Chirocephalus kerkyrensis is a fairy shrimp typical of temporary water bodies in Mediterranean plain forests and has undergone a substantial decline in number of populations in recent years due to habitat loss. We assessed patterns of genetic connectivity and phylogeographic history in the seven extant populations of the species from Albania, Corfu Is. (Greece), Southern and Central Italy.Mediterranean temporary water bodies are important reservoirs of biodiversity and host a unique assemblage of diapausing aquatic invertebrates. These environments are currently vanishing because of increasing human pressure. C. kerkyrensis. We used multiple phylogenetic, phylogeographic and coalescence-based approaches to assess connectivity and historical demography across the whole distribution range of the species. C. kerkyrensis is genetically subdivided into three main mitochondrial lineages; two of them are geographically localized  and one encompasses a wide geographic area . Most of the detected genetic variation (≈81%) is apportioned among the aforementioned lineages.We analyzed sequence variation at two mitochondrial DNA genes (Cytochrome Oxidase I and 16s rRNA) in all the known populations of Multiple analyses of mismatch distributions consistently supported both past demographic and spatial expansions with the former predating the latter; demographic expansions were consistently placed during interglacial warm phases of the Pleistocene while spatial expansions were restricted to cold periods. Coalescence methods revealed a scenario of past isolation with low levels of gene flow in line with what is already known for other co-distributed fairy shrimps and suggest drift as the prevailing force in promoting local divergence. We recommend that these evolutionary trajectories should be taken in proper consideration in any effort aimed at protecting Mediterranean temporary water bodies. Chirocephalus is the most speciose anostracan genus in the Palaearctics, and the second one worldwide Pristicephalus as an independent genus Chirocephalus is divided to four; three of these  are distributed in the West-Palaearctic area. The Ponto-Mediterranean bairdi-group is distributed along the northern coasts of the east-Mediterranean basin, from peninsular Italy to Jordan and Israel, through the Balkan Peninsula and Asia Minor With 49 species, Chirocephalus kerkyrensis Pesta, 1936 is the westernmost representative of the bairdi-species group. The species, first identified in the temporary water bodies of Corfu Island (Greece) C. kerkyrensis has never been recorded north of Rome, where it seems to be replaced by the widespread and more euryoecious congener C. diaphanus Prévost, 1803 C. kerkyrensis has vanished and consequently many of the populations formerly known have progressively disappeared Temporary water bodies are extremely important reservoirs of biodiversity in the circum – Mediterranean area due to the instability of the permanent hydrographical surface network. A directive from the European Union (Council Directive 92/43/EEC) recognized these habitats as worthy of special conservation efforts; this view was further ratified by the Ramsar Convention on Wetlands (Resolution VIII.33/2002) C. kerkyrensis across its entire distribution range by including all its extant populations. We sequenced fragments of two mitochondrial DNA (mtDNA) genes - Cytochrome Oxidase I (COI) and 16s rRNA (16S) - which have proved useful in addressing questions at the population level in anostracans per se. Second, the essentially scattered distribution of Mediterranean temporary water bodies (and hence of the species inhabiting them) further contributes to hamper gene flow. Even when cysts of a given species are transported from pond to pond, donor and recipient water bodies must be inhabited by the same species for effective exchanges of genes across locations to happen.Here we examine the geographical distribution of mitochondrial lineages in C. kerkyrensis to test whether the aforementioned paradox is valid or not within a species with a relatively wide, yet fragmented, geographical distribution. We show how our molecular data are useful to clarify some taxonomic vagaries and to infer levels and patterns of genetic connectivity across the whole C. kerkyrensis geographic range. By revealing the degree of genetic uniqueness within the species and how this is distributed geographically we aim to further contribute to the understanding of the evolutionary trajectories in Mediterranean diapausing invertebrates. Such knowledge is an essential prerequisite for the set-up of an adequate management of the fragile and imperiled habitat represented by temporary ponds of plain and low altitude Mediterranean forests.We wanted to determine the degree of genetic structuring in rd codon position is by far the most variable partition with 62.5% of variable sites . We found only a single amino acid substitution at the ingroup level in the COI dataset. Sequences are generally A+T rich (63.9%) and anti-G biased (19%); this pattern is particularly evident in COI 3rd codon positions . Multiple χ2 tests of homogeneity of base frequencies failed to detect any significant differences whatever data partition considered (both genes together and separately and for COI each codon position separately). Estimates of mtDNA diversity are reported in h) ranges from 0.200 (CP) to 0.777 (KO3); mean number of pairwise differences between all pairs of haplotypes (π) varies from 0.668 (AVE) to 7.688 (KO3).We sequenced about 1 kb of mtDNA for each of the 93 individuals included in the study; the final alignment includes 560 bp for the COI gene and 465 bp for the 16S gene for a total length of 1025 bp. We observed only a few gaps in the final alignment, all confined to the 16S partition and to ingroup vs. outgroups comparisons. Levels of sequence variability are higher in COI than in 16S (24.8% vs. 18.5%) but percentages of parsimony informative sites are comparable across the two genes (39.5% vs. 32.5%). COI 3C. kerkyrensis sequenced for the study revealed a total of 27 unique haplotypes (both genes combined). The 93 individual of FST values  when populations were analyzed without any a priori grouping . AMOVA recovered significant population structure at each hierarchical level with the vast majority of the detected variation being apportioned among groups .Pairwise T values  range begrouping . Based or = 0.362, P = 0.001) up to 23 km (point of x-intercept). The point of x-intercept is 81 km for Central Italian+Greek populations with positive and significant values before it . Albanian+Southern Italian populations and all populations together (distance class size = 100 km in both circumstances) showed significant positive values before 307 and 175 km, respectively . Finally, the Mantel test revealed no sign of a significant IBD among populations .The multiple spatial autocorrelation analyses revealed significant positive spatial genetic structure for each group/distance class tested. Central Italian populations (distance class size = 10 km) showed significant positive values (SSDP≥0.001); no deviations from the expected mismatch distributions are observed when the same populations/groups of populations were tested for the spatial expansion model (0.578≥SSDP≥0.061). The analyses of mismatch distributions were thus more effective in supporting spatial over purely demographic expansions. Considering the demographic model, expansions were always preceded by severe reductions in population sizes and resulted in high female effective population sizes . Estimates of times since expansion yielded roughly congruent figures for the two models with the exceptions of AVE , KO3 and CP (but for these two populations the demographic expansion model was rejected). When populations were pooled into three groups Albanian+Southern Italian and Central Italian populations had similar ages  and had greater ages than the Greek populations . Under the spatial expansion model, spreading of populations relied on small or very small (m≤0.12) migration rates in most cases but two . Fu's FS tests showed no significant deviations of FS from values expected under neutrality .Summary statistics of mismatch parameters for both demographic and spatial expansions are shown in T for all comparisons at any level; TMRCA is indeed from 1.7 (between Greek populations) to 5.6  times higher than T. This evidence suggests isolation with low levels of gene flow (mean M = 2.9). The only exception to this otherwise generalized scenario is the comparison of Albanian+Southern Italian vs. Greek populations; here the difference between TMRCA and T is less extreme (TMRCA/T = 0.9) but M is still small (0.825), suggesting more recent divergence and no ongoing gene flow.C. kerkyrensis, a species with a scattered Central - Mediterranean distribution and mostly bound to temporary ponds in low altitude oak or mixed woods, a habitat currently declining due to increasing urbanization and agricultural expansion Here we present a comprehensive phylogeographic study on the fairy shrimp It is important to stress that in the remainder of the study we will limit comparisons to studies centered on freshwater branchiopods only, because halophilic species often exhibit rates of molecular evolution faster than those of their freshwater counterparts C. kerkyrensis stellaeC. stellae) C. stellae was synonymized with C. kerkyrensis; later on this systematic arrangement was further recognized as valid Based on slight morphological differences in male antennae and in the ornamentation of female abdominal segments observed in samples collected in Central Italian ponds, these populations were assigned to the subspecies Tanymastix stagnalis by using the same mtDNA markers  Branchinella ranges between 5% and 10% for 16S Chirocephalus (including a single population of C. kerkyrensis) returned an average interspecific genetic distance value of 10.5% C. kerkyrensis are definitively close to the lower values. We conclude that the different lineages identified in this study constitute regional clusters within the species phylogeography; our data hence give further support to the current taxonomic arrangement We have molecularly identified three major allopatric and divergent lineages. Before processing our samples, we checked adult males and females for variation in the above mentioned morphological characters and we found them to be highly variable both within and between populations without the evidence of any clear pattern  . Sequence divergence among major haplogroups  ranges from 1.1%  to 3.2%  for the 16S gene and between 2.5%  and 5.3%  for COI. These values encompass those obtained for 14 populations of the fairy shrimp C. kerkyrensis has almost exclusively been recorded in temporary ponds in Mediterranean lowland oak or mixed woods, predominantly close to the coast. The Southern Italian location is the only exception to this otherwise generalized pattern in that is the single known pond where the species occurs at an altitude higher than 130 m above the sea level (ca. 500 m) C. kerkyrensis at an altitude atypical for the species should