah populations. From this analysis, all three Φ categories were highly significant  . The Φst values from the AFLP, ISSR and the combined data sets were separately correlated with geographical distance and all revealed non significant correlations The analysis revealed high levels of heterozygosity, with total heterozygosity from all populations (0.2771 ± 0.0018) being higher than that from comparable analyses of self-pollinating annual plants 0.131) . The ISS1 . The I2 of each other. Pahcoon, was the site from which highest number of populations were analyzed. (9 populations), whereas, from other sites smaller numbers of populations were analyzed.The principle conclusion of this study is that large amount of genetic variation measured by AMOVA, within populations at a particular area significantly dwarfed that observed among sites, among populations growing in burns or washes, or collected during subsequent years growing at a given site. The conclusion that the genetic variation between neighbors is greater than that found between temporally- or spatially-separated populations, is dramatically reflected in the plants sampled along transects through the Pahcoon Springs burn. Only a small fraction (12.6%) of the total genetic variance is found among the 8 sub-samples from the extreme corners of this burn that covered more than 5000 hectares , while tPlatanthera leucophaea, Holsinger et. al [B is substantially larger than the estimates from the AMOVA analyses . In our study, AFLP + ISSR analysis also showed such difference (θB = 0.3305 Vs Φst = 0.156) whereas, exactly opposite values were found separate analysis of AFLP and ISSR data sets .F-statistic was estimated by using Bayesian approach with an analogue of the F-statistic, the Φ-statistic. Low but significant genetic differentiation was estimated among sites (Φct) from AFLP (0.027), ISSR 0.093) and AFLP + ISSR (0.046) data sets, whereas within populations, the Φst values were very high . Another major difference from the current study was that G. macleayana showed significant isolation by distance.Dormancy is a major adaptive response of native plants that allows them to cope with environmental variation and provide a means of habitat selection -29. Morenceolata , Callunavulgaris , Clarkiaillensis  and Lesqfendleri  it has bfendleri ,38. Othefendleri . Studiescleayana , which aSeed dormancy increases the effective generation time of this annual plant and by doing so, prevents genetic decay and inhibits the formation of spatial structure between geographically distinct populations . AdditioN. attenuata has all the characteristics of species pollinated by moths at night (white fragrant flowers scenting and becoming receptive at night) but day-active humming birds (Selaphorus sp.) and bumblebees (Bombus sp.) are also known to visit the flowers [Hyles lineata and Manduca species and could be dispersed by wind, water transport and animals, but none of these mechanisms are well documented. The seeds are eaten by various ground squirrels [N. attenuata calyx is sticky and glandular and could be dispersed by adhering to animals. However, the plants ability to produce the defense secondary metabolite nicotine in substantial quantities in its calyx [N. attenuata seeds, burned the sagebrush to promote its growth and are likely to have transported seeds throughout its range in North America [N. attenuata genotypes across the landscape by humans who were smoking this plant may have contributed to the lack of correlation between geographical and pair wise Φst values, as reflected by Mantel test for isolation by distance.Seeds of quirrels  but are quirrels  suggeststs calyx  may be a America . Hence, N. attenuata populations from Utah revealed by AFLP and ISSR analysis is a likely result of combination of random dispersal by humans and its seed dormancy.In summary, we conclude that the unusual nature of the N. attenuata populations in Utah showed: 1) high similarity across collection sites; 2) small difference between populations growing in burns or washes; 3) small differences between growing seasons; and 4) large difference between individuals growing within populations.We conclude that the genetic structure of 2 region of the SW corner of Utah (T38S R10W-T43S R19WUSA). Collections from Arizona (Flagstaff), Oregon (Eugene) and California (Sequoia Natl. Park) served as out-groups. In Utah, seeds were collected from plants growing at 6 locations for a number of years and were used for a time series analysis  were exposed for 1 h to 100 μL liquid smoke : water  in 1-mL shell vials and 5 seedlings were planted in soil and grown to the rosette-stage in a glasshouse. Leaves from one plant randomly selected plant from each collection were harvested for DNA extraction.Leaves were flash-frozen in liquid nitrogen, ground to powder and suspended in 750 μL of 100 mM Tris/50 mM EDTA (pH 8.0), containing 250 μg/mL RNase A. Eight μL liquid laundry detergent  were added. After 60 min incubation at 60°C and subsequent addition of 80 μL of 5 M NaCl, the suspension was centrifuged for 5 min at 16,000 × g. The supernatant was removed and extracted with phenol/chloroform. The DNA was precipitated with 600 μL isopropanol, pelleted by centrifugation at 16,000 × g for 5 min, washed with 200 μL 70% ethanol and dissolved in 50 μL of water. The purity and concentration of the extracted DNA were assessed by electrophoresis on a 1% agarose gel and optical density spectrometric measurements. Both AFLP and ISSR procedures were performed on the same DNA samples.Restriction. The enzyme combination EcoRI/MseI was used to restrict 500 ng of genomic DNA per sample. A 10 μL digestion mix  was added to 10 μL preparation of genomic DNA and incubated at 37°C for 3 h. (2) Ligation of adaptators. The double stranded EcoRI and MseI adaptator sequences designed by Zabeau and Vos [Pre-amplification. Primers designed by Vos [Amplification. Three 6-selective nucleotide EcoRI and MseI primer combinations, also designed by Vos [Nicotiana tabacum by Ren & Timco [The four-step AFLP marker production procedure of Sharbel  was foll and Vos  were ligd by Vos  complemed by Vos . (4) Ampd by Vos  and demo & Timco , were us & Timco . Each of & Timco .The separate PCR amplification products generated by each of the three primer combinations were loaded together with a ROX 500 GeneScan size standard onto the ABI Prism 310 automated genetic analysis system as described in the manufacturer's instructions. The samples were run with the following GeneScan settings: "GS STR POP 4 (1 mL) D" module; 150000 V run Voltage; 5 second sample injection; 60°C gel temperature, and 9 m Watt's laser power. The distinct emission spectra of the three fluorescently labeled Eco RI-primer types made it possible to distinguish the DNA fragments resulting from each of the different primer combinations separately while the samples were being separated in the same electrophoresis capillary.Collection of raw data and size alignment of the AFLP fragments was performed with ABI Prism GeneScan Analysis Software (Applied Biosystems) with the internal standard. Aligned data were subsequently imported into Genographer  for band2) 0.8 U Taq DNA polymerase (Eppendorf) 0.1 mM dNTPs, 0.3 μM primer. After 5 min initial denaturation at 94°C, 45 cycles of 1 min denaturation, 45 s annealing at 50°C, and 2 min for extension at 72°C, were followed by 5 min final extension in the PCR cycling program. A total of 55 primers were screened and 5 primers (Table The PCR reaction 25 μL) contained 20 ng genomic DNA, buffer  clustering method and PCO  options of software MVSP  programGenetic diversity was estimated for SET II   as heterozygosity using the Bayesian approach of Holsinger et. al. For thiThe SET II was used to calculate molecular variance from the combined and separate AFLP and ISSR data sets  as partitioned into individual and population components with an AMOVA (ver1.55: ). We alsRB carried out the entire ISSR analysis, the analysis of the AFLP data and contributed to writing the manuscript. DS grew the plants, extracted the DNA and conducted the AFLP analysis. CAP collected seeds, grew the plants and extracted the DNA. ITB was responsible for coordinating the study, collecting seeds for the analysis, and wrote the manuscript.Nicotiana attenuata. Levels of significance are given in the upper diagonal of the matrix: *p < 0.05, **p < 0.01, ***p < 0.001 and NS, Non Significant at p < 0.05. p-value Indicates the probability that a random genetic distance (Φst) is larger than observed distance and are based on 1000 iterations steps.Table 5 Pair-wise genetic difference  among 25 populations of Click here for file


Anopheles gambiae populations is important for the current tactics in mosquito control and for the proposed strategy using genetically-modified mosquitoes (GMM). Genetically-isolated mosquito populations on islands are a potential site for testing GMM. The objective of this study was to determine the genetic structure of A. gambiae populations on the islands in Lake Victoria, western Kenya.Understanding the genetic structure of island A. gambiae populations from five islands on Lake Victoria and six villages from the surrounding mainland area in the Suba District were examined using six microsatellite markers. The distance range of sampling sites varied between 2.5 and 35.1 km.The genetic diversity and the population genetic structures of 13 ST = 0.019) and between the island and mainland populations (FST = 0.003). A total of 12 private alleles were found, and nine of them were from the island populations.A similar level of genetic diversity between island mosquito populations and adjacent mainland populations was found. The average number of alleles per locus was 7.3 for the island populations and 6.8 for the mainland populations. The average observed heterozygosity was 0.32 and 0.28 for the island and mainland populations, respectively. A low but statistically significant genetic structure was detected among the island populations (FA level of genetic differentiation between the island and mainland populations was found. Large extent of gene flow between the island and mainland mosquito populations may result from wind- or human-assisted dispersal. Should the islands on Lake Victoria be used as a trial site for the release program of GMM, mosquito dispersal between the islands and between the island and the mainland should be vigorously monitored. Plasmodium [Despite 50 years of malaria vector control efforts, malaria remains a major public health threat in tropical and subtropical countries -3. In reasmodium  has signasmodium .A. gambiae cell lines were successfully transformed with the Hermes element [Minos transposable element bearing an exogenous gene was efficiently integrated into the genome of Anopheles stephensi [A. gambiae [A. gambiae genome sequences will greatly facilitate identification and cloning of parasite-inhibiting genes [One potential alternative malaria control strategy is based on the genetic disruption of mosquito vector competence -13. This element ,15, and tephensi ,17. Gene gambiae , and gen gambiae . Availabng genes .A. gambiae population genetic structure in the African continent has been examined [A. gambiae; however, no significant genetic structure was detected for mosquito populations between western Kenya and West Africa. The minimum area associated for a deme of A. gambiae in western or coastal Kenya is larger than 50 km [et al. [Anopheles arabiensis populations from the high plateau of Madagascar and those from Réunion and Mauritius islands (FST ranges from 0.080 to 0.215). Population substructure was also detected on the island of São Tomé, West Africa [The success of the transgenic mosquito approach depends on the spread and even fixation of parasite-inhibiting genes into natural populations. Presently, releasing transgenic mosquitoes to the field is premature. Isolated islands have been suggested as an ideal natural site for testing transgenic mosquito release strategies and spatial spreading of transgenes ,21,22. Iexamined -28. Thesan 50 km . Simard  [et al.  found a A. gambiae mosquitoes from five islands on Lake Victoria and the surrounding mainland in western Kenya. This information is valuable for selecting field sites to test transgene release strategies and evaluating the spread of transgenes in nature.The present study examined the genetic diversity and the population genetic structures of A. gambiae mosquitoes are the major malaria vectors in this region [Anopheline female mosquitoes were collected from seven villages on five islands in Lake Victoria and from six villages in the mainland Suba District, western Kenya Fig. . The sams region .A. gambiae sensu lato (s.l.) specimens were separated from other anophelines according to the identification key provided by Gillies and Coetzee [At least 170 anopheline mosquitoes were collected from four to 28 houses within each village using the pyrethrum spray collection method . Mosquit Coetzee  and thenA. gambiae species complex cannot be identified by morphology alone [A. gambiae s.l. females per village were tested. If the initial PCR testing failed to amplify for a sample, then the PCR analysis was repeated once or twice until successful amplification was achieved. If a sample could not be identified after three PCR amplifications, it was scored as unknown.PCR analysis was conducted for species identification using the rDNA-PCR method because individual species within the gy alone . About 1A. gambiae populations from the Lake Victoria islands and the surrounding mainland in western Kenya).Six microsatellite markers were used for specimen genotyping, including AGXH1D1 and AGXH131 of Chromosome X, AG2H46 and AG2H79 of Chromosome 2, and AG3H29C and AG3H33C of Chromosome 3 ,18,22,232, 1.0 μg BSA, 1.0 unit Taq polymerase and about 20 ng genomic DNA. Cycling conditions in a MJ Research PTC-220 thermocycler were 35–40 cycles of 94°C for 30 seconds, 55°C for 30 seconds and 72°C for 45 seconds. Allele sizes were determined using Gene ImagIR computer software [A Li-Cor Model 4200 Automated DNA Analyzer  was used for gel electrophoresis. For the apparatus to detect PCR products, one primer in every pair of microsatellite primers must be fluorescently labelled. To reduce the cost associated with synthesis of fluorescently labelled primers, we used the "tailed primer" method ,35; thatsoftware . The allIS statistics and probability test were used to determine whether distortion from HWE resulted from heterozygosity deficiency or excess using. Because the probability test is robust to low allele frequencies, rare alleles were not pooled. Variations in heterozygosity among the populations were analyzed following Weir's method [ST) using FSTAT 2.8 [ST statistic appears to be more sensitive to detect intraspecific differentiation than RST [Microsatellite polymorphism was measured by the number of alleles and heterozygosity at each locus. Using the probability test available in the GENEPOP computer program , conforms method , using tSTAT 2.8 . FST stathan RST ,41. The than RST  were calthan RST . A dendrST/(1 - FST) against the natural logarithm of straight-line geographical distance between population pairs [The isolation-by-distance model of population genetic structure was tested by linear regression of pair-wise Fon pairs . Statiston pairs .A moderate to high level of polymorphism was found in six loci across the 13 populations See the . The thrA. gambiae populations [A total of 14.1% loci (11 out of 78 tests) showed significant departure from Hardy-Weinberg equilibrium, all due to heterozygote deficiency. This was caused entirely by heterozygote deficiency in the locus AG2H46, a locus known for the presence of null alleles in western Kenyan ST = 0.019, P < 0.001) was almost twice as high as the six mainland populations . Genetic differentiation between island and mainland populations was also small . Pair-wise comparisons between all populations revealed that only seven pairs  exhibited significant FST values, and six of them were between an island and a mainland population.A low, but significant, genetic structure was detected among the seven island and the six mainland populations Table . The genST/(1 - FST) (P < 0.001), suggesting that the population genetic structure of A. gambiae populations from the island and mainland is consistent with the isolation-by-distance model. When the Ruri population is removed from the analysis, the correlation was still statistically significant (P = 0.015). Therefore, the population genetic structure of our study populations is consistent with the isolation-by-distance model. The cluster analysis revealed that the Ruri population, located farther inland from the other populations, was out-grouped from other populations with a significant bootstrap value, while other mainland and island populations were intermixed with non-significant branch bootstrap values  and among the six villages in the mainland in an area of approximately 40 × 20 km2 (FST = 0.010). The degree of genetic differentiation between the island populations in this study was less than for the island A. gambiae populations of São Tomé, western Africa (FST = 0.032) [ST estimates in the populations in this study were probably caused by shorter distance between islands (3–15 vs. 23–38 km) [ST estimates for the mainland populations in this study were comparable to other studies on the western Kenya populations (FST = 0.0033) [ST = 0.003). Thus, there is a very small degree of genetic isolation between island and mainland populations. This estimation is consistent with the private allele distribution in the studied populations, in which nine of the 12 private alleles were from the island populations. Further evidence for a small degree of genetic differentiation between island and mainland populations is from pair-wise population comparisons in which six out of the seven pairs that exhibited significant genetic differentiation were between an island population and a mainland population.A small but statistically significant genetic structure was detected for = 0.032) . The low3–38 km)  and a la 0.0033) ,27. The A. gambiae is usually less than 1 km [et al. [A. gambiae mosquitoes was related to the predominant wind direction at night, suggesting that wind assisted the dispersal of mosquitoes from their breeding site. A. gambiae have been shown to fly up to 7 km with the assistance of wind [The low level of genetic differentiation between island and mainland mosquito populations implies large gene flow between the two areas (83.1 migrants per generation). The normal flight range of han 1 km . The dis [et al.  found th of wind ,53. ThisAedes polynesiensis populations from islands found no significant effect of geographic distance on the population genetic structure, but detected a significant correlation between gene flow and commercial traffic by planes and/or boats between islands [A. arabiensis to the Mascarene islands and Madagascar was thought to be caused by human transportation by steamship lines [A. gambiae larvae were collected at the bottom of a wooden fishing boat [Mosquito migration may also be assisted by human activities. A study on  islands . The intip lines ,56. In Ling boat . RushingA. gambiae populations have implications for the ecological safety evaluation of the transgenic mosquito release program. During the initial field test of environmental safety and public health consequences by transgenic mosquito release, ideal sites would be islands that are totally genetically isolated from other islands and the mainland, with a sufficient number of human inhabitants and active malaria transmission on the island. Such an island may be extremely difficult to find, so islands with some genetic isolation from the mainland may have to be chosen. If so, the Lake Victoria islands could be used as field test sites; however, due to potential gene flow between the islands and between the islands and the mainland, mosquito dispersal between the islands and between the islands and the mainland should be vigorously monitored. After the release of the genetically modified mosquitoes, long-term monitoring programs should be launched to evaluate the spread of the transgenes to any unintended areas. In addition, methods to minimize the negative effects of transgene leak need to be developed prior to the field trial of transgene release [The results of this study of the population genetic stricture of island and mainland  release .This study showed that a low level of genetic differentiation existed between the island and mainland populations and no any genetically-isolated population was found among the 13 mosquito populations. If the islands on Lake Victoria were used as a trial site for the program to release genetically-modified mosquitoes, short-term and long-term mosquito dispersal between the islands and between the island and the mainland should be vigorously monitored.HC conducted species identification using PCR, microsatellite analyses and drafting the manuscript. NM was responsible for sample collection, and participated in species identification and drafting the manuscript. JB and GY supervised the study, and assisted data analysis and manuscript preparations.A. gambiae populations from the Lake Victoria islands and the surrounding mainland in western Kenya.A table of sample size, allelic number, heterozygosities and breeding coefficient of 13 Click here for file


