mtDNA of Gelao from Southwest China

Forensic Sci Int Genet. 2010 May 20. [Epub ahead of print]

Mitochondrial DNA polymorphisms in Gelao ethnic group residing in Southwest China.

Liu C, Wang SY, Zhao M, Xu ZY, Hu YH, Chen F, Zhang RZ, Gao GF, Yu YS, Kong QP.

Abstract

Gelao ethnic group, an aboriginal population residing in southwest China, has undergone a long and complex evolutionary process. To investigate the genetic structure of this ancient ethnic group, mitochondrial DNA (mtDNA) polymorphisms of 102 Gelao individuals were collected and analyzed in this study. With the aid of the information extracted from control-region hypervariable segments (HVSs) I and II as well as some necessary coding-region segments, phylogenetic status of all mtDNAs under study were determined by means of classifying into various defined haplogroups. The southern-prevalent haplogroups B, R9, and M7 account for 45.1% of the gene pool, whereas northern-prevalent haplogroups A, D, G, N9, and M8 consist of 39.2%. Haplogroup distribution indicates that the Gelao bears signatures of southern populations and possesses some regional characters. In the PC map, Gelao clusters together with populations with Bai-Yue tribe origin as well as the local Han and the Miao. The results demonstrate the complexity of Gelao population and the data can well supplement the China mtDNA database.

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Geographical affinities of HapMap samples

PLoS ONE doi:10.1371/journal.pone.0004684

Geographical Affinities of the HapMap Samples

Miao He et al.

Abstract

Background

The HapMap samples were collected for medical-genetic studies, but are also widely used in population-genetic and evolutionary investigations. Yet the ascertainment of the samples differs from most population-genetic studies which collect individuals who live in the same local region as their ancestors. What effects could this non-standard ascertainment have on the interpretation of HapMap results?

Methodology/Principal Findings

We compared the HapMap samples with more conventionally-ascertained samples used in population- and forensic-genetic studies, including the HGDP-CEPH panel, making use of published genome-wide autosomal SNP data and Y-STR haplotypes, as well as producing new Y-STR data. We found that the HapMap samples were representative of their broad geographical regions of ancestry according to all tests applied. The YRI and JPT were indistinguishable from independent samples of Yoruba and Japanese in all ways investigated. However, both the CHB and the CEU were distinguishable from all other HGDP-CEPH populations with autosomal markers, and both showed Y-STR similarities to unusually large numbers of populations, perhaps reflecting their admixed origins.

Conclusions/Significance

The CHB and JPT are readily distinguished from one another with both autosomal and Y-chromosomal markers, and results obtained after combining them into a single sample should be interpreted with caution. The CEU are better described as being of Western European ancestry than of Northern European ancestry as often reported. Both the CHB and CEU show subtle but detectable signs of admixture. Thus the YRI and JPT samples are well-suited to standard population-genetic studies, but the CHB and CEU less so.

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Genetic structure in East Asia using 200K SNPs

The table of paired F_st values for East Asian populations is here. The PCA plots are seen on the left.

PLoS ONE 3(12): e3862. doi:10.1371/journal.pone.0003862

Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays

Chao Tian et al.

Abstract

Accounting for population genetic substructure is important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to different continental populations the understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's less than 0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. PCA showed substructure both between different East Asian groups and within the Han Chinese population. These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies.

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More ASHG 2008 abstracts

The previous batch is here.

Analysis of East Asia Genetic Substructure: Population Differentiation and PCA Clusters Correlate with Geographic Distribution