be sought in occasional long-distance dispersal(s) of cysts carried inland by wind and/or migratory birds C. kerkyrensis can be fit into the Avise's phylogeographic category I FST value between ALB and AVE (0.508) is indeed comparable to that among Central Italian populations (FST = 0.446±0.13) regardless of the very different geographical scale  lineages and, hence, pronounced genetic subdivision to develop C. kerkyrensis by using 22 allozymic loci Phylogeographic studies in European freshwater branchiopods have consistently retrieved patterns of extreme subdivision and large degrees of regionalism Our data could never reject a model of spatial expansion neither at the population nor at the haplogroup level, while demographic expansion was rejected for two populations (KO3 and CP). This suggests that mismatch distributions are supporting past fluctuations in range size better than past demographic fluctuations of populations. When demographic and spatial expansions are both supported, time estimates since last demographic expansion generally predate estimates since last spatial expansion . These tDemographic expansions are consistently placed during warm, interglacial phases of the Pleistocene that witnessed an expansion of oak forest in the Mediterranean region m values in T) and time to the most common ancestor (TMRCA), with the former being always higher than the latter, a pattern that suggests past isolation with low levels of migration M  the effect of genetic drift is larger in small populations and II) time to fixation of local genetic variants is inversely proportional to effective population size.C. kerkyrensis seems prone to experience depletion of its original gene pool. The presence of phylogeographic gaps not only among the major haplogroups but also at a very regional scale  suggests that this phenomenon might already have begun. As a matter of fact, extinctions of populations harboring intermediate haplotypes may result in the appearance of phylogeographic gaps within as well as between populations C. kerkyrensis owing to its ability to maintain gene flow over short distances only .The emerging scenario is thus one where dispersal of cysts works successfully across small distances only . In light of the above considerations, of the fact that the range of the species is naturally fragmented and that a number of ponds where the species was known to occur in the past have recently vanished On the other hand, we cannot exclude that further samplings in the Balkan area whose temporary water bodies are largely unexplored, would return additional populations of the species, as recently happened with the Albanian site, and, hence, would possibly lead to partially reconsider the phylogeographic scenario proposed here. More generally, the questions left open in this study are the result of a lack of knowledge on the distribution of Southern European anostracans, which is still largely fragmentary and mostly reflects ranges of activity of the few experts of the group C. kerkyrensis have been sampled for the study. Details on sampling localities and sample sizes are given in All known extant populations of P = 0.987); we therefore only report analyses based on the two genes combined. We used PAUP* 4.0b10 to calculate base frequencies and to test for base frequency homogeneity across taxa (χ2 test).Sequences were edited and aligned using Sequencher 4.6 (Gene Code Corporation); alignments were also checked by eye. Phylogenetic analyses (see details below) were initially carried out on each gene region separately. Resulting topologies were almost identical in all cases (data not shown). The suitability of pooling sequence data from the two sequenced genes was further assessed by the incongruence length difference test  Chirocephalus marchesonii  and Eubranchipus sp.  as outgroups. C. marchesonii is basal to C. kerkyrensis in a COI-based phylogeny of the genus Eubranchipus sp. was chosen to represent an additional genus within the family Chirocephalidae. We used MODELTEST We analyzed data phylogenetically with We used the software TCS h), mean number of pairwise differences between all pairs of haplotypes (π) and the nucleotide diversity (nπ). Levels of genetic structure were initially tested with any a priori grouping of populations by a hierarchical analysis of molecular variance (AMOVA) in ARLEQUIN with 10,000 replications FST values for all pairs of populations; statistical significance of FST values was assessed by 10,000 permutations with Bonferroni correction for multiple tests.We employed ARLEQUIN 3.0 r) were estimated with 1,000 bootstrap replicates FST values and geographic distances among all pairs of populations.To test for genetic similarity among individuals whose geographic separation falls within a given distance class we applied the spatial autocorrelation analysis. To take into consideration the interplay between distant class sizes and the true (but unknown) extent of spatial genetic structure the analysis was conducted on the following groups of populations at increasing distance class sizes: Central Italy (distance class size = 10 km), Central Italy+Corfu Is. (distance class size = 50 km), Albania+Southern Italy and all populations together (in both cases with a distance class size of 100 km). Each analysis was run in GENALEX 6 with 999 permutations; confidence intervals of the correlation coefficient  and after (time 1) expansion. Mismatch distributions were also employed to fit the infinite island model τ, θ = 0θ = 1θ and M = 2Nm (θ is 2Nμ at demographic equilibrium and m is the rate at which the sampled deme would exchange migrants with a unique population of infinite size after T generations). In both models τ is a mutation-scaled measure of time since expansion (demographic or geographic) and can be used to estimate time in generations (T) since expansion, using T = τ/2μ (where μ is the mutation rate). Goodness of fit was assessed by the sum of square deviations (SSD) between the observed and the expected mismatch, and its significance was determined by a parametric bootstrap with 10,000 replicates. In addition, we used the Fu's FS test FS values against a distribution generated from 10,000 random samples under the null hypothesis of selective neutrality. Negative and significant FS values are taken as an evidence of deviation from neutrality.ARLEQUIN was also used to assess the fit of demographic θ = 2efμN where efN is the effective female population size and μ is the mutation rate, migration rate (M = 2efNm), time of population divergence from pairwise-sample comparisons (T = t/efN), and the expected time to the most common recent ancestor (TMRCA = tμ). Assuming isolation to prevail in most cases over migration, we did not attempt to estimate directionality of gene flow. The model allows distinguishing between a past isolation with recent migration (probably after secondary contact) and a recent isolation with low or any migration T and TMRCA are small. In the second scenario, there will be broader differences between T and TMRCA with T being consistently higher than TMRCA and levels of migration will be low. The program was run under a finite sites model (HKY), using five independent Markov chains with 5,000,000 steps and an initial 10% burn-in. The best estimates of θ, M and T were those displaying the highest posterior probabilities. Comparisons were carried out at two hierarchical levels: (1) between each possible pair of groups identified phylogenetically and phylogeographically (same groups as in the AMOVA) and (2) between geographically adjacent populations. Here, all possible pairwise comparisons among populations within the following areas were considered: Central Italy, Corfu Is., and Southern Italy+Albania. Values for efN, t, and TMRCA were calculated using a generation time of 1–10 years and a mutation rate as above. The choice of such broad generation time range derives from the fact that no precise data on generation time in C. kerkyrensis are available. Moreover, the one- year generation time usually adopted in temperate systems is questionable for organisms capable to produce resting eggs, which can store viable propagules for many years Bayesian sampling coalescence-based methods implemented in MDIV


Fagus lucida and F. longipetiolata, 21 and 28 populations, respectively) was conducted to test whether they have responded to historical events in a concerted fashion and to determine whether their phylogeographic structure is exclusively due to Quaternary events or it is also associated with pre-Quaternary events. Twenty-three haplotypes were recovered for F. lucida and F. longipetiolata (14 each one and five shared). Both species exhibited a species-specific mosaic distribution of haplotypes, with many of them being range-restricted and even private to populations. The two beeches had comparable total haplotype diversity but F. lucida had much higher within-population diversity than F. longipetiolata. Molecular dating showed that the time to most recent common ancestor of all haplotypes was 6.36 Ma, with most haplotypes differentiating during the Quaternary.  Our results support a late Miocene origin and southwards colonization of Chinese beeches when the aridity in Central Asia intensified and the monsoon climate began to dominate the East Asia. During the Quaternary, long-term isolation in subtropical mountains of China coupled with limited gene flow would have lead to the current species-specific mosaic distribution of lineages.In subtropical China, large-scale phylogeographic comparisons among multiple sympatric plants with similar ecological preferences are scarce, making generalizations about common response to historical events necessarily tentative. A phylogeographic comparison of two sympatric Chinese beeches ( Because sharing of haplotypes among woody congeneric species is common (see Discussion), a distribution map of shared haplotypes between F. lucida and F. longipetiolata was analyzed separately; the population NP of F. longipetiolata was excluded from the analyses of genetic structure because of its small sample size (n = 2). We first evaluated whether there is a phylogeographic signal in the haplotype distribution by comparing GST with NST using the software HAPLONST (Pons and Petit K groups until the percentage of explained variance among groups reached a limit (K = 2–20). In addition, an AMOVA analysis was also implemented to partition the genetic variance within and between species using ARLEQUIN 3.1  (Rogers and Harpending r) was obtained by examining the null distribution of 5000 coalescent simulations of these statistics. Small raggedness values represent a population, which has experienced sudden expansion, whereas high values of the raggedness index suggest stationary or bottlenecked populations. Second, we calculated Fs statistic of Fu  were used as functional outgroups. BEAST 1.7.4 has three substitution models  and three site heterogeneity models . We used GTR + G based on the result of AIC from jModelTest , 37.2–52.3 Ma  and 23.0–33.9 Ma , and normal distribution priors were set for these calibration points. The