The greater Himalayan region demarcates two of the most prominent linguistic phyla in Asia: Tibeto-Burman and Indo-European. Previous genetic surveys, mainly using Y-chromosome polymorphisms and/or mitochondrial DNA polymorphisms suggested a substantially reduced geneflow between populations belonging to these two phyla. These studies, however, have mainly focussed on populations residing far to the north and/or south of this mountain range, and have not been able to study geneflow patterns within the greater Himalayan region itself. We now report a detailed, linguistically informed, genetic survey of Tibeto-Burman and Indo-European speakers from the Himalayan countries Nepal and Bhutan based on autosomal microsatellite markers and compare these populations with surrounding regions. The genetic differentiation between populations within the Himalayas seems to be much higher than between populations in the neighbouring countries. We also observe a remarkable genetic differentiation between the Tibeto-Burman speaking populations on the one hand and Indo-European speaking populations on the other, suggesting that language and geography have played an equally large role in defining the genetic composition of present-day populations within the Himalayas.
Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.
Understanding genetic population substructure is important in evolutionary biology, behavioral ecology, medical genetics and forensic genetics, among others. Several algorithms have recently been developed for investigating genetic population substructure. However, detecting genetic population substructure can be cumbersome in humans since most of the genetic diversity present in that species exists among individuals from the same population rather than between populations. We developed a Genetic Algorithm for Genetic Ancestry (GAGA) to overcome current limitations in reliably detecting population substructure from genetic and genomic data in humans, which can also be applied to any other species. The method was validated by means of extensive demographic simulations. When applied to a real, human genome-wide SNP microarray dataset covering a reasonable proportion of the European continent, we identified previously undetected fine-scale genetic population substructure. Overall, our study thus not only introduces a new method for investigating genetic population substructure in humans and other species, but also highlights that fine population substructure can be detected among European humans.
Species identification can be interesting in a wide range of areas, for example, in forensic applications, food monitoring and in archeology. The vast majority of existing DNA typing methods developed for species determination, mainly focuses on a single species source. There are, however, many instances where all species from mixed sources need to be determined, even when the species in minority constitutes less than 1 % of the sample. The introduction of next generation sequencing opens new possibilities for such challenging samples. In this study we present a universal deep sequencing method using 454 GS Junior sequencing of a target on the mitochondrial gene 16S rRNA. The method was designed through phylogenetic analyses of DNA reference sequences from more than 300 mammal species. Experiments were performed on artificial species-species mixture samples in order to verify the method’s robustness and its ability to detect all species within a mixture. The method was also tested on samples from authentic forensic casework. The results showed to be promising, discriminating over 99.9 % of mammal species and the ability to detect multiple donors within a mixture and also to detect minor components as low as 1 % of a mixed sample.
To gain insights into evolutionary forces that have shaped the history of Bornean and Sumatran populations of orang-utans, we compare patterns of variation across more than 11 million single nucleotide polymorphisms found by previous mitochondrial and autosomal genome sequencing of 10 wild-caught orang-utans. Our analysis of the mitochondrial data yields a far more ancient split time between the two populations (∼3.4 million years ago) than estimates based on autosomal data (0.4 million years ago), suggesting a complex speciation process with moderate levels of primarily male migration. We find that the distribution of selection coefficients consistent with the observed frequency spectrum of autosomal non-synonymous polymorphisms in orang-utans is similar to the distribution in humans. Our analysis indicates that 35% of genes have evolved under detectable negative selection. Overall, our findings suggest that purifying natural selection, genetic drift, and a complex demographic history are the dominant drivers of genome evolution for the two orang-utan populations.
