In 1985, Sir Alec Jeffreys developed the variable-number tandem repeat method used to identify individuals and giving researchers the first DNA fingerprints. These initial methods were used in anthropological genetics, a field that uses a comparative approach to answer questions about human history, including the discernment of the origin of Native American populations and the discrimination of clan affiliation from individuals in Siberia. The technological and methodological advances since this time have led to the use of many more markers, including restriction fragment length polymorphisms, Y chromosomal and autosomal short tandem repeats, single nucleotide polymorphisms, and direct sequencing not only to identify individuals, but to examine frequencies and distributions of markers (or “prints”) of entire populations. In the field of anthropological genetics these markers have been used to reconstruct evolutionary history and answer questions concerning human origins and diaspora, migration, and the effects of admixture and adaptation to different environments, as well as susceptibility and resistance to disease. This review discusses the evolution of DNA markers since their application by Sir Alec Jeffreys and their applications in anthropological genetics. Methods and Theories of Anthropological Genetics[Current Developments in Anthropological Genetics[Anthropological Genetics: Theory, Methods and Applications[Investigative Genetics. In population studies, genetic markers have been defined as “discrete, segregating genetic traits which can be used to characterize populations by virtue of their presence, absence, or high frequency in some populations and low frequencies in others” [Anthropological genetics is a synthetic field that examines evolutionary theory of interest to anthropologists while applying genetic methodologies . This in Genetics. This in Genetics-5. The flications. The fielications. Anthroplications. Schanfilications. See the others” ; in a seIn 1985, Alec Jeffreys and his colleagues developed a method using VNTRs or minisatellites of DNA to identify specific individuals for forensic purposes and parenthood determination . These DP = 0.05). Siberian populations clustered with the Native American groups were statistically significantly different from European and African Americans [During the late 1980s and early 1990s, frequency distributions of VNTRs were used as genetic markers to discriminate between ethnically defined populations -15. In americans   and linear discriminant function analysis was used to classify unknown individuals to a specific clan. The Kizhi community contained three major clans, Irkit, Todosh, and Kipchak, and other smaller clans. Linear discriminant function correctly classified 72% of all unknowns entered into the analysis. The highest correct classification occurred when 80% of the research subjects were placed in the Todosh clan, followed by 75% correct classification of individuals assigned to the Irkit clan, and 60% into the Kipchak clan. Those Kizhi individuals who were not affiliated with the Irkit, Todosh, or Kipchak were assigned randomly to a fourth group. If all of the clan assignments were random in regards to the VNTR loci, individuals would have been correctly assigned 25% of the time, while the unassigned individuals were classified into that category 29% of the time. These data suggest that VNTR markers have detected genetic similarities within each clan that permit a high probability of correct assignment of each individual to a correct clan  reveal the number of migrations that have occurred from Siberia into the Americas?Technological advances have allowed for more efficient means of investigating the genetic makeup of individuals with the use of DNA fingerprints such as STRs. In anthropological genetics, these markers have been used as ancestry-informative markers to reconstruct the human diaspora and to interpret the evolutionary history of human populations to answer questions of population origins, migration, and admixture. STRs, also known as microsatellites, are sequences of 2 to 6 base pairs (bp) repeated in a region of DNA from 3 to 100 times. Variant alleles usually result from slipped strand mispairing during DNA replication. In this review, we focus on the anthropological genetic questions that have been investigated during the last decade using STRs. STR variation can be examined in a number of different ways to test hypotheses concerning anthropological genetics. The following examples demonstrate the usefulness of STRs in answering evolutionary questions, such as (1) Are the Basque inhabitants of Spain and France remnants of the Paleolithic populations of Europe prior to the expansion of agriculture and Indo-European languages from the Middle East, circa 10,000 years B.P.? Are they Iberian groups that have been geographically isolated from their neighbors or are they related to distant populations from North Africa or the Caucasus? (2) How much gene flow did the populations of the Aleutian Islands experience from Russian, English, and/or Scandinavian sources? (3) Can a single ubiquitous STR allele , which is ubiquitous in the Americas but present in only two indigenous Siberian populations, Koryaks and Chukchi, both groups located proximally to the former location of the land bridge, Beringia  consisting of SNPs for estimating individual bio-geographical ancestry and admixture. These are genetic loci with large frequency differences between ancestral populations allowing them to act as “prints” or marks of a specific population . They inBecause of high throughput sequencing and the characterization of entire genomes, Johnson et al. have been able to reconstruct the history of admixed populations using DNA recombination to parse out the more specific geographical sources of the parental populations . The shoAmong the projects underway to better understand genome wide diversity is the 1000 Genomes Project, which is currently sequencing 2,500 genomes from individuals from all over the world in an attempt to reveal the extent of the diversity contained in the human species and determine how this genetic diversity translates into specific phenotypes . This prThe last decade has also seen an emergence of technology that has allowed for investigation of ancient genomes beyond mtDNA, traditionally a focus in ancient molecular studies because of the abundance of mitochondria in skeletal remains. These advances have included the sequencing of entire genomes of ancient remains of Neandertals and a hominin group from Siberia, called Denisovans, that were identified by their unique genetic characteristics ,45. ThesIn anthropology, whole genome studies of ancient individuals have also been used to answer questions regarding the peopling of the Americas. A human hair tuft, excavated in 1986 at Qeqertasussuk, a Saqqaq archeological site from West Greenland, was rediscovered in a museum in Copenhagen. Because of the permafrost conditions, there was excellent preservation of both mitochondrial and genomic DNA. The whole mtDNA genome was first sequenced from this Paleo-Eskimo, dating back 4,000 to 5,000 years B.P. . The mtDRasmussen et al. sequenced the whole genome of the Paleo-Eskimo and recovered 353,151 high confidence SNPs .A1, Q1 NRY haplogroup, brown eyes, non-European light skin, increased risk of baldness, higher body mass index, dry cerumen, shovel-shaped incisors, and a metabolism that was adapted to a cold environment [TP53 on chromosome 17, suggested that Saqqaq man possessed a more active form of p53 by coding for an Arg variant which is related to the more effective regulation of metabolism in cold climates [Because of the identification of the vast array of SNPs in the Saqqaq genome, it was possible to identify the functional SNPs in this 4,000 year old Paleo-Eskimo. Rasmussen et al. utilized the observed SNPs to reconstruct the following phenotypes of Saqqaq man: blood group subtype ironment . These pironment . SimilarWith the rapid changes in technology and data analyses, DNA genetic markers will play a significant role in future anthropological genetics. Whole genome sequencing is going to become cheaper and faster. The main hurdle for scientists will be the analysis of immense data sets (millions of nucleotides) that are being generated by massive sequencing programs. Within anthropological genetics, these developments are going to mean improvements in the use of molecular data in forensics , genetic epidemiology, and population genetics. Greater emphasis can then be placed on unraveling the cultural and environmental factors that shape the expression of our genomes.Anthropological geneticists investigating disease associations and adaptation have long worked toward uncovering the genetic variation that leads to disease and disease susceptibility. These attempts have, over the past decade, generally been performed using genome wide association studies that have identified some common variants that can lead to, or provide protection from, pathology. However, many of these diseases and disorders may be caused by rare variants that do not give a strong enough signal for identification . The 10Future studies of admixed populations will be based on whole genomic sequencing, the effects of recombination, linkage disequilibrium and the use of panels of ancestry informative markers. In the past, the effects of natural selection on admixture estimates could only be examined using imprecise approaches such as the examination, locus by locus, of deviations from expectation under a specific gene flow model. Through the use of whole genomic sequencing, regions of the genome can be examined for the signature of selection in both modern and ancient populations. In addition, rare alleles found only in specific groups should allow for a more detailed picture of human history and better define the complicated ways in which humans interact with one another and the environment.In the 1980s, Sir Alec Jeffreys first pioneered DNA fingerprints as a means of identifying individuals. Since that time many more genetic markers and polymorphisms have been developed to identify unknown individuals of forensic interest. Now, an individual’s entire genome can be considered a DNA fingerprint, but its size, and the computational power necessary for analysis, makes its use in forensics inefficient and costly. The changing technology has resulted in the discovery of many more genetic markers  that are better suited for forensic and anthropological analyses, as well as cheaper and faster ways of achieving these analyses.The future application of genetic markers (DNA fingerprints) is wide open and the next decade of research will lead to a better understanding of the origins and evolution of our species. It is unclear how far back in time studies of ancient DNA will take us, but these new methodologies will provide anthropologists with a refined story of human history, unraveling the complexities of human migration, admixture, and the successful and unsuccessful ways in which hominin genomes were selected by their environment. We are in the initial stages of personalized medicine in which our familial genomic endowment will determine specific treatments. We envisage a future where genetic information, a fingerprint of an individual’s genome, will be readily available and utilized for the assessment of ancestry, health risks and the treatment of disease, and crimes will be solved by comparisons of DNA from individuals of interest in particular cases with huge DNA data bases. When Sir Alec Jeffreys first began his work using fingerprints to identify individuals for forensic purposes, it opened a door to research that has allowed a better understanding of who we are both as individuals and as a species.AIMs: Ancestry informative markers; NRY: Y-specific non-recombining region; SABOR: San Antonio center for biomarkers of risk of prostate cancer; SAFDS: San Antonio family diabetes study; SNPs: Single nucleotide polymorphisms; STRs: Short tandem repeats; VNTRs: Variable-number tandem repeats.The authors declare that they have no competing interests.MHC and KGB participated in the writing of the manuscript. Both authors read and approved the final manuscript.