A large number of microsatellites have been extensively used to comprehend the genetic diversity of different global groups. This paper entails polymorphism at 15 STR in four predominant and endogamous populations representing Karnataka, located on the southwest coast of India. The populations residing in this region are believed to have received gene flow from south Indian populations and world migrants, hence, we carried out a detailed study on populations inhabiting this region to understand their genetic structure, diversity related to geography and linguistic affiliation and relatedness to other Indian and global migrant populations.ST value. Iyengar and Lyngayat were placed above the regression line in the R-matrix analysis as opposed to the Gowda and Muslim. AMOVA indicated that majority of variation was confined to individuals within a population, with geographic grouping demonstrating lesser genetic differentiation as compared to linguistic clustering. DA distances show the genetic affinity among the southern populations, with Iyengar, Lyngayat and Vanniyar displaying some affinity with northern Brahmins and global migrant groups from East Asia and Europe.Various statistical analyses were performed on the microsatellite data to accomplish the objectives of the paper. The heretozygosity was moderately high and similar across the loci, with low average GThe microsatellite study divulges a common ancestry for the four diverse populations of Karnataka, with the overall genetic differentiation among them being largely confined to intra-population variation. The practice of consanguineous marriages might have attributed to the relatively lower gene flow displayed by Gowda and Muslim as compared to Iyengar and Lyngayat. The various statistical analyses strongly suggest that the studied populations could not be differentiated on the basis of caste or spatial location, although, linguistic affinity was reflected among the southern populations, distinguishing them from the northern groups. Our study also indicates a heterogeneous origin for Lyngayat and Iyengar owing to their genetic proximity with southern populations and northern Brahmins. The high-ranking communities, in particular, Iyengar, Lyngayat, Vanniyar and northern Brahmins might have experienced genetic admixture from East Asian and European ethnic groups. The Indian subcontinent is regarded as a natural genetic laboratory, owing to the co-existence and interaction of socio-culturally, linguistically, ethnically and genetically diversified endogamous populations in a geographical terrain. It is believed that the earliest humans leaving Africa for Eurasia might have taken a coastal route across Saudi Arabia, through Iraq, Iran, to Pakistan and finally entered India along the coastlines . A seconAnthropologically, southern and northern populations are distinct and these differences are further substantiated by (i) the presence of Neolithic sites in this region suggests that Neolithic people of southern India came from north by land and the west-coast by sea , (ii) thThe present study was carried out on one of the largest southern states, Karnataka, positioned on the southwest coast of India, with a dwelling of about 50 million people. This expanse has been a rich source of prehistoric discoveries dating back to the Paleolithic era that are akin to those seen in Europe . KarnataA few studies utilizing classical markers have been carried out on southern populations ,11,12, iAmong the different caste and tribal groups inhabiting the southwest coast of India, we have selected four predominant Dravidian-speaking communities from Karnataka: Iyengar Brahmin, Lyngayat, Gowda and Muslim, they not only belong to dissimilar groups of the Indian caste hierarchy but also have varied migration histories, conferring them uniqueness and significance from a genetic perspective. The present microsatellite study primarily attempts to understand the genetic structure of the four selected populations and to determine their genetic relationship with other linguistically and ethnically similar groups of southern India and Brahmin groups of northern India. It has been suggested that that despite the linguistic homogeneity in southern India, these populations have remained genetically diversified . Hence, ST value of 0.009 elucidates the low degree of genetic differentiation in them. However, the GST value for the pooled Indian and global populations demonstrated a high value at 2.3% (data not shown). Genetic relationship of studied populations with other similar southern groups; Vanniyar, Gounder, Pallar and Tanjore Kallar [A distances indicate that among these groups, Iyengar, Lyngayat and Vanniyar are more similar to the northern Brahmins (0.030). Furthermore, genetic distances emphasize the affinity of Lyngayat with Tanjore Kallar (0.029), Iyengar (0.026) and Vanniyar (0.028). Estimation of relatedness between the southern and global populations shows that all the southern communities formed a separate cluster, nevertheless, genetic distances disclose the affinity of upper caste Indian communities; Iyengar, Lyngayat, Vanniyar, Bihar and Oriya Brahmin with Europeans and East Asians. The Indian populations were most distant to Africans.Allele frequency at 15 STR was used to compute the heterozygosity (observed) for the four studied populations, which varied for each locus, and population but reflected similar values, ranging between 0.724 and 0.797 , irrespective of their geographic or linguistic grouping Table . The geoIn recent years, population genetics has witnessed extensive use of microsatellite markers to understand and evolutionary histories of contemporary human populations ,32-34. TThe most distinctive feature revealed by the fifteen microsatellites was the considerable genetic homogeneity amongst the four diverse caste groups residing in southwest India. The presence of an almost similar allele frequency pattern , suggestAMOVA test strongly suggests that genetic diversity among the southern populations was mainly confined to intra-population variation, further emphasizing the genetic homogeneity in them. Analysis using different genetic markers corroborate with our finding that the genetic diversity in human populations can be mainly attributed to variation within populations ,34,36,37An exploration of the genetic differentiation based on geographical grouping of populations discloses the genetic similarity among populations residing in a region. Nevertheless, the geographic affinity was comparably lesser to that observed within the two linguistic families, viz., Dravidian and Indo-European. Our finding provides evidence to the strong linguistic affinity prevailing amongst the Dravidian speaking populations and imparts them genetic distinctness from the Indo-European linguistic group. Even though prior studies have indicated that genetic clusters often correspond closely to predefined regional and linguistic groups , AMOVA sThe genetic differentiation of the studied populations with relevant global migrant groups was estimated to be 2.3%, relatively lower than the 9% observed in another similar study , which hThe populations selected in this study comprise of three major Hindu castes-Iyengar, Lyngayat, Gowda and a Muslim community, inhabiting the southwest coastal terrain of Karnataka (11.3 – 18.45°N latitudes and 74.12 – 78.40°E longitudes). All the populations belong to the Dravidian linguistic family and are speakers of the local dialect, Kannada, but differ in caste hierarchy and socio-religious practices. Consanguineous marriages have been reported in Karnataka, with inbreeding levels of the order 0.020 to 0.033, in general .Iyengar hold a high position in the Indian caste hierarchy and sporadic accounts on Brahmin, suggests that they primarily migrated from the upper Gangetic plains to southern India. Nonetheless, few bioanthropological studies have revealed that morphologically Brahmins of a geographical region are similar to the local groups.Lyngayat community was initially formed, as a religious cult by the amalgamation of people from different castes and geographical regions but later developed into a distinct community practicing strict marriage endogamy with social sub-divisions such as clans, sub-castes and sects .Gowda is a low ranking agriculturist caste group that typically exhibits the Dravidian socio-cultural characteristic of consanguineous marriage. It is believed to have moved in from the adjoining area of Tamil Nadu.th century, introduced new genes only in northern India, suggesting that Muslims from Southern India are mainly local converts [Muslim is a linguistically heterogeneous, complex religio-ethnic group, . It is bconverts .The 15 STR marker set analyzed in this study consists of thirteen tetra nucleotide repeat loci: D3S1358, THO1, D21S11, D18S51, D5S818, D13S317, D7S820, D16S539, CSF1PO, vWA, D8S179, TPOX, FGA and two penta nucleotide repeat loci: Penta D, Penta E. Their repeat size makes them less prone to slippage of polymerase during enzymatic amplification compared to the dinucleotide repeats, allowing unambiguous typing [The blood samples were collected from unrelated individuals belonging to – Iyengar (65), Lyngayat (98), Gowda (59) and Muslim (45) communities, residing in different districts of Karnataka. DNA was extracted from blood by the phenol-chloroform method , followeST), observed heterozygosity and pairwise genetic distances (DA) were computed using allele frequencies [Allele frequencies of the 15 STR loci were calculated using the gene counting method . The genquencies . The DA quencies . Neighboquencies , and itsAnalysis of molecular variance (AMOVA) was performed using the Arlequin Ver. 2.00 package . Two levTo assess the gene flow experienced by these populations, the rii value, i.e., the genetic distance of a population from the centroid was calculated using the regression model . This moii is the distance from the centroid, pi is the frequency of the allele in ith population and  is the mean allelic frequency.where, rSTR – Short Tandem RepeatAMOVA – Analysis of Molecular VarianceNJ tree – Neighbor-Joining treeRR carried out the molecular studies, analyzed the genetic data and drafted the manuscript. VKK participated in the design, conceiving and preparation of manuscript. Both authors read and approved the final manuscript.