Despite being located at the crossroads of Asia, genetics of the Afghanistan populations have been largely overlooked. It is currently inhabited by five major ethnic populations: Pashtun, Tajik, Hazara, Uzbek and Turkmen. Here we present autosomal from a subset of our samples, mitochondrial and Y- chromosome data from over 500 Afghan samples among these 5 ethnic groups. This Afghan data was supplemented with the same Y-chromosome analyses of samples from Iran, Kyrgyzstan, Mongolia and updated Pakistani samples (HGDP-CEPH). The data presented here was integrated into existing knowledge of pan-Eurasian genetic diversity. The pattern of genetic variation, revealed by structure-like and Principal Component analyses and Analysis of Molecular Variance indicates that the people of Afghanistan are made up of a mosaic of components representing various geographic regions of Eurasian ancestry. The absence of a major Central Asian-specific component indicates that the Hindu Kush, like the gene pool of Central Asian populations in general, is a confluence of gene flows rather than a source of distinctly autochthonous populations that have arisen in situ: a conclusion that is reinforced by the phylogeography of both haploid loci.
The presence of a southeast to northwest gradient across Europe in human genetic diversity is a well-established observation and has recently been confirmed by genome-wide single nucleotide polymorphism (SNP) data. This pattern is traditionally explained by major prehistoric human migration events in Palaeolithic and Neolithic times. Here, we investigate whether (similar) spatial patterns in human genomic diversity also occur on a micro-geographic scale within Europe, such as in the Netherlands, and if so, whether these patterns could also be explained by more recent demographic events, such as those that occurred in Dutch population history.
We newly collected data on a total of 999 Dutch individuals sampled at 54 sites across the country at 443,816 autosomal SNPs using the Genome-Wide Human SNP Array 5.0 (Affymetrix). We studied the individual genetic relationships by means of classical multidimensional scaling (MDS) using different genetic distance matrices, spatial ancestry analysis (SPA), and ADMIXTURE software. We further performed dedicated analyses to search for spatial patterns in the genomic variation and conducted simulations (SPLATCHE2) to provide a historical interpretation of the observed spatial patterns.
We detected a subtle but clearly noticeable genomic population substructure in the Dutch population, allowing differentiation of a north-eastern, central-western, central-northern and a southern group. Furthermore, we observed a statistically significant southeast to northwest cline in the distribution of genomic diversity across the Netherlands, similar to earlier findings from across Europe. Simulation analyses indicate that this genomic gradient could similarly be caused by ancient as well as by the more recent events in Dutch history.
Considering the strong archaeological evidence for genetic discontinuity in the Netherlands, we interpret the observed clinal pattern of genomic diversity as being caused by recent rather than ancient events in Dutch population history. We therefore suggest that future human population genetic studies pay more attention to recent demographic history in interpreting genetic clines. Furthermore, our study demonstrates that genetic population substructure is detectable on a small geographic scale in Europe despite recent demographic events, a finding we consider potentially relevant for future epidemiological and forensic studies.
Population substructure; Genetic cline; Genome-wide diversity; SNP; Europe; Netherlands
An estimation of the post mortem interval (PMI) is frequently touted as the Holy Grail of forensic pathology. During the first hours after death, PMI estimation is dependent on the rate of physical observable modifications including algor, rigor and livor mortis. However, these assessment methods are still largely unreliable and inaccurate. Alternatively, RNA has been put forward as a valuable tool in forensic pathology, namely to identify body fluids, estimate the age of biological stains and to study the mechanism of death. Nevertheless, the attempts to find correlation between RNA degradation and PMI have been unsuccessful. The aim of this study was to characterize the RNA degradation in different post mortem tissues in order to develop a mathematical model that can be used as coadjuvant method for a more accurate PMI determination. For this purpose, we performed an eleven-hour kinetic analysis of total extracted RNA from murine's visceral and muscle tissues. The degradation profile of total RNA and the expression levels of several reference genes were analyzed by quantitative real-time PCR. A quantitative analysis of normalized transcript levels on the former tissues allowed the identification of four quadriceps muscle genes (Actb, Gapdh, Ppia and Srp72) that were found to significantly correlate with PMI. These results allowed us to develop a mathematical model with predictive value for estimation of the PMI (confidence interval of ±51 minutes at 95%) that can become an important complementary tool for traditional methods.