detailed justification for each calibration point is provided by Sauquet et al.  to confirm sampling adequacy and convergence of the chains to stationary distribution. The effective sample size (ESS) of parameters was used to examine the mixing of the chains. Resulting chronograms were visualized in FIGTREE 1.3.1 (http://tree.bio.ed.ac.uk/software/figtree).For testing whether genetic differentiation is due to pre-Quaternary and/or the Quaternary events, we calculated the divergence time of all haplotypes of i et al. , using at Posada  for thist et al. : Table 2atpI-atpH and ndhJ-trnF) was 1918 bp. Twenty-five substitutions and two indels (of 10 bp) were detected. A total of 25 haplotypes were characterized by 21 substitutions in four Chinese beeches . The two species shared four haplotypes with F. engleriana and F. hayatae [H17, H18, H19, and H20, corresponding to H1, H2, H4, and H5 in Lei et al. , and F. longipetiolata harbored eight private ones .The length of the two combined chloroplast intergenic spacers , and H4 was also present in relatively distant populations . Other F. lucida haplotypes were restricted to one or two populations. In addition, more than half of the populations (12 of 21) were polymorphic, and ancestral haplotypes H17 and/or H19 occurred in 11 of the polymorphic populations. In F. longipetiolata, range-wide distributed haplotypes were not detected. Most populations (25 of 28) were monomorphic, and population-specific haplotypes were also common in F. longipetiolata . The only haplotypes relatively widespread were H18  and H20 , whereas two regionally widespread haplotypes  were found.There were no obvious geographic structures in the haplotype distribution of ida Fig. B and F. ata Fig. C. Each sF. lucida and F. longipetiolata  was slightly lower in F. lucida (0.887 ± 0.047) than in F. longipetiolata (0.927 ± 0.020), but within-population diversity (hS) of the former (0.262 ± 0.058) was much higher than that of the latter (0.060 ± 0.033). Consequently, genetic differentiation in F. lucida  was much lower than that in F. longipetiolata . Permutation tests indicated that NST was not significantly higher than GST both in F. lucida  and F. longipetiolata . Consistent with the mosaic distribution of haplotypes, SAMOVA analyses indicated that FCT increased gradually with K values and reached a maximum value at K = 18 . A low and nonsignificant raggedness value  in F. lucida suggests that the species might conform to the model of sudden population expansion. A significant raggedness value  found in F. longipetiolata suggests that this beech, instead, might have not experienced a sudden population expansion. Fu's Fs is considered to be more sensitive in detecting population expansion  and F. longipetiolata  indicated, however, that both beeches did not experience a recent demographic expansion. The historical demography was also inferred using the Bayesian skyline plot  was estimated to 6.38 Ma (95% HPD 2.29−13.25 Ma). Lineages started to diversify during the Pliocene; most haplotypes, however, diverged from each other during the Quaternary (2.49–0.50 Ma)  and the few shared haplotypes are mainly restricted to the central part of the network where the most ancient alleles are supposed to occur , FCT is not significantly different from zero  . Lineages started to diversify around the Miocene–Pliocene boundary, and this process would have continued during the Pliocene and intensified during the Pleistocene: the estimated age of all the recovered haplotypes of Chinese beeches is younger than 2.6 Mya  in the Miocene. In post-Miocene times, Fagus underwent range reduction and/or migration toward the south, coupled with extinction from the northernmost latitudes, western North America and Central Asia  is uncertain (Denk and Grimm 18O) and carbon (δ13C) isotope records, the Cenozoic global cooling, which resumed after the Mid-Miocene Climate Optimum (ca. 15 Ma), experienced an additional cooling and a small-scale ice-sheet expansion by the late Miocene–early Pliocene, ca. 6–7 Mya , contrasting levels of intrapopulation diversity between the two beeches can only be explained by differences in their population size. Indeed, Fagus lucida has a wider ecological niche and always maintains larger populations  than F. longipetiolata. In large populations, high genetic diversity is generally expected, and ancestral haplotypes are more likely to be retained  are needed to make direct comparisons of gene flow between F. lucida and F. longipetiolata.Apart from the species-specific distribution of haplotypes, other differences between the phylogeographic structure of mer Fig. B, but nomer Fig. C, which Ellegren . Therefo


The Caribbean basin is home to some of the most complex interactions in recent history among previously diverged human populations. Here, we investigate the population genetic history of this region by characterizing patterns of genome-wide variation among 330 individuals from three of the Greater Antilles , two mainland , and three Native South American  populations. We combine these data with a unique database of genomic variation in over 3,000 individuals from diverse European, African, and Native American populations. We use local ancestry inference and tract length distributions to test different demographic scenarios for the pre- and post-colonial history of the region. We develop a novel ancestry-specific PCA (ASPCA) method to reconstruct the sub-continental origin of Native American, European, and African haplotypes from admixed genomes. We find that the most likely source of the indigenous ancestry in Caribbean islanders is a Native South American component shared among inland Amazonian tribes, Central America, and the Yucatan peninsula, suggesting extensive gene flow across the Caribbean in pre-Columbian times. We find evidence of two pulses of African migration. The first pulse—which today is reflected by shorter, older ancestry tracts—consists of a genetic component more similar to coastal West African regions involved in early stages of the trans-Atlantic slave trade. The second pulse—reflected by longer, younger tracts—is more similar to present-day West-Central African populations, supporting historical records of later transatlantic deportation. Surprisingly, we also identify a Latino-specific European component that has significantly diverged from its parental Iberian source populations, presumably as a result of small European founder population size. We demonstrate that the ancestral components in admixed genomes can be traced back to distinct sub-continental source populations with far greater resolution than previously thought, even when limited pre-Columbian Caribbean haplotypes have survived. Latinos are often regarded as a single heterogeneous group, whose complex variation is not fully appreciated in several social, demographic, and biomedical contexts. By making use of genomic data, we characterize ancestral components of Caribbean populations on a sub-continental level and unveil fine-scale patterns of population structure distinguishing insular from mainland Caribbean populations as well as from other Hispanic/Latino groups. We provide genetic evidence for an inland South American origin of the Native American component in island populations and for extensive pre-Columbian gene flow across the Caribbean basin. The Caribbean-derived European component shows significant differentiation from parental Iberian populations, presumably as a result of founder effects during the colonization of the New World. Based on demographic models, we reconstruct the complex population history of the Caribbean since the onset of continental admixture. We find that insular populations are best modeled as mixtures absorbing two pulses of African migrants, coinciding with the early and maximum activity stages of the transatlantic slave trade. These two pulses appear to have originated in different regions within West Africa, imprinting two distinguishable signatures on present-day Afro-Caribbean genomes and shedding light on the genetic impact of the slave trade in the Caribbean. Genomic characterization of diverse human populations is critical for enabling multi-ethnic genome-wide studies of complex traits First, native pre-Columbian populations suffered dramatic population bottlenecks soon after contact. This poses a challenge for reconstructing population genetic history because extant admixed populations have retained a limited proportion of the native genetic lineages Disentangling the origin and interplay among ancestral components during the process of admixture enhances our knowledge of Caribbean populations and populations of Caribbean descent, informing the design of next-generation medical genomic studies involving these groups. Here, we present SNP array data for 251 individuals of Caribbean descent sampled in South Florida using a parent-offspring trio design and 79 native Venezuelans sampled along the Caribbean coast. The family-based samples include individuals with grandparents of either Cuban, Haitian, Dominican, Puerto Rican, Colombian, or Honduran descent. The 79 native Venezuelan samples are of Yukpa, Warao, and Bari tribal affiliation. We construct a unique database which includes public and data access committee-controlled data on genomic variation from over 3,000 individuals including HapMap To characterize population structure across the Antilles and neighboring mainland populations, we combined our genotype data for the six Latino populations with continental population samples from western Africa, Europe, and the Americas, as well as additional admixed Latino populations see . To maxiK ancestral populations. We explored K = 2 through 15 ancestral populations . Using cross-validation we found that K = 7 and K = 8 have the lowest predicted error , the average difference in mainland populations was not significant , except for Haiti. Although Haitians do show the same trend, with only two parent pairs, it is nearly impossible to assess significance , and the mathematical details are described in Our initial structure analysis was based on our high-density dataset  comprised a Chibchan component mainly represented by the Cabecar from Costa Rica and the Bari from Venezuela. Higher-order clusters pulled out Amazonian population isolates such as the Surui and Warao, as well as northern populations including the Eskimo-Aleut and Pima, in agreement with the outliers detected in our ASPCA analysis . Because >25% of European ancestry was required for inclusion in ASPCA, only two Haitian haplotypes were analyzed, and thus these were not included in the statistical analysis. Nonetheless, it is noteworthy that one of them clusters with the French, in agreement with historical and linguistic evidence regarding European settlements on the island , we did not observe a deviated clustering pattern from the Iberian cluster: the effect is much weaker and not significant  segments that are shared with Latino populations, as measured by a summed pairwise IBD statistic that is informative of the total amount of shared DNA between pairs of populations see . To explST