For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease. For many infectious diseases, transmission is strongly influenced by pathogen, host, and vector migration across complex landscapes Genetic assignment methods can provide such measures; they are a set of powerful statistical approaches that, at their most basic, can be used to establish population membership of individuals. When applied to organisms distributed among spatially distinct, interconnected populations, the techniques can be used to derive quantitative estimates of movement across a network, and determine the degree to which landscape features aid or impede movement. Genetic assignment methods have, for the most part, been limited to applications in ecology and conservation biology. This is despite their utility for estimating the magnitude and direction of key movements in infectious disease systems, where they could reveal important environmental and ecological features that facilitate or limit the spread of disease with important implications for control.For example, estimates of pathogen transport can be used to design more efficient anthelmintic treatment campaigns for important macroparasites of humans Nm, the number of migrants exchanged between populations per generation, using gene flow estimators based on Wright's infinite island model While many free-living pathogens, vectors, and intermediate hosts are capable of moving several kilometers, their specific mobilities are rarely estimated or incorporated into efforts to control disease coalesce until the common ancestor is reached, and in this way, present-day samples can be used to infer the past, including past migration among mating populations. Coalescent-based estimates of migration rates, obtained by comparison of allele frequency distributions observed in population samples, assume that all potential source populations have been sampled and that populations have followed relatively simple demographic progressions (constant size or deterministic expansion) while experiencing constant migration Coalescent theory describes the statistical properties of gene trees under a standard demographic model (namely the Fisher-Wright model). Present day samples of a non-recombining gene can be seen as lying on a branch of a gene tree rooted at the most recent common ancestor of the sample. Moving backward in time from each branch, genes K populations, with K, the number of subpopulations, among the inferred parameters.ATs use multilocus genotypes to identify the source population of individuals that have migrated within the past several generations Bayesian models  provide a convenient means to deal with complex (and inherently stochastic) phenomena that determine the genetic properties of individuals and populations Recent infectious disease applications of ATs have estimated pathogen, vector, and host dispersal characteristics in order to explain patterns of transmission and better target control activities. Here, we review four such applications.Triatoma, using insecticides. The hematophagous triatomines carry Trypanosoma cruzi, the protozoan parasite that causes Chagas disease in much of Latin America. The insects are present in sylvatic and peridomestic populations, with transient and seasonal invasion of homes leading to blood meals and transmission T. dimidiata to assess dispersal of individuals, better understand domestic infestation, and inform vector control. Insects were sampled from domestic, peridomestic, and sylvatic populations, genotyped at eight microsatellite loci, and analyzed using F statistics and both Bayesian- and likelihood-based ATs T. dimidiata is capable of dispersal over large geographic distances in the Yucatán Peninsula (up to 280 km) as suggested by low population differentiation and weak genetic structure. In this case, ATs provided a clearer picture than conventional Fst, allowing for the identification of immigrants even among populations with low genetic differentiation and no detectable correlation between genetic and geographic distance (isolation by distance). ATs indicated that 10%–22% of the insects collected within homes were immigrants from the peridomestic and sylvatic areas. Dispersal was detected in the opposite direction as well, with several insects in peridomestic and sylvatic areas having originated from populations within homes. The ecological basis of genetic structure in this study provided dispersal information that supports pesticide application and refuge removal in peridomestic areas. This zone appears to serve as an important “transit area” between sylvatic and domestic populations, contributing to household reinfestation after control, and largely agreeing with the findings from a small study in Bolivia In the absence of a vaccine or effective theraputics, Chagas disease control is largely dependent on elimination of the vector, members of the genus Coccidioides soil fungi, found in arid zones of the southwestern United States and northwestern Mexico, can cause community-acquired pneumonia and severe disseminated disease (coccidioidomycosis) when inhaled by a vertebrate host Coccidioides infections in these settings is poorly understood. To improve molecular surveillance, identify sources of infection, and allow the early detection and management of outbreaks, Fisher et al. Coccidioides spp. clinical isolates to their populations of origin. The application of ATs to these organisms was complicated by their haploid, rather than diploid, genome, requiring the authors to modify existing AT methods.The Coccidioides immitis and Coccidioides posadasii were genotyped at nine microsatellite loci. Isolates were both clinical and environmental in origin, and spanned the worldwide distribution of Coccidioides spp. Sixteen clinical isolates of unknown origin were obtained from patients diagnosed in the nonendemic state of New York. Using a modified AT procedure, 12 of these isolates were assigned to source populations with high probability, most to a source that matched the recent travel history of the patient. Thus, source identification in this nonendemic area was able to detect common-source infections. In two cases, however, travel history did not match assignment, raising questions about whether genetic differentiation was driven by host travel or pathogen dispersal; either an incomplete travel history or exposure to an isolate that had dispersed a great distance could explain the mismatches More than 160 isolates from eight geographical populations of Yersinia pestis, the bacterium that causes plague, is readily passed between wildlife and humans via flea vectors. In the plains regions of North America, black-tailed prairie dogs (Cynomys ludovicianus) live in high-density, communal colonies that favor the spread of plague, making this species an important host for Y. pestis. Oropsylla hirsuta is a flea very commonly associated with C. ludovicianus, and is thought to contribute substantially to Y. pestis transmission Y. pestis. The dominant hypothesis in this transmission system, and many others, is that host movements determine vector movements, and thus concordance between host and vector population genetic characteristics would be expected. The study used ATs, among other genetic analyses, to test this hypothesis, sampling 112 prairie dogs from six colonies in north-central Montana and genotyping them at 14 microsatellite loci. At the same time, 84 fleas were collected directly from prairie dog burrows and genotyped at seven microsatellite loci. Genetic structure and variability were analyzed using multiple methods, including the estimation of recent migration rates of prairie dogs and fleas using the Bayesian techniuque described in detail in m≥0.05), and the scale of their genetic neighborhood was on the order of a typical colony size. In contrast, the vector was well mixed, showing considerable migration between colony pairs (22 of 30 intercolony migration rates showed m≥0.05) and limited colony-level population structure. Because fleas and prairie dog hosts sampled from the same locations show limited concordance in population genetics, it is likely that prairie dogs are not the primary means of O. hirsuta dispersal in these colonies. Thus, the authors concluded that other hosts should be considered when responding to plague outbreaks, as O. hirsuta occurs on a variety of host species that may be important in dispersing Y. pestis–infected fleas The authors found that the host and vector differed widely in genetic structure: prairie dog hosts exhibited low intercolony migration (eight of 30 intercolony migration rates showed Procyon lotor) is widely distributed throughout North and Central America, and is capable of occupying a broad range of habitats in close proximity to humans. P. lotor is also the most frequently reported rabid wildlife species, and is a particularly important carrier of the rabies virus in the mid-Atlantic and northeastern US. Because of the risk of transmission of rabies to humans, the US Department of Agriculture conducts routine oral rabies vaccination programs targeting P. lotor and several other important wildlife species. In a large and expensive annual program, recombinant virus vaccine is delivered to P. lotor populations in the eastern US in attractive baits. A key question in optimizing these oral rabies vaccine programs is how geographic features  can be used to better target delivery of baits along important P. lotor dispersal corridors, reducing their virus trafficing potential. In a study in southwestern Pennsylvania state, Root, Puskas,and colleagues P. lotor dispersal, and thus can be used to improve oral vaccination programs.The common raccoon  valleys. Thus, ridge and valley features may not be suitable for use in optimizing the geographic placement of oral vaccine baits, despite the finding in other settings that major rivers and mountains may constrain P. lotor dispersal Live raccoons were trapped from five study sites distributed along valleys separated by a high elevation ridge; the authors aimed to test the hypothesis that the ridge isolated the populations on either side. DNA from a total of 185 raccoons was genotyped at nine microsatellite loci, and Bayesian clustering Contemporary movements of hosts can contribute to increased frequency and intensity of malaria epidemics in some regions Among the epidemiological methods that can benefit from ATs are spatial models of infectious disease transmission, which incorporate knowledge of the location, movement rate, and travel direction of hosts, vectors, and pathogens to explain observed patterns of transmission and evaluate intervention options. ATs can provide a quantitative description of migration between populations in transmission models, particularly in the context of network models that explicitly represent the exchange of individuals between populations Coccidioides case, independent loci can be used to estimate the relatedness between isolates and, when combined with travel patterns of infected hosts, assignments can be used to improve surveillance in nonendemic areas, leading to the identification of common source cases that may have otherwise gone undiagnosed Challenging epidemiological questions can be addressed by ATs. The source of infection for recombining organisms  can be determined. As in the Another key epidemiologcal use for ATs is in assessing the landscape determinants of disease spread. ATs make it possible to formally test previously held beliefs about the role of specific landscape features in governing the mobility of vectors, hosts, and pathogens. Just as valleys and ridges were found not to govern the movement of racoon vectors of rabies Schistosoma japonicum, the parasite that causes schistosomiasis in East and Southeast Asia. This organism is subject to transport in the environment via multiple pathways Diffusive processes are ubiquitous in infectious disease transmission ATs represent just one analytical avenue in a sophisticated suite of powerful genetic analysis tools available for such epidemiological applications, including other methods for inferring demographic parameters and for identifying genes or genomic regions involved in human diseases Figure S1S and the matrix of multilocus genotypes of sampled specimens, X. Among the unobserved variables (parameters) are the quantities of interest in infectious disease systems, including the interpopulation migration rates in matrix m and the specific migrant ancestry of individuals in vector M.Probabilistic graphical model indicating the conditional dependencies (directed edges) in the Wilson and Rannala (PDF)Click here for additional data file.Table S1Data and parameters of the inference model implemented in Wilson and Rannala's (PDF)Click here for additional data file.Table S2Descriptions of different types of genetic markers and the corresponding advantages and disadvantages when analyzed using assignment tests.(PDF)Click here for additional data file.Text S1Bayesian assignment tests.(PDF)Click here for additional data file.Text S2Genetic markers.(PDF)Click here for additional data file.