Moldova has a rich historical and cultural heritage, which may be reflected in the current genetic makeup of its population. To date, no comprehensive studies exist about the population genetic structure of modern Moldavians. To bridge this gap with respect to paternal lineages, we analyzed 37 binary and 17 multiallelic (STRs) polymorphisms on the non-recombining portion of the Y chromosome in 125 Moldavian males. In addition, 53 Ukrainians from eastern Moldova and 54 Romanians from the neighboring eastern Romania were typed using the same set of markers. In Moldavians, 19 Y chromosome haplogroups were identified, the most common being I-M423 (20.8%), R-M17* (17.6%), R-M458 (12.8%), E-v13 (8.8%), R-M269* and R-M412* (both 7.2%). In Romanians, 14 haplogroups were found including I-M423 (40.7%), R-M17* (16.7%), R-M405 (7.4%), E-v13 and R-M412* (both 5.6%). In Ukrainians, 13 haplogroups were identified including R-M17 (34.0%), I-M423 (20.8%), R-M269* (9.4%), N-M178, R-M458 and R-M73 (each 5.7%). Our results show that a significant majority of the Moldavian paternal gene pool belongs to eastern/central European and Balkan/eastern Mediterranean Y lineages. Phylogenetic and AMOVA analyses based on Y-STR loci also revealed that Moldavians are close to both eastern/central European and Balkan-Carpathian populations. The data correlate well with historical accounts and geographical location of the region and thus allow to hypothesize that extant Moldavian paternal genetic lineages arose from extensive recent admixture between genetically autochthonous populations of the Balkan-Carpathian zone and neighboring Slavic groups.
DNA analysis of ancient skeletal remains is invaluable in evolutionary biology for exploring the history of species, including humans. Contemporary human bones and teeth, however, are relevant in forensic DNA analyses that deal with the identification of perpetrators, missing persons, disaster victims or family relationships. They may also provide useful information towards unravelling controversies that surround famous historical individuals. Retrieving information about a deceased person’s externally visible characteristics can be informative in both types of DNA analyses. Recently, we demonstrated that human eye and hair colour can be reliably predicted from DNA using the HIrisPlex system. Here we test the feasibility of the novel HIrisPlex system at establishing eye and hair colour of deceased individuals from skeletal remains of various post-mortem time ranges and storage conditions.
Twenty-one teeth between 1 and approximately 800 years of age and 5 contemporary bones were subjected to DNA extraction using standard organic protocol followed by analysis using the HIrisPlex system.
Twenty-three out of 26 bone DNA extracts yielded the full 24 SNP HIrisPlex profile, therefore successfully allowing model-based eye and hair colour prediction. HIrisPlex analysis of a tooth from the Polish general Władysław Sikorski (1881 to 1943) revealed blue eye colour and blond hair colour, which was positively verified from reliable documentation. The partial profiles collected in the remaining three cases (two contemporary samples and a 14th century sample) were sufficient for eye colour prediction.
Overall, we demonstrate that the HIrisPlex system is suitable, sufficiently sensitive and robust to successfully predict eye and hair colour from ancient and contemporary skeletal remains. Our findings, therefore, highlight the HIrisPlex system as a promising tool in future routine forensic casework involving skeletal remains, including ancient DNA studies, for the prediction of eye and hair colour of deceased individuals.
Skeletal remains; Forensic DNA phenotyping; Eye colour; Hair colour; HIrisPlex; Ancient DNA; Human appearance; Władysław Sikorski
Many details surrounding the origins of the peoples of Oceania remain to be resolved, and as a step towards this we report seven new complete mitochondrial genomes from the Q2a haplogroup, from Papua New Guinea, Fiji and Kiribati. This brings the total to eleven Q2 genomes now available. The Q haplogroup (that includes Q2) is an old and diverse lineage in Near Oceania, and is reasonably common; within our sample set of 430, 97 are of the Q haplogroup. However, only 8 are Q2, and we report 7 here. The tree with all complete Q genomes is proven to be minimal. The dating estimate for the origin of Q2 (around 35 Kya) reinforces the understanding that humans have been in Near Oceania for tens of thousands of years; nevertheless the Polynesian maternal haplogroups remain distinctive. A major focus now, with regard to Polynesian ancestry, is to address the differences and timing of the ‘Melanesian’ contribution to the maternal and paternal lineages as people moved further and further into Remote Oceania. Input from other fields such as anthropology, history and linguistics is required for a better understanding and interpretation of the genetic data.
