SNP identification, linkage disequilibrium, and haplotype analysis for a 200-kb genomic region in a Korean population

Understanding patterns of linkage disequilibrium (LD) across genomes may facilitate association mapping studies to localize genetic variants influencing complex diseases, a recognition that led to the International Haplotype Mapping Project (HapMap). Divergent patterns of haplotype frequency and LD across global populations require that the HapMap database be supplemented with haplotype and LD data from additional populations. We conducted a pilot study of the LD and haplotype structure of a genomic region in a Korean population. A total of 165 SNPs were identified in a 200-kb region of 22q13.2 by direct sequencing. Unphased genotype data were generated for 76 SNPs in 90 unrelated Korean individuals. LD, haplotype diversity, and recombination rates were assessed in this region and compared with the HapMap database. The pattern of LD and haplotype frequencies of Korean samples showed a high degree of similarity with Japanese data. There was a strong correlation between high LD and low recombination frequency in this region. We found considerable similarities in local LD patterns between three Asian populations (Han Chinese, Japanese, and Korean) and the CEPH population. Haplotype frequencies were, however, significantly different between them. Our results should further the understanding of distinctive Korean genomic features and assist in designing appropriate association studies.     

Fine-scale map of encyclopedia of DNA elements regions in the Korean population

The International HapMap Project aims to generate detailed human genome variation maps by densely genotyping single-nucleotide polymorphisms (SNPs) in CEPH, Chinese, Japanese, and Yoruba samples. This will undoubtedly become an important facility for genetic studies of diseases and complex traits in the four populations. To address how the genetic information contained in such variation maps is transferable to other populations, the Korean government, industries, and academics have launched the Korean HapMap project to genotype high-density Encyclopedia of DNA Elements (ENCODE) regions in 90 Korean individuals. Here we show that the LD pattern, block structure, haplotype diversity, and recombination rate are highly concordant between Korean and the two HapMap Asian samples, particularly Japanese. The availability of information from both Chinese and Japanese samples helps to predict more accurately the possible performance of HapMap markers in Korean disease-gene studies. Tagging SNPs selected from the two HapMap Asian maps, especially the Japanese map, were shown to be very effective for Korean samples. These results demonstrate that the HapMap variation maps are robust in related populations and will serve as an important resource for the studies of the Korean population in particular.     

Linkage disequilibrium patterns and tagSNP transferability among European populations

The pattern of linkage disequilibrium (LD) is critical for association studies, in which disease-causing variants are identified by allelic association with adjacent markers. The aim of this study is to compare the LD patterns in several distinct European populations. We analyzed four genomic regions (in total, 749 kb) containing candidate genes for complex traits. Individuals were genotyped for markers that are evenly distributed at an average spacing of approximately 2-4 kb in eight population-based samples from ongoing epidemiological studies across Europe. The Centre d'Etude du Polymorphisme Humain (CEPH) trios of the HapMap project were included and were used as a reference population. In general, we observed a conservation of the LD patterns across European samples. Nevertheless, shifts in the positions of the boundaries of high-LD regions can be demonstrated between populations, when assessed by a novel procedure based on bootstrapping. Transferability of LD information among populations was also tested. In two of the analyzed gene regions, sets of tagging single-nucleotide polymorphisms (tagSNPs) selected from the HapMap CEPH trios performed surprisingly well in all local European samples. However, significant variation in the other two gene regions predicts a restricted applicability of CEPH-derived tagging markers. Simulations based on our data set show the extent to which further gain in tagSNP efficiency and transferability can be achieved by increased SNP density.     