India has experienced several waves of migration since the Middle Paleolithic. It is believed that the initial demic movement into India was from Africa along the southern coastal route, approximately 60,000–85,000 years before present (ybp). It has also been reported that there were two other major colonization which included eastward diffusion of Neolithic farmers (Elamo Dravidians) from Middle East sometime between 10,000 and 7,000 ybp and a southern dispersal of Indo Europeans from Central Asia 3,000 ybp. Mongol entry during the thirteenth century A.D. as well as some possible minor incursions from South China 50,000 to 60,000 ybp may have also contributed to cultural, linguistic and genetic diversity in India. Therefore, the genetic affinity and relationship of Indians with other world populations and also within India are often contested. In the present study, we have attempted to offer a fresh and immaculate interpretation on the genetic relationships of different North Indian populations with other Indian and world populations.A and Reynold's Fst) were calculated among the nine studied populations, Caucasians and East Asians. This analysis was based upon the allelic profile of 20 STR markers to assess the genetic similarity and differences of the north Indian populations. North Indians showed a stronger genetic relationship with the Europeans (DA 0.0341 and Fst 0.0119) as compared to the Asians (DA 0.1694 and Fst – 0.0718). The upper caste Brahmins and Muslims were closest to Caucasians while middle caste populations were closer to Asians. Finally, three phylogenetic assessments based on two different NJ and ML phylogenetic methods and PC plot analysis were carried out using the same panel of 20 STR markers and 20 geo-ethnic populations. The three phylogenetic assessments revealed that north Indians are clustering with Caucasians.We have first genotyped 20 tetra-nucleotide STR markers among 1800 north Indian samples of nine endogamous populations belonging to three different socio-cultural strata. Genetic distances (Nei's DThe genetic affinities of Indians and that of different caste groups towards Caucasians or East Asians is distributed in a cline where geographically north Indians and both upper caste and Muslim populations are genetically closer to the Caucasians. Approximately, 60,000–85,000 years before present (ybp) the African exodus occurred and early modern humans got settled in South Asia. They moved further along the southern Asian coast to reach Southeast Asia, New Guinea, and Australia . The exIt has been shown  that IndIt is believed that the Indian populations were derived from a small number of female founders, and the ethnic differentiation occurred subsequently through demographic expansions and geographic dispersal. This is further corroborated by the findings of shared haplogroup branches, without specific clustering of lineages in correlation with languages or the socio-cultural hierarchies of caste or tribal populations  ,11,16,17To meet this objective, we genotyped 20 tetra-nucleotide STR markers among 1800 north Indian samples from nine endogamous populations belonging to three different socio-cultural strata. Three of the upper caste populations were Bhargavas, Chaturvedis and other Brahmins, while the middle caste populations were Kayastha, Mathurs, Rastogies and Vaish. Two Muslim populations were Shia and Sunni. Selection of the STR markers was based on the global survey carried out by Perez-Lezaun et al 1987 . In ordeWe have observed 176 alleles at 20 STRs. The allele number ranged from 7 to 9 at sixteen STR loci  while ≥ 10 alleles have been observed at the remaining four STRs i.e. D3S1358, D16S310, HPRT and F13A. Average number of observed alleles was 8.8. The maximum numbers of 164 alleles have been observed in Shia, and minimum in Vaish (146). All the STRs were in HWE. Locus wise average observed heterozygosity is shown in additional file A being 0.034. Interestingly, all the nine population depicted relatively higher distances from Asian populations. Independently, the three upper caste Brahmin populations (Fst = 0.0116 and DA = 0.0332) were closest to the Europeans while four middle caste populations (Fst = 0.0167 and DA = 0.0482) were genetically more distant. The genetic distances with the Asian populations exhibited a totally different pattern where middle caste populations were least distant from Asians and upper caste Brahmins and Muslim sects were most distant [Table Pair wise genetic distances were calculated based on the allele frequencies of 20 STR markers. The distance matrices were generated Table  and haveA genetic distance) and ML phylogram based on variance in allele frequency distribution on 20 STRs were analyzed [Figure We have compared our populations with 16 world populations  [et al., 2003 [In order to prove the phylogenetic accuracy of STR loci, a panel of only 10 autosomal STR loci has been used to infer phylogenetic relationships among well-defined geo-ethnic population groups and it has been observed that despite of the high allelic variability, STR loci are successful in reconstructing the accurate human phylogenies. To achieve this goal, a database of 22 geographically targeted and racially diverse set – population from forensic literature was compiled -41. Both, (2001) ,29 on th, (2001) , which il., 2003  also revet al 2002 [We further compared our populations with other Indian and the world populations. On the basis of allele frequencies calculated at 6 STR loci in 35 Indian populations (including nine populations of the present study), we have deduced that the geographical barriers, and to some extent ethnic origin have been the major source of genetic structuring of Indian populations along with little effect of socio-cultural practices. Similar observations have been made by Kashyap  al 2002  in their al 2002 .The results based on 20 STR markers have revealed that all the populations have similar allele frequency distribution which may be suggestive of a common ancestry or a continuous gene flow among these populations. We did Gst, Fst and AMOVA assessment for all the nine populations Figure . It was It has been proposed that the genetic make up of the Indian populations is an admixture of Caucasians and Asians. Bamshad et al. 2001  studied The phylogenetic analysis of nine endogamous/consanguineous populations of North India based on 20 STR loci have unwrapped the information about the genetic affinities of north Indians. Our results have demonstrated that intra-population differences were marginal still there was a definite pattern of genetic variation found in different populations. Finally, we observed genetic affinities of Indians and that of different caste groups towards Caucasians or East Asians which are differentially distributed where geographically north Indians and socially both upper caste and Muslim populations are genetically closer to the Caucasians. However, the genetic configuration of Indians is as complex hence more genetic data from the sub-continent is highly necessitated to unravel the intricacy of Indian genetic composition.Present study is the first and one of the largest population based analysis (N = 1800) from this part of India. Moreover, we have taken into consideration a statistically significant sample size from all the caste populations. Total 200 samples have been collected from each of the nine populations i.e. Bhargavas, Chaturvedis, Brahmins, Kayastha, Mathurs, Rastogies, Vaish and Shia and Sunni Muslims (Uttar Pradesh). All the samples were adult with mean age of 38.8 ± 3.4 years and were residents of Uttar Pradesh since last three generations. Prior to the sample collection, regional addresses and detailed computerized lists of the populations have been prepared from different districts of Uttar Pradesh. Random numbers were generated with the help of computer and adult individuals living in different parts of Uttar Pradesh have been questioned about their ethnicity caste affiliations and surnames and the birthplaces of their parents as per the order of the random number. Only unrelated subjects were considered eligible to participate. The demographic profile and other ethnical and familial information were filled in a detailed Performa. Three-generation pedigree charts were prepared to assure un-relatedness in all the samples.Whole blood was obtained by venipuncture and about 5 ml of blood was collected in EDTA vacutainer tubes after obtaining the informed consent from the subjects. The study was performed with the approval of the institutional ethical reviewing committee of Sanjay Gandhi Post Graduate Institute of Medical Sciences (SGPGIMS), Lucknow and the government of India.High molecular weight genomic DNA was extracted by salting out method using phenol-chloroform as described by Coomey et al. 1993  and was A panel of 20 STR markers namely, FGA, D5S818, D7S820, D11S2010, D13S767, D9S926, D2S1328, D18S848, D14S306, D3S1358, ACPP, TPO, Tho1, VWA, FES, F13A1, D16S310, DHFRP2, HPRT and D4S243 were genotyped using PCR based locus specific amplification as mentioned earlier . One of Allele frequencies at each of the marker have been obtained by direct counting method from the observed number of alleles at a locus divided by total number of gametes. Deviation from the assumption of Hardy Weinberg equilibrium at genotypic frequencies for all markers in random north Indian population was estimated using Fischer's exact test based on 1000 Markov-Chain algorithm steps in Arlequin v2 software. Bonferroni correction to the p value was applied.A , and Reynold's Fst based on the allele frequency distribution of 20 STR were calculated to assess the genetic relationship of north Indians with the Europeans and Asians. Both the distance matrices namely Nei's DA , and Reynold's Fst were calculated using GENDIST option in PHYLIP v3.5c [Two different genetic distances Nei's DIP v3.5c .A , and Reynold's Fst using GENDIST option in PHYLIP v3.5c [Phylogenetic analysis carried out for different populations by two enrooted radial phylograms, Neighbor Joining or NJ-phylogenetic Tree and Maximum Likelihood or ML-phylogenetic Tree. The NJ algorithm was used to construct the branching array from a matrix of genetic distances calculated from different distance matrices namely Nei's DIP v3.5c . The optIP v3.5c .FK carried out laboratory experiments statistical analysis and drafted the manuscript. AKP, MT and ST were involved in sample collection and laboratory analysis. PSB helped in intrepretation of data and editing of the manuscript. MB helped in the statistical analysis. SA has conceptualized the paper provided important intellectual inputs in the preparation of the manuscript. All authors read and approved the final manuscript.Observed Heterozygosity at 20 STR markers among nine north Indian populations. Locus wise average observed heterozygosity for 20 STR marker in nine populations (present study).Click here for file


