With the gradual development of intelligence, human got curious to know his origin and evolutionary background. Historical statements and anthropological findings were his primary tool for solving the puzzles of his own origin, until came the golden era of molecular markers which took no time to prove it’s excellence in unveiling answers to the questions regarding the migration pattern of human across different geographical regions. As a bonus these markers proved very much beneficial in solving criminal offenses and in understanding the etiology of many dreaded diseases and to design their prevention. In this review, we have aimed to throw light on some of the promising molecular markers which are very much in application now-a-days for not only understanding the evolutionary background and ancient migratory routes of humans but also in the field of forensics and human health. Since the origin, spread of mankind across the world has always been an emerging area of interest for modern biologists. Humans migrated “out of Africa” to other geographical locations around the world and eventually diversified into distinct human races populating distinct geographical regions. Human diversity did not only remain restricted to their socio-cultural and linguistic domains but also have penetrated deep inside their genetic root. The wealth of genetic/allelic diversity is not only an excellent resource for human diversity studies but also is highly informative for the study of human genetic predisposition of various diseases . Thus thSince human genome varies from individual to individual, no two individuals are alike genetically or phenotypically. With the development of various molecular techniques the application of genetics to the study of human evolution gave rise to the fields of molecular evolution and molecular anthropology. Various informative and polymorphic genetic markers were discovered and the gene frequency data emerging out from their analyses largely contributed to the successful study of evolution and diversity of human races worldwide. The use of a good number of uniparental and biparental markers for genetic diversity studies is a recent trend in which Y-haplogroup, mitochondrial DNA (mtDNA), human leukocyte antigen (HLA) and killer-cell immunoglobulin-like receptor (KIR) are the promising ones. The inheritance pattern emerging out from the analyses of these markers stirred a debate on the validity of two distinct models of human dispersals since their inception more than 25 years ago .Homo sapiens, distributed throughout the Old World and all regional populations were connected by gene flow as they are today. Some skeletal features developed and persisted for varying periods in the different geographical regions justifying the development of recognizable regional morphologies in the continents of Africa, Europe, and Asia. On the other side, the “recent out of Africa” model  which according to The application of mtDNA to trace the evolutionary pattern and the migration events in human is based on the fact that certain haplotypes are observed in peoples of certain geographical regions of the World  on the Y chromosome. There is now extensive knowledge regarding the geographic origins of Y-SNPs based on studies of global populations . BecauseY haplogroup diversity has been carried out by Earlier studies indicated that Y-chromosome polymorphisms were geographically restricted and that FST values for the NRY were higher than those for mtDNA . Hammer Additionally, Y-chromosome microsatellites find extensive application in forensic researches whereby databases of population haplotype frequencies are established for Europe, the United States and for Asia. Y microsatellite analysis provides assailant specific profile during diagnosis of the rape case when the rapist is mainly azoospermic . PaterniThe major histocompatibility complex (MHC)/HLA is unique in that it is the most polymorphic genetic system in the human genome and the only system to display functional polymorphism . Due to Human leukocyte antigen polymorphism study has been carried out in many of the ethnic populations of India including the primitive tribal group Toto . DebnathApart from being an invaluable tool for population genetic studies, MHC polymorphism has important role in organ transplantation and human disease associations. HLA associations have also helped in defining syndromes of disease categories having common/shared pathogenic mechanism like ankylosing spondylitis and related spondylo-arthropathies that are presumed to be associated with HLA-B27. HLA association studies in infectious and autoimmune diseases show the presence of susceptibility and protective alleles in populations of different ethinic origins . HLA assHuman leukocyte antigen associations with diseases vary in different populations. Disease predisposing genes and their molecular subtypes could help to determine and predict the incidence of the diseases in some populations. It is therefore important to have a population based database of HLA alleles and their frequencies of prevalence in healthy individuals so that disease predisposing influence of a particular phenotype could effectively be assessed in the populations.Being a functionally a polymorphic system, investigations into the distribution of MHC alleles in world populations are very important in this regard since the MHC genetic makeup of each of these populations would reflect interplay of both the basic genetic origin and effects of natural phenomenon such as founder effect and environmental selection. Differences in the prevalence of HLA alleles in different populations in varied environmental conditions could be utilized to assess the role of each of these alleles in conferring survival advantage to human populations.Killer-cell immunoglobulin-like receptors were first described by Immunogenetic studies based on KIR genes in different ethnic populations around the world show significant differences in the distribution of group A and B haplotypes. Whereas in the Japanese population group A genotypes  were found at frequencies well above 50%, only a single individual out of 67 exhibited a group A genotype in a survey among Australian Aborigines ,b.The KIR frequencies of many of the ethnic populations were analyzed worldwide. In one such work, KIR gene profile was studied for the Rajbanshi population, an essential caste population of Sub-himalayan part of north-eastern India . It was Figure 3 (adopted from The frequencies of the inhibitory KIR genes in most of the world population groups are very high except those on the B haplotypes, i.e., KIR2DL2, KIR2DL5A, and KIR2DL5B. Detailed analysis revealed that indigenous populations such as aborigines and Amerindians have outlying frequencies of the KIR genes. Obviously there is a close inverted correspondence between the frequencies of KIR3DL1 and KIR3DS1 genes in an individual population. Based on KIR haplotype B genes In humans, KIRs recognize HLA class I proteins leading to the inhibition or activation of cytotoxic cell activity and cytokine production by T and NK cells thus focusing on the role of these receptors in immunological responses of NK cells . The intHuman have developed their interest in unveiling the mysteries of human migratory pattern and evolutionary trends since his origin. These above mentioned markers are serving the scientific world to trail back through time to understand the dispersal pattern of humans. To add to their importance, these markers are also responsible for understanding the underlying etiology of certain disease pathogenesis. Application of these markers especially Y-SNPs in forensics has been an interesting achievement in the past decade. Apart from these markers, a group of recently emerging markers which are gaining the attention of the researchers all over the world are the toll-like receptors TLRs; . In addiThe authors declare that the research was conducted in the absence of any commercialor financial relationships that could be construed as a potential conflict of interest.