Evaluation of the SNP tagging approach in an independent population sample—array-based SNP discovery in Sami

Significant efforts have been made to determine the correlation structure of common SNPs in the human genome. One method has been to identify the sets of tagSNPs that capture most of the genetic variation. Here, we evaluate the transferability of tagSNPs between populations using a population sample of Sami, the indigenous people of Scandinavia. Array-based SNP discovery in a 4.4 Mb region of 28 phased copies of chromosome 21 uncovered 5,132 segregating sites, 3,188 of which had a minimum minor allele frequency (mMAF) of 0.1. Due to the population structure and consequently high LD, the number of tagSNPs needed to capture all SNP variation in Sami is much lower than that for the HapMap populations. TagSNPs identified from the HapMap data perform only slightly better in the Sami than choosing tagSNPs at random from the same set of common SNPs. Surprisingly, tagSNPs defined from the HapMap data did not perform better than selecting the same number of SNPs at random from all SNPs discovered in Sami. Nearly half (46%) of the Sami SNPs with a mMAF of 0.1 are not present in the HapMap dataset. Among sites overlapping between Sami and HapMap populations, 18% are not tagged by the European American (CEU) HapMap tagSNPs, while 43% of the SNPs that are unique to Sami are not tagged by the CEU tagSNPs. These results point to serious limitations in the transferability of common tagSNPs to capture random sequence variation, even between closely related populations, such as CEU and Sami. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Combinatorial effects of four histone modifications in transcription and differentiation

Linkage disequilibrium (LD) has received much attention recently because of its value in localizing disease-causing genes. Due to the extensive LD between neighboring loci in the human genome, it is believed that a subset of the single nucleotide polymorphisms in a region (tagSNPs) can be selected to capture most of the remaining SNP variants. In this study, we examined LD patterns and HapMap tagSNP transferability in more than 300 individuals. A South Indian sample and an African Mbuti Pygmy population sample were included to evaluate the performance of HapMap tagSNPs in geographically distinct and genetically isolated populations. Our results show that HapMap tagSNPs selected with r(2) >= 0.8 can capture more than 85% of the SNPs in populations that are from the same continental group. Combined tagSNPs from HapMap CEU and CHB+JPT serve as the best reference for the Indian sample. The HapMap YRI are a sufficient reference for tagSNP selection in the Pygmy sample. In addition to our findings, we reviewed over 25 recent studies of tagSNP transferability and propose a general guideline for selecting tagSNPs from HapMap populations.     

Comparison of linkage disequilibrium patterns between the HapMap CEPH samples and a family-based cohort of Northern European descent

The International HapMap Consortium has determined the linkage disequilibrium (LD) patterns of four major human populations. The aim of our investigation was to compare the LD patterns of the HapMap CEPH (Centre d'Etude du Polymorphisme Humain) samples with a family-based cohort of similar ancestry to determine its usefulness as a reference population for disease association studies. We examined four genomic regions on chromosomes 7q, 12p, and 14q totaling 14.3 Mb, initially identified in our linkage study of obesity and the metabolic syndrome. Near identical patterns of LD were detected in both populations. Furthermore, tagSNPs selected based on the HapMap CEPH cohort data capture over 98% of the variants at an r2 > 0.8 in the disease cohort. This confirms the usefulness of the CEPH cohort of the HapMap as a reference sample for further investigations into the genomic variation of populations of Northern European descent.     

EvoSNP-DB: A database of genetic diversity in East Asian populations

Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/]. [BMB Reports 2013; 46(8): 416-421]     

Efficient selection of tagging single-nucleotide polymorphisms in multiple populations

Common genetic polymorphism may explain a portion of the heritable risk for common diseases, so considerable effort has been devoted to finding and typing common single-nucleotide polymorphisms (SNPs) in the human genome. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), suggesting that only a subset of all SNPs (known as tagging SNPs, or tagSNPs) need to be genotyped for disease association studies. Based on the genetic differences that exist among human populations, most tagSNP sets are defined in a single population and applied only in populations that are closely related. To improve the efficiency of multi-population analyses, we have developed an algorithm called MultiPop-TagSelect that finds a near-minimal union of population-specific tagSNP sets across an arbitrary number of populations. We present this approach as an extension of LD-select, a tagSNP selection method that uses a greedy algorithm to group SNPs into bins based on their pairwise association patterns, although the MultiPop-TagSelect algorithm could be used with any SNP tagging approach that allows choices between nearly equivalent SNPs. We evaluate the algorithm by considering tagSNP selection in candidate-gene resequencing data and lower density whole-chromosome data. Our analysis reveals that an exhaustive search is often intractable, while the developed algorithm can quickly and reliably find near-optimal solutions even for difficult tagSNP selection problems. Using populations of African, Asian, and European ancestry, we also show that an optimal multi-population set of tagSNPs can be substantially smaller (up to 44%) than a typical set obtained through independent or sequential selection.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