estimates among the K = 8 ancestral clusters from ST. However, we observe an FST = 0.021  or mainland Latinos (0.04) were slightly inflated . Hence, we applied a different strategy, in which ASPCA is performed separately for short (thus older) and long (younger) ancestry tracts. For this purpose, we split the African segments of each haploid genome into two categories based on a 50-cM length cutoff and intersected the data with a reference panel of West African populations . Then, fOne caveat of this analysis is that short ancestry tracts are more likely to be misassigned. To rule this out as a source of the signal, we added an intermediate block size category (>5 cM and <50 cM) and repeated the size-based ASPCA analysis. We observed that, despite the signal being somewhat weaker due to less data, a similar trend was observed after excluding extremely short tracts . FinallyOur results reveal consistent differences in the admixture processes occurring on Caribbean islands as compared to neighboring mainland populations. First, admixture timing estimates are consistently different between these two groups, with admixture starting around 16–17 generations ago in the islands and 14 generations ago in mainland populations. Second, in the Caribbean, we find evidence of a single pulse of Native American ancestry into admixed populations. Since Native American tracts are shorter, on average, than tracts of any other ancestry (and therefore older), this suggests an initial contribution at the time of European contact with limited subsequent contribution, consistent with the rapid decimation of the native population. Mainland populations from Colombia and Honduras, on the other hand, exhibit longer Native American tracts and are best fit by a model with a greater contribution of Native American ancestry. Third, Caribbean populations show evidence of limited number of European pulse events, suggesting a limited number of founders contributed disproportionally to the present day population. Continental populations, on the other hand, show evidence of repeated migration events of European ancestry, consistent with a continuing expansion of Europeans during colonialism. Finally, our data also suggest that multiple pulses of African migration contributed significantly to genetic ancestry in the Caribbean, consistent with records of historical slave trade routes. In contrast, African ancestry tracts in mainland populations are consistent with a more limited influx of African migrants.th century, consistent with an approximate difference of two generations between the estimated onset of admixture according to our island and mainland models. Here we have focused on Colombians and Hondurans as population samples from mainland territories with coastal access to the Caribbean, but we have previously reported admixture timing estimates for Mexicans as well, starting 15 generations ago The abundance of historical accounts regarding European colonization of the New World facilitates the contrast between written and genetic records. Our models show remarkable agreement with historical records. The earliest European contact in the Americas dates back to 1492, involving the Caribbean island of Hispaniola (today's Dominican Republic and Haiti). First contact dates are upper bounds on the time at which demographically substantial admixture would have taken place. The fact that our admixture timing estimate  is so close to first contact emphasizes that the colonization proceeded rapidly, with substantial admixture taking place very quickly, as opposed to it being a more drawn out process. Later European voyages reached the coasts of Central and South America, so permanent European settlements did not occur in the mainland until the first half of the 16In contrast to other regions in the Americas where indigenous peoples are numerous, the genetic characterization of Native American components in the Caribbean required indirect reconstruction via genomic assembly of indigenous ancestry tracts transmitted to extant admixed individuals. By applying ancestry-specific PCA and cluster-based analyses integrating a large number of indigenous groups throughout the Americas, we found that Amazonian populations from South America show the closest relationship with Caribbean indigenous components. This was also observed in a different sample set from the 1000 Genomes Project . Despite covering a large geographic area of South America , most Amazonian sampled populations cluster together in PCA space, suggesting a common origin. Logical candidates for the origin of the ancestors of Caribbean populations include indigenous coastal groups south of the Lesser Antilles. Here, therefore, we have included three additional tribes from the Venezuelan coast. However, despite their closer geographic location, none of these groups primarily accounted for the indigenous ancestry of the insular Caribbean samples, pointing to an inland origin rather than a coastal one. Nonetheless, our cluster-based analysis revealed that native Venezuelan components do share membership with several Central American indigenous populations, such as the Costa Rican Cabecar, and, to a lesser extent, with Mayan groups from Guatemala and the Yucatan peninsula of present day Mexico, suggesting substantial gene flow across the Caribbean Sea in pre-Columbian times. Archaeological evidence, including the distribution of jade, obsidian, pottery, and other commodities, supports the existence of maritime-based interaction networks between central Mesoamerica, the Isthmo-Colombian area, and northern Venezuela In a recent genomic survey of the relationships between Native American peoples, Reich and colleagues How do we account, then, for a shared clustering between more distant tribes, mostly of Amazonian origin, and insular Caribbean haplotypes? One possible explanation is that the fluvial nature of most of these settlements (across the Amazon and Orinoco basins) may have facilitated the movement of people to the coast, from which they migrated north through the Lesser Antilles and eventually contributed to Caribbean native components. Our results are consistent with archaeological records suggesting that the ancestors of the indigenous people that Columbus encountered might have come from populations that migrated from the Lower Orinoco Valley around 2.5 to 3 kya Additionally, our results align with the classification of languages spoken by pre-Columbian inhabitants of the Caribbean. The Taínos were the major group living in the Greater Antilles and surrounding islands at the moment of European contact. Taínos and insular Caribs spoke Arawakan languages Overall, our analysis of indigenous ancestry tracts from extant admixed genomes supports previous linguistic, archaeological, and ancient DNA evidence about the peopling of the Caribbean; furthermore, it points to a greater involvement of inland Amazonian populations during the last migration into the Antilles prior to European contact. Earlier migrations may have occurred , as pre-ceramic archaeological evidence of human presence in the Greater Antilles dates back more than 7,000 years ago ST values between the Latino-specific and southern European components, compared to southern versus northern Europe differentiation; 3) significant deviation of the distribution of European haplotypes from the main cluster of Iberian samples in ASPCA space; and 4) increased IBD sharing among Latino individuals compared with Europeans. Additionally, a similar signature was observed in an independent dataset of Latino samples from the1000 Genomes Project using a combined approach that integrates IBD and local ancestry tracts . These findings suggest that early European waves of migration into the New World involved a reduced ancestral population size, mainly composed of Iberians, bearing a subset of the diversity present within the source population and causing the derived admixed populations to diverge from current European populations. Furthermore, we find differences between mainland and insular Caribbean populations including 1) different time estimates for the onset of admixture as revealed by ancestry tract length analysis  a Latino-specific European component revealed by clustering algorithms, which is not assigned to source populations within Europe except Spain and Portugal, and detected at lower-order clusters compared to other European and Native American sub-continental components; 2) inflated Fanalysis ; 2) sepaanalysis ; and 3) analysis . The facth century th century: the Viceroyalty of New Spain  and the Viceroyalty of Peru . An additional viceroyalty in South America was created in 1717 with Bogota as capital , promoting economic and population growth.There is documented evidence of extensive migration from the islands to the continent throughout the 16Interestingly, the estimated time for the second pulse of European migrants into the ancestors of present-day Colombians  coincides with the creation of the Colombian-based Viceroyalty of New Granada, accounting for the large increase (from 12.5% to 75%) of European ancestry in the model based on tract length distributions. This small contribution of European ancestry at the onset of admixture in Colombians reinforces the idea that their patterns of European diversity are heavily impacted by a reduced number of founders. In contrast, Mexican-derived European haplotypes do not appear to be impacted by founder events as much as the Caribbean populations analyzed here. A possible explanation is that present-day Mexico was the center of the wealthy Viceroyalty of New Spain, one of the largest European settlements under Spanish rule. This status ensured continuous exchange with Spain throughout colonial times, resulting in a larger ancestral population size.th century, accounting for more than half of the slave trade. This period of increased activity coincides with the estimated age of the second (and stronger) pulse of African tracts according to our model , pointing to the late 18th century. In other words, the estimated time separation between these two pulses  based on genetic data is in extraordinary agreement with historical records, recapitulating the span between the onset of African slave trade and its period of maximum intensity right before its rapid decline during the 19th century We find that populations from the insular Caribbean are best modeled as mixtures absorbing two independent waves of African migrants. Assuming a 30-year generation time th–16th centuries, wherein most enslaved Africans were carried off from Senegambia and departed for the Americas from the Gorée Island, near Cape Verde th century.To address the question of whether there was also a separation in space between the origins of these two pulses, we relied on the fact that chromosomes from older contributions to admixture have undergone more recombination events, thus leading to shorter continuous African ancestry tracts. By conducting two different but complementary size-based analyses restricted to genomic segments of inferred African ancestry, we provide compelling evidence that short African