Alternative means of malaria control are urgently needed. Evaluating the effectiveness of measures that involve genetic manipulation of vector populations will be facilitated by identifying small, genetically isolated vector populations. The study was designed to use variation in microsatellite markers to look at genetic structure across four Lake Victoria islands and two surrounding mainland populations and for evidence of any restriction to free gene flow.loci distributed broadly throughout the genome and analysed for genetic structure, effective migration (Nem) and effective population size (Ne).Four Islands (from 20–50 km apart) and two surrounding mainland populations (96 km apart) were studied. Samples of indoor resting adult mosquitoes, collected over two consecutive years, were genotyped at microsatellite FST ranged from 0.014–0.105 and several pairs of populations had Ne m < 3. The loci showed broad heterogeneity at capturing or estimating population differences.Ne estimates showed island populations to consist of smaller demes compared to the mainland ones. Most populations were significantly differentiated geographically, and from one year to the other. Average geographic pair-wise These island populations are significantly genetically differentiated. Differences reoccurred over the study period, between the two mainland populations and between each other. This appears to be the product of their separation by water, dynamics of small populations and local adaptation. With further characterisation these islands could become possible sites for applying measures evaluating effectiveness of control by genetic manipulation. Plasmodium resistance to affordable antimalarial drugs [Anopheles gambiae and Anopheles funestus, the two primary malaria vectors in sub-Saharan Africa [Malaria kills over a million people annually, most from sub-Saharan Africa . Additioal drugs . Controln Africa ,4.Plasmodium survival have all been considered in genetic control, but most work has mainly focused on the identification of target genes that could modify the mosquito's ability to support Plasmodium sporogonic development [An alternative malaria control strategy being investigated in a number of laboratories is to genetically modify the vectorial capacity of vector populations by driving a genetic construct into the natural population. Genes that influence blood meal host selection, mosquito longevity, or elopment -10. The elopment -13, targelopment -18 and ielopment , less prA. gambiae is one of the vectors [A. gambiae in Africa is complex. Microsatellite-, allozyme-and mitochondria-based studies have suggested extensive gene flow between populations in Senegal and western Kenya, a geographical distance of 6,000 km [A. gambiae in West Africa [A. gambiae island populations in Sao Tome [A. arabiensis from the islands of Madagascar, Mauritius and Reunion have also shown extensive differentiation [A. gambiae populations across wide geographical distances  is due to high rates of gene flow among large populations or shared ancestral polymorphisms from a recent population expansion event [Studies of population genetic structure are vital to any vector-targeted control measure, especially where  vectors . This sp6,000 km ,22. In ct Africa -26and hit Africa . In addiSao Tome  and A. antiation . It is non event . Physicaon event ,32.A. gambiae on islands in Lake Victoria, a part of Africa where A. gambiae populations are generally thought to consist exclusively of the Savanna chromosomal form and the S molecular form. The purpose of this study was to use variation in microsatellite markers to investigate the genetic structure of populations of A. gambiae s.s on several islands in northern Lake Victoria with a view to determining whether geographic separation of these islands (from 20–50 km) was associated with any evidence suggesting restriction to gene flow. Chen and others [A. gambiae populations on islands 2.5–21 km apart in eastern Lake Victoria. Genetic structuring among the island populations and between islands and surrounding mainland populations was still detectable, though low. Isolated populations are potentially useful sites for studies to evaluate the potential impact of malaria control measures that involve genetic manipulation of natural vector populations.This study is focused on population structure of d others  in a stuA. gambiae populations involving one from each of four islands in northern half of Lake Victoria and two from the surrounding southern Uganda mainland were studied  of both sexes morphologically identified from other anophelines, based on a species identification key [tion key , were pret al [Genomic DNA was extracted from single mosquitoes by kit, using procedures in Mukwaya et al. , or, foret al . Individet al ,37,38. FGenotyping PCR was as follows: each 25 μl reaction contained 3.75 ng genomic DNA, 125 mM KCl, 25 mM Tris-HCl, PH 8.3, variable concentrations of MgCl2, 0.2 mM dNTP  0.011 mM each of either Fam, Tet and Hex or Blue, Green and Black Beckman coulter dye tagged forward primer and unlabeled reverse primer  and 0.25 μl of home-made Taq DNA Polymerase. Yr 1 amplification was from GeneAmp 9600, whereas GeneAmp 9700 thermocycler (Applied Biosystems) was used for yr 2. The cycling program consisted of one cycle at 96°C, 5 minutes; thirty-five cycles of 94°C, 30 seconds; 55°C or optimal, 20 seconds; 72°C, 30 seconds; and one cycle of 72°C, 5 minutes. The Fam-Tet-Hex labeled PCR products constituted five of the 17 yr 1 loci set and were fragment size scored on the ABI 377 automatic sequencer using default settings of the genotyper software (Applied Biosystems). The remaining 12 loci of the data set were pool-plexed (two groups of six loci each) and genotyped using dye-labelled chemistry on the CEQ 8000 Beckman-Coulter capillary array genetic analysis system. Yr 2 were also pool-plexed into two groups (one of four and other of 6 loci) and similarly genotyped. A pool comprised; 1 μl product of each of 6 PCR reactions, 0.5 μl of a 400 bp size standard (Beckman-Coulter) and 30 μl SLS buffer (Beckman-Coulter). Both genotypers generate output fragment/allele sizes that are of within system reproducible non-integer lengths. Sizing of the outputs into integer length format useable by input files of the various genetic analysis programs is necessary. All Beckman-Coulter run samples were sized by binning, an automated process that relies on prior knowledge of the spectrum range of most possible apparent sizes for the generation of nominal fragment length sizes, with CEQ8000 software. This created an allele list that was used repeatedly to identify alleles whenever a locus was run under the same conditions. Sized alleles were manually inspected for correctness. Proper use of the binning option is described in the CEQ 8000 Genetic Analysis System User's Guide (Beckman-Coulter PN 608315).0, and over Fk for its superior Ne estimation when > 3 alleles per locus are present. Fc was calculated according to Nei and Tajima [FST); RST [FST mainly in assumption for model of microsatellite evolution; and Nm an index of migration rate. Pair-wise FST were generated using MSA, RST were got from the program ARLEQUIN [FST = 1/1+4Nem adopted from equation 5.17 [FST distributions were compared using paired t-test and the Wilcoxon-signed rank test from the SPSS package. Isolation by distance as the model explaining the observed population structure was tested by regression of Pair-wise Population FST/(1 - FST) against natural logarithm (ln) of pair wise geographical distances (Spearman Rank Correlation Test). The procedure was carried out online as computed in GENEPOP. Significance of the correlation coefficient was from Mantel tests. The geographical distances used were straight-line measurements between map points.Within population deviations from Hardy-Weinberg (HW) expectations at each locus were tested by exact tests using an online (web) version of GENEPOP an update of version 1.2  and alsod Tajima  and was d Tajima ;Waples [d Tajima  before sd Tajima  to get NST); RST  an indexARLEQUIN  and Nem ion 5.17 . To furtA. gambiae. In Bukasa, all year one (yr 1) samples were A. gambiae, while the yr 2 collection was composed of about 80% A. gambiae and 20% Anopheles arabiensis. Within population Hardy-Weinberg (HW) equilibrium tests  found eight of 17 yr 1 loci in HW equilibrium across all populations. H544 was the only locus out of equilibrium in every population. The equilibrium status of the remaining 8 loci varied in a population