Accounting for genetic substructure within European populations has been important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to other continental populations an understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation(Fst) and Principal Components Analyses(PCA) are examined using >200K genotypes from multiple populations of East Asian ancestry(total 298 subjects). The population groups included those from the Human Genome Diversity Panel[Cambodian(CAMB), Yi, Daur, Mongolian(MGL), Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, and Xibo], HapMap(CHB and JPT), and East Asian or East Asian American subjects of Vietnamese(VIET), Korean(KOR), Filipino(FIL) and Chinese ancestry. Paired Fst(Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups(CHB/KOR, 0.0019; CHB/JPT, 00651; CHB/VIET, 0.0065) with larger separation with FIL(CHB/FIL, 0.014). Low levels of differentiation were also observed between DAI and VIET(0.0045) and between VIET and CAMB(0.0062). Similarly, small Fsts were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan. For example, the four For PCA, the first two PCs showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations.corner groups were JPT, FIL, CAMB and MGL with the CHB forming the center group, and KOR was between CHB and JPT. Other small ethnic groups were also in rough geographic correlation with their putative origins. These studies have also enabled the selection of a subset of East Asian substructure ancestry informative markers(EASTASAIMS) that may be useful for future genetic association studies in reducing type 1 errors and in identifying homogeneous groups.

Worldwide Population Structure using SNP Microarray Genotyping

We genotyped 348 individuals sampled from 24 populations world-wide using the Affymetrix 250k NspI microarray chip. For context, we added matching genotypes from 210 HapMap individuals for a total of 250,823 loci genotyped in 543 individuals from 28 populations. We included populations from India and Daghestan to provide detail between the genetic poles of Western Europe, East Asia, and sub-Sahara Africa. With so many markers, principal components analyses reveal genetic differentiation between almost all identified populations in our sample. Northern and southern European populations (FST = 0.004, p <0.01) are statistically distinguishable, as are upper and lower caste groups in India (FST = 0.005, p <0.01). All individuals are accurately classified into continental groups, and even between closely-related populations, genetic- and self-classifications conflict for only a minority of individuals (e.g. ~2% between upper and lower Indian castes; k-means clustering.) As expected, the HapMap CHB+JPT, CEU, and YRI samples are most similar to our east Asian, west European, and African samples, respectively. The HapMap CEU samples and our northern European ancestry samples were both collected from Utah. Although individual samples cannot be reliably classified into their collection of origin, the groups are statistically distinguishable despite their high similarity (FST = 0.0005, n.s.). Our Japanese group is also statistically distinguishable from the HapMap JPT group (FST = 0.006, p <0.01), and in this comparison, most samples can be correctly classified. With such large numbers of genotypes, significant differences can be found even between very similar population samplings. Our results provide guidelines for researchers in selecting suitable control populations for case-control studies.

Frequency distribution and selection in 4 pigmentation genes in Europe

Pigmentation is one of the more obvious forms of variation in humans, particularly in Europeans where one sees more within group variation in hair and eye pigmentation than in the rest of the world. We studied 4 genes (SLC24A5, SLC45A2, OCA2 and MC1R) that are believed to contribute to the pigment phenotypes in Europeans. SLC24A5 has a single functional variant that leads to lighter skin pigmentation. Data on 83 populations worldwide (including 55 from our lab) show the variant (at rs1426654) has almost reached fixation in Europe, Southwest Asia, and North Africa, has moderate to high frequencies (.2-.9) throughout Central Asia, and has frequencies of .1-.3 in East and South Africa. The variant is essentially absent elsewhere. SLC45A2 also has a single functional variant (at rs16891982) associated with light skin pigmentation in Europe. Data on 84 populations worldwide show the light skin allele is nearly fixed in Northern Europe but has lower frequencies in Southern Europe, the Middle East and Northern Africa. In Central Asia the frequency of the SLC45A2 variant declines more quickly than the SLC24A5 variant. It is absent in both East and South Africa. In OCA2 we typed 4 SNPs (rs4778138, rs4778241, rs7495174, rs12913832) with a haplotype associated with blue eyes in Europeans. This haplotype shows a Southeastern to Northwestern pattern in Europe with frequencies of .25 (.05 homozygous) in the Adygei to .85 (.75 homozygous) in the Danes. In MC1R we typed 5 SNPs (rs3212345, rs3212357, rs3212363, C_25958294_10, rs7191944) that cover the entire MC1R gene and found a predominantly European haplotype that ranges in frequency from .35 to .65 in Europe, reaching its highest levels in Southwest Asia and Northwestern Europe. Extended Haplotype Heterozygosity (EHH) and normalized Haplosimilarity (nHS) show evidence of selection at SLC24A5 in not only our European and Southwest Asian populations but also our East African populations. Neither SLC45A2 or OCA2 showed evidence of selection in either test. MC1R did not show evidence of selection for our European specific haplotype but we did see some evidence both upstream and downstream in our nHS test in Europe.