In order to describe the mtDNA setup of Laos more thoroughly, the data were subjected to population genetic comparisons with 16 East Asian groups.Vast migrations and subsequent assimilation processes have shaped the genetic composition of Southeast Asia, an area of close contact between several major ethnic groups. To better characterize the genetic variation of this region, we analyzed the entire mtDNA control region of 214 unrelated donors from Laos according to highest forensic quality standards. To detail the phylogeny, we inspected selected SNPs from the mtDNA coding region. For The Laos sample exhibited ample mtDNA diversity, reflecting the huge number of ethnic groups listed. We found several new, so far undescribed mtDNA lineages in this dataset and surrounding populations. The Laos population was characteristic in terms of haplotype composition and genetic structure, however, genetic comparisons with other Southeast Asian populations revealed limited, but significant genetic differentiation. Notable differences in the maternal relationship to the major indigenous Southeast Asian ethnolinguistic groups were detected.http://www.empop.org upon publication and will be available as the first mtDNA reference data for this country.In this study, we portray the great mtDNA variety of Laos for the first time. Our findings will contribute to clarify the migration history of the region. They encourage setting up regional and subpopulation databases, especially for forensic applications. The Laotian sequences will be incorporated into the collaborative EMPOP mtDNA database  The country was severely affected by the Vietnam War. In 1975, the Lao People's Democratic Republic was established. It has a population of almost seven million [Laos is the only landlocked country of Mainland Southeast Asia. Under Siamese control since the 18 million -8. Laos  million . Laotian million . The num million . In 2000 million ,12. Gene220 blood samples were acquired from volunteers of both sexes from The Lao People's Democratic Republic. Total DNA was extracted from peripheral blood lymphocytes using automated standard protocols . All donWe generated full mtDNA control region (CR) sequence data of 220 samples by chain termination sequencing. All experiments were performed according to the EMPOP forensic standard procedures to ensure highest sequence quality and reliable base calling . ContiguWe performed partial coding region (codR) sequencing in order to refine the phylogeny of samples that could not be assigned to a haplogroup more specific than paragroups M*, N* or C*. For samples of paragroup M*, we examined up to four segments  comprising SNPs diagnostic for M haplogroups, haplogroups D, G, and subhaplogroups. Samples of paragroup C* were inspected for their haplogroup C4 and C7 status by sequencing nps 5820-6660. This fragment was also used to test for B4 subhaplogroups and D5b1, where relevant. To detect haplogroups of paragroup N*, we analyzed nps 4450-5860 and nps 6340-7770. Primer sequences and experimental conditions were applied as published before . To scruIn order to endorse a reference haplogroup nomenclature, we used the comprehensive mtDNA "phylotree", release 8 , for assA posteriori data quality control was performed using the NETWORK software provided on the EMPOP website  [release) ,20. Thisrelease) . The resIdentical haplotypes  were inspected for maternal relatedness by typing up to 17 autosomal STR loci using the AmpFℓSTR SGM Plus PCR Amplification Kit (Applied Biosystems) and the PowerPlex 16 System (Promega). Five samples were thereafter removed from the dataset, applying a cutoff likelihood ratio of 1000 . One samIn order to shed light on the genetic structure and population genetic history of Laos and Southeast Asia, the Laos sample was compared to surrounding populations. Both countrywide and ethnic subpopulation samples from recent literature were compiled ,17,23-26ST values using PASW Statistics 18 (SPSS Inc.).The random match probability for each population was calculated as sum of squared haplotype frequencies . We performed intra- and interpopulation comparisons: the number of mean pairwise differences within and between populations, molecular diversity indices, and an analysis of molecular variance (AMOVA) were calculated using Arlequin (version 3.5.1.2) . Also thThe 214 Laotian samples classified into 64 distinct haplogroups . 45% of Macrohaplogroup N  comprised 57% of the samples in 37 haplogroups. 26% of the samples were assigned to haplogroup B, almost equally to B4 and B5. 26 out of the 27 haplogroup B5 samples were found to be haplogroup B5a. 22% of the samples belonged to haplogroup F, of which 79% belonged to F1a and its subhaplogroups. Macrohaplogroup M  comprised 43% in 27 haplogroups. 32% of the samples belonged to haplogroup M, distributed among ten subhaplogroups. 25% of the M samples, however, remained M*. No maternal west Eurasian or African admixture was detected.Figure The power of discrimination by CR was calculated 99.26%, the random match probability 0.74%. The number of mean pairwise differences for full CR was 13.14 ± 5.94. This high number is due to the double origin of East Asian mtDNA lineages in both macrohaplogroup M and N.http://www.empop.org, 2nd release) yielded three hits for 16086Y, the latter two positions remained unobserved. The proportion of CR profiles revealing a heteroplasmic position was 3.7%, in agreement with observations in blood samples from other populations (1-9.5%) [Point heteroplasmies at a single CR position were observed in eight samples. Two of these (16093Y and 152Y) were the most common point heteroplasmic positions observed in a dataset of 5015 global samples . One pos(1-9.5%) .After CR sequencing, a number of Laos samples displayed new SNP motifs within haplogroups B and D that were found recurrent in other Central, East and Southeast Asian populations  ,24,29-31The partial codR sequencing had a great impact on the phylogenetic resolution of the dataset. It helped to confirm and exclude haplogroups without or with recurrent CR motifs. In addition, new codR SNP patterns were detected. The assays applied therefore constitute valuable time-, cost- and DNA-saving alternatives to whole mitochondrial genome sequencing for phylogenetic purposes.The paragroup M* codR sequencing assay was performed on 41 samples. 14 samples were confirmed to belong to a described M haplogroup, haplogroups D or G. New, recurrent SNP motifs with matching haplotypes from Thailand, Vietnam, Hong Kong and the Philippines ,23,24,32,3224,32 The recently described haplogroup M71 was diverse in the Laos sample. Several new sublineages (including the postulated "M71a1" ) could bhttp://www.mitowheel.org. Interestingly, two out of the 11 base substitutions caused amino acid substitutions , while nine were silent mutations. SNP variants persistent in the face of purifying selection are expected to be silent, adaptive or neutral  [We inspected the recurrent codR SNPs for their effect on amino acid level using the "MitoWheel" v1.2 ed here) . This fiThe Laos sample showed mtDNA diversity characteristic of Southeast Asian populations. The composition of haplogroups was in agreement with other populations from this region ,23-25,35In Laos, haplogroups B4a and R9 were less frequent than expected from the literature. This is partly explained by "technical" reasons: samples assigned to haplogroup "R9a" by HVS-I-motifs  actuallyLittle Northern contribution was detected. The presence of haplogroups described as Northern (East) Asian ,7,25,36,We compared the genetic composition of the current sample to that of populations from Thailand , VietnamThe numbers of intrapopulation MPD were highly similar. The highest intrapopulation diversity was found in the mixed Han sample 10.96) followed by Laos (10.93); the lowest in Vietnam (10.62). The intrapopulation RMP ranged between 0.004 (Han) and 0.011 (Thailand) indicating that the populations were highly differentiated. Laos was intermediate with a value of 0.008 (see Table 0.96 follAll populations shared haplotypes to varying extents. 47 haplotypes (28%) of the Laos sample were found in the other populations. Thailand was at the top (16% shared haplotypes) followed by Vietnam (12%) and Hong Kong (8%). The mixed Han sample only shared 3% of its haplotypes with Laos and its most frequent shared haplotype was only a singleton in the Laos sample . Variance among populations only accounts for 0.84%. The AMOVA results were statistically significant  to 7.The order of the populations in the MPD and RMP analyses was different when only HVS-I was analyzed (see previous section), which demonstrates the impact of larger reading frames. It can be supposed that the results of analyses with more information included are closer to truth.All populations shared haplotypes with the Laos sample. 46% of the Laos haplotypes were found in other populations. This high percentage is due to the short mtDNA segment and the high number of populations involved. The geographically closer populations, i.e. Thailand , Hong KoAMOVA again showed that the observed genetic variation was mainly attributable to differences within populations 98.09%). Variance among populations accounted for 1.91% . All intermediate FST values were yielded in comparisons including the Tibet [ST values for most other groups. The outlier position of the two Northern samples detected in several genetic comparisons supports the concept of isolation by geographic distance with subsequent differentiation.Mainly low, but also some intermediate Fhe Tibet  or the Nhe Tibet  sample, Most differences in genetic structure were highly significant. Only the mixed Han sample  and the ST values , a dispersal into the continent and onto the islands, and the subsequent differentiation of ethnic groups with common origin but diverging lineages  [in situ differentiation model  ,26,37,38th century AD and later moved to the central and Southern plains, thereby repelling the Austro-Asiatic population to the highlands or assimilating them. Today, the Daic "lowlander" living in the plains and along the rivers constitute the major proportion (60-65%) of the Laos population. They are dominant in language, culture, media and politics [The original genetic structure of MSEA with distinct areas inhabited by the main ethnic groups - the Daic in the coastal areas of the Southeast, the Austro-Asiatic in Western and central MSEA, the Sino-Tibetan (Tibeto-Burmans and Han) in the North and the Hmong-Mien in today's central China - has been blurred by massive migrations ,7. In thpolitics ,6,10,39.politics ,5,8.Traces of these migrations might be visible in the extant mtDNA composition of Laos. To shed more light on the population genetic history, it was meaningful to compare the cross-sectional Laos sample to those of the ethnic groups that together constitute the population of this country.ST values and localization in the MDS plot were the Austro-Asiatic [An interesting picture was revealed ; codR: coding region (of the mtDNA); d.f.: degrees of freedom; HVS: hypervariable segment; kYBP: thousand years before present; MDS: multidimensional scaling; MPD: mean pairwise