tracts are enriched with haplotypes from northern coastal West Africa, represented by Mandenka samples from Senegal and Brong from western Ghana, near the Ivory Coast. This is in agreement with documented deportation flows during the 15th century. Later deportation flows in the 19th century involved ports of origin near the Congo River in West Central Africa. The closest population sample of our reference panel from this region is represented by the Kongo, which also shows higher affinity with longer ancestry tracts, compatible with a later contribution to admixture in the Caribbean. The 19th century also saw the abolition of slavery in most parts of the world; however, the massive international flow of people it involved remains as one of the deepest signatures in the genomes of descendent populations. While the geographic extension of the regions of origin of African slaves brought to the Americas has been widely documented, it was unclear until now the extent to which particular sub-continental components have shaped the genomic composition of present-day Afro-Caribbean descendants. Our ancestry-specific and size-based analyses allowed us to discover that African haplotypes derived from Caribbean populations still retain a signature from the first African ancestors despite the later dominance of African influx from multiple sub-continental components.The volume of captives being embarked from the bights of Benin  and Biafra  was so elevated after 1700 that part of its shore soon became known as the “Slave Coast” Our genome-wide dense genotyping data from six different populations of Caribbean descent, coupled with the availability of large-scale reference panels, allowed us to address long-standing questions regarding the origin and admixture history of the Caribbean Basin. The differences between insular and continental Caribbean populations underscore the importance of characterizing admixed populations at finer scales. We report ancestry-specific recent bottlenecks affecting particular Latino groups, but not others, which may have important implications in the expected relative proportion of deleterious mutations and elevated allele frequencies that can be detected via association studies in theses populations. Finally, the extensive population stratification within sub-continental components implies that medically relevant genetic variants may be geographically restricted, reinforcing the need for sequencing target populations in order to discover local variants that may only be relevant in Latino-specific association studies for disease.rd or higher degree of relatedness between parents as inferred by IBD, and five trios were filtered due to cryptic relatedness between members of different trios above 10% IBD. After filtering, 65 complete trios remained for haplotype-based analyses. To study population structure and demographic patterns involving relevant ancestral populations, 79 previously collected samples from three native Venezuelan tribes were genotyped using the same array . We combined our data with publicly available genomic resources and assembled a global database incorporating genome-wide SNP array data for 3,042 individuals from which two datasets with different SNP densities were constructed (see Generated data and assembled datasets for this study are summarized in cted see . The higK = 2 through 15) were successively tested. Log likelihoods and cross-validation errors for each K clusters are available in ST based on allele frequencies was calculated in ADMIXTURE v1.22 for each identified cluster at K = 8 and values are available in K = 2 through 20. Log likelihoods, cross validation errors and FST values from ADMIXTURE are available in K = 3 on the X chromosome and autosomes separately. The Wilcoxon signed rank test, a non-parametric version of the paired Student's t-test that does not require the normality assumption, was applied to assess the significance of the difference in X and autosomal ancestry proportions. This tests whether the average difference of ancestry proportions assigned to a given source population for the X and for the autosomes of each sample is significantly different from zero. The test was applied to the entire collection of Latino samples, revealing an over-arching trend, and then to each population in turn to identify any between-population differences. A rejection of the null hypothesis means that the ancestry proportions on the X and the autosomes are significantly different from one another but does not imply which proportion is larger. We provide box plots as a visual aid to show the direction of the difference  were performed using R 2.15.1.An unsupervised clustering algorithm, ADMIXTURE fference . Global http://sites. google.com/site/pcadmix/K = 3 ancestral groups. This approach relies on phased data from reference panels and the admixed individuals. To maintain SNP density and maximize phasing accuracy we restricted to a subset of reference samples with available Affymetrix 6.0 trio data, namely 10 YRI, 10 CEU HapMap3 trios, and 10 Native American trios from Mexico Family trio genotypes from our six Caribbean populations and continental reference samples were phased using BEAGLE 3.0 software TractsTracts calculates the expected counts per bin. Assuming that counts in each bin are Poisson distributed, it produces a likelihood estimate that is used to fit model parameters. For each population, we report the model with the best Bayesian Information Criterion (BIC) −2 Log(L)+k Log (n), with n = 153. Because we imposed a fixed number of migration pulses, we must keep in mind that migrations are likely to have been more continuous than what is displayed in the best-fitting models. One way to interpret the pulses are time points that the migrations probably spanned. Resolving the duration of each pulse would likely require refined models and a great deal more data.We used the software To explore within-continent population structure, we applied the following approach for each of the continental ancestries  of admixed genomes. The general framework is shown in p-values. As Iberians we considered: POPRES Spanish, POPRES Portuguese, Andalusians, and Galicians; and as Caribbean Latinos: CUB, PUR, DOM, COL, and HON. Additional tests were performed comparing Portuguese versus the rest of Iberians and between an independent dataset of Mexican individuals analyzed by Moreno-Estrada, Gignoux et al. (in preparation) projected onto ASPCA space using the same reference panel of European populations. A bivariate test was performed to measure the relative deviation from the Iberian cluster of the distribution given by the Caribbean versus the Mexican dataset. To determine whether insular versus mainland Caribbean populations disperse over significantly different ranges in ASPC2, a Wilcoxon rank test was performed between (COL+HON) versus . Haitians were excluded due to low sample size (N = 2 haplotypes). Boxplot is available in To measure the observed deviation in ASPCA of European haplotypes derived from admixed Caribbean populations with respect to the cluster of Iberian samples, a bootstrap resampling-based test was performed. The null distribution was generated from comparing bootstraps of Portuguese and Spanish ASPCA values as models of the intrinsic Iberian population structure. We then compared the ASPCA values of the admixed individuals and tested if the observed differences between Iberian ASPCA values and those of the admixed individuals are more extreme than the differences within Iberia. The distance was determined using the chi-squared statistic of Fisher's method combining ASPC1 and ASPC2 t-tests for each bootstrap. We ran 10,000 bootstraps to determine one-tailed K = 3. For each individual we then divide African ancestry tracts into small (0 to 50 cM) and large (>50 cM) size classes. Given a partition of African ancestry tracts, we take all sites included in one tract class, say short tracts, and run PCA on our sub-continental West African reference populations for only these sites. Using the first two PCs from this analysis, we fit a bivariate normal distribution to each reference population cluster. We then project our test sample into this PCA space, and estimate the probability of it coming from each reference population using the fitted distributions. This procedure is repeated for each tract class, for each individual. For each admixed Caribbean population, we can then estimate the probability that a given class of African ancestry tracts comes from a specific West African source population as the average probability of assignment to this population across all individuals. Finally, under the assumption that a given class of African tracts must come from one of the provided reference populations, we rescale these probabilities to sum to one. Each assignment estimate is also provided with error bars representing the standard error of the mean. We compare the short and long assignment probabilities for each Caribbean population to identify distinct sources for “older” and “younger” West African migratory source populations. Haitians were not included in the analysis due to low sample size (n = 4). Due to concerns that shorter tracts have a higher likelihood of mis-assignment, we added a medium tract size class (5 cM to 50 cM) to see if the results were simply due to very short (0 cM to 5 cM) European or Native American tracts being mis-classified as African. We compare the results for short and medium tracts and find that the trends are maintained suggesting the observation that older shorter tracts appear to be primarily from the Mandenka and Brong source populations is not simply due to short tract mis-assignmentGiven the evidence from our tract length analysis for a second pulse of African migrants into the admixture of insular Caribbean Latinos, a modified size-based ASPCA analysis was performed. A reference panel was built integrating three different resources To identify likely regions of Yoruba versus Mandenka ancestry in the African component, we modified our implementation of PCAdmix to perform local ancestry deconvolution solely of the African segments of the admixed genomes. The modification is achieved in the final step of the algorithm: whereas the standard approach estimates a single HMM across an entire chromosome, here we fit J disjoint HMMs spanning each of the J blocks of African ancestry in a given chromosome for a given individual. Applying the method, we obtained posterior probabilities for Mandenka versus Yoruba ancestry within the previously inferred African segments. We then selected only those sub-regions that were confidently called as Mandenka or Yoruba, and stratified them by physical size.Figure S1Principal component 1 versus lower order PCs defining sub-continental components among Native American populations. Top: PC5 separates Venezuelan population isolates from the rest of Native Americans. Bottom: PC7 separates Mesoamerican from Andean groups. Mexicans and Hondurans distribute between the European and Mesoamerican clusters, whereas Colombians slightly deviate towards the Andean and Venezuelan clusters. Global