Aythya ferina), a long-distance migratory duck and potential vector of highly pathogenic avian influenza. We collected several hundred samples from breeding and wintering grounds across Eurasia including some H5N1-positive individuals and generated partial sequences of the mitochondrial control region and multilocus microsatellite genotypes. Genetic differentiation among breeding populations was significant for both marker types but higher for maternally inherited mtDNA than for biparentally inherited nuclear markers. There was only weak genetic divergence between ducks sampled in Europe and East Asia, and genetic differentiation between populations was not generally associated with geographical distance. No evidence of genetic substructure was detected for ducks sampled on the European wintering grounds. Our results suggest limited breeding-site fidelity, especially in females, but extensive population admixture on the wintering grounds. The specific role of pochards as natural vectors of zoonotic pathogens and in particular H5N1 remains to be clarified but our results point to wintering grounds as potential hotspots for disease transmission.An understanding of the distribution and spatial structure of the natural vectors of zoonothic pathogens is of interest for effective disease control and prevention. Here, we investigate the range-wide population genetic structure of common pochard ( Zoonoses are diseases that are transmitted from animals to humans . Most zoAnas acuta) wintering in Japan and North America, respectively, share breeding areas in eastern Russia (Odocoileus virginianus), a vector of chronic wasting disease  dynamics of associated pathogens e.g., . In partn Russia . This spn Russia . At a mo disease . Consequ disease .Aythya ferina, pochards hereafter) have been listed as a high-risk species in relation to AI by the European Union (2005) because they were repeatedly detected as carriers of H5N1 among a number of wild bird species. During the H5N1 outbreak in winter 2005/2006, pochards were either ranked first or second among wild bird species in terms of the number of birds found infected in France, Germany, and Switzerland  virus subtypes , and thetzerland . The spetzerland , the distzerland . The vertzerland  and theitzerland  are of aBased on ring recovery data, In this study, we use molecular data to describe the range-wide population structure of pochards. Our primary aim was to delineate the patterns of genetic differentiation between ducks on the breeding and wintering grounds across Eurasia, with a particular focus on assessing the previously postulated subdivisions. We further examine the congruence between nuclear and mitochondrial markers with different modes of inheritance to investigate sex-specific differences in the rates of gene flow . These aN≥ 9 for mitochondrial and/or nuclear markers were defined as population samples and included in all population genetic analyses while samples from other localities were included in the phylogeographic analyses only. Samples collected between June and August were considered to be from breeding populations, samples collected between November and February from wintering populations. For the breeding season, we obtained seven population samples plus smaller samples from eight additional locations. On the wintering grounds, population samples were obtained from 12 sites and additional samples from another four sites , and Germany . In total, 345 samples were available from 34 localities in 16 countries . Localitur sites . Three sur sites . Genomicur sites .ctr), including most of the hypervariable region (HVR) I, was amplified using the primers M1 , 1 μl MgCl2 (25 mM), 1 μl of each primer (10 pmol/μl), 2.5 μl 10× buffer (containing 1.5 mM MgCl2), and 0.2 μl Taq polymerase  and 2 μl template DNA (20–100 ng/μl). The PCR amplification profile included an initial denaturation step of 93°C for 2 min, followed by 35 cycles of 93°C for 30 sec, 56°C for 30 sec, and 72°C for 1 min, and a final extension step of 72°C for 7 min. PCR products were purified with the GenElute™ PCR clean-up kit (Sigma) according to the manufacturer's protocol. Sequencing reactions were carried out in a volume of 10 μl with the Terminator Ready Reaction Mix “Big Dye”  according to the guidelines of the manufacturer. The cycling protocol was as follows: 50 sec at 96°C, followed by 35 cycles of 10 sec at 96°C, 10 sec at 50°C, and 4 min and 30 sec at 60°C. The products were purified using sodium acetate precipitation, and were separated and detected on an ABI Prism 3100 Genetic Analyzer (Applied Biosystems).A fragment of the mitochondrial control region  are a known issue in some diving ducks, including the genus Aythya , and mayAythya . Here, wAythya . Second,Aythya . FinallyAll samples were screened at 14 autosomal microsatellite loci initially developed for related species . The 14 k), the number of haplotypes (NH), haplotype diversity (H), and nucleotide diversity (π) were calculated for each population sample using DnaSP v.5.0 (AR), number of alleles (NA), and observed (HO) and expected heterozygosities (HE) in each population sample with FSTAT v.2.9.3.2 . Further, haplotype networks were constructed based on a median-joining algorithm (http://www.fluxus-engineering.com). The phylogeographic structure at the nuclear microsatellite markers was investigated with principal coordinates analyses (PCoA) based on pairwise Euclidian distances between individual genotypes in GENALEX v.6.2  and geographical distance in kilometers between pairs of populations. The significance of the association was assessed based on 1000 permutations.All population genetic analyses were carried out separately for the seven breeding populations and the 12 wintering populations. Analyses of molecular variance AMOVA;  implemenei model  and for K) was varied between 1 and 7 for breeding and 1 and 12 for wintering ducks, respectively, and we carried out 10 independent runs per K. The most likely K was assessed as suggested by We also used individual-based clustering approaches for the microsatellite data to investigate the genetic structure among breeding and wintering ducks. For Bayesian analyses with STRUCTURE v.2.3.1 , we usedFST = 0.001, 0.0025, 0.005, 0.01, 0.02, and 0.025) with samples sizes, numbers of markers, and allele frequencies corresponding to the empirical data. Statistical power was defined as the proportion of times the null hypothesis of equal allele frequencies across populations was rejected using a chi-square test or a Fisher's exact test.To assess the statistical power of our microsatellite markers to detect given levels of population differentiation, we performed power analyses in POWSIM v.4.0 . We genek) was similar in breeding and wintering populations .Sequences of 601 bp from the mitochondrial control region were obtained for 274 individuals, and 143 haplotypes were identified based on 80 polymorphic sites. Forty-seven haplotypes were shared by two to 36 individuals and the remaining 96 were singletons. The average number of pairwise nucleotide differences . There was no evidence of genotypic disequilibrium after Bonferroni correction. Significant heterozygote deficits were observed in 17 of 228 locus-specific tests with locus Caud13 being affected six times . For mtDNA, five of 21 pairwise comparisons between populations were significant (ST) increased with geographical distance between sampling locations . Based on the microsatellite markers, we obtained a global FST estimate of 0.018 (P < 0.0001), and five of 21 pairwise FST values were significant .The population-based analyses provided no evidence of major migratory divides across Eurasia. The four geographical groups  did not explain a significant proportion of the genetic variation for mtDNA or microsatellites . The varnificant , and thenificant . These cnificant . Again, Individual-based clustering approaches provided no evidence of genetic substructuring among ducks from breeding populations. STRUCTURE analyses showed highest support for one genetic cluster across Eurasia . DAPC inP > 0.15; ST of 0.02 (P = 0.0156), and two of 66 pairwise comparisons were significantly different from zero . For the microsatellite data, the overall population structure was very low but statistically significant , while none of the pairwise FST values were significant . No evidence of genetic substructure was detected by STRUCTURE  to investigate its movement patterns and the specific factors causing restricted gene flow between some of the breeding populations in more detail. Given that individuals are capable of traveling thousands of kilometers during annual migration, we would not expect physical restrictions to limit dispersal between breeding grounds. Indeed, the apparent absence of an isolation by distance (IBD) pattern between populations across Eurasia may suggest that