differences; MSEA: Mainland Southeast Asia; mtDNA: mitochondrial DNA; np: nucleotide pair; RMP: random match probability; SNP: single nucleotide polymorphism; STR: short tandem repeat.MB designed and conducted experiments, retrieved data, performed calculations, interpreted results and conceived and wrote the manuscript. BZ conducted experiments, interpreted results and contributed to the manuscript. AR retrieved data, performed calculations, interpreted results and contributed to writing and editing the manuscript. AK helped in organizing DNA samples and contributed to the manuscript. DH, BH, SS, TS and JH helped in conceiving the study, organized DNA samples, performed DNA extractions and contributed to the manuscript. TK performed laboratory work and contributed to the manuscript. PS provided data and contributed to the manuscript. WP conceived and coordinated the entire project, supervised experiments, interpreted and validated results and contributed to writing and editing the manuscript. All authors approved the final version of the manuscript.Donor provenience list. The Laos province of birth is given for every donor.Click here for fileQuasi-median network portraits from 214 mtDNA control regions from Laos. Network torsos of HVS-I  and HVS-II . Condensed and filtered haplotypes are represented by the nodes, their haplogroup and number is indicated. Prehaplogroups are denoted as haplogroups. A plus sign indicates that haplotypes of several haplogroups have been condensed in that node. Transitions are marked in green, transversions in red.Click here for fileInterpretation of quasi-median networks from 214 mtDNA control regions from Laos. In this file, the networks in Additional file Click here for fileMtDNA polymorphisms of the 214 samples from Laos. The analyzed range, haplotype (as full list of differences to the revised Cambridge Reference Sequence [Sequence ) and hapSequence , releaseClick here for fileRefined phylogeny of haplogroup B4e. This modified CR phylogeny is indicated by five samples from Laos, Vietnam [ Vietnam , Hong Ko Vietnam  and Japa Vietnam . The tre Vietnam , releaseClick here for fileAMOVA results for five East Asian populations . Part A: Design and results of AMOVA. Part B: Population average pairwise differences. Part C: FST comparison among populations. References: this study, [s study, ,23,24Click here for fileShared haplotypes within the Laos population sample. Only one example haplotype is indicated per shared haplotype. Part A: comparison with four East Asian populations (nps 16024-16497 30-407). Part B: comparison with 16 East Asian populations (nps 16024-16383). References: this study, [s study, ,17,23-26Click here for fileAMOVA results for 17 East Asian populations . Part A: Design and results of AMOVA. Part B: Population average pairwise differences. Part C: FST comparison among populations. References: this study, [s study, ,17,23-26Click here for file


Geschlossener Hof, a hereditary norm which might have favored male dispersal, coincides with a significant intra-group diversity for mtDNA but not for Y chromosome, a genetic pattern which is opposite to those expected among patrilocal populations. Together with previous evidence regarding the possible effects of “local ethnicity” on the genetic structure of German speakers that have settled in the eastern Italian Alps, this finding suggests that taking socio-cultural factors into account together with geographical variables and linguistic diversity may help unveil some yet to be understood aspects of the genetic structure of European populations.Great European mountain ranges have acted as barriers to gene flow for resident populations since prehistory and have offered a place for the settlement of small, and sometimes culturally diverse, communities. Therefore, the human groups that have settled in these areas are worth exploring as an important potential source of diversity in the genetic structure of European populations. In this study, we present new high resolution data concerning Y chromosomal variation in three distinct Alpine ethno-linguistic groups, Italian, Ladin and German. Combining unpublished and literature data on Y chromosome and mitochondrial variation, we were able to detect different genetic patterns. In fact, within and among population diversity values observed vary across linguistic groups, with German and Italian speakers at the two extremes, and seem to reflect their different demographic histories. Using simulations we inferred that the joint effect of continued genetic isolation and reduced founding group size may explain the apportionment of genetic diversity observed in all groups. Extending the analysis to other continental populations, we observed that the genetic differentiation of Ladins and German speakers from Europeans is comparable or even greater to that observed for well known outliers like Sardinian and Basques. Finally, we found that in south Tyroleans, the social practice of  A considerable body of evidence shows that geographic distance is a good predictor of the genetic structure of European populations. A southeast-northwest cline, possibly associated with the Pleistocene settlement of the continent and the Neolithic demic diffusion from the Fertile Crescent ,2 but s, has beeThe Alps are one of the broadest mountain ranges of Europe, with a longitudinal extension of approximately 1,200 kilometers. They cover eight different countries and over 100 peaks of over 4000 m a.s.l. There is a substantial consensus among archeologists regarding the notion that many alpine areas had already been inhabited in the Paleolithic ,17, withAt present, Alpine populations can be considered as a mosaic of groups that are separated by physical and cultural boundaries, whose remarkable cultural diversity is clearly demonstrated by the presence of minorities that speak Franco-Provençals, Occitans, French, German, Ladin, Friulian and Sloven languages ,24. FromIn this study, we present new high resolution data on Y chromosomal variation in three distinct Alpine ethno-linguistic groups, Italian, Ladin and German. Combined with data on Y chromosome and mitochondrial variation taken from our previous research work and the literature, these results are used to answer four questions: (i) how is genetic diversity patterned in alpine ethno-linguistic groups?; (ii) what micro-evolutionary forces might have shaped their genetic structure?; (iii) how do the observed patterns compare with what has been noticed in other European groups, in particular with well known genetic outliers and other groups settled in great mountain ranges?; (iv) are there factors, other than geography and language, that should be taken into account when studying the genetic structure of European mountain populations?Our study is primarily based on unpublished Y chromosome data  from 610 unrelated individuals belonging to 15 populations from the Eastern Italian Alps ; Ladins ], five to the German-linguistic isolates . Ladins are thought to be related to pre-Indo-European speaking tribes who probably represent the most ancient settlers of the Alps . The DolThe dataset was integrated with an extensive search of literature data on unilinear transmitted markers  relativeComitato Etico per la Sperimentazione con l’Essere Umano” of the University of Trento (samples from Trentino), “South Tyrolean Ethics Committee”  and the institutional review board of the Istituto Italiano di Antropologia (samples from Veneto and Friuli). All participants provided written informed consent to participate in this study.Buccal swabs were collected in apparently healthy and unrelated donors selected according to the place of birth of the sampled individual and of their parents and grandparents. The procedure and informed consent were reviewed and approved by the “The DNA was extracted using the ‘Nucleic Acid Isolation System’ by the QuickGene-810 instrument following the standard protocols for blood and swab samples (FUJIFILM) or using a modified “salting-out” procedure. The 17 Y-chromosomal short tandem repeats (STRs) included in the AmpFlSTR Yfiler Amplification Kit  were typed in all samples . The population data obtained were submitted to the Anthro-Digit database (http://www.isita-org.com/Anthro-Digit/data.htm).Phylogenetic relationships between markers and nomenclature follow the International Society of Genetic Genealogy ,  and the number of different haplotypes (H). Multi-Dimensional Scaling of Fst genetic distances based on Y chromosome STRs  and a PWe used a coalescent based simulation approach in order to evaluate whether the observed values of within-group genetic diversity may be attributed solely to the size of the founding group  and German speakers. Their genetic characterization highlights a high level of diversity not only among single populations, but also within linguistic groups, a pattern which is likely to be due to a complex interplay of demographic histories and isolation determined by environmental and cultural factors. The extent of diversity among Alpine populations is shown by the plots based on STR and SNP data . The spaTo gain further insights into the genetic diversity occurring within each linguistic group, we went one step further by focusing on their genetic structure. The Italian speaking group was found to be the most genetically homogeneous. Within group variation  is lower than in other Alpine groups and geographically distant European populations, but higher than observed among Northern Italian populations . Furtherth century, and the consequent reduction in their settlement area and demographic size [The genetic differentiation among Ladin valleys noticed in the plots is supported by other analyses of STR haplotype distribution. Their intra-group variation  is similar to what has been found in geographically distant European populations , around two times higher than that found for geographically distant European populations. Moreover, the haplotype diversity values in these populations are the lowest of the the dataset, with the exception of Lessinia see . DiffereThe genetic differentiation between the two Cimbri populations of Luserna and Lessinia deserves further discussion. Both these communities derive from Bavarian populations that colonized a vast territory of the Eastern Italian Alps starting from 1053 AD  to 1216On the whole, our genetic characterization indicates three main genetic patterns. Italian speaking populations show slightly higher level of within-group diversity than observed among distant European populations. The strongest signals of departure from the European genetic background can be seen among German speaking populations, while the intra-group and intra-population diversity level of Ladins fall between the former two groups. These signals seem to reflect the different demographic history of the three groups and their genetic isolation due to the mountainous environment  and use of different languages from their neighbors (Ladins and German speakers). Nonetheless, the fact that the Y chromosome is a single locus transmitted by father to sons means that our inference needs further support from other genetic systems with a diverse mode of