dependent manner  except in three out of 136 (2%) pairings for yr 1. The three loci pairs that showed non-random association were H93 vs 29C1, H117 vs H544 and H117 vs MBP1B. All loci pairings used in yr 2 showed random association (LD tests P > 0.05).Molecular species identification  showed ar one yr  samples  carries , attribu2 0.05,5,17 = 5.662, P = 0.340 for yr 1; yr 2 was similar), differences in allele composition and manner of pairing were evident from the highly significant genic and genotypic differentiation all P <<0.0001. Genic and genotypic differentiation tests are for allelic and genotypic distributions across populations, with the null hypothesis being .The loci were highly polymorphic in all populations as seen from number of alleles and heterozygosities  corroborated the MLNE values.The effective population size (Ne), which is the size of an ideal population that behaves, with respect to allele fluctuations, like the observed real population, was estimated from the program MLNE. . The Ne FST comparisons between population pairs revealed significant differentiation . The yr 1 FST distribution from a survey across the 10 loci used in year 2 . MICRO-CHECKER null allele adjusted data sets, when re-analysed for FST gave similar levels of population differentiation as the unadjusted ones. Global FST differentiation across combined all yr 1 loci among the four islands  was comparable to that between island and mainland populations  and only a little lower than was observed between the two mainland populations   versus ln distance was evaluated , in that there was little correlation between geographical distance and degree of differentiation  showed the existence of structuring with varying degrees of restriction to gene flow between population pairs . Bukasa yr 1 samples were collected November/December 2001, while yr 2 got collected during months of April/May 2003. These samples, while spatially true replicates, were not replicates temporally. Relative frequencies of various members of the A. gambiae complex are known to fluctuate with season and geographical location [Populations, other than the mainland ones, were significantly differentiated across the years to the extent that they were substantially different even from themselves, from one year to another. This is evidence, in these populations, for demographic instability probably emanating from seasonal changes and is indicative of small population sizes on the islands. In spite of overall differentiation across the years; the within yr 1 location .A. gambiae population size in Kenya [Effective population size (Ne) comparisons across populations are usually not factored into structure analysis due to lack of reliable direct methods of estimates ,44. The in Kenya  corroborFST  model while RST assumes and requires strict adherence to a step-wise mutation (SMM) model for microsatellite evolution [FST values were regarded as the more robust ones. Low but significant genetic structure was found among the island population (FST = 0.019) and between island and mainland populations (FST = 0.003) situated from 3–20 km apart in the Western Kenya-Lake Victoria study [a extremely differentiate the populations. Excluding them from the analysis substantially drops most inter island differences and the inter mainland pair difference although island to mainland difference and Bukasa differences are less affected  indicate that gene flow is indeed substantially though not completely restricted, between many pairs Table . It is sht range  and 7 kmht range . While iutiously . This stutiously .A. gambiae populations around the continent. Most of the FST were much higher than (FST = 0.014) expected for mainland populations at similar range of separation distances [FST = 0.104, [A. arabiensis amongst Madagascar, Mauritius and Reunion  across the barrier through ferry or boat traffic ; island= 0.104,  and A. a- 0.215, ) that in- 0.215, , they arA. gambiae populations across physical barriers.These lake islands are significantly genetically differentiated from the two mainland populations. Several of them are also differentiated from one another. The genetic differences are real for they reappeared in yr 2. These genetic differentiations are possibly the product of several factors: the islands physical separation across water, effects of their small population size and local ecological adaptation. Although the relative contribution of each differentiating factor is yet to be quantified, when done these islands could become candidate sites for measures evaluating effectiveness of control by genetic manipulation. Lastly, this study adds to the body of data that has found substantial structure among JKK carried out study design, sample processing, data acquisition, analysis and interpretation and manuscript preparation. LGM conceived of the study. AS substantially participated in data analysis. APM was key in data collection techniques and analysis. MBC greatly helped draft the manuscript. NJB helped with marker selection resources. FHC participated in the design of the study and substantially helped draft the manuscript.Details and variability summary of 17 yr 1 microsatellites. A table of yr 1 sample size, loci names and their chromosomal location, repeat motif, number of alleles, heterozygosities and population breeding coefficients.Click here for fileDetails and variability summary of 17 yr 1 microsatellites continuation. A continuation table of yr 1 sample details from additional file one.Click here for fileDetails and variability summary of 17 yr 1 microsatellites continued. Caption for the contents in additional files Click here for fileFST differentiations excluding loci that showed evidence of null allelesYr 1 population . This is an analysis of year 1 differentiations with all loci that showed evidence of null alleles excluded.Click here for file


Ongoing modernization in India has elevated the prevalence of many complex genetic diseases associated with a western lifestyle and diet to near-epidemic proportions. However, although India comprises more than one sixth of the world's human population, it has largely been omitted from genomic surveys that provide the backdrop for association studies of genetic disease. Here, by genotyping India-born individuals sampled in the United States, we carry out an extensive study of Indian genetic variation. We analyze 1,200 genome-wide polymorphisms in 432 individuals from 15 Indian populations. We find that populations from India, and populations from South Asia more generally, constitute one of the major human subgroups with increased similarity of genetic ancestry. However, only a relatively small amount of genetic differentiation exists among the Indian populations. Although caution is warranted due to the fact that United States–sampled Indian populations do not represent a random sample from India, these results suggest that the frequencies of many genetic variants are distinctive in India compared to other parts of the world and that the effects of population heterogeneity on the production of false positives in association studies may be smaller in Indians (and particularly in Indian-Americans) than might be expected for such a geographically and linguistically diverse subset of the human population. Genomic studies of human genetic variation are useful for investigating human evolutionary history, as well as for designing strategies for identifying disease-related genes. Despite its large population and its increasing complex genetic disease burden as a result of modernization, India has been excluded from most of the largest genomic surveys.The authors performed an extensive investigation of Indian genetic diversity and population relationships, sampling 15 groups of India-born immigrants to the United States and genotyping each individual at 1,200 genetic markers genome-wide. Populations from India, and groups from South Asia more generally, form a genetic cluster, so that individuals placed within this cluster are more genetically similar to each other than to individuals outside the cluster. However, the amount of genetic differentiation among Indian populations is relatively small. The authors conclude that genetic variation in India is distinctive with respect to the rest of the world, but that the level of genetic divergence is smaller in Indians than might be expected for such a geographically and linguistically diverse group. In addition to its use in understanding human evolutionary history, investigation of human genetic variation and population structure is important for the design and analysis of studies that map disease-susceptibility loci. For example, if human genetic disease is largely a consequence of common alleles and haplotypes, identifying common variants in a given population provides a database of predictors that can be tested in that population for association with disease status –3. In exDuring the last few decades, the prevalence in India of complex genetic diseases associated with increased life span and with an urban and western lifestyle—including coronary artery disease, non-insulin-dependent diabetes, and metabolic syndrome—has risen considerably and is now greater than in most other populations –12. HoweTo assess both the patterns of genetic variability within India as well as the distinctiveness of Indian variation with respect to that of other groups, we examined autosomal genetic variation at 729 microsatellite and 471 insertion/deletion polymorphisms in a collection of 432 individuals of Indian descent sampled in the United States. These individuals represent 14 groups defined by language, as well as one additional cultural group . BecauseLevels of genetic variation in the Indian