PCA analysis based on the high-density dataset (∼390 K SNPs) and thus limited to reference panel populations with available Affymetrix SNP array data (see (TIF)Click here for additional data file.Figure S2K = 2 through 15 based on the high-density dataset (∼390 K SNPs) including 7 admixed Latino populations and 19 reference populations. A low-frequency Southern European component restricted to Mediterranean populations at lower order Ks and specifically to Iberian populations at higher order Ks, accounts for the majority of European ancestry among Latinos (black bars). It further decomposes into population-specific clusters (purple bars) denoting higher similarities within the European portion among Latinos compared to European source populations.ADMIXTURE results from (TIF)Click here for additional data file.Figure S3ADMIXTURE metrics at increasing K values based on Log-likelihoods (A) and cross-validation errors (B) for results shown in (TIF)Click here for additional data file.Figure S4K = 3 using the same set of ancestral populations as in P-values on top correspond to the Wilcoxon signed rank test applied to assess statistical significance (see Comparison of ADMIXTURE estimates obtained from autosomes and the X chromosome in different Latino/Caribbean populations. A) Cluster-based results for ance see . C) Box (TIF)Click here for additional data file.Figure S5p-values shown for the combined set of Latino Caribbean samples and for each population in Correlation between male and female continental ancestries. Parents' ancestry proportions from each trio were used to compare correlation coefficients between the observed values and 100,000 permuted male-female pairs ((TIF)Click here for additional data file.Figure S6Tracts. For each demographic scenario, the observed distribution is compared to the predictions of the best-fitting migration model (displayed below each distribution). Solid lines represent model predictions and shaded areas are one-sigma confidence region surrounding the predictions. Three different demographic scenarios were considered, all of which assume the involvement of European and Native American tracts at the onset of admixture, followed by the introduction of African migrants . The second and third models allow for an additional pulse of European  and African  ancestry, respectively. Likelihood values for each model are shown on top of each plot. Pie charts above each migration model are proportional to the estimated number of migrants being introduced at each point in time (black arrows). GA: generations ago.Ancestry tract lengths distribution per population and demographic model tested in (TIF)Click here for additional data file.Figure S7ASPCA analysis of Native American haplotypes derived from admixed genomes (solid circles) and reference panel populations from (TIF)Click here for additional data file.Figure S8K = 2 through 20 based on the low-density dataset (∼30 K SNPs) including additional admixed Latino and Native American reference populations (see K = 20 (four of the remaining five being of European ancestry and one of West African ancestry). Clusters involving multiple populations are identified by those with the highest membership values. Throughout lower and higher order Ks, several South American components (yellow and green bars), show varying degrees of shared genetic membership with Mesoamerican Mayans, accounting for up to nearly half of their genome composition (see ADMIXTURE results from (TIF)Click here for additional data file.Figure S9ADMIXTURE metrics at increasing K values based on Log-likelihoods (A) and cross-validation errors (B) for results shown in (TIF)Click here for additional data file.Figure S10ASPCA distribution of Iberian samples (red circles) compared to European haplotypes derived from our Latino Caribbean samples (top panel) and from an independent cohort of Mexican samples (bottom panel). The relative deviation from the Iberian cluster is significantly different comparing the Caribbean versus the Mexican dataset (see the main text for details).(TIF)Click here for additional data file.Figure S11ASPC2 values per population from the European-specific PCA analysis shown in (TIF)Click here for additional data file.Figure S12IBD sharing between different Caribbean Latino populations and a representative subset of POPRES European populations as measured by a summed pairwise IBD statistic. For each Latino population, maximum pairwise IBD levels were observed in those pairs involving Spanish and, to a lesser extent, Portuguese samples, in agreement with our ASPCA results.(TIF)Click here for additional data file.Figure S13IBD sharing between pairs of individuals within A) Caribbean Latinos and B) a representative subset of POPRES European populations. Inset histograms display counts lower than 50 for the same binning categories. The overall count of pairs sharing short segments of total IBD is higher among Europeans, probably as a result of an older shared pool of source haplotypes. In contrast, the higher frequency of longer IBD matches among Latinos is compatible with a recent European founder effect. After excluding within-population pairs of Latino individuals (top right), there are still more and longer IBD matches among Caribbean populations compared to Iberians (bottom right).(TIF)Click here for additional data file.Figure S14ASPCA analysis of African haplotypes derived from admixed genomes with >25% of African ancestry (black symbols) and a representative subset of African HapMap3 and other West African reference panel populations from (TIF)Click here for additional data file.Figure S15ASPCA analysis of short versus long African ancestry tracts from admixed genomes and West African reference panel populations. To exemplify our size-based ASPCA approach, the African genome of a Puerto Rican individual is displayed (denoted by PUR). Left: PUR clusters with Mandenka when only sites within short ancestry tracts (<50 cM) are considered to perform PCA. Right: a similar background distribution is obtained but the same PUR individual no longer clusters with Mandenka when considering long ancestry tracts (>50 cM).(TIF)Click here for additional data file.Figure S16African ancestry size-based ASPCA results per population sample. Considering three different classes of ancestry tract lengths , scaled assignment probabilities are shown for each African source population. Values on the y-axis are the average probability of assignment to each potential source population across all individuals within each Latino population (see (TIF)Click here for additional data file.Table S1Summary of Latino populations and assembled reference panels.(PDF)Click here for additional data file.Table S2p-values of male vs. female ancestry.Correlation (PDF)Click here for additional data file.Table S3ST divergences between estimated populations for K = 8 using ADMIXTURE.F(PDF)Click here for additional data file.Table S4ST divergences between estimated populations for K = 20 using ADMIXTURE.F(PDF)Click here for additional data file.Text S1Methodology of the Ancestry-Specific PCA (ASPCA) implementation.(PDF)Click here for additional data file.


India is known for its vast human diversity, consisting of more than four and a half thousand anthropologically well-defined populations. Each population differs in terms of language, culture, physical features and, most importantly, genetic architecture. The size of populations varies from a few hundred to millions. Based on the social structure, Indians are classified into various caste, tribe and religious groups. These social classifications are very rigid and have remained undisturbed by emerging urbanisation and cultural changes. The variable social customs, strict endogamy marriage practices, long-term isolation and evolutionary forces have added immensely to the diversification of the Indian populations. These factors have also led to these populations acquiring a set of Indian-specific genetic variations responsible for various diseases in India. Interestingly, most of these variations are absent outside the Indian subcontinent. Thus, this review is focused on the peopling of India, the caste system, marriage practice and the resulting health and forensic implications. India is well-known for its human and geographical diversities. It has a variety of landscapes ranging from desert to evergreen forest, fertile plains to southern dry plateaus, shallow swamps to deep bays, and lowlands to the high Himalayas. They all give refuge to diverse populations of humans, plants, animals and microbes. India also has extensive river systems that feed the fertile plains and provide adequate food. It is bordered by Nepal, China and Bhutan in the north, Burma and Bangladesh in the east, and Pakistan in the west. There are 4,635 anthropologically well-defined human populations; 532 are tribes, including 72 ancestral tribes with the hunter and gatherer lifestyle. The sizLinguistically, Indians are classified into four major language families; Indo-European, Dravidian, Austroasiatic and Tibeto-Burman Figure. Indo-EuThere are various evidences supporting the peopling of India by the early modern humans. It is well established that the modern human originated in Africa about 200,000 years before present (YBP),6. They Homo sapiens technologies in Africa. Further, a partial cranium recovered from Narmada Basin was dated back to around 300,000 to 250,000 YBP[Recently, archaeological evidence supporting the early peopling of India was discovered in the Kurnool district of Andhra Pradesh, one of the southern Indian states,10. This,000 YBP,12. Over,000 YBP,8,13-34.There has been tremendous interest among historians, archaeologists, anthropologists, linguists and geneticists to understand the unique structure of Indian populations and their affinities with the rest of the world. Most importantly, researchers working on various diseases often find that disease-causing genetic variations are different in Indian populations. During the last two decades, many exciting observations have been made regarding Indian people by several investigators; however, these findings have remained scattered. Thus, we have made an attempt to present an overview of the peopling of India, the caste system, endogamous marriage practice, and the resulting health and forensic implications.An interesting finding about the Indian population is the evidence of the early settlement in Andaman and Nicobar Islands by a group of modern humans, whose ancestors made the first journey out-of-Africa. The Andaman and Nicobar Islands are located in the Bay of Bengal Figure. The stuThere are fewer archaeological and genetic records on the origin of Andaman Islanders. Our group and EndiRig Veda, which was written between 1700 and 1100 BC[India is a land of social stratifications, such as castes, tribes and religious groups. Although the precise date of origin for the caste system in India is unclear, the written evidence about the organisation of the caste system exists in the  1100 BC. Caste i 1100 BC. The div 1100 BC.There are several genetic studies on the caste systems in India