dispersal occurs at least partially over very large distances as IBD can only build up if dispersal is spatially restricted . UnfortuIt is worth noting that IBD in pochard may not have built up because populations are not at mutation–drift equilibrium, for example, because of a recent range expansion of the species. At a local scale, such an expansion has occurred. During the last centuries, changes in the availability of suitable water bodies and food sources have led to a westward extension of the species’ breeding range into Central and Western Europe  However,N = 18), compared to 33% of the males . Along similar lines, In this context, attention should be paid to potential sex differences in colonization and dispersal patterns of pochard given the higher level of genetic differentiation among breeding grounds in maternally inherited mtDNA than in biparentally inherited microsatellite markers . Of courFST values were observed between European and Asian populations (Pochards sampled on the disjunct wintering grounds in Europe, the Caspian Sea, and eastern Asia show remarkably little genetic differentiation given the large geographical distances between them. Only population-based analyses including the wintering grounds in Asia revealed very weak signals of genetic subdivision. The latter result—taken alone—could be interpreted as reflecting a subdivision at least between the wintering grounds in Europe and East Asia at the western and eastern edges of the distribution range . Indeed,ulations . More imulations  demonstrGiven the very high levels of genetic diversity and relatively low genetic structure, it is not surprising that an aggregation of individuals from multiple breeding populations does not produce a classical population genetics signal for admixture among strongly subdivided populations such as elevated diversity or deviations from Hardy–Weinberg expectations (e.g., Wahlund effect; Extensive movements within and/or between winters are also the likely cause for the apparent genetic homogeneity among European wintering grounds of pochard. A subdivision was earlier proposed between a northwestern population wintering around the North Sea and a southeastern population wintering in central Europe and around the Mediterranean and Black Seas . HoweverThe absence of a clear association between genetic variation and geography and, in particular, the apparent mixing of ducks on wintering grounds imposes strong limitations on further analyses of the transmission and spread of pathogens of pochard. H5N1-positive individuals from European wintering grounds shared mtDNA haplotypes with ducks from several continental regions, and genetic differentiation was insufficient to use individual-based assignment methods to trace the geographic origin of pochard with highly variable microsatellite genotypes. However, complete panmixia is apparently prevented by low levels of breeding philopatry, which indicates that even higher genetic resolution might allow the identification of the large-scale region of origin of individuals gathering on wintering grounds. Such an analysis would require hundreds or thousands of markers distributed across the entire genome, as recently exemplified in humans, which also show globally low genetic population structure see . AdditioIt must be noted, however, that direct links between the movement of individuals or populations of pochard and the transmission and spread of HPAI H5N1 will be difficult to establish without considerably improved knowledge on the natural host spectrum, infection pathways, and the consequences of infection. H5N1-positive individuals were repeatedly found among pochard wintering in Europe but infections have also been detected in a number of other waterfowl species . Six pubContinent-wide transport of HPAI by individual birds may be rather unlikely but transfer in a stepping-stone fashion through successively infected birds appears nevertheless possible . In poch


Guignardia citricarpa. This disease causes irreparable losses due to the premature falling of fruit, as well as its severe effects on the epidermis of ripe fruit that renders them unacceptable at the fresh fruit markets. Despite the fact that the fungus and the disease are well studied, little is known about the genetic diversity and the structure of the fungi populations in Brazilian orchards. The objective of this work was study the genetic diversity and population differentiation of G. citricarpa associated with four sweet orange varieties in two geographic locations using DNA sequence of ITS1-5.8S-ITS2 region from fungi isolates. We observed that different populations are closely related and present little genetic structure according to varieties and geographic places with the highest genetic diversity distributed among isolates of the same populations. The same haplotypes were sampled in different populations from the same and different orange varieties and from similar and different origins. If new and pathogenic fungi would become resistant to fungicides, the observed genetic structure could rapidly spread this new form from one population to others.One of the most important diseases that affect sweet orange orchards in Brazil is the Citrus Black Spot that is caused by the fungus  Guignardia citricarpa Kiely, is a foliage and fruit disease of citrus, affecting oranges, mandarins, lemons, and grapefruit [ Citrus black spot, caused by apefruit . The affapefruit . The funapefruit . The life cycle of this pathogen includes both asexual and sexual reproduction. Asexual pycnidiospores are disseminated from plant to plant via rain splash and despite their potential for long-distance movement, the epidemy is restricted . HoweverG. citricarpa morphology [Although studies have been conducted on rphology , diseaserphology , inocularphology , and disrphology , 10, no rphology . The genrphology .Botrytis cinerea from different hosts in California [Mycosphaerella graminicola from Texas and Switzerland [Guignardia mangiferae [Cercospora and Mycosphaerella [ A number of molecular techniques have been used to investigate genetic diversity and population differentiation of pathogen populations in plants. Among them, amplified fragment length polymorphism (AFLP) seems to be a more effective polymerase-chain-reaction-(PCR-) based technique than others, such as random amplified polymorphic DNA (RAPD), because it produces much more polymorphic fragments . Microsalifornia  and RFLPtzerland . The ITSngiferae  and verihaerella .G. citricarpa populations, we used sequence information present in the ITS1-5.8S-ITS2 region. The objectives of this study were to (i) characterise the population structure of G. citricarpa from different geographic regions and sweet orange varieties by determining genetic diversity and population differentiation, (ii) analyse the natural selection pressure causing genetic diversity and restriction of gene flow among populations, and (iii) analyse the possible disease management strategies associated with the genetic structure of G. citricarpa. Therefore, to obtain valuable information on the genetic structure of the G. citricarpa typical colonies. Colonies were then transferred to other Petri plates in order to purify the culture. Fragments of these colonies were then placed in tubes with liquid PD medium in order to produce abundant mycelium for DNA extraction.The sampling was done in two different geographic areas: in the Conchal district , located in São Paulo State, and in the Itaboraí district , located in Rio de Janeiro State. In each place, 24 symptomatic fruits were collected, one fruit per plant, in order to obtain one isolate per plant. This was done for the four sweet Orange varieties analysed: “Natal,” “Pêra Rio,” “Valência,” and “Folha Murcha.” In the same places, in one single plant, 24 symptomatic fruits were collected in order to obtain 24 isolates from the same plant for each variety. These four varieties were chosen because they represent the most cultivated citrus trees in Brazilian orchards and are highly susceptible to CBS. On each fruit previously hygienized, three or four CBS symptoms were excised, placed on Petri plates with PDA  medium and observed for appearance of Guignardia isolates from this study were characterised in oatmeal medium according to Baldassari et al. [All i et al. .