populations, as measured by microsatellite heterozygosity, are compatible with a general reduction of this genetic variation statistic with increasing distance from sub-Saharan Africa ,22, rangComparing allele frequencies in the groups from India to those in other geographic regions, allele frequency correlation coefficients are highest for the populations previously studied in Central/South Asia, followed by those of Europe and the Middle East and of East Asia . This sistF in India had similar magnitude to the level of divergence among cosmopolitan groups in Europe and East Asia  with the Indian genotypes produced higher likelihoods than those that used only one cluster (K = 1). This observation, together with the reasonably strong support in the neighbor-joining tree for particular groupings within India, suggests that a detectable amount of population structure does exist in the Indian data and that the addition of more loci might cause clusters corresponding to specific subsets of the Indian sample to become distinguishable. It is noteworthy, however, that in previous analyses of other geographic regions [The low level of genetic divergence in India was reflected by the fact that the STRUCTURE program had difficulty detecting population structure within India B. Howeveulations , 55 of 8 regions ,28 usingstF values within India substantially overlapped those of either Europe/Middle East or East Asia was the Parsi population. stF values for the Parsis were similar within India and with populations from Europe and the Middle East, in agreement with their likely origins and their similar membership in the blue and red clusters in stF between pairs of populations within India did not show a strong correlation with geographic distance  did not show noticeably different patterns of pairwise dle East . AlthougThe relatively high correlation coefficients of allele frequencies between European or Middle Eastern populations and Indian populations  suggest that European allele frequencies are often reasonably predictive of frequencies in India, particularly for microsatellites A and 7C.Although India  was observed to be distinctive with respect to the remainder of the sample, at the same time, genetic differentiation within India was found to be relatively small. Thus, inclusion of a single population from India in a genome-wide survey of variation is likely to increase the accuracy of predictions made about frequencies of genetic variants in India, in comparison with those that could be made based on frequencies in groups that are currently well studied. For example, for 87% of the indels, the Gujarati sample had an absolute allele frequency difference of less than 0.1 from the non-Gujarati Indians, whereas the corresponding values were 57% for a mixture of French, Italians, and Russians and 43% for a mixture of Japanese and Han Chinese B.Because of the relationship between genetic heterogeneity and the production by population structure of spurious associations in case-control association studies ,5,29, anstF between castes  remained small, having a similar magnitude to stF among the three language groups . However, these slightly larger stF values between castes compared with among language groups  suggest that a more complete investigation of the relative importance of caste and language would be worthwhile.Note that with the exception of the Parsis, this investigation incorporated individuals into the study based on primary spoken language, considering 14 of the most frequently spoken languages of India . Although different studies have sometimes reached divergent conclusions about the magnitude of Indian differentiation and its determinants –17,30–38stF = 0.018, considerably greater than the value seen here. By necessity, however, our study required sampling in the United States in order to allow high-throughput genotyping of the large number of markers that we investigated, and it was not possible to include groups without an appreciable presence in the United States. Although our sample is likely to be reasonably representative of first-generation individuals of Indian descent currently located in the United States, such individuals likely do not provide a random sample of the source populations in India, as urban and relatively mobile populations and populations of higher caste and socioeconomic status are overrepresented among immigrants. Thus, if variables such as caste and socioeconomic status do play important roles in producing genetic structure, more genetic differentiation would certainly be expected for a sample of the same linguistic groups in India compared to what we have seen in the United States. Additionally, if higher caste is correlated with a European or western Asian component of ancestry, a sample in the United States may be biased towards finding a greater similarity of populations from India to those of the Europe/Middle East rather than to those of East Asia. However, despite the limitations of our study, it remains significant that in the largest genomic analysis of India performed to date, across a broad range of language and geography within India, such a low level of genetic divergence was observed.It is also possible that genetic divergence would have been larger if Indian tribal populations had been included along with the relatively cosmopolitan groups we examined or if Indian representatives of other language families besides Dravidian and Indo-European had been included ,38,41,42Individuals of Indian descent were enrolled into the study by PIP in various cities in the United States, primarily Houston, Texas, and New Brunswick, New Jersey. Nearly all of these individuals were first-generation immigrants, and particular care was taken to ensure that all four grandparents of each individual spoke the same language and originated from the same state in India. For many of them, other demographic information was gathered, including caste and endogamic group affiliations if applicable, religious sect, and brief medical history. All individuals gave their informed consent for participation, and the study was approved by the Institutional Review Board of Baylor College of Medicine. Among the 673 DNA individuals sampled, three sets of duplicate individuals were later identified , and one member of each pair was discarded . The sample was designed so that when subdividing participants by their primary spoken Indian language, 14 languages, each having a relatively localized distribution within India, would be well represented. One additional cultural group, the Parsis, was also sampled. As the number of Gujaratis sampled  was large in comparison with sample sizes for other language groups, this study utilized a subset consisting of 432 individuals in the 15 groups . TogetheFor the Kannada, Tamil, and Telugu groups, caste information was available on nearly all individuals. Because most castes were represented by relatively few individuals, analysis of caste in these samples utilized a subdivision into Brahmins  and non-Brahmins .http://www.gentra.com) from 10 ml of blood. The remainder was used to establish a lymphoblastoid cell line by standard procedures [Blood (20 ml) was collected from each individual. DNA was isolated using the Puregene DNA isolation kit  had been previously typed in the HGDP-CEPH Human Genome Diversity Cell Line Panel –21. HoweG test statistic of independence [G statistic was determined. In implementing the G test, all 673 typed Indians were compared to only the Pakistanis in the HGDP-CEPH panel, a collection of 198 individuals . Of the 932 loci considered, 923 had G < 45, and the other nine had G > 100. These nine loci  were excluded from consideration. As GGAA10C09 had already been excluded on the grounds of an inability to determine the shift in allele sizes, 922 loci remained for the combined analysis with the HGDP-CEPH panel, 207 indels and 715 microsatellites. Among the 715 shared microsatellites, primers had changed between datasets for 133, while for the remaining 582 there was no change. All analysis utilized these 922 loci except where otherwise specified.To identify systematic changes in allele calling , for each locus, the allele sizes of one dataset were translated by a constant, and the pendence  between The set of 952 individuals used here from the HGDP-CEPH Human Genome Diversity Cell Line Panel  is the “stF and geographic distance were computed with and without the Hindi and Konkani groups. For microsatellites, the correlation coefficient between stF and geographic distance was −0.11 (p = 0.32) with Hindi and Konkani excluded, and 0.13 (p = 0.28) with Hindi, Konkani, and Parsi excluded; for indels, these two correlations equaled −0.04 (p = 0.74) and 0.31 (p = 0.01), respectively. These values do not differ substantially from those obtained when the Hindi and Konkani groups were retained in the analysis /2, where p and q denote the frequency of the allele in the two populations. Thus, alleles were weighted linearly in proportion to their mean frequency. For indels, we used a weight of 1−2|(p+q)/2−1/2|, so that indel alleles were weighted linearly based on nearness of the minor (or major) allele frequency to 1/2. Due to its symmetry around 1/2, this scheme gives equal weight to the minor and major alleles of biallelic markers. The p-value for the null hypothesis that a weighted correlation coefficient equaled zero was obtained as the fraction of bootstrap replicates  in which the correlation coefficient was negative.Expected heterozygosity was computed using the sample size–corrected estimator . Fst wased as in  Click here for additional data file.Table S2(8 KB PDF)Click here for additional data file.Table S3(12 KB PDF)Click here for additional data file.