Using principal components analysis to identify candidate genes for natural selection.

Genetic markers that differentiate populations are excellent candidates for natural selection due to local adaptation, and may shed light into physiological pathways that underlie disorders with varying frequencies around the world. Principal Components Analysis (PCA) has emerged as a powerful tool for the characterization and analysis of the structure of genomewide datasets. In prior work, we described an algorithm that can be used to select small subsets of genetic markers (SNPs) that correlate well with population structure, as captured by PCA. Our method can be used to detect SNPs that differentiate individuals from different geographic regions, or even neighboring subpopulations. We set out to explore the nature and properties of the genes where population-differentiating SNPs reside, by analyzing the publicly available Human Genome Diversity Panel dataset (650,000 SNPs for 1,043 individuals, 51 populations). Applying our SNP selection algorithms, we chose small subsets of SNPs that almost perfectly reproduce worldwide population structure as identified by PCA. We determined SNP panels both for population differentiation within seven geographic regions, as well as around the globe. We then explored the hypothesis that the selected SNPs attained their current worldwide allele frequency patterns as a response to the pressure of natural selection. Comparing our lists to recently published reports, we found a significant overlap with other genomewide scans for selection, thus validating our hypothesis. For example, EDAR (involved in the development of hair follicles) harbors the most differentiating SNPs in our world-wide panels. SNPs located in genes that are involved in skin and eye pigmentation (OCA2, MYO5C, HERC1, HERC2) are also among the top population differentiating markers. In East Asia, SNPs residing at the ADH cluster appear among the most important SNPs for population structure, while, in Europe, the same is true for genes that are involved in immune response to pathogens (CR1, DUOX2, TLR, and HLA). Finally, a comprehensive gene ontology analysis is presented.

YAP in 25 ethnic groups from Yunnan China

YAP defines haplogroup DE of the human Y-chromosome phylogeny, which joins together the haplogroup E, found in Negroids and Caucasoids, with haplogroup D, found mainly among Mongoloids, including the archaic Ainu, but also non-Mongoloid populations such as the Andaman Islanders.

The YAP frequencies listed here are, in all probability mostly of haplogroup D.

Sci China C Life Sci. 2003 Apr;46(2):135-140.

The geographic polymorphisms of Y chromosome at YAP locus among 25 ethnic groups in Yunnan, China.

Shi H, Dong Y, Li W, Yang J, Li K, Zan R, Xiao C.

The genetic polymorphisms of Y chromosome at YAP locus in 25 ethnic groups (33 populations) of China were analyzed in a total of 1294 samples. The average YAP+ frequency of the 33 populations was 9.2%, coinciding with published data of Chinese populations. Primi has the highest YAP+ frequency (72.3%), which is also the highest YAP+ among all the eastern Asian populations studied. The YAP+ occurred in 17 populations studied including Tibetan (36.0%), Naxi (37.5% and 25.5%), Zhuang (21.3%), Jingpo (12.5%), Miao (11.8%), Dai (11.4%, 10.0%, 3.3% and 2.0%), Yi (8.0%), Bai of Yunnan (6.7% and 6.0%), Mongol of Inner Mongolia (4.3%), Tujia of Hunan (2.6%), Yao (2.2%) and Nu (1.8%). The other 15 populations are YAP-including Lahu (2 populations), Hani, Achang, Drung, Lisu, Sui, Bouyei, Va, Bulang, Deang, Man and Hui and Mongol of Yunnan and Bai of Hunan. The YAP+ frequencies varied among the different ethnic groups studied, and even different among the same ethnic group living in different geographic locations. Using the genetic information, combined with the knowledge of ethnology, history and archaeology, the origin and prehistoric migrations of the ethnic groups in China, especially in Yunnan Province were discussed.

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