Genetic evidence supports linguistic affinity of Mlabri--a hunter-gatherer group in Thailand.

Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
BMC Genetics (Impact Factor: 2.81). 03/2010; 11:18. DOI: 10.1186/1471-2156-11-18
Source: PubMed

ABSTRACT The Mlabri are a group of nomadic hunter-gatherers inhabiting the rural highlands of Thailand. Little is known about the origins of the Mlabri and linguistic evidence suggests that the present-day Mlabri language most likely arose from Tin, a Khmuic language in the Austro-Asiatic language family. This study aims to examine whether the genetic affinity of the Mlabri is consistent with this linguistic relationship, and to further explore the origins of this enigmatic population.
We conducted a genome-wide analysis of genetic variation using more than fifty thousand single nucleotide polymorphisms (SNPs) typed in thirteen population samples from Thailand, including the Mlabri, Htin and neighboring populations of the Northern Highlands, speaking Austro-Asiatic, Tai-Kadai and Hmong-Mien languages. The Mlabri population showed higher LD and lower haplotype diversity when compared with its neighboring populations. Both model-free and Bayesian model-based clustering analyses indicated a close genetic relationship between the Mlabri and the Htin, a group speaking a Tin language.
Our results strongly suggested that the Mlabri share more recent common ancestry with the Htin. We thus provided, to our knowledge, the first genetic evidence that supports the linguistic affinity of Mlabri, and this association between linguistic and genetic classifications could reflect the same past population processes.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Swiss Fleckvieh was established in 1970 as a composite of Simmental (SI) and Red Holstein Friesian (RHF) cattle. Breed composition is currently reported based on pedigree information. Information on a large number of molecular markers potentially provides more accurate information. For the analysis, we used Illumina BovineSNP50 Genotyping Beadchip data for 90 pure SI, 100 pure RHF and 305 admixed bulls. The scope of the study was to compare the performance of hidden Markov models, as implemented in structure software, with methods conventionally used in genomic selection [BayesB, partial least squares regression (PLSR), least absolute shrinkage and selection operator (LASSO) variable selection)] for predicting breed composition. We checked the performance of algorithms for a set of 40 492 single nucleotide polymorphisms (SNPs), subsets of evenly distributed SNPs and subsets with different allele frequencies in the pure populations, using F(ST) as an indicator. Key results are correlations of admixture levels estimated with the various algorithms with admixture based on pedigree information. For the full set, PLSR, BayesB and structure performed in a very similar manner (correlations of 0.97), whereas the correlation of LASSO and pedigree admixture was lower (0.93). With decreasing number of SNPs, correlations decreased substantially only for 5% or 1% of all SNPs. With SNPs chosen according to F(ST) , results were similar to results obtained with the full set. Only when using 96 and 48 SNPs with the highest F(ST) , correlations dropped to 0.92 and 0.90 respectively. Reducing the number of pure animals in training sets to 50, 20 and 10 each did not cause a drop in the correlation with pedigree admixture.
    Animal Genetics 12/2012; 43(6):696-703. · 2.58 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A key aim of evolutionary biology - inferring the action of natural selection on wild species - can be achieved by comparing neutral genetic differentiation between populations (F(ST) ) with quantitative genetic variation (Q(ST) ). Each of the three possible outcomes of comparisons of Q(ST) and F(ST) (Q(ST) ( ) > F(ST) , Q(ST) ( ) = F(ST) , Q(ST) ( ) < F(ST) ) is associated with an inference (diversifying selection, genetic drift, uniform selection, respectively). However, published empirical and theoretical studies have focused on the Q(ST) ( ) > F(ST) outcome. We believe that this reflects the absence of a straightforward biological interpretation of the Q(ST) < F(ST) pattern. We here report recent evidence of this neglected evolutionary pattern, provide guidelines to its interpretation as either a canalization phenomenon or a consequence of uniform selection and discuss the significant importance this issue will have for the area of evolutionary biology.
    Molecular Ecology 10/2012; · 6.28 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: There is considerable ethno-linguistic and genetic variation among human populations in Asia, although tracing the origins of this diversity is complicated by migration events. Thailand is at the center of Mainland Southeast Asia (MSEA), a region within Asia that has not been extensively studied. Genetic substructure may exist in the Thai population, since waves of migration from southern China throughout its recent history may have contributed to substantial gene flow. Autosomal SNP data were collated for 438,503 markers from 992 Thai individuals. Using the available self-reported regional origin, four Thai subpopulations genetically distinct from each other and from other Asian populations were resolved by Neighbor-Joining analysis using a 41,569 marker subset. Using an independent Principal Components-based unsupervised clustering approach, four major MSEA subpopulations were resolved in which regional bias was apparent. A major ancestry component was common to these MSEA subpopulations and distinguishes them from other Asian subpopulations. On the other hand, these MSEA subpopulations were admixed with other ancestries, in particular one shared with Chinese. Subpopulation clustering using only Thai individuals and the complete marker set resolved four subpopulations, which are distributed differently across Thailand. A Sino-Thai subpopulation was concentrated in the Central region of Thailand, although this constituted a minority in an otherwise diverse region. Among the most highly differentiated markers which distinguish the Thai subpopulations, several map to regions known to affect phenotypic traits such as skin pigmentation and susceptibility to common diseases. The subpopulation patterns elucidated have important implications for evolutionary and medical genetics. The subpopulation structure within Thailand may reflect the contributions of different migrants throughout the history of MSEA. The information will also be important for genetic association studies to account for population-structure confounding effects.
    PLoS ONE 01/2013; 8(11):e79522. · 3.53 Impact Factor

Full-text (2 Sources)

Available from
May 29, 2014