based on mtDNA and Y-chromosome markers,34,40-44A noteworthy view can be put forward on the development and maintenance of the caste system on the basis of genetic observations Figure33,51,5,551,52. Even though there is a continued debate on the Aryan migration into India, detectable gene flow from west Eurasia has been shown by many studies,44,51,53During the past two decades, we have witnessed remarkable advancements in technology. We have advanced from low resolution genetic markers to high throughput whole genome sequencing. Despite these advancements, studies using high density markers were lacking in the Indian scenario. Therefore, we made an attempt to extensively study various Indian populations using Affymetrix (SNP 6.0) array.We predicted that the present day Indian populations might have arisen from a relatively small group of ancestors with limited gene flow and long term isolation. We also predicted that there might have been two ancestral groups in prehistoric India: an ancestral North Indian (ANI) population distantly related to those in the Middle East, Central Asia and Europe 30% to 70%), and an ASI population not related to groups outside India. We estimated that the ASI populations showed 39% to 71% ANI ancestry. Thus, the extant Indian populations are admixtures of both ANI and ASI. Interestingly, indigenous Andaman Islanders are the only ASI-related groups without ANI ancestry[% to 70%,In addition to the large number of indigenous populations, India has experienced immigration of several populations in the past, further adding to the complexities of Indian population structure. Among the recent migrants, we have extensively studied Siddi, Muslim and Jewish populations inhabiting India.th and 19th centuries and sold to the Nawabs and the Sultans of India to serve as soldiers and slaves. Earlier, we showed the presence of a Y-chromosome Alu insertion; an African-specific marker, in 40% of Siddis[The Siddis are mainly found in three Indian states - Gujarat, Karnataka and Andhra Pradesh -and have typical African features such as dark skin, curly hair, broad nose, and so on. Historically, it is known that they were brought to India by Portuguese traders between the 17f Siddis. The mitf Siddis-58. In af Siddis. We furtf Siddis.th and 19th centuries was about 1,500.Y-chromosome results revealed the presence of African-specific haplogroups. Further, extensive investigation on Y-STRs revealed that the Siddis are the direct descendants of the Bantu-speakers of sub-Saharan Africa. We observed an Indian-specific gene pool in Siddis but the Siddi-specific gene pool was not observed in neighbouring Indian populations. This firmly suggests the unidirectional gene flow from the Indian population to the Siddis, confirming the rigidity of the Indian social structure. We alsoth century, a Turkic kingdom was established in Delhi and in the 16th century the famous Mughal Empire appeared in India. The Muslim immigrations were especially male-mediated in the form of invaders from Iran and Arabia. The majority of the present day Indian Muslims are believed to be the descendants of converts from local Hindu  populations. Thus, we undertook an extensive study among Indian Muslims from diverse geographical regions to trace their genetic structure, origin and affinity using Y-chromosome and mtDNA markers. Even though we observed their genetic affinity with indigenous Indian non-Muslim populations, a small frequency of the Middle Eastern ancestry was also noticed. Therefore, the genetic analysis of Indian Muslims shows the spread of Muslims in India was mainly mediated by cultural adaptation linked with minor gene flow from the Middle East[Another well-documented recent migration is that of the Muslim population. The Arab Muslims established their first kingdom in India by conquering Sindh in 711 AD,60. Duridle East,62.Each linguistic group in India has a strong genetic affinity between its members. Therefore, any recent change in language could be reflected in the genome. When people move from one place to another, as per human tendency, they try to adapt themselves to the new place. Over time, some of the migrants adopt the local language for better communication and, in turn, for better living. Thus, language shift is a phenomenon where a new language is adopted by a population with virtually no influence on their genetic make-up. There are several examples of language shift around the world-65. In IIn India, the first evidence of inconsistency between language and gene pool was noticed by us among the Hindi (Indo-European)-speaking Mushar population. mtDNA aThe second evidence of discrepancy was observed among the Bharia tribe of the central Indian state of Madhya Pradesh. We carried out an extensive characterization of genetic ancestry of Bharia, a Dravidian speaking group, and its Indo-European-speaking neighbours (Bhil and Sahariya) along with other Austroasiatic-speaking groups. mtDNA analysis showed the presence of lineages that are commonly found among the Austroasiatic groups,66. In aThere are 104 million Austroasiatic speakers around the globe. There exist two major branches of the Austroasiatic language in India. The Munda branch is mostly spoken by eastern, northeastern, and central Indians, and the Khasi-Aslian branch is located in Meghalaya and (Andaman) Nicobar Islands. There avice versa in matrilocal societies[The presence of both patrilocal and matrilocal societies further adds to the complexities of the Indian social structure. The societies in which a woman moves to her husband’s home after marriage are called patrilocal societies, and the societies in which a man moves to his wife’s home is a matrilocal society. Thus, these social customs are expected to have an impact on the patterns of genetic variation among the population of a given region. It is indeed observed that there is localization of male-specific Y-chromosomal variants and wide dispersal of female-specific mtDNA variants in patrilocal societies and ocieties-75. Howeocieties, have anocieties.MSTN and DOK5 genes, which have potential implications in lipid metabolism and the aetiology of type 2 diabetes in Indians[Several boundaries acting at different levels within the Indian populations have added to the human diversity in the country. Indian populations have been shaped by a long-term genetic isolation of different populations that predates the caste system in India. The allele frequency differences between the groups in India are larger than those in Europe, reflecting strong founder effects whose signatures have been preserved for thousands of years due to firm social customs and strict endogamy. We therefore predict that there is an excess of population and region-specific diseases in India. This prediction is well correlated with several population- or region-specific diseases and medical conditions, for example, Madras motor neuron disease,78, Hand Indians.MYBPC3) is associated with inheritable cardiomyopathies in India due to skipping of wild type exon 33[Our previous study revealed that the deletion of 25 bp in the myosin binding protein-C3 gene ( exon 33. We alsoG6PD gene that gives protection against malaria is commonly found in Africa. Even though the Siddis have African origin, the A-variant was found only in 10% of the Siddi individuals. This is primarily because of their admixture with the neighbouring Indian populations, which in turn has diluted the frequency of the A-variant. This makes the present day Siddis more susceptible to malaria than their African ancestors.We have also observed the implications of the admixture of ethnically diverse populations, who have undergone selection processes through environmental influence. The best example is the Siddis, the Indo-African population, whose admixture with the neighbouring Indian populations has remarkable medical and social implications. The A-variant of the The differences in disease rates between populations are largely due to the frequency differences in disease-causing genetic variants. It is said that these genetic variants occur frequently on chromosome segments inherited from the ancestral population with the higher disease-variant frequency. Thus, eThe structure of the Indian population also has implications in forensic genetics. Highly polymorphic STR markers provided by Applied Biosystems, Foster City, CA, USA, and Promega, Madison, WI, USA are being extensively used for medicolegal purposes. The abilities of these markers to differentiate individuals are quite efficient. However, the strict endogamy practices and small population size of some Indian populations has presented a potential challenge to the efficiency of these methods. For example, three Y-STRs loci were found to be monomorphic for Onges, and one for Nicobarese people. There mThe amelogenin gene, which is present on both X and Y chromosomes differs in size. This fact has been widely used in forensic casework and prenatal diagnosis to identify sex; however, regarding the same marker among the diverse Indian populations, we have observed a deletion of Y-chromosome-specific amelogenin in 1.85% of Indian males. These iIn a mass disaster or crime investigation, genetic markers play a major role in victim identification. We have shown earlier that every Indian population forms a separate cluster. Therefoin situ origin of several deep-rooting mtDNA lineages in India, suggesting that Indian populations are genetically unique and harbour the second highest genetic diversity after Africans. The genomic complexity brought on by endogamous practice for thousands of years, language shifts and sex-specific admixture are highly challenging to study and need further, extensive genetic characterization. The complex genomic architecture of Indian populations adds difficulty in understanding diseases and implementing preventive measures. The accumulation of various mutations due to endogamy leads to recessive diseases in the Indian population, which further increases the total disease burden of the country. Several questions pertaining to the origin of the caste system, the arrival and spread of the major language families and finding disease-associated genetic variants require effective approaches combining various disciplines such as archaeology, historical linguistics, genetics, bioinformatics and pharmacology. Even though studies with high density markers have added much to the knowledge about the Indian populations, whole genome approaches are expected to answer many of the existing questions.Based on the extensive genetic studies carried out on different Indian populations, we infer that each of them is a genetically distinct ethnic population in part due to high levels of endogamy. High resolution genetic studies revealed the ANI: ancestral North Indian; ASI: ancestral South Indian; bp: base pairs; mtDNA: mitochondrial DNA; SNP: single nucleotide polymorphism; STR: short tandem repeat; YBP: years before present.The authors declare that they have no competing interests.RT and KT wrote the manuscript and performed graphical work. Both the authors read and approved the final manuscript.