μL of buffer 1X ; 0,8 μL of MgCl2 5 mM; 0,4 μL of each dNTP 10 mM; 0,3 μL Taq DNA polymerase and 5 pmol of each primer, with 60 ng of genomic DNA and sterile water q.s.p. to 20 μL. DNA was amplified in Termocycler PTC-100 , with 1 initial cycle at 94°C during 2 min, 39 cycles at , and 1 final cycle at 72°C for 5 min. Amplified samples were separated by electrophoresis in an agarose gel (1.2%) containing ethidium bromide  and 1 KbDNA Ladder. The samples were visualised under UV light with a GEL DOC 1000 system—Bio-Rad (data not shown). The obtained DNA fragments were purified and sequenced after PCR with the DYEnamic ET Dye Terminator Kit  according to the manufacturer's instructions. Thermocycler conditions were the same as previously described. DNA fragments were precipitated with isopropanol 75%, washed with ethanol 70%, and resuspended with 3 μL of “loading buffer”  and denatured at 95°C during 2 min. Electrophoresis was conducted in a sequencer, ABI Prism 3700 DNA Sequencer . The ITS region of each isolate was submitted to sequencing two times at both ends of each strand (Primer Forward + Primer Reverse).DNA from isolates was extracted according to the Kuramae-Izioka  protocolABI Analysis Data Collection and converted to nucleotide sequences by DNA Sequencing Analysis Software Version 3.3. The DNA sequences were then submitted to software Phred/Phrap/Consed [The electropherograms were obtained with the software p/Consed  and Sequp/Consed . The aliGenetic distances were calculated between groups of pathogenic isolates from the same plant, from different plants, and from different geographic origins. These estimates were calculated in order to evaluate the genetic diversity among the intra- and intergroup, according to Nei's equations . The intAverage pairwise differences were estimated from comparisons within a library of the number of sequence differences between a given clone and all other clones  Table 5Table 5. FST values were used to evaluate the genetic diversity within the groups of isolates in relation to the total genetic diversity according the equation FST = (θT − θW)/θT, where θT is the genetic diversity of all isolates and θW is the diversity within the group of isolates [isolates . Analysiisolates . Populatisolates . Gene flisolates  by the sisolates .The aligned sequences were used to verify the genetic relationships among the isolates from same and different sweet Orange varieties from the two places. Dendrograms were built using the Distance Method and grouped by the algorithm, Neighbour Joining  and the Pathogenicity tests were conducted according Baldassari et al.  using 22Guignardia typical colonies were obtained from all the varieties and geographic origins, in a total of 384 isolates. All samples, in the same and different plants in the 4 orange varieties and two different places, were composed of 24 isolates  and its ID are showed in supplementary material available online at doi:10.1100/2012/368286.The obtained sequences were submitted to a quality analysis in order to use only those that displayed high quality. All sequences showed the desired quality by software Phred/Phrap/Consed. This was done in order to prevent mistakes during later analysis. None of the sequences showed apparent heterozygotes in this region. All sequences were submitted to GenBank , Itaboraí isolates presented a genetic distance slightly lower (0.01527) than the group of isolates from Estiva Gerbi/Conchal (0.01714). The genetic distance between (intergroup) all isolates from these two regions was 0.01637.Isolates from Estiva Gerbi/Conchal, obtained from a single plant of “Folha Murcha” presented the highest intragroup genetic distance (0.02500), whereas the lowest was presented by the “Natal” variety (0.00972) from Itaboraí .When Itaboraí isolates where analysed, the isolates from the same plant of the “Folha Murcha” variety presented the highest intragroup genetic distance (0.02027). The lowest intragroup distances were presented by isolates from different plants of the “Natal”variety (0.00972) . In ItabAmong the isolates from Estiva Gerbi/Conchal, the isolates from a single plant of the “Folha Murcha” variety presented the higher intragroup genetic distance (0.02500), and the lower distance was represented by isolates from a single plant of the “Natal” variety (0.01025) . In EstiThe highest intergroup genetic distances were represented by isolates from the same geographic origin, EstivaGerbi/Conchal, by single-plant isolates of “Folha Murcha” and “Valência” (0.02361) . Among tThe lowest divergence was represented by groups of isolates from different geographic origins, by isolates from “Natal” of different plants from Itaboraí and “Valência” and different plants from Estiva Gerbi/Conchal (0.01049). These two populations can be considered as having lowest genetic diversity.These diversity indices showed that the highest genetic diversity was found for the groups of isolates from São Paulo state, IE and IV, from the same plant of “Folha Murcha” and “Valência” varieties, respectively . These tF values, little genetic differentiation among G. citricarpa populations was observed at various hierarchical levels  , representing 90.86 percent of the observed genetic diversity. The fixation index among populations within regions was also significant , representing 9.98 percent of the observed genetic diversity. The fixation index among the two regions is almost insignificant , indicating that there is gene flow between regions.According to lations) . The anaFSC = 0.102, P ≤ 0.005). The lowest was represented for “Valência” and “FolhaMurcha” . In Estiva Gerbi/Conchal/SP, the highest differentiation was also observed for “Pêra” and “Natal” , and the lowest was observed for “Valência” and “FolhaMurcha” . Between the two regions, “Pêra” and “Natal” showed the highest genetic differentiation , and “Valência” and “FolhaMurcha” represented the lowest . When we analysed the same orange variety from both places, the highest population differentiation was displayed by the “Pêra” variety  and the lowest by “Valência” .When differentiation indices were calculated for groups of isolates according to the orange variety , we obseFST = 0.172, P ≤ 0.005) and the lowest for “Valência” populations from the same and different plants (V and I) . In Estiva Gerbi/Conchal/SP, the highest differentiation was also observed for the “Pêra” population of the same plant and the “Natal” population of different plants (IP and NC)  and the lowest for “Valência” and “Folha Murcha” populations from the same plant (IV and IE) . When populations of the two places were compared, the highest differentiation was by the “Pêra” population of the same plant and the “Natal” population of different plants (PR and NC) ; the lowest differentiation was represented by the “Valência” population from the same plant and “FolhaMurcha” populations from different plants (IV and FI) .Genetic differentiation was also estimated for the groups of isolates according to variety, sampling, and geographic origin . In ItabThe analysed populations also shared haplotypes , and theGene flow was also detected among the studied populations . All samIn Estiva Gerbi/Conchal/SP, the highest level of gene flow between populations was detected between the sample of different plants of “Valência” and different plants of “Folha Murcha”  and the lowest between the “Valência” population of the same plant and the “Pêra” population of the same plant . The highest levels of gene flow were seen when populations from the two geographic origins were compared .G. citricarpa sequences obtained from GeneBank displayed great similarity between each other, as is exemplified by populations obtained from the same  was found within the populations. A minor diversity was found within regions (9.98%) and can be credited possibly to influences of the host over the populations. Little genetic diversity was found between the two sampled sites, showing that the same or similar haplotypes were found in all populations, despite the fact that the two geographical areas are distant from one another (around 650 km) and have different climatic and soil conditions.In this study, the sequence information was used to identify SNP markers to detect genetic variation and revealed a low degree of genetic variability within and among the sixteen studied populations. The diversity indices for the G. citricarpa also displayed no traits inherent to a specific pathogen to any of the studied orange varieties, with a high number of haplotypes being shared by different populations of the same and different orange varieties and by populations of the two different geographic areas. As the two areas where the populations were collected are not close to one another geographically and citriculture is widespread between the two areas, this can facilitate gene flow among populations. The diversity indices also showed that sampling done in the same plant presented similar genetic diversity as the sampling conducted in different plants, probably because one plant can host different G. citricarpa haplotypes. The coexistence of different pathogen haplotypes within the same host plant, as detected by this work, has diverse biological implications beyond the increased opportunities for sexual reproduction. Colonization of the host by different genotypes of the same pathogen leads to an increase of within-host