An evaluation of the performance of tag SNPs derived from HapMap in a Caucasian population

The Haplotype Map (HapMap) project recently generated genotype data for more than 1 million single-nucleotide polymorphisms (SNPs) in four population samples. The main application of the data is in the selection of tag single-nucleotide polymorphisms (tSNPs) to use in association studies. The usefulness of this selection process needs to be verified in populations outside those used for the HapMap project. In addition, it is not known how well the data represent the general population, as only 90–120 chromosomes were used for each population and since the genotyped SNPs were selected so as to have high frequencies. In this study, we analyzed more than 1,000 individuals from Estonia. The population of this northern European country has been influenced by many different waves of migrations from Europe and Russia. We genotyped 1,536 randomly selected SNPs from two 500-kbp ENCODE regions on Chromosome 2. We observed that the tSNPs selected from the CEPH (Centre d'Etude du Polymorphisme Humain) from Utah (CEU) HapMap samples (derived from US residents with northern and western European ancestry) captured most of the variation in the Estonia sample. (Between 90% and 95% of the SNPs with a minor allele frequency of more than 5% have an r² of at least 0.8 with one of the CEU tSNPs.) Using the reverse approach, tags selected from the Estonia sample could almost equally well describe the CEU sample. Finally, we observed that the sample size, the allelic frequency, and the SNP density in the dataset used to select the tags each have important effects on the tagging performance. Overall, our study supports the use of HapMap data in other Caucasian populations, but the SNP density and the bias towards high-frequency SNPs have to be taken into account when designing association studies.     

Population analysis of vitamin D receptor polymorphisms and the role of genetic ancestry in an admixed population

The vitamin D receptor (VDR) is an essential protein related to bone metabolism. Some VDR alleles are differentially distributed among ethnic populations and display variable patterns of linkage disequilibrium (LD). In this study, 200 unrelated Brazilians were genotyped using 21 VDR single nucleotide polymorphisms (SNPs) and 28 ancestry informative markers. The patterns of LD and haplotype distribution were compared among Brazilian and the HapMap populations of African (YRI), European (CEU) and Asian (JPT+CHB) origins. Conditional regression and haplotype-specific analysis were performed using estimates of individual genetic ancestry in Brazilians as a quantitative trait. Similar patterns of LD were observed in the 5' and 3' gene regions. However, the frequency distribution of haplotype blocks varied among populations. Conditional regression analysis identified haplotypes associated with European and Amerindian ancestry, but not with the proportion of African ancestry. Individual ancestry estimates were associated with VDR haplotypes. These findings reinforce the need to correct for population stratification when performing genetic association studies in admixed populations.     

中国汉族人群CYP4F3基因多态性的研究

目的:研究CYP4F3基因单核苷酸多态性(SNP)在中国汉族人群中的分布,为进一步研究该基因群体遗传学特征及与疾病易感性的相关性提供更为详实的数据。方法:对CYP4F3基因进行重测序,构建连锁不平衡模式,选择标签SNP在192例北京和424例广州汉族个体中进行基因分型。结果:CYP4F3基因重测序共检出30个SNP,连锁不平衡分析显示广州和北京地区人群的连锁不平衡模式不同,但选择的8个标签SNP的等位基因和基因型频率分布在2个人群中的差异无统计学意义。结论:中国北京地区汉族与广州地区汉族人群CYP4F3基因多态性无显著差异,但不同种族间存在差异。     