inheritance. Therefore, we thought it would be useful to repeat the analysis of intra and inter-population diversity with maternally transmitted mitochondrial DNA polymorphisms (hypervariable region 1) ,30,40. DAs discussed above, the intensity of the genetic signals observed in the Alpine linguistic groups seems to comply with what is to be expected for isolated population groups characterized by a different demographic profile. Therefore, a cause effect relationship between these two conditions and the different patterns of genetic diversity is worth taking into consideration. However, it did not escape our attention that such intensity seems to be inversely correlated with the supposed size of the founding groups, reflecting present census values see . We then2= 0.61, p=0.99). Coherently, the alpine populations are widely dispersed in the MDS plot of Y-STR genetic distances despite their geographic proximity   and fromGeschlossener Hof (“closed holding”), which entails an impartible transfer of the farm [Geschlossener Hof may lead to a pattern which is opposite to what would be expected for patrilocal groups. This is, in fact, the case of Tyrolean populations, who show only statistically significant intra-group variation for mtDNA polymorphisms . Therefore, the Geschlossener Hof could have shaped intra-group variation of paternal lineages in the opposite way to “local ethnicity” [South Tyroleans provide an exception to the high and statistically significant Y-chromosome intra-group diversity of Alpine populations. A possible explanation for this finding comes from their particular social structure. In fact, since at least the early fourteenth century South Tyroleans have mostly complied with an inheritance and succession system known as the farm ,53. Thisthe farm ,55,56,57In conclusion, the comparison between Y chromosomal and mitochondrial patterns of variation suggests that not only geographic factors and linguistic diversity, but also socially induced sex biased gene flow should be taken into account when studying the genetic structure of Alpine populations. We believe this is an important avenue for any future research work which aims to shed light on the yet to be explored complexity of the genetic structure of European populations.Figure S1Topology used for the simulations of evolutionary scenarios.(TIF)Click here for additional data file.Figure S2Multi-dimensional scaling plot of Fst genetic distances among Alpine populations based on mtDNA HVR-I sequences . Acronyms are given in (TIF)Click here for additional data file.Figure S3Haplotype diversity of Alpine populations: (a) mitochondrial DNA values based on HVR-I region; (b) Y chromosome values based on 15 STRs (acronyms as in (TIF)Click here for additional data file.Figure S4Analysis of molecular variance (AMOVA) within groups under study based on mtDNA sequences (hypervariable region 1) and 15 Y chromosome STRs.(TIF)Click here for additional data file.File S117-loci Y-STR haplotypes and haplogroups of the populations under study.(XLS)Click here for additional data file.Table S1Literature data (Y chromosome 5 STRs) on populations settled in mountain ranges.(DOC)Click here for additional data file.Table S2Literature data on mtDNA (sequences of the hypervariable region 1) on Alpine populations.(DOC)Click here for additional data file.Table S3Analysis of molecular variance (AMOVA) among linguistic groups .(DOC)Click here for additional data file.Table S4Literature data (Y chromosome 15 STRs) on European and Northern Italian open populations.(DOC)Click here for additional data file.Table S5Analysis of the molecular variance (AMOVA) within European and Northern Italy open populations groups based on 15 Y chromosome STRs (acronyms as in (DOC)Click here for additional data file.Table S6Y chromosome (15 STRs) genetic diversity in 15 Alpine populations.(DOC)Click here for additional data file.Table S7Haplogroup frequency distribution in populations under study (acronyms as in (DOC)Click here for additional data file.Table S8Mean census size and analysis of molecular variance (AMOVA) within Alpine linguistic groups under study based on 15 Y chromosome STRs (acronyms as in (DOC)Click here for additional data file.Table S9Analysis of molecular variance (AMOVA) within groups under study based on 5 Y chromosome STRs, including results of jacknife procedure (acronyms as in (DOC)Click here for additional data file.


Crassostrea gigas originated from the Pacific coast of Asia, but was introduced into several European countries in the early 1970s. Natural populations have now spread across the length of the western seaboard of Europe. To elucidate the demographic and selective processes at play during this rapid expansion, genome-scan analysis was performed on different populations. High diversities and low differentiation were observed overall, but significant genetic differentiation was found among newly established populations and between the newly established northern group and a nearly panmictic group composed of southern European populations and a population from Japan. Loss of genetic diversity was also seen in the north, likely caused by founder events during colonization. The few strongly supported outlier loci revealed a genetic structure uncorrelated with the north/south differentiation, but grouping two samples from the Danish fjords (northern group) and one from the Dutch Scheldt estuary (southern group) with the one from Japan. These findings might reflect the following: (i) parallel adaptation to similar environmental pressures (fjord-like environment) within each of the two groups or (ii) a footprint of a secondary introduction of an alternative genomic background maintained by multifarious isolation factors. Our results call for a closer examination of adaptive genetic structure in the area of origin. Crassostrea gigas, is endemic to the Pacific coast of Asia, but has been translocated and introduced into many countries worldwide, mainly for aquaculture purposes  natural dispersion, (ii) an increased ability of transplanted stocks to reproduce locally or (iii) a combination of both these processes. Hence, from the 1990s, the area of reproduction started to expand. Pacific oysters began to reproduce in Brittany (France) and now form large reefs in soft sediments and on rocks in this area , although high fecundities and the large size of oyster populations would allow an appreciable influx of new mutations in each generation. During invasion, local adaptation is likely to produce so-called soft sweeps  in manufacturer's buffer. Selective PCRs were performed on 5 μL diluted preselective amplification product (1:9 in 0 X TE) in 20 μL of 5 ng selective primers, 0.2 mm of each dNTP, 1.5 mm MgCl2 and 0.4 units GoTaq (Promega) in manufacturer's buffer. Conditions for preselective and selective PCRs were as given in Vos et al.  for both AFLP and microsatellite loci.After automatic analysis with GeneMapper® software, AFLP genotypes were filtered using AFLPScore  where each class is a population, was performed for all loci  with ade4 package implemented in R  were computed using genetix 4.03  Nei  and pairFST were then computed using AFLP-SURV 1.0 , with K = 1–10 and a burn-in of 50 000 iterations followed by 300 000 MCMC repetitions. We considered both raw probability values of lnP(X|K) and the ΔK estimate , Bayescan v2.0  software. Only 240 were used for further analyses . For AFLPs .Diversity estimators were plotted for the three kinds of markers . Both mior AFLPs C, heteroFST values were, respectively, 0.0129, 0.0160 and 0.0294, and all significantly different from zero . Correspondence analysis on populations for all loci . It is interesting to note that there is no genetic differentiation between the sample from Japan and any of those from the southern part of Europe. The second group encompasses the locations the furthest north in Europe, with populations located in Germany, Denmark and Sweden. In this group, global FST values were significantly different from zero ; the minimum value was found for microsatellites (0.0107) and the maximum for AFLPs (0.0243). The three populations from Denmark were significantly different from each other , global all loci  revealedch other .K = 2) as statistically most likely for both codominant and dominant markers . In northern and southern populations, five and eight loci were found to be outliers, respectively, by this method. With Bayescan, eight, three and five outliers were detected in the population groups ‘all’, ‘northern’ and ‘southern’, respectively. With DFDIST, seven, nine and eight outliers were found in all, northern and southern populations, respectively. For all populations, only four loci were identified as outliers with all methods , only one (123) for northern populations and two (146 and 167) for southern ones. No particular geographical gradients in allele frequency were observed , two for northern ones (ATPase H+ and glutathione S-transferase) and two for southern ones (glutaryl-CoA dehydrogenase–like protein and BQ427367).structure analysis.With the other methods, only ATPase H+ appeared to be a significant outlier for all populations. For this locus, allele frequency ranged from 0.6413 (Limfjord) to 0.9894 (Wadden Sea) with a mean of 0.902 . The difC. gigas into France, repeated introductions of hundreds of tons of adults from British Columbia and thousands of tons of spat from Japan were made over the 5 years following the first massive introduction of adults at the beginning of the 1970s . Likewise, marine species with long planktonic larval development (2–4 weeks in Crassostrea gigas according to water temperature and food availability) often exhibit low levels of population genetic structure related to high levels of gene flow , sometimes very distant ones. These practices increase gene flow and therefore reduce genetic structure. The lack of genetic differentiation between Japan and southern Europe and the absence of diversity loss in the latter suggest that the bottleneck related to introduction was not sufficient to affect the genetic diversity, either because the number of founders was sufficiently high or because there have been repeated introductions , spat was primarily imported from British and Irish hatcheries , 5% of 306 AFLP loci were consistently characterized as outliers between ecotypes on three shores  with all methods used. For AFLPs, four outliers (2%) were detected within the 240 AFLP loci scored, which could appear low compared with that given in the literature for other species. A review by Nosil et al.  on 18 reFST due to shared co-ancestry .Interestingly, among these most differentiated loci, we noticed a tendency for parallel genetic structure, grouping together some samples of the northern group in Denmark (ISE and LIM), a sample of the southern group in the Netherlands (OOS) and the Japanese sample (OSH). An uncorrelated structure between some outliers and the neutral fraction of the genome is clearly visible in the CA, in which the first axis reveals the genome-wide genetic structure between the southern and northern groups, while the second axis reveals the outlier-specific genetic structure that differentiates