competition and a selection of higher pathogen virulence .G. citricarpa populations separated by thousands of kilometres were genetically similar, as indicated by low population differentiation and high genetic identity. The low levels of population differentiation were reflected in corresponding high values of Nm (gene flow). Despite the fact that low FST values may arise from gene flow as well as recent population expansion even in the absence of gene flow [ We believe that the gene flow is not restricted between populations in the same geographic area or in populations from the two geographic areas because citriculture is widespread in Brazil. ene flow , we beliFST values among populations from different geographic areas and also among populations of the same area, we believe the mechanism of dispersal is at work in G. citricarpa. Propagation structures in G. citricarpa are either sexually formed ascospores or asexual pycnidia. The fungal spores generated by mitosis (“conidia”) formed inside specialised organs (“pycnidia”) are frequent in G. citricarpa and are found on fruit lesions during the ripening stage, but they are unlikely to function as dispersal units over long distances [ Low levels of population differentiation and corresponding high levels of genetic similarity suggest that gene flow has had a significant impact on the genetic structure of these populations . In lighistances . Ascospoistances , whereasistances . So, it istances , 37.FST values. In the absence of such observations, evidence seems to favour ascospores as the common dispersal unit at the present spatial scale. However, an alternative explanation may be that wind or human activities acted as vectors for dispersing pycnidia over larger distances than expected. If pycnidia had been abundant at the particular spatial scale in our study, we would have expected to see possibly higher within-habitat As is common with most organisms, plant-pathogenic fungi rely on the processes of mutation and recombination as the ultimate source of genetically based variation. Within a species, gene flow between populations supplements these processes as propagules spread from one epidemiological area to another and from one deme to the next .The major focus of population genetics is to understand the evolutionary processes shaping and maintaining the distribution of genetic variation distributing within and among populations . The defG. citricarpa populations, changing its structure and increasing the probability of selecting resistant strains to the fungicide's active molecules. Selection or emergence of resistant strains can be done in Brazil by an increase of selection pressure and because the teleomorph and anamorph phases of G. citricarpa are currently found in affected Brazilian orchards. Given the little genetic differentiation among the studied populations, this suggests frequent recombination events [In Brazilian citriculture, the current and regular use of fungicides can cause a selective pressure over the n events , we can n events .Gibberella zeae (GST < 0.05), also suggesting that these populations were panmictic. Low levels of GST also have been reported between populations of other plant-pathogenic fungi, including Rhizoctonia [Rhynchosporium [Botrytis cinerea [ Dusabenyagasani et al.  made simzoctonia , Rhynchoosporium , and Bot cinerea , and in FST (<0.01 among the two sites) and an estimate of very high genetic identity  both suggest that these sixteen G. citricarpa populations are part of a much larger, probably panmictic, pathogen population covering much of the Brazilian Southeastern. Despite being collected in different years and from sites over 650 km apart, the low values for  The likelihood that high levels of gene flow occur on a regional scale indicates a substantial risk for the regional spread of mutant alleles that enable the breakdown of resistance genes or fungicide-resistance. Since the mutant allele travels regionally in ascospores (gene flow) instead of conidia (genotype flow), the mutant allele will move between fields in a recombined genetic background that has not been preselected for a highly fit combination of coadapted alleles. As a result, the development of new virulent pathotypes or fungicide resistant strains may in many cases be gradual rather than abrupt . In thisCrotalaria sp. and Cajanus cajan between the citrus lines. The use of a rotary cutter permits the covering of the fallen citrus leaves and makes the spread of ascospores more difficult. The use of these cultures between citrus lines also has the advantage of increasing soil nitrogen levels and reducing the fall of the citrus leaves. The management of fallen citrus orange leaves has been highly recommended to Brazilian citrus producers. This has been done by recommending the cultivation of species like Guignardia mangiferae isolates used for this study. ITS1-5.8S-ITS2 DNA region of each isolate was amplified in order to perform the population genetic structure described on this research. The DNA sequence was deposited in GenBank and received an Acession Number presented on Table.This Table contains the Click here for additional data file.


ST value point towards greater diversity and differentiation which suggests the possibility of early demographic expansion of the study groups. The phylogenetic analysis revealed 13 paternal lineages, of which six haplogroups: C5, H1a*, H2, J2, R1a1* and R2 accounted for a major portion of the Y chromosome diversity. The higher frequency of the six haplogroups and the pattern of clustering in the populations indicated overlapping of haplogroups with West and Central Asian populations. Other analyses undertaken on the population affiliations revealed that the Indo-European speaking populations along with the Dravidian speaking groups of southern India have an influence on the tribal groups of Gujarat. The vital role of geography in determining the distribution of Y lineages was also noticed. This implies that although language plays a vital role in determining the distribution of Y lineages, the present day linguistic affiliation of any population in India for reconstructing the demographic history of the country should be considered with caution.The present study was carried out in the Indo-European speaking tribal population groups of Southern Gujarat, India to investigate and reconstruct their paternal population structure and population histories. The role of language, ethnicity and geography in determining the observed pattern of Y haplogroup clustering in the study populations was also examined. A set of 48 bi-allelic markers on the non-recombining region of Y chromosome (NRY) were analysed in 284 males; representing nine Indo-European speaking tribal populations. The genetic structure of the populations revealed that none of these groups was overtly admixed or completely isolated. However, elevated haplogroup diversity and F India is the second most populous country in the world with a population of 1.21 billion Archaeological and paleontological evidence dating back to the middle and late Pleistocene era points towards early human occupation of the Indian subcontinent The unique and complex structure of the Indian population is attributed to the multiple waves of migration and the resultant gene-flow which occurred in the past Within this complex scenario, many interaction models such as gene-language, gene-geography and gene-ethnicity have been contested. Previous studies have shown inverse correlation between genetic affinities and geographical distance Keeping the above in view, we present an analysis based on the study of 48 bi-allelic markers in nine Indo-European speaking tribal groups of Southern Gujarat which lies in the western part of India. The main objectives of the study were (a) to study the distribution of Y haplogroups; (b) to study the relative influence of language, geography or ethnicity on the genetic structure of populations using the pattern of Y haplogroup clustering and finally (c) to relate the observed pattern of Y haplogroup clustering with the Y chromosome lineages which arrived in India largely from the Northern corridor at different points of time. To achieve the study objectives the results were first compared with published studies on the Indian populations and then with available data on the Eurasian populations. The Indian populations were selected keeping in view the availability of data, their linguistic and socio-culture status and geographical position. Similarly, the Eurasian populations for which published sources were available were considered for analysis since the historical migrations from these regions are known.This study was approved by the Departmental Ethical Committee of the Department of Anthropology, University of Delhi. Informed written consent was obtained from all the participants. A 5 ml