Moldova has a rich historical and cultural heritage, which may be reflected in the current genetic makeup of its population. To date, no comprehensive studies exist about the population genetic structure of modern Moldavians. To bridge this gap with respect to paternal lineages, we analyzed 37 binary and 17 multiallelic (STRs) polymorphisms on the non-recombining portion of the Y chromosome in 125 Moldavian males. In addition, 53 Ukrainians from eastern Moldova and 54 Romanians from the neighboring eastern Romania were typed using the same set of markers. In Moldavians, 19 Y chromosome haplogroups were identified, the most common being I-M423 (20.8%), R-M17* (17.6%), R-M458 (12.8%), E-v13 (8.8%), R-M269* and R-M412* (both 7.2%). In Romanians, 14 haplogroups were found including I-M423 (40.7%), R-M17* (16.7%), R-M405 (7.4%), E-v13 and R-M412* (both 5.6%). In Ukrainians, 13 haplogroups were identified including R-M17 (34.0%), I-M423 (20.8%), R-M269* (9.4%), N-M178, R-M458 and R-M73 (each 5.7%). Our results show that a significant majority of the Moldavian paternal gene pool belongs to eastern/central European and Balkan/eastern Mediterranean Y lineages. Phylogenetic and AMOVA analyses based on Y-STR loci also revealed that Moldavians are close to both eastern/central European and Balkan-Carpathian populations. The data correlate well with historical accounts and geographical location of the region and thus allow to hypothesize that extant Moldavian paternal genetic lineages arose from extensive recent admixture between genetically autochthonous populations of the Balkan-Carpathian zone and neighboring Slavic groups. The Republic of Moldova is located at a geographical intersection between eastern and southeastern Europe. It shares borders with Romania to the west and Ukraine to the north, east, and south. The country is home to approximatly 4 million people, 69 percent of whom are ethnic Moldavians, with sizable minorities of Ukrainians (11%) and Russians (9%), mostly living in the eastern part of the Republic (Transnistria) and in urban areas. Moldavians speak the Moldavian language, which belongs to the Eastern Romance group of languages and is very close to the Romanian.th millennium BC th millennium BC. The culture lasted till ca. 2750 BC and covered a vast area extending from the Carpathian Mountains in the west to the Dnieper River in the east, and south to the shores of the Black Sea nd millennium BC Modern humans began to inhabit Moldova’s territory in the Upper Paleolithic. During the Neolithic, Moldova was settled by the Starčevo–Kőrös–Criş and Linear Pottery cultures, which dominated the Balkans and central Europe in the 6th c. BC –4th c. AD) the northern Thracian tribes, the Dacians and Getae, dominated the Carpathian Basin including the Moldovan territory th - 7th centuries BC), succeeded by the Scythians (7th –3rd centuries BC) and Sarmatians (3rd c. BC –4th c. AD). Also, Bastarnae, possibly a mixed Celto-Germanic group, settled in the southern parts of the region th century the Slavs had settled there and came into close economic and cultural contact with the Romanized population During the Iron Age  indicate close genetic affinities of Moldavians with other southeastern European groups In this paper, we evaluated the composition of Y-chromosome lineages using the combination of 37 binary and 17 STR markers in 125 Moldavian individuals coming from two spatially separated settlements of the Republic of Moldova. For comparison, 53 Ukrainians from eastern Moldova (Transnistria) and 54 Romanians from eastern Romania were typed using the same set of markers. Comparisons to other published populations from nearby regions were made to further assess the phylogenetic context of the Moldavian Y-chromosomal pool. The results show that present-day Moldavians share their paternal ancestry with both Balkan and eastern/central European populations. This supports the historical accounts that Moldavians arose from an admixture between Vlachs and eastern Slavs.A total of 232 unrelated male individuals were analyzed in the present study. The sample set comprised self-designated Moldavians from the northern settlement of Sofia and southeastern settlement of Karahasani, as well as Ukrainians from the eastern village of Rashkov in Transnistria (Republic of Moldova) and Romanians from the towns of Piatra-Neamt and Buhusi from eastern Romania . Taking 37 binary markers known to identify specific paternal lineages within Europe and West/Central Asia were analyzed in hierarchical order in agreement with the Y-chromosome phylogeny . 33 of tIn addition, all samples were genotyped for 17 Y-chromosome short tandem repeats . The primers used were described by de Knijf et al. ST (for haplogroup) and RST (for haplotype) distance calculations, and AMOVA based on STR data were performed using Arlequin ver. 3.5 software ST were performed using 1,000 permutations and for FST and AMOVA with 10,000 permutations. RST distances among compared populations were represented in two dimensions with multidimensional scaling (MDS) using the STATISTICA v.6 software package . STATISTICA was also used to perform the principal component (PC) analysis on the covariance matrix of the Y haplogroup frequencies.Statistical analyses such as haplogroup and haplotype diversity assessments, pairwise Fhttp://www.fluxus-technology.com). Networks were calculated by the median-joining method after having processed the data with the reduced median method Network analysis of the STR data was carried out with the software package NETWORK version 4.6 (ST) and AMOVA analyses given their duplicated nature and the impossibility of assigning each allele to DYS385a or DYS385b. The DYS385a and DYS385b loci were excluded from the construction of the phylogenetic network inside haplogroup I-M423 for the same reason. However, the DYS385a and DYS385b loci were included in constructing the network of the haplogroup R-M17*, as they diverged strongly enough to always produce two distinct peaks during sequencing. Therefore both loci could be identified in all individuals carrying R-M17* chromosomes and used as two independent markers. DYS385a and DYS385b were also included in the diversity calculations, although it may have caused slight underestimates.The DYS385a and DYS385b microsatellites were not considered in genetic distance (RHaplogroup frequencies in the two Moldavian (separate and pooled), Romanian and Ukrainian samples are reported in In Moldavian males, 19 haplogroups were identified. The most frequent of them were I-M423 and R-M17*, comprising 20.8% and 17.6%, respectively, of all Moldavian Y-chromosomes. These were followed by haplogroups R-M458 (12.8%), E-v13 (8.8%), R-M269* and R-M412* (both 7.2%). All of the remaining lineages were present at frequencies of less than 5% in the Moldavian paternal gene pool. The haplogroup distributions were similar in the two Moldavian samples  and were in agreement with those reported previously for the Moldavian population In Romanians, 15 haplogroups were found. The most common Y haplogroup in this population was I-M423 (40.7%). This is the highest frequency of the I-M423 haplogroup reported so far outside of the northwest Balkans. The next most frequent among Romanian males was haplogroup R-M17* (16.7%), followed by R-M405 (7.4%), E-v13 and R-M412* (both 5.6%).In Ukrainians, 13 haplogroups were identified. The haplogroup R-M17* was the most frequent (34.0%), followed by I-M423 (20.8%), R-M269* (9.4%), N-M178, R-M458 and R-M73 (each 5.7%). The proportions of these haplogroups were in accordance with those observed in other Slavic populations from eastern and central Europe No significant difference in the haplogroup frequency distribution was detected between Sofia Moldavians and other populations from the current study (P>0.05). Pairwise comparisons of Karahasani Moldavians showed significant differences between them and Romanians (P = 0.00309), as well as Ukrainians (P = 0.00432). These differences remained significant, even after applying the Bonferroni correction for multiple testing . The Karahasani population displayed a high frequency of the R-M458 haplogroup, characteristic for eastern and central Europe. In addition, the Karahasani Moldvians showed a lower frequency of the I-M423 chromosome than the Romanians. A significant difference in Y-haplogroup composition was also detected between Romanians and Ukrainians (P = 0.00376 uncorrected for multiple comparisons and P = 0.02256 adjusted for multiple comparisons).We used Principle Component (PC) analysis to compare the present data with those reported for eastern, central, and southern European populations . These p-chromosomal STRs haplotypes were obtained from 228 individuals, among which 181 different haplotypes were identified. In all cases but one, the chromosomes sharing a haplotype belonged to the same haplogroup. Hence, 182 compound binary-STR haplotypes were observed, among which 148 (81.3%) were individual-specific (ST comparison between the Y-STR haplotypes (based on 15 STRs) in our samples showed that haplotype distributions were very similar in the two Moldavian samples (P = 0.28086). Yet, no significant difference was found between Moldavian and Romanian, as well as between Moldavian and Ukrainian samples. Of all pairwise comparisons, the only significant difference was observed between Romanians and Ukrainians (P = 0.01406). However, this value did not remain significant following the Bonferroni correction (P = 0.08436).Y-STR polymorphisms were analyzed to obtain a more detailed view of Y-chromosome variation in the populations under study. Complete Yspecific . STR hapspecific , indicatST genetic distances between all populations under comparison were also obtained , we were able to compare our data to those from the published literature . In the obtained  and subjobtained . There iST comparisons showed that northern and southeastern Moldavians exhibit unequal ties to their neighbors. However, this type of phylogenetic analysis is known to be influenced by multiple-testing problems. To avoid these, AMOVA analyses were performed by assigning the populations to five groups: Moldavians, Romanians, Balkans, eastern/central Europe (eastern and western Slavs), and Italians  than to those of Romanians . It should be noted, however, that the total number of individuals from each population used in these analyses is small. Therefore, further study will be needed to clarify in detail the relationship of the R-M17* chromosomes in Moldavians, Romanians and Ukrainians.Haplogroups I-M423 and R-M17* were found in relatively high frequencies in Moldavians and their closest geographic neighbors, eastern Romanians and Ukrainians. In order to explore the genetic similarities of the I-M423 and R-M17* Moldavian chromosomes with those from Romanian and Ukrainian populations, median-joining networks based on 15 and 17 STRs haplotypes were generated on the background of haplogroups I-M423 and R-M17*, respectively . In bothThe results of the present study show that the Moldavian paternal gene pool presents features characteristic to those found in east/central Europe and the Balkans. This is particularly supported by the following observations: (i) Moldavians display high frequencies of haplogroups I-M423 and R-M17, which are found within the populational variation characterizing paternal gene pools of southeastern and eastern Europe ; (ii) thST distances between STR haplotypes, Romanian populations appeared scattered among the Balkan populations and did not cluster with the Moldavians  out of 125 Moldavian Y chromosomes studied here belonged to haplogroups of apparently northern/central Asian origins. These results are in good agreement with earlier studies on Y-chromosome variation in eastern and central Europe, asserting a minimal impact of gene flow from Siberia/central Asia In conclusion, the results presented in this report allow to hypothesize that an admixture of autochthonous populations of the Balkan-Carpathian zone with neighboring Slavic populations was likely the main factor that contributed to the diversity of the Y-chromosomal genetic pool of present-day Moldavians and, in particular, to the differences in the Y chromosomal lineage composition between Moldavian and Romanian populations. Analyses of mitochondrial DNA and genome-wide assessments of haplotype sharing between Moldavians and neighboring populations would be essential to produce a comprehensive picture of phylogeographic origins of Moldavian genetic lineages.Figure S1Y chromosomal haplogroups defined by the 37 binary markers used. The solid lines represent haplogroups found in the study while the dashed lines are haplogroups not detected in the sample.(TIF)Click here for additional data file.Table S1Frequencies of Y-chromosome haplogroups in the 28 populations included in the PCA.(XLS)Click here for additional data file.Table S2Y-STR haplotypes by haplogroups in the populations studied.(XLS)Click here for additional data file.Table S3Reference populations used in the MDS and AMOVA analyses.(XLS)Click here for additional data file.Table S4ST distances among 29 populations based on Y–STR haplotypes.R(XLS)Click here for additional data file.