two samples of the southern group (OOS and OSH) and two samples of the northern group (ISE and LIM). The simplest hypothesis that could explain this pattern would be parallel adaptation to similar environmental pressures in these four populations, which is a hypothesis regularly put forward in the literature  and populations from areas of southern Europe where C. gigas is cultivated. However, northern populations  showed a decrease in diversity, coupled with a stronger genetic structure. This result agrees with the assertions that (i) the number of oysters that participated in the introduction of C. gigas in northern populations was far lower than the large quantities introduced from Japan in the 1970s and (ii) that the invasion wave due to the acclimatization of the species in Europe has yet not reached northern latitudes, but is presently localized somewhere on the North Sea coast of Germany. From a practical point of view, this study demonstrates the genetic impact of aquaculture on a newly introduced species and consequently shows that care must be taken when considering the stocks that are chosen at the beginning of a breeding programme. Indeed, as there are very few means to manage diseases in molluscs (Renault This genomic study on the invasiveness of the Pacific cupped oyster in Europe aimed to disentangle the demographic and adaptive factors as well as to consider the impact of aquaculture on the patterns of genetic structure observed. We used numerous markers for the analysis of a specific context of an economically important species during its invasive phase in Europe. We did not observe any loss of diversity during introduction, although some was seen during the northern spread of the species in Europe. There is little, if any, evidence of adaptation following the introduction of  Renault , breedin


The Mon-Khmer speaking peoples inhabited northern Thailand before the arrival of the Tai speaking people from southern China in the thirteenth century A.D. Historical and anthropological evidence suggests a close relationship between the Mon-Khmer groups and the present day majority northern Thai groups. In this study, mitochondrial and Y-chromosomal DNA polymorphisms in more than 800 volunteers from eight Mon-Khmer and ten Tai speaking populations were investigated to estimate the degree of genetic divergence between these major linguistic groups and their internal structure.A large fraction of genetic variation is observed within populations . The genetic divergence between populations is much higher in Mon-Khmer than in Tai speaking groups, especially at the paternally inherited markers. The two major linguistic groups are genetically distinct, but only for a marginal fraction (1 to 2%) of the total genetic variation. Genetic distances between populations correlate with their linguistic differences, whereas the geographic distance does not explain the genetic divergence pattern.The Mon-Khmer speaking populations in northern Thailand exhibited the genetic divergence among each other and also when compared to Tai speaking peoples. The different drift effects and the post-marital residence patterns between the two linguistic groups are the explanation for a small but significant fraction of the genetic variation pattern within and between them. Northern Thailand consists of many plains and mountains, usually stretching in a north-south direction. Most of this wide area is covered by forests and fertile land that was occupied by large numbers of people since prehistoric times .Today, the Tai speaking peoples represent the major linguistic group in Northern Thailand, but archaeological evidence reveals that this area was occupied by Mon-Khmer speaking groups such as Mlabri, H'tin, Lawa, and Mon since the prehistoric period . The firGenetic variation of the Y-chromosome and the mitochondrial genome has been used widely in population genetic studies. As they are transmitted uniparentally, through either paternal or maternal lineages, the population history can be reconstructed separately for each gender. These data can be used, therefore, to identify unequal contributions between males and females in migration rates, polygamy patterns and specific rules of post-marital residence -6. Here In total, 321 Y-STRs haplotypes, and 277 mtDNA haplotypes were observed among 416 males, and among 842 individuals, respectively. Statistics describing the levels of genetic variation within populations, and their mean in Mon-Khmer and Tai groups, are reported in Table st Fvalue among Mon-Khmer populations compared to the st Fvalue among Tai populations (Table Around 97% and 77% of haplotypes are private (found in a single population) at Y-chromosome and mtDNA, respectively. Haplotype sharing is therefore very limited, though higher for both markers among Tai than among Mon-Khmer populations (6 vs 4 for Y-chromosome and 27 vs 14 for mtDNA). The two major groups, Mon-Khmer and Tai, share only one Y-chromosome haplotype and 22 mtDNA haplotypes. The MDS plot of the paternal lineages  than in female  lineages.The AMOVA analysis was used to estimate the proportion of the genetic variation accounted for by groups defined on the basis of their linguistic affinities Table . The oveThe genetic divergence between populations, at both paternally and maternally inherited markers, is higher in the Mon-Khmer group  than the Tai group , and this difference is larger for Y-chromosomes (Table The proportion of genetic variation between the two linguistic groups is quite limited (around 1 to 2%). This fraction is statistically different from zero only for the much larger mtDNA data set. Thus it seems that, on average, Tai and Mon-Khmer populations are similar, or, to be more precise, only slightly more divergent than populations within each group. We note, however, that the interpretation of this hierarchical analysis is not straightforward, since the average level of population differentiation within the two linguistic groups is very different.Finally, Bayesian analysis of population structure (BAPS) was employed to ascertain how many different groups of populations are supported by Y chromosome and mtDNA data. Despite the limited power of this approach when only one locus is analyzed, results of both markers are consistent with the MDS explorative analysis Figure  and 3. IThe relative impact of geographic and linguistic distances on the genetic divergence between pairs of populations were clearly different. Geography seems to have little relation to mtDNA and Y-chromosome differentiation, whereas genetic distances are significantly correlated with linguistic affiliation in language families and dialects Table . The parThe main observation from our study is that the genetic divergence between populations, in the paternal lineages, is higher in the Mon-Khmer than in the Tai. This difference is probably a signature of historical and/or demographic processes combined with cultural differences in the post-marital residence patterns. A plausible explanation of our results is that Tai immigrants maintained genetic homogeneity whereas drift, during and after the Tai colonization, enhanced the genetic divergence among Mon-Khmer populations, since after the Tai invasion in the thirteenth century, the Mon-Khmer group was fragmented and some ethnic groups were exiled to rural areas .Paternal and maternal lineages provide contrasting results, as has been observed frequently in human population studies . TypicalOverall, only a small fraction of the observed genetic distances can be attributed to the Mon-Khmer/Tai distinction (between 1 to 2%). This result, which should be interpreted carefully, because population divergence patterns are very different within the Mon-Khmer and the Tai, might indicate that the original immigrants and residents in Northern Thailand were genetically similar, or that gene flow occurred after the Tai immigration. The first hypothesis, given the large cultural difference between Mon-Khmer and Tai people, seems unlikely. The second hypothesis, assuming that Tai immigrants incorporated Mon-Khmer residents , with thWhen linguistic differences between populations are considered in more detail, including distance measures for languages and dialects, a larger fraction of genetic variation (around 6 to 8%) can be explained by linguistic affiliation as shown in several ethnic groups -14, and Finally, we would like to mention the specific case of the Mon. Historical evidence indicates that the Mon had been the most developed Mon-Khmer civilization before the arrival of Tai people in the thirteenth century . This faMon-Khmer and Tai speaking populations show a different pattern of internal genetic structure. Most of Mon-Khmer populations are highly divergent, in the paternal lineages, among each other as well as when compared to Tai populations, and two of them, the H'tin , also exhibit the same pattern in the maternal lineages. On the other hand, the Tai populations are genetically similar for both markers. These results can be explained by different drift effects in the two groups, possibly enhanced in small and fragmented populations in the Mon-Khmer, and cultural differences in the post-marital residence patterns.We studied 842 volunteers  from 18 villages belonging to 9 ethnic groups from the northern part of Thailand . Results were then analyzed by GeneMapper software v. 3.0 and 3.7 .MtDNA control region of eight Mon-Khmer speaking villages was amplified using published primer pairs . The purHM634245-HM634590).The HVR-1 sequences of all samples were submitted to GenBank (accession numbers h) [π)[To describe genetic diversity within populations, the number of observed haplotypes and the haplotype diversity (h) , were cah) [π) was calcst Rfor Y-STRs [st Φfor mtDNA sequences. We consistently refer to these statistics in the text as st Fstatistics. Matrices of the st Fwere then represented in two dimensions by means of a multidimensional scaling (MDS) Pairwise genetic distance between populations were computed using r Y-STRs  and Φst The analysis of molecular variance (AMOVA)  was perfBayesian analysis of population structure using the software BAPS version 5.2 -31, an aGeographic-, genetic-, and linguistic-distance matrices were tested for possible correlation. Matrices were compared by means of nonparametric Mantel partial correlation tests . DiversiLinguistic distances between pairs of populations were defined as simple dissimilarity indices on the basis of the hierarchical classification of languages reported in Ethnologue . PopulatThe authors declare that they have no competing interests.WK and JK contributed equally in collecting samples, molecular genetic data generating, statistical analysis, interpretation of data, and drafting the manuscript. SF participated in performing the statistical analysis and helped to draft the manuscript. SN participated in interpretation of data and discussion. MS participated in molecular genetic data generating. GB involved in revising the manuscript critically for important intellectual content. DK conceived of the study and coordination, discussed, and revised the manuscript. All authors read and approved the final manuscript.