blood sample was drawn by a trained medical practitioner from randomly chosen 284 healthy, unrelated males from nine tribal population groups of Valsad and Surat districts of Gujarat. A description of relevant population characteristicsof study groups along with populations from other studies is presented in iir, which is given by the formula:ip and P are the frequency of the haplogroups in a population i and in the pooled populations respectively. In the second stage of the model, Harpending and Ward propose an island model of population structure in which there is a linear relationship between gene diversity and the distance from the centroid which is calculated by the formula:ih and H correspond to the gene diversity value in the population i and in all the populations as a whole respectively. As per the model, outlier populations that have undergone systematic migrations will show greater gene diversity than predicted by the regression line, while outlier groups that are isolated will exhibit lower than predicted gene diversity.The revised Y-Chromosome phylogenetic tree ST values were calculated on haplogroup frequencies and analysed through non metric multidimensional scaling (MDS) in SPSS version 16.0 using ALSCAL programme. The MDS plot was constructed in order to graphically represent the nature of clustering between the study populations and other world populations.In order to determine whether the Y chromosome haplogroup distribution among Indian populations is structured on the basis of ethnicity, geography or linguistic affiliation, an analysis of molecular variance (AMOVA) based on haplogroup frequencies was computed for the various tentative categories using ARLEQUIN software, version 3.1 For carrying out AMOVA on different populations secondary source haplogroup frequency data  was compThe frequency distribution of Y chromosome haplogroups among the study populations along with the phylogenetic relationship between them is presented in M69 mutation, which is a characteristic of haplogroup H was found on 114 of the total 284 Y chromosomes. Haplogroup H was further segregated into three lineages, H1 by the presence of M52-C allele, H2 by the presence of Apt-A allele and H* by absence of the two alleles. These haplogroups were further subdivided into a number of sub-clades. Lineage H1a* of H1 group was observed 71 times and represented the most frequently occurring lineage across all the populations. Its frequency varied from a minimum of 3.45% among Pavagadhi Chaudhari to a maximum of 62.5% in Vasava. Lineage H2 represented the second most frequently occurring lineage among the H haplogroup and third most common haplogroup among all the haplogroups. Its frequency varied from 3.45% among Pavagadhi Chaudhari to 40.74% among Mota Chaudhari. However, H2-Apt was found to be absent among Vasava and Gamit populations. While lineage H* was observed in only three individuals, one each from Konkana, Gamit and Mota Chaudhari.R1a1*a sub-clade of R haplogroup was found to be the next most frequently occurring lineage after H1a*. Its frequency was found ranging from 5.56% in Gamit to 62.07% in Pavagadhi Chaudhari. Its sister sub-clade R2-M124 was observed 27 times with a frequency varying from 5.56% among Gamit to 20.83% among the Konkana tribe. Barring Valvi Chaudhari, R2 was absent from all other Chaudhari groups.J2 with its two sub-clades J2b2* and J2a constituted a major portion of Haplogroup J in the current study. Except Konkana and Mota Chaudhari, either of the two J2 sub-clades was present in all other groups. J2b2* sub-clade was observed in 21 Y chromosomes. Its frequency was found to be 11% in Gamit, 19% in Valvi Chaudhari and 21% in Pavagadhi Chaudhari. The remaining four populations of Dhodia, Dubla, Vasava and Nana Chaudhari exhibited similar frequency values varying in a narrow range between 4% and 4.48%. Sub-clade J2a was observed only 8 times in the nine groups. It was present in four of the groups with a minimum frequency of 3.17% in Dhodia to a maximum frequency of 7.14% in Dubla.Out of the seven sub-clades of C haplogroup, only one sub-clade C5 with its two main derivatives C5a and C5* was observed 21 times in all the populations except Pavagadhi Chaudhari. C5a lineage was observed to be 62 times more frequent then its sister branch C5*. Its frequency varied from 3.17% in Dhodia to 12.5% in Valvi Chaudhari, while that of C5* was found to vary from 3.7% in Mota Chaudhari to 9.38% in Valvi Chaudhari.Parahaplogroup F* along with the other parahaplogroup K* and two haplogroups L and Q accounted for 13.03% of the total haplogroups. After initial screening of M89-T allele, 11 samples failed to resolve further and were therefore grouped under F*. Similarly, 8 individuals did not exhibit any mutation except G allele for M9 and were therefore grouped under K*. Other two sub-clades L1-M27 and Q3-M346 were present, but in low frequencies only.h) which is equivalent to gene diversity for haploid genomes ranged from 0.586 in Pavagadhi Chaudhari to 0.899 in Valvi Chaudhari.Haplogroup diversity values for each of the nine populations along with haplogroup distribution are given in iir). The values of gene diversity (ih) and genetic distances from centroid (iir) used in the nine study population groups along with their standard errors are given in We compared the study populations with 24 additional world populations already published in separate studies . A stresThe North-Western corridor of India has witnessed many waves of migrants from different parts of the world, with a majority being male migrants Our analysis based on Y chromosomal UEPs apportioned the study samples into 13 haplogroups representing 10 major Y lineages  in India. Haplogroup diversity (0.772) was found to be comparable with Dravidian speaking populations (0.723), but higher than Indo-European speaking populations (0.684) in the country The indigenous versus exogenous origin of Indian paternal lineages has been widely contested. Among the study populations, six sub-haplogroups namely, C5, H1a*, H2, J2, R1a1* and R2 constituted the major paternal lineages that together accounted for 85.92% of the Y chromosomes. While the indigenous origin of sub-clades C5, H1a*, H2 and R2 are accepted, the status of sub-clades J2 and R1a1* are contested as they are believed to have been introduced in India with the demic diffusion of Proto-Dravidian Neolithic agriculturists from West Asia and the influx of Indo-European pastorals from Central Asia. It is worth mentioning here that the high frequency and associated diversity of a haplogroup is correlated with the possible place of origin of a particular haplogroup Haplogroup C is widely distributed in Eastern and Central Asia, Oceania and Australia Haplogroup J is predominantly found among the populations of West Asia, North Africa, Europe, Central Asia, Pakistan, and India In the present investigation sub-clade R2 occurred with a frequency of 9.51%, which is similar to its frequency reported from other Indian populations The MDS plot  also refLack of any major exogenous contribution of Y lineages and existence of high haplogroup diversity indicate the possible male assimilation from other neighbouring populations of India among the study groups. Analysis of molecular variance  performeThe present investigation indicates that tribes of Gujarat show both high genetic diversity and genetic differentiation. It is therefore conceivable that these groups, with a fairly large population size, have passed through a long evolutionary history experiencing an early demographic expansion and later fission of the populations. Further affinities of study groups with Indo-European speaking non tribes followed by Dravidian speaking tribal groups suggest the possibility that these native tribal population groups of Western India might have adopted the Indo-European language during the process of cultural assimilation and absorption while still retaining their genetic links with the Dravidian speaking tribal populations. Thus, it is recommended that the present day linguistic affiliation of any Indian population should be considered with caution while reconstructing the demographic history of the country. In conclusion, a study based on the recently discovered bi-allelic loci and microsatellite loci in the populations can shed light on the possible explanation of the overlapping of haplogroup distribution between tribes of Gujarat with other Asian populations and further deepen the understanding of the population history of India.Table S1Y chromosome haplogroup frequencies data among study populations and other populations of India considered for AMOVA.(XLS)Click here for additional data file.Table S2Y chromosome haplogroup frequencies data among study populations and other populations of World considered for MDS analyses.(XLS)Click here for additional data file.


Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. The role of small- vs. large-scale environmental changes in the generation and maintenance of genetic variation in natural populations remains a central but neglected issue in biological research . Mismatch distributions and haplotype networks for each locality of each species were also plotted  and the following neutrality tests: Tajima's D Tajima , Fu and anova) taking the same three genetic diversity indices as the response variables, and the species, locality type and interaction between the two as independent effects. For this analysis, we used data from individual lineages within Tropheus sp. when more than one mitochondrial lineage was present in the same locality. Homogeneity of variances in haplotype diversity, nucleotide diversity and theta values across species was confirmed with Bartlett's test .To gauge the effect of inhabiting the different shoreline sections, we classified the localities sampled as either shallow or deep according to their position in relation to the lake's sub-basins  and perfBartlett  before pbeast v 1.5.3 . We implemented a strict molecular clock, and priors for population size were obtained using the Bayesian Skyline method  and plotted the estimated population size changes through time. To provide an approximate time frame for the demographic histories re-covered, we employed a substitution rate of 0.0325–0.057 per site per million of years  with 4 haplotypes present in more than 1 locality. Haplotype diversity within Tropheus sp. was higher, with 176 haplotypes recovered from 382 sequences analysed, but only 5 of these haplotypes were found in more than 1 locality. No haplotypes were found in more than 2  localities.Population differentiation within each species was generally high  with FstE. cyanostictus, highest values for haplotype diversity, nucleotide diversity and theta were all found in the southern, shallow localities  including all the specimens collected in that locality; and (ii) only those specimens belonging to the most abundant mtDNA lineage . While we present all results in For ariation  needs toTropheus sp. populations were again lowest at deep shorelines, while higher values were (on average) observed in the shallow localities at the southern end of the lake  within each locality. In some of the analyses performed , convergence was not attained after 100 million generations. In these cases, we simplified the nucleotide substitution model (using a single category of mutations and no invariable sites) and used 5 (instead of 10) groups for the Bayesian skyline, and ran the analyses again. In one case , even this simplified model did not reach convergence (low ESS for most parameters), and, we do not present these results. Analyses of the other two populations reached convergence with the simplified model, and results are included in Estimated demographic histories for each species and locality are shown in et al. et al. et al. et al. We compared patterns of genetic diversity and demographic dynamics of co-distributed cichlid fish species inhabiting both deep and shallow shorelines of Lake Tanganyika. Genetic differentiation between populations of each species was generally high, in accordance with previous studies, where strong geographical structuring has been described for all three species  and measures of genetic diversity within populations  and 5. Tistories . This reThe observed relationship between shoreline type and genetic diversity was, however, the opposite of our expectation: the genetic diversity estimates for populations inhabiting the deep shorelines were significantly lower than those for populations inhabiting the shallow shorelines at the southern end of the lake. This is surprising, given that populations from the deep areas are likely to be older, and to have had more constant population sizes, and as such should have accumulated and maintained higher levels of diversity at neutral genetic markers.et al. . Thus, higher habitat availability would likely result in more populations (isolated by distance) instead of higher effective population sizes of each population.An alternative explanation is that these populations have higher effective population sizes than those at deeper shoreline sections. This could be due to locations at shallower shorelines exhibiting a gentler slope, leading to wider bands of appropriate habitat in these locations. However, the actual slope varies in both areas: we find big rocks, boulders and cobble shores in various inclinations in both the deep and the shallow shorelines. Furthermore, the phylopatric nature of all three species analysed means that they form populations isolated by distance even over continuously rocky habitat  inhabiting different deep shorelines at the central sub-basin of Lake Tanganyika exhibit similarly reduced levels of genetic diversity, thus suggesting that the pattern we recovered is representative for populations inhabiting deep shorelines throughout the lake.A second possible explanation is that the deep localities covered in this study  and V. moorii . It is thus possible that other processes in addition to lineage sorting have reduced the variation of these populations even further. One might argue that relatively frequent selective sweeps in these areas could lead to strong reduction in haplotype diversity due to the selective advantage of the sweeping haplotype. Indeed, a similar explanation has been advanced to cope with the observation that, across a variety of taxa, species exhibiting larger effective population sizes do not exhibit comparably higher mtDNA genetic diversity (Bazin et al. et al. E. cyanostictus and V. moorii than for Tropheus sp. (E. cyanostictus and V. moorii are monogamous breeders, while Tropheus sp. are polygamous (Kohda et al. et al. It should be noted that the reduction in haplotype diversity observed in populations from deep shorelines is surprisingly large. For instance, in locality 9, only 4 haplotypes were found in heus sp. . This obet al. (et al. (et al. et al. Arnegard et al.  was the  (et al.  hypothes. et al. . Second,. et al. , as well. et al. . In view. et al. , exchang


For years, studies of founder populations and genetic isolates represented the mainstream of genetic mapping in the effort to target genetic defects causing Mendelian disorders. The genetic homogeneity of such populations as well as relatively homogeneous environmental exposures were also seen as primary advantages in studies of genetic susceptibility loci that underlie complex diseases. European colonization of the St-Lawrence Valley by a small number of settlers, mainly from France, resulted in a founder effect reflected by the appearance of a number of population-specific disease-causing mutations in Quebec. The purported genetic homogeneity of this population was recently challenged by genealogical and genetic analyses. We studied one of the contributing factors to genetic heterogeneity, early Native American admixture that was never investigated in this population before. Consistent admixture estimates, in the order of one per cent, were obtained from genome-wide autosomal data using the ADMIXTURE and HAPMIX software, as well as with the fastIBD software evaluating the degree of the identity-by-descent between Quebec individuals and Native American populations. These genomic results correlated well with the genealogical estimates. Correlations are imperfect most likely because of incomplete records of Native founders’ origin in genealogical data. Although the overall degree of admixture is modest, it contributed to the enrichment of the population diversity and to its demographic stratification. Because admixture greatly varies among regions of Quebec and among individuals, it could have significantly affected the homogeneity of the population, which is of importance in mapping studies, especially when rare genetic susceptibility variants are in play. A major goal of medical and population genetics is to understand