Indian populations endowed with unparalleled genetic complexity have received a great deal of attention from scientists world over. However, the fundamental question over their ancestry, whether they are all genetically similar or do exhibit differences attributable to ethnicity, language, geography or socio-cultural affiliation is still unresolved. In order to decipher their underlying genetic structure, we undertook a study on 3522 individuals belonging to 54 endogamous Indian populations representing all major ethnic, linguistic and geographic groups and assessed the genetic variation using autosomal microsatellite markers.The distribution of the most frequent allele was uniform across populations, revealing an underlying genetic similarity. Patterns of allele distribution suggestive of ethnic or geographic propinquity were discernible only in a few of the populations and was not applicable to the entire dataset while a number of the populations exhibited distinct identities evident from the occurrence of unique alleles in them. Genetic substructuring was detected among populations originating from northeastern and southern India reflective of their migrational histories and genetic isolation respectively.Our analyses based on autosomal microsatellite markers detected no evidence of general clustering of population groups based on ethnic, linguistic, geographic or socio-cultural affiliations. The existence of substructuring in populations from northeastern and southern India has notable implications for population genetic studies and forensic databases where broad grouping of populations based on such affiliations are frequently employed. Human diversity in India is defined by 4693 different, documented population groups that include 2205 major communities, 589 segments and 1900 territorial units spread across the country ,8.The striking social attribute of the Indian populations is their strict practice of endogamy across all social ranks that has resulted in emergence of diverse population-specific social traditions and formation of distinct linguistic dialects due to subsequent isolation of populations. Although uniparental, biallelic markers have deciphered the common major Paleolithic contributions , resolutWith these rationales, we have analyzed 15 highly polymorphic autosomal microsatellite markers including 13 core forensic loci, which have been extensively used to reveal the ethnological and anthropological affinity of diverse populations  from Chattisgarh; Irular, Chakkiliyar, Gounder and Pallar  from the southern state of Tamil Nadu; showed genetic isolation, evident from the presence of alleles confined within these populations Figure . On the Significantly, most frequent alleles were shared among some ethnically and linguistically related populations. The populations of Sikkim, Lai and Lusei of Mizoram that shared Mongol ancestry had a high frequency of allele 12 of the D7S820 locus. Analogous results were obtained for allele 13 of the D5S818 locus, which was in high incidence amongst the Bhutia of Sikkim and Mara of Mizoram. The Indo-Caucasoids, Lingayat of Karnataka; Yadav and Baniya of Bihar, and the geographically proximate Australoid, Kurmi had allele 7 of the Penta E locus in high frequency. Allele 18 of the same locus was present in high frequencies among the Dravidian speaking Australoids, Gowda of Karnataka; Irular of Tamil Nadu as well as among the Indo-European speaking Indo-Caucasoids, Khandayat and Gope of Orissa.Analysis of molecular variance Table  failed tIn the countrywide dataset, at K = 5, associated with maximum posterior probability Table , individAt the regional level Figure , amongstIn the East, Bihar Brahmin, Bhumihar, Kayasth, Rajput, Yadav, Bihar Kurmi, Orissa Brahmin, Khandayat, Karan, Juang and Paroja shared similar membership to multiple clusters revealing a common genetic structure. Baniya of Bihar were found similar to two of the northern Indian populations while Gope and few individuals from Saora of Orissa shared similar identities as the populations from Mizoram of northeastern India.The northeastern populations from Mizoram were identified to be distinct from those of Sikkim. Three clusters were evident with Hmar, Mara, Lai and Lusei of Mizoram all representing one group while Lepcha of Sikkim were distinct representing the second group and the third group comprised Nepali and Bhutia of Sikkim.In the south, Lingayat, Gowda, Brahmin and Muslim of Karnataka along with Vanniyar, Gounder and Pallar of Tamil Nadu separated from rest of the populations. Irular of Tamil Nadu and Yerukula of Andhra Pradesh presented distinct identities while Chenchu and Naikpod Gond of Andhra Pradesh exhibited similar affinities. Rest of the populations from Tamil Nadu; Chakkiliyar, Paraiyar, Tanjore Kallar and from Andhra Pradesh; Brahmin, Raju, Komati, Kamma Chaudhury, Kapu Naidu, Reddy and Lambadi displayed mixed membership to multiple clusters.Populations from western and central India showed absence of any distinct grouping with individuals having symmetrical membership across inferred clusters. The above results reveal genetic similarity across populations with a few presenting distinct identities that did not follow traditional groupings of geography, language or ethnicity. Populations from southern India and northeastern India largely exhibited structuring while most Indian populations shared similar membership in multiple clusters.Contemporary molecular studies on Indian populations were focused to uncover the genetic relationship among geographically, linguistically or ethnically related populations -25. ReceThe immense diversity within the ethnic and linguistic affiliations of the populations inhabiting India had always been a debatable issue, whether some of them had originated indigenously or were the results of earlier migrations -29. The Majority of the Indian populations in general exhibited extensive admixture with each population displaying membership to multiple clusters. Populations such as Khatri, Baniya, Chenchu, Yerukula and Naikpod Gond, however, were substructured. Interestingly, populations comprising the southern Indian region exhibited substructuring with a number of populations clustering into a separate group while the rest were found similar to the general Indian population structure. This group comprising Iyenger Brahmin, Lingayat, Gowda and Muslim from Karnataka and Gounder, Vanniyar and Pallar from Tamil Nadu probably represents those populations that have resisted recent geneflow, and accumulated characteristic allele frequencies because of genetic drift leading to their differentiation from the rest of the populations. In addition, Irular of Tamil Nadu and Yerukula of Andhra Pradesh were found distinctive while Chenchu and Naikpod Gond of Andhra Pradesh grouped together. However, these populations at lower K grouped into clusters similar to those of Tanjore Kallar, Paraiyar and Chakkiliyar of Tamil Nadu and Brahmin, Raju, Komati, Kamma Chaudhury, Kappu Naidu, Kapu Reddy and Lambadi of Andhra Pradesh.Our analyses failed to reveal any genetic groups that correlate to language, geography, ethnicity or socio-cultural affiliation of populations. Of course, the absence of evidence of structuring of the Indian populations based on ethnic, linguistic, geographic or socio-cultural affiliations may be related to the ascertainment bias of selection of these highly polymorphic forensic microsatellite markers. Future studies employing a large number of microsatellites/SNPs might yield higher resolution to decipher stronger associations between populations. The occurrence of few populations distinct from the general populace suggests genetic drift due to isolation of such populations have resulted in their characteristic allele frequencies. This cryptic population structure would have significant implications in forensic investigations where computations of statistical significance of a DNA match rely on ethnic identities often defined by the country of origin. The existence of substructuring in populations from northeastern and southern India also cautions against broad grouping of populations based on geographic, ethnic or linguistic affiliation that are frequently employed in population genetic studies.A total of 3522 consenting individuals from fifty four populations belonging to three major ethnic groups and affiliated to four major language families from across the country were included in this study Table  after ap®16 system  or AmpFlSTR ®Identifiler™ PCR Amplification Kit  that coamplify fifteen microsatellite loci according to manufacturers' specifications. The amplified products were separated on a denaturing 5% polyacrylamide gel using the ABI Prism™ 377 DNA Sequencer . The genotypes were analyzed with GeneScan® Analysis 3.1, Genotyper® 2.5  and PowerTyper™ 16 Macro v2  softwares.DNA was extracted either from blood or buccal swabs by standard methods . AmplifiAnalysis of molecular variance, AMOVA , was perStructure 2.1 program [K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned probabilistically to populations, or jointly to two or more populations if their genotypes indicate they are admixed. Each run used 100,000 estimation iterations for K = 2 to 8 after a 20,000 burn-in length. Each run was carried out several times to ensure consistency of the results. Posterior probabilities for each K were computed for each set of runs.We used a model-based clustering method for inferring population groups using genotype data consisting of unlinked markers as implemented in  program . The modThe author(s) declare that they have no competing interests.VKK designed the course of the study and contributed significantly in manuscript preparation. SG carried out statistical analysis and participated in manuscript preparation. TS analyzed the data and drafted the manuscript. GHB performed experiments on Andhra Pradesh samples and participated in manuscript preparation. SEH provided analytical inputs for manuscript preparation. RT provided critical information for data processing and manuscript preparation.All authors read and approved the final manuscript.