Previous studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10–30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed <20% of the male lineages. We found strong evidence for genetic structure, associated primarily with the current mode of subsistence. Coalescence analysis suggested that the social stratification was established 4–6 Kya and there was little admixture during the last 3 Kya, implying a minimal genetic impact of the Varna (caste) system from the historically-documented Brahmin migrations into the area. In contrast, the overall Y-chromosomal patterns, the time depth of population diversifications and the period of differentiation were best explained by the emergence of agricultural technology in South Asia. These results highlight the utility of detailed local genetic studies within India, without prior assumptions about the importance of Varna rank status for population grouping, to obtain new insights into the relative influences of past demographic events for the population structure of the whole of modern India.
The forensic genetics field is generating extensive population data on polymorphism of short tandem repeats (STR) markers in globally distributed samples. In this study we explored and quantified the informative power of these datasets to address issues related to human evolution and diversity, by using two online resources: an allele frequency dataset representing 141 populations summing up to almost 26 thousand individuals; a genotype dataset consisting of 42 populations and more than 11 thousand individuals. We show that the genetic relationships between populations based on forensic STRs are best explained by geography, as observed when analysing other worldwide datasets generated specifically to study human diversity. However, the global level of genetic differentiation between populations (as measured by a fixation index) is about half the value estimated with those other datasets, which contain a much higher number of markers but much less individuals. We suggest that the main factor explaining this difference is an ascertainment bias in forensics data resulting from the choice of markers for individual identification. We show that this choice results in average low variance of heterozygosity across world regions, and hence in low differentiation among populations. Thus, the forensic genetic markers currently produced for the purpose of individual assignment and identification allow the detection of the patterns of neutral genetic structure that characterize the human population but they do underestimate the levels of this genetic structure compared to the datasets of STRs (or other kinds of markers) generated specifically to study the diversity of human populations.
When a forensic DNA sample cannot be associated directly with a previously genotyped reference sample by standard short tandem repeat profiling, the investigation required for identifying perpetrators, victims, or missing persons can be both costly and time consuming. Here, we describe the outcome of a collaborative study using the Identitas Version 1 (v1) Forensic Chip, the first commercially available all-in-one tool dedicated to the concept of developing intelligence leads based on DNA. The chip allows parallel interrogation of 201,173 genome-wide autosomal, X-chromosomal, Y-chromosomal, and mitochondrial single nucleotide polymorphisms for inference of biogeographic ancestry, appearance, relatedness, and sex. The first assessment of the chip’s performance was carried out on 3,196 blinded DNA samples of varying quantities and qualities, covering a wide range of biogeographic origin and eye/hair coloration as well as variation in relatedness and sex. Overall, 95 % of the samples (N = 3,034) passed quality checks with an overall genotype call rate >90 % on variable numbers of available recorded trait information. Predictions of sex, direct match, and first to third degree relatedness were highly accurate. Chip-based predictions of biparental continental ancestry were on average ~94 % correct (further support provided by separately inferred patrilineal and matrilineal ancestry). Predictions of eye color were 85 % correct for brown and 70 % correct for blue eyes, and predictions of hair color were 72 % for brown, 63 % for blond, 58 % for black, and 48 % for red hair. From the 5 % of samples (N = 162) with <90 % call rate, 56 % yielded correct continental ancestry predictions while 7 % yielded sufficient genotypes to allow hair and eye color prediction. Our results demonstrate that the Identitas v1 Forensic Chip holds great promise for a wide range of applications including criminal investigations, missing person investigations, and for national security purposes.