Fst supported that the inbred accessions represented seven sub-populations including processing, large-fruited fresh market, large-fruited vintage, cultivated cherry, landrace, wild cherry, and S. pimpinellifolium. Further divisions were found within both the contemporary processing and fresh market sub-populations. These sub-populations showed higher levels of genetic diversity relative to the vintage sub-population. The array provided a large number of polymorphic SNP markers across each sub-population, ranging from 3,159 in the vintage accessions to 6,234 in the cultivated cherry accessions. Visualization of minor allele frequency revealed regions of the genome that distinguished three representative sub-populations of cultivated tomato , particularly on chromosomes 2, 4, 5, 6, and 11. The PCA loadings and Fst outlier analysis between these three sub-populations identified a large number of candidate loci under positive selection on chromosomes 4, 5, and 11. The extent of linkage disequilibrium (LD) was examined within each chromosome for these sub-populations. LD decay varied between chromosomes and sub-populations, with large differences reflective of breeding history. For example, on chromosome 11, decay occurred over 0.8 cM for processing accessions and over 19.7 cM for fresh market accessions. The observed SNP variation and LD decay suggest that different patterns of genetic variation in cultivated tomato are due to introgression from wild species and selection for market specialization.The effects of selection on genome variation were investigated and visualized in tomato using a high-density single nucleotide polymorphism (SNP) array. 7,720 SNPs were genotyped on a collection of 426 tomato accessions (410 inbreds and 16 hybrids) and over 97% of the markers were polymorphic in the entire collection. Principal component analysis (PCA) and pairwise estimates of  Solanum lycopersicum L), breeding has involved the competing forces of narrowed genetic variation due to best by best crosses followed by selection Selection of favorable alleles through domestication and breeding has led to dramatic changes in seed and fruit attributes, plant habit, and productivity. For tomato (in silico mining of expressed sequence tag (EST) databases Novel sequencing technologies have uncovered sufficient variation to investigate the effect of human selection across an entire plant genome 2 interspecific populations: 3,503 markers in the S. lycopersicum LA0925 x S. pennellii LA0714 (EXPEN 2000) population and 4,491 markers in the Moneymaker x S. pimpinellifolium LA0121 (EXPIM 2012) population High-throughput SNP discovery has been accompanied by the development of array-based genotyping platforms that permit rapid scoring of several thousand markers in parallel S. pimpinellifolium were incorporated into processing breeding in order to develop compact plants amenable to “once over” (i.e. destructive) harvest The analysis of variation in tomato populations has often focused on differences between cultivated and wild species. In contrast, relatively little is known about which genes or genomic regions distinguish market classes within cultivated genepools. In the early 1900s, significant effort was placed on the evaluation of wild germplasm as a source of new resistance genes In order to investigate genetic variation on the tomato genome due to contemporary breeding, we subjected a collection of 426 accessions to high-throughput genotyping using the SolCAP SNP array. The tomato accessions represented different market classes of cultivated tomato and closely related wild species. Knowledge of the genetic and physical organization of the SNPs We used an array consisting of 7,720 SNPs distributed throughout the genome In order to assess the quality of SNP calls, we duplicated 34 accessions that were randomly selected using independent DNA preparations and genotyping facilities. The average proportion of consistent calls across all accessions was 98.7%. Cluster analysis was performed, and for all 34 accessions, the nearest neighbor was the duplicate accession. The proportion of consistent calls increased to 99.3% by excluding three accessions, OH981136 , Purple Clabash , and Principle Borghese . One of the duplicate samples for OH981136 showed higher rates for no call (8.8%) and heterozygote call (8.4%) relative to the other sample . The data quality between two samples of Purple Clabash was also different from each other . Heterozygote call rates were similar for the two samples. The duplicate samples of Principe Borghese differed by 5.9%, but showed similar rates for no call (0.8% vs. 1.0%) and heterozygote call (0.2% vs. 0.2%). These results suggest that overall reproducibility is high, and that differential calls may result from DNA quality that affects the percentage of “no call”, residual heterozygosity, and variation within accessions.The data were analyzed to determine the polymorphism rate based on the inbred accessions. A total of 7,500 SNPs (97.2%) were polymorphic and 61 SNPs (0.8%) were monomorphic . Among tS. pimpinellifolium accessions. The heterozygosity with all scorable markers  was 0.02 for processing, 0.01 for large-fruited fresh market, 0.01 for large-fruited vintage, and 0.04 for S. pimpinellifolium accessions. Using only markers that were polymorphic within each sub-population , the processing, fresh market, and vintage accessions showed heterozygosity levels of 0.02, 0.01, and 0.02, respectively. The heterozygosity for S. pimpinellifolium was 0.05.The proportion of heterozygous SNPs was assessed within cultivated tomato germplasm and a priori knowledge of germplasm pedigree, age, market class, and origin: 141 processing, 122 fresh market, 88 vintage, 43 wild cherry, and 16 S. pimpinellifolium. Principal component analysis (PCA) and linkage disequilibrium (LD) analysis supported separation of the fresh market sub-population into a group of 110 large-fruited accessions and 12 cherry accessions (cultivated cherry). Similarly, the vintage sub-population was divided into 61 large-fruited accessions, 15 cherry accessions which clustered with the cultivated cherry sub-population, and 12 landrace accessions , while PC2 separated processing, fresh market, and vintage germplasm  explained 22% and 16% of the total variance, respectively. PC1 separated the  P<0.01; . A subse P<0.01; . The sec P<0.01; . Althoug P<0.01;  and Hein P<0.01;  were gro P<0.01;  was clas P<0.01; .Fst was used to test the significance of genetic differentiation between sub-populations  . The S. pimpinellifolium accessions were separated from all other sub-populations with estimates of pairwise Fst ranging between 0.57–0.81  . The culP<0.005; . The FsFst. The processing accessions can be divided into two groups consisting of 82 and 52 accessions, respectively (Fst  = 0.27 P<0.005) and distinct from the other germplasm , expected heterozygosity (He), and polymorphic information content (PIC). Within cultivated germplasm, the highest estimates of A, He, and PIC were found in the cultivated cherry accessions  was identified in the cultivated cherry sub-population. There were 5,909 and 5,650 polymorphic markers in the wild cherry and ulations . For theulations . Fewer pulations . For exaA and He are adjusted for population size. To address the concern, we performed rarefaction analysis to estimate polymorphic marker accumulation curves S. pimpinellifolium, wild cherry, and cultivated cherry sub-populations were the most diverse groups based on the curves. Within the large-fruited cultivated sub-populations, fresh-market accessions were more diverse than vintage accessions. The accumulation curves for the processing and vintage accessions merged at n = 60, despite the fact that they were well separated between n = 10 to 25. This result suggests that differences in number of polymorphisms detected between these sub-populations may be population size dependent.The number of polymorphic markers in sub-populations increases with the size of the population. This fact led to concerns that our estimates of diversity might be skewed by population size differences despite the fact that S. pimpinellifolium accessions. These plots revealed different MAF patterns over the entire genome with chromosomes 2, 4, 5, 6, and 11 being particularly variable between the cultivated sub-populations  was then estimated within each sub-population . We grapulations . The proulations . Common ulations . Since tulations . The proulations .PCA loadings measure the correlation between PC and SNP, and provide an estimate of how much each SNP contributes to variance. We extracted loadings from the PCA of only cultivated germplasm  and dispFst outlier method based the expected distribution of Fst and HeWe also investigated loci that may be under positive selection between the three cultivated sub-populations using an Fst outlier detection. Candidate loci included genes that affect fruit size, shape, and color, disease resistance, and plant morphology  and vintage (which are polymorphic for FAS) germplasm , 3 (Psy1), 6 (B), 8 (gf), and 10 (u) y, Psy1 and gf are found in regions of the genome with SNPs that have moderately high absolute values associated with PCA loadings and somewhat variable MAF between sub-populations, these regions do not appear to be highly discriminatory (Fst outlier approach. The old gold crimson (cog) allele of the B gene encodes a mutation in the fruit specific lycopene beta-cyclase SP allele. In contrast, the region of chromosome 8 containing gf contains several SNPs detected as outliers based on Fst between processing and vintage germplasm  Ve1, Tm2∧2, Sw5, and Ph-3) Ph-2) Ph-2 and Ph-3 show MAF patterns that distinguish processing from fresh market and vintage sub-populations  SP5 and SP, respectively) that control plant habit and may be key selection points in differentiating vintage from contemporary sub-germplasm SP5 gene is in a region of the genome containing SNPs with high loadings for PC2, but does not appear to have been detected by Fst outlier analysis (jointless gene (j) on chromosome 11 j-2 gene on chromosome 12 Genes affecting plant morphology are distributed across several chromosomes. A region on chromosome 2 that appears to differentiate sub-populations contains the compound inflorescence gene  2r value of 0.2 or a value estimated using the 95th percentile method resulted in similar values for LD decay over chromosomes in the three sub-populations.The extent of LD across each chromosome was analyzed for the processing, large-fruited fresh market, and large-fruited vintage sub-populations. Pairwise 2r values estimated using the 95th percentile method ranged from 0.11 to 0.23. In the processing sub-population, the baseline 2r value based on the 95th percentile method was 0.23 and led to estimates of LD decay that ranged from 0.8 cM on chromosome 