phenotypic consequences of genetic variation Nouvelle-France, of European and mainly French origins, forming the majority of today’s province of Quebec, Canada, is known for a number of recessive diseases that are endemic, of increased frequency and/or due to a population specific mutation(s) th century Numerous founder events accompanied European colonization of the Americas, creating populations that remained isolated due to geographic barriers and/or distinctive cultural/religious/ethnic identities Nouvelle-France is documented in historical records In addition to a diverse contribution of European founders The aim of the present study was to obtain a more reliable estimate of the Native American ancestry in the Quebec genome using autosomal DNA diversity as well as genealogical data. This study builds on single nucleotide variations (SNVs) from 205 individuals representing different regional groups of the contemporary Quebec population , some ofrd generation) individuals from 10 groups from Quebec  includes individuals from Northern America , whereas the European reference sample (CEU+French) consisted of HapMap CEU (n = 108) and French (n = 28) from the Human Genome Diversity Panel (HGDP). Extended reference sample of Europeans contained in addition, HGDP Italians (n = 12) and Tuscans (n = 8), as well as HapMap Tuscans TSI (n = 88) .To infer local ancestry under a haplotype-based model, we used the HAPMIX software version 1.2 2<0.1 in sliding windows of size 50 shifting every 10 SNVs), yielding a subset of 46,344 SNVs.We estimated the global ancestry using the model-based approach implemented in the ADMIXTURE software version 1.22 ibscale = 4) that we merged using the scripts provided by the authors. We performed the analysis with the unmasked complete data and for each Native American individual separately, we discarded afterwards shared IBD segments located in masked genomic regions. We retained the remaining shared IBD segments of at least 1 cM. All IBD segments shared with Native Americans were finally pooled for each Quebec individual.We used fastIBD from the BEAGLE software version 3.3.2 3f statistic implemented in the ADMIXtools software rolloff analysis) were used to estimate the linkage disequilibrium (LD) decay due to admixture. ALDER decay curves obtained using only one reference population were fitted starting at 0.8 and 0.7 cM (determined by the software) for the Quebec and French+CEU sample respectively using the masked Native North Americans as reference. The rolloff decay curve for the Quebec sample was estimated with two reference populations, Native North Americans (unmasked) and Europeans, and was fitted starting at 0.5 cM.We calculated the The R statistical environment version 2.15.0 Patched Of the 8424 founders  identified in the 195 genealogies of the Quebec individuals, 39 were of documented Native American origin. The genetic contribution (GC), based on genealogical data, is the expected proportion of the genome transmitted by an ancestor to a given individual. The GC was calculated using the GENLIB package, a genealogical analysis tool developed at BALSAC for the S-PLUS environment and transferred to the R environment for internal use. The mean GC was obtained by summing the GC of all Native American founders to all Quebec individuals and dividing by the number of individuals.Using HAPMIX In this paper we also explore the use of Identity-by-Descent (IBD) estimation by fastIBD Importantly, estimates of Native American ancestry by the three methods that use genomic data are in very good agreement . DiscrepWhen compared to genealogical estimates of the expected genomic contribution of Native American founders , the besth century  Using the genealogical record, we can evaluate the time period of admixture. It extends from the beginning of the colony in the early 1600s to the first half of 19 century , or rougions ago , i.e. abions ago . The samions ago . This is records , especiaMoreover, it is plausible that part of the “missing” genealogical information involves individuals who were admixed prior to their first registration in Quebec civil records. For instance, in a previous study The advantages of using genetically isolated, founder populations in gene mapping have often been discussed in the context of studies on the genetic bases of Mendelian disorders, as well as on genetic susceptibility genes of complex diseases These results were obtained using the sample of 52 Native North American genomes described above. In order to test how the choice of the Native American or European reference individuals affected our results, we conducted the same analyses using different reference populations. We observed a small difference in the extent of admixture using different sets of reference genomes. These differences likely reflect geographic proximity and time depth of shared ancestry of the populations we could analyze  and S3.Our study also shows that the analysis of IBD sharing performed very well in the analysis of recent admixture, comparable or perhaps even better than HAPMIX. Therefore, IBD sharing can be used to assist population structure analysis in association studies. Others have also shown that the analysis of IBD sharing is a promising tool for reconstructing populations’ demographic history m meioses from an ancestor is expected to share 2m− of this ancestor’s genome, i.e. on average about 0.1%, or 3.3 cM, after 10 generations. However, the length  of a shared segment has a mean of 100cM/m, or about 10 cM after 10 generations, suggesting that some individuals carry fairly long shared fragments and others not at all, explaining the variance among individual genomes. One percent Native ancestry can be understood as if everybody shared a Native American ancestor 6–7 generations ago. Indeed, a recent study based on four Quebec regional populations indicates that between 53 and 78% of Quebecers have at least one Native American ancestor in their genealogy In conclusion, using dense genotypic data and deep-rooted genealogical data, we estimated the Native American ancestry in a population sample from Quebec, Canada. The Native American genetic contribution calculated using genealogical data was low. Unlike most studied admixed populations that have greater admixture proportions Figure S1HAPMIX results in the Quebec population groups using different reference populations. Boxplots of the percentage of Native American ancestry from 3 runs of the ADMIXTURE software performed with different reference populations listed in the titles of the individual plots. See (TIFF)Click here for additional data file.Figure S2ADMIXTURE results in the Quebec population groups using different reference populations. Boxplots of total length of IBD sharing between the Quebec individuals and different Native American reference populations from 3 runs of fastIBD. See (TIFF)Click here for additional data file.Figure S3IBD sharing between the Quebec population groups and different Native American populations. Boxplots of total length of IBD sharing between the Quebec individuals and different Native American reference populations from 3 runs of fastIBD. See (TIFF)Click here for additional data file.Figure S4Plot of the number (bars) and genealogical genetic contribution (dots) of the Native American (red) and non Native American (blue) founders by marriage year in the genealogies of the Quebec individuals.(TIFF)Click here for additional data file.Figure S5First 4 eigenvectors of the Principal Component Analysis of the genomic data. Note - Global ancestry was estimated by PCA on the genotypic data using the EIGENSOFT software version 3.0 (TIFF)Click here for additional data file.Table S1Genetic contribution and admixture indices among Quebec individuals.(DOCX)Click here for additional data file.Table S2Reference populations used in the analyses.(DOCX)Click here for additional data file.Table S3Genetic contribution and admixture indices in the Quebec subpopulations.(DOCX)Click here for additional data file.