Electronic supplementary material
The online version of this article (doi:10.1007/s00414-012-0788-1) contains supplementary material, which is available to authorized users.
DNA intelligence; Forensic DNA phenotyping; SNP; Prediction; Relatedness; Kinship; Ancestry; Eye color; Hair color; Sex
Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions previously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N=529) and the Netherlands (N=2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P=6 × 10−4), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P=0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity.
face; facial trait; genetic association; cleft-lip with or without cleft palate; prediction; normal trait variation
Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes—PRDM16, PAX3, TP63, C5orf50, and COL17A1—in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.
Monozygotic twins look more alike than dizygotic twins or other siblings, and siblings in turn look more alike than unrelated individuals, indicating that human facial morphology has a strong genetic component. We quantitatively assessed human facial shape phenotypes based on statistical shape analyses of facial landmarks obtained from three-dimensional magnetic resonance images of the head. These phenotypes turned out to be highly promising for studying the genetic basis of human facial variation in that they showed high heritability in our twin data. A subsequent genome-wide association study (GWAS) identified five candidate genes affecting facial shape in Europeans: PRDM16, PAX3, TP63, C5orf50, and COL17A1. In addition, our data suggest that genetic variants associated with NSCL/P also influence normal facial shape variation. Overall, this study provides novel and confirmatory links between common DNA variants and normal variation in human facial morphology. Our results also suggest that the high heritability of facial phenotypes seems to be explained by a large number of DNA variants with relatively small individual effect size, a phenomenon well known for other complex human traits, such as adult body height.
For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia.
Design and methods
Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling.
Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields.
Genetic epidemiology; Melanoma; Meta-analysis; Pooled-analysis; Skin cancer; Study design
The small alpine district of East Tyrol (Austria) has an exceptional demographic history. It was contemporaneously inhabited by members of the Romance, the Slavic and the Germanic language groups for centuries. Since the Late Middle Ages, however, the population of the principally agrarian-oriented area is solely Germanic speaking. Historic facts about East Tyrol's colonization are rare, but spatial density-distribution analysis based on the etymology of place-names has facilitated accurate spatial mapping of the various language groups' former settlement regions. To test for present-day Y chromosome population substructure, molecular genetic data were compared to the information attained by the linguistic analysis of pasture names. The linguistic data were used for subdividing East Tyrol into two regions of former Romance (A) and Slavic (B) settlement. Samples from 270 East Tyrolean men were genotyped for 17 Y-chromosomal microsatellites (Y-STRs) and 27 single nucleotide polymorphisms (Y-SNPs). Analysis of the probands' surnames revealed no evidence for spatial genetic structuring. Also, spatial autocorrelation analysis did not indicate significant correlation between genetic (Y-STR haplotypes) and geographic distance. Haplogroup R-M17 chromosomes, however, were absent in region A, but constituted one of the most frequent haplogroups in region B. The R-M343 (R1b) clade showed a marked and complementary frequency distribution pattern in these two regions. To further test East Tyrol's modern Y-chromosomal landscape for geographic patterning attributable to the early history of settlement in this alpine area, principal coordinates analysis was performed. The Y-STR haplotypes from region A clearly clustered with those of Romance reference populations and the samples from region B matched best with Germanic speaking reference populations. The combined use of onomastic and molecular genetic data revealed and mapped the marked structuring of the distribution of Y chromosomes in an alpine region that has been culturally homogeneous for centuries.