11 (both LOESS and NLR) to 7.7 cM on chromosome 8 (LOESS) and 35.2 cM on chromosome 6 (NLR) , while the greatest distance for LD decay was found on chromosome 1 (9.9 cM for LOESS) and chromosome 3 (11.8 cM for NLR)  , 6, 7. Lfor NLR) , 6, 7. EA high density array with 7,720 SNP markers was used to genotype the SolCAP germplasm panel consisting of 410 inbred accessions. This diverse germplasm enabled the development of a cluster file for accurate SNP calling with the GenomeStudio software . Over 98% of SNP markers generated consistent calls between duplicate samples across 34 accessions, with differences due mostly to DNA quality. Also, 7,375 SNP markers (96%) were polymorphic with <10% missing data in the entire germplasm. We found that the level of heterozygosity (proportion of heterozygotes) was low, but variable between market classes of germplasm.The SNPs provide excellent genome coverage, but their distribution is not reflective of chromosome size. For example, chromosome 1 is cytologically one of the largest, yet is underrepresented by SNPs relative to chromosome 11 which is cytologically small. It is possible that this distribution represents a distortion of the true measure of polymorphism, heterozygosity, or genetic diversity due to the sampling of markers. However, the germplasm presented in this study were well represented in the sequencing and SNP discovery pipeline Cultivated germplasm was divided into distinct sub-populations. The genetic differentiation between processing and fresh market germplasm reflects human selection for distinct ideotypes tailored to the needs of specific production systems. The contemporary processing and fresh-market germplasm were also distinct from vintage germplasm, which is consistent with previous findings S. pimpinellifolium. Although differences between processing and vintage sub-populations may be population size dependent, rarefaction analysis provides strong support for increased variation in fresh-market sub-population relative to vintage sub-population. Tomato has undergone genetic bottlenecks during domestication and through selection after the introduction of the crop into Europe Genetic diversity for each sub-population was measured using allelic richness, expected heterozygosity, and polymorphic information content. The descriptive statistics in the contemporary sub-populations exceeded levels found in the vintage sub-population, but were lower relative to the cherry sub-populations and Fst outliers based on a deviation from the expected distribution of Fst and He. Thus, these chromosomes appear to be under diversifying selection relative to other regions of the genome.The analysis of minor allele frequency (MAF) across the genome demonstrates genetic differentiation between sub-populations in specific chromosome regions. The different MAF patterns between three cultivated sub-populations  were particularly evident on chromosomes 2, 4, 5, 6, and 11. The same regions of the genome were highlighted by SNPs contributing high absolute values to PCA loadings and by SNPs detected as Fst outlier detection with the position of genes affecting fruit shape, size and color, disease resistance, and plant morphology , fruit color (e.g. gf and u), disease resistance (e.g.Cf-2 and I-2), and plant morphology (e.g. s and SP5).In order to investigate potential regions of the genome under selection, we superimposed MFA patterns, PCA loadings, and SNPs identified from rphology . Taken tdmt, Epi, glo, and si) have been mapped relative to morphological markers on this chromosome (http://tgrc.ucdavis.edu). Other areas under selection that are poorly explained by candidate genes include the chromosome 5 centromere which differentiates processing germplasm from the other sub-populations.Our results also suggest several chromosomes or regions of chromosomes with no obvious candidate genes to explain the observed differentiation. Chromosome 4 was identified as highly important for genetic differentiation between the sub-populations of cultivated germplasm. The role of this chromosome is less clear, though multiple loci affecting plant habit  and wide geographic distribution in the native region Common alleles at many loci in the 2r values relative to the other chromosomes. This variation may reflect structure within sub-populations due to selection. When the a priori vintage germplasm sub-population was based on age of variety, regardless of fruit size or geographical origin, the LD decay pattern for chromosome 4 displayed extensive LD and what appeared to be parallel patterns of decay. When the vintage accessions were separated into large fruited vintage and cultivated cherry/landrace groups, the dual pattern of LD decay disappeared and LD was reduced  germplasm panel, was assembled from the National Plant Germplasm System (NPGS), the C. M. Rick Tomato Genetics Resource Center (TGRC), and from public plant breeding programs. Accessions from eight universities in the United States and Canada were represented including Cornell University (USA), North Carolina State University (USA), Ohio State University (USA), Oregon State University (USA), Pennsylvania State University (USA), University of Florida (USA), University of California-Davis (USA), and Ridgetown College, University of Guelph (Canada). The germplasm panel represented only the red-fruited species cessions . ProcessThe SolCAP germplasm panel was genotyped using a tomato array with 7,720 SNPs as implemented in the Infinium assay . Details of the SolCAP SNP discovery pipeline are described previously For each accession of the SolCAP germplasm, genomic DNA was isolated from fresh young leaf tissue according to a modified CTAB method Fst, descriptive statistics, and Fst outlier detection, we used 4,393 polymorphic SNPs (excluding the 13 markers) with <10% missing data that were genetically mapped in the Moneymaker x LA0121 F2 population of 184 plants Fst. Polymorphism of these markers was determined based on the observation of at least one alternative allele in the 410 inbred accessions. For linkage disequilibrium (LD) analysis, the 4,393 SNP markers were filtered for a MAF of ≥10% within each sub-population.Physical positions of 7,666 SNPs were previously determined relative to the tomato genome sequence The genetic relationship between sub-populations was analyzed using PCA as implemented in R FstFst with a reduction of sample size (n = 40) for processing, fresh market, vintage sub-populations in order to estimate Fst without bias due to different population sizes. The analysis was iterated for three separate sets of accessions with n = 40 for each market class. The P-value for the pairwise Fst was obtained from 10,000 permutations of genotypes and a Bonferroni correction was applied. Genetic diversity within each sub-population was assessed based on allelic richness (A) He) A and He were estimated using the MSA software which corrects for sample size ip is the frequency of the ith allele As a measure of population differentiation, pairwise This analysis was used to estimate how the number of polymorphic markers increases relative to sample size The minor allele was determined based on the allele calls for 410 inbred accessions. Minor allele frequency (MAF) was then calculated across all chromosomes for each of sub-populations and sub-groups within the processing and fresh market sub-populations. This approach permitted the comparison of allele frequencies between sub-populations. MAF was graphed to visualize genetic variation based on physical map position across 12 chromosomes using the R package ggplot2 Fst- outlier detection method as implemented in the LOSITAN workbench Fst and expected heterozygosity (He). Five simulations for each pairwise comparison were run with 10,000 iterations. Simulations were conducted using the neutral mean, forced mean, and a mutation model with infinite alleles. Under these options, LOSITAN estimated a 95% confidence interval, and SNPs that fell outside of this range were identified as under positive selection (higher than expected Fst for an estimated He).In order to identify loci under positive selection between processing, fresh market, and vintage sub-populations, we used an 2r between markers within each chromosome was then calculated using TASSEL v 2.1 2r values were plotted against the genetic distance (cM) between markers. Curves of LD decay were fitted using locally weighted scatterplot smoothing (LOESS) 2r values between adjacent markers were calculated using the model of Hill and Weir 2r values: a fixed value of 0.2 th percentile of the distribution of the unlinked markers The extent of LD across each chromosome was measured using the SNP genotypes in three representative groups of cultivated tomatoes . Pairwise Figure S1Linkage disequilibrium (LD) decay on chromosome 4 for vintage, cultivated cherry, and landrace accessions. LD measures r2 against genetic map distance between pairs of SNP markers. Decay curves are represented by red (LOESS) and blue (non-linear regression). The baseline r2values were indicated by horizontal dashed line  and solid line .(TIF)Click here for additional data file.Figure S2Minor allele frequency (MAF) for further divisions within both processing and fresh market germplasm. The minor allele was determined relative to allele calls for all 410 inbred accessions based on 7,310 SNPs, and then MAF was estimated and graphed within each sub-group. Proc 1 and Proc 2 indicate sub-groups of processing germplasm, and FM 1 and FM2 indicate sub-groups of fresh market germplasm.(TIF)Click here for additional data file.Table S1The SolCAP germplasm panel used in this study.(XLSX)Click here for additional data file.Table S2SNP quality, polymorphism, map position and genotypes for the SolCAP germplasm.(XLSX)Click here for additional data file.Table S3Sub-groups within the processing and fresh market germplasm based on PC1 and PC2 of PCA.(XLSX)Click here for additional data file.Table S4Minor allele frequency of 7,310 SNP markers with physical map positions in the sub-populations and sub-groups of the SolCAP germplasm.(XLSX)Click here for additional data file.Table S5PCA loadings for PC1 and PC2 in the three representative sub-populations of cultivated germplasm .(XLSX)Click here for additional data file.Table S6Candidates for loci under positive selection between processing and fresh market sub-populations.(XLSX)Click here for additional data file.Table S7Candidates for loci under positive selection between processing and vintage sub-populations.(XLSX)Click here for additional data file.Table S8Candidates for loci under positive selection between fresh market and vintage sub-populations.(XLSX)Click here for additional data file.Table S9Fst outlier detection.28 tomato loci for integration with MAF patterns, PCA loadings, and (XLSX)Click here for additional data file.