In a large variety of genetic studies, probabilistic inferences are made based on information available in population databases. The accuracy of the estimates based on population samples are highly dependent on the number of chromosomes being analyzed as well as the correct representation of the reference population. For frequency calculations the size of a database is especially critical for haploid markers, and for countries with complex admixture histories it is important to assess possible substructure effects that can influence the coverage of the database. Aiming to establish a representative Brazilian population database for haplotypes based on 23 Y chromosome STRs, more than 2,500 Y chromosomes belonging to Brazilian, European and African populations were analyzed. No matter the differences in the colonization history of the five geopolitical regions that currently exist in Brazil, for the Y chromosome haplotypes of the 23 studied Y-STRs, a lack of genetic heterogeneity was found, together with a predominance of European male lineages in all regions of the country. Therefore, if we do not consider the diverse Native American or Afro-descendent isolates, which are spread through the country, a single Y chromosome haplotype frequency database will adequately represent the urban populations in Brazil. In comparison to the most commonly studied group of 17 Y-STRs, the 23 markers included in this work allowed a high discrimination capacity between haplotypes from non-related individuals within a population and also increased the capacity to discriminate between paternal relatives. Nevertheless, the expected haplotype mutation rate is still not enough to distinguish the Y chromosome profiles of paternally related individuals. Indeed, even for rapidly mutating Y-STRs, a very large number of markers will be necessary to differentiate male lineages from paternal relatives.
The geographic origin and time of dispersal of Austroasiatic (AA) speakers, presently settled in south and southeast Asia, remains disputed. Two rival hypotheses, both assuming a demic component to the language dispersal, have been proposed. The first of these places the origin of Austroasiatic speakers in southeast Asia with a later dispersal to south Asia during the Neolithic, whereas the second hypothesis advocates pre-Neolithic origins and dispersal of this language family from south Asia. To test the two alternative models, this study combines the analysis of uniparentally inherited markers with 610,000 common single nucleotide polymorphism loci from the nuclear genome. Indian AA speakers have high frequencies of Y chromosome haplogroup O2a; our results show that this haplogroup has significantly higher diversity and coalescent time (17–28 thousand years ago) in southeast Asia, strongly supporting the first of the two hypotheses. Nevertheless, the results of principal component and “structure-like” analyses on autosomal loci also show that the population history of AA speakers in India is more complex, being characterized by two ancestral components—one represented in the pattern of Y chromosomal and EDAR results and the other by mitochondrial DNA diversity and genomic structure. We propose that AA speakers in India today are derived from dispersal from southeast Asia, followed by extensive sex-specific admixture with local Indian populations.
Austroasiatic; mtDNA; Y chromosome; autosomes; admixture
We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically distinct North-American sites. The AIMs-only and genome-wide first principal components (PC1) both corresponded to the previously described North or Northwest-Southeast axis of European variation. We found that the genome-wide PCA captured this primary dimension of variation more precisely and identified additional axes of genome-wide variation of relevance to epithelial ovarian cancer. Associations evident between the genome-wide PCs and study site corroborate North American immigration history and suggest that undiscovered dimensions of variation lie within Northern Europe. The structure captured by the genome-wide PCA was also found within control individuals and did not reflect the case-control variation present in the data. The genome-wide PCA highlighted three regions of local LD, corresponding to the lactase (LCT) gene on chromosome 2, the human leukocyte antigen system (HLA) on chromosome 6 and to a common inversion polymorphism on chromosome 8. These features did not compromise the efficacy of PCs from this analysis for ancestry control. This study concludes that although AIMs panels are a cost-effective way of capturing population structure, genome-wide data should preferably be used when available.
The Cham people are the major Austronesian speakers of Mainland Southeast Asia (MSEA) and the reconstruction of the Cham population history can provide insights into their diffusion. In this study, we analyzed non-recombining region of the Y chromosome markers of 177 unrelated males from four populations in MSEA, including 59 Cham, 76 Kinh, 25 Lao, and 17 Thai individuals. Incorporating published data from mitochondrial DNA (mtDNA), our results indicated that, in general, the Chams are an indigenous Southeast Asian population. The origin of the Cham people involves the genetic admixture of the Austronesian immigrants from Island Southeast Asia (ISEA) with the local populations in MSEA. Discordance between the overall patterns of Y chromosome and mtDNA in the Chams is evidenced by the presence of some Y chromosome lineages that prevail in South Asians. Our results suggest that male-mediated dispersals via the spread of religions and business trade might play an important role in shaping the patrilineal gene pool of the Cham people.