Designing Genome-Wide Association Studies: Sample Size, Power, Imputation, and the Choice of Genotyping Chip

Genome-wide association studies are revolutionizing the search for the genes underlying human complex diseases. The main decisions to be made at the design stage of these studies are the choice of the commercial genotyping chip to be used and the numbers of case and control samples to be genotyped. The most common method of comparing different chips is using a measure of coverage, but this fails to properly account for the effects of sample size, the genetic model of the disease, and linkage disequilibrium between SNPs. In this paper, we argue that the statistical power to detect a causative variant should be the major criterion in study design. Because of the complicated pattern of linkage disequilibrium (LD) in the human genome, power cannot be calculated analytically and must instead be assessed by simulation. We describe in detail a method of simulating case-control samples at a set of linked SNPs that replicates the patterns of LD in human populations, and we used it to assess power for a comprehensive set of available genotyping chips. Our results allow us to compare the performance of the chips to detect variants with different effect sizes and allele frequencies, look at how power changes with sample size in different populations or when using multi-marker tags and genotype imputation approaches, and how performance compares to a hypothetical chip that contains every SNP in HapMap. A main conclusion of this study is that marked differences in genome coverage may not translate into appreciable differences in power and that, when taking budgetary considerations into account, the most powerful design may not always correspond to the chip with the highest coverage. We also show that genotype imputation can be used to boost the power of many chips up to the level obtained from a hypothetical “complete” chip containing all the SNPs in HapMap. Our results have been encapsulated into an R software package that allows users to design future association studies and our methods provide a framework with which new chip sets can be evaluated.     

Use of autosomal loci for clustering individuals and populations of East Asian origin

We studied the genetic relationships among East Asian populations based on allele frequency differences to clarify the relative similarities of East Asian populations with a specific focus on the relationships among the Koreans, the Japanese, and the Chinese populations known to be genetically similar. The goal is to find markers appropriate for differentiating among the specific populations. In this study, no prior data existed for Koreans and the markers were selected to differentiate Chinese and Japanese. We typed, using AB TaqMan assays, single-nucleotide polymorphisms (SNPs) at 43 highly selected mostly independent diallelic sites, on 386 individuals from eight East Asian populations (Han Chinese from San Francisco, Han Chinese from Taiwan, Hakka, Koreans, Japanese, Ami, Atayal, and Cambodians) and one Siberian population (Yakut). We inferred group membership of individuals using a model-based clustering method implemented by the STRUCTURE program and population clustering by using computer programs DISTANCE, NEIGHBOR, LSSEARCH, and DRAWTREE, respectively, calculating genetic distances among populations, calculating neighbor-joining and least-squares trees, and drawing the calculated trees. On average 52% of individuals in the three Chinese groups were assigned into one cluster, and, respectively, 78 and 69% of Koreans and Japanese into a different cluster. Koreans differentiated from the Chinese groups and clustered with the Japanese in the principal component analysis (PCA) and in the best least-squares tree. The majority of Koreans were difficult to distinguish from the Japanese. This study shows that a relatively few highly selected markers can, within limits, differentiate between closely related populations.Electronic Supplementary Material Supplementary material is available for this article at     

Highly Punctuated Patterns of Population Structure on the X Chromosome and Implications for African Evolutionary History

It is well known that average levels of population structure are higher on the X chromosome compared to autosomes in humans. However, there have been surprisingly few analyses on the spatial distribution of population structure along the X chromosome. With publicly available data from the HapMap Project and Perlegen Sciences, we show a strikingly punctuated pattern of X chromosome population structure. Specifically, 87% of X-linked HapMap SNPs within the top 1% of F_ST values cluster into five distinct loci. The largest of these regions spans 5.4 Mb and contains 66% of the most highly differentiated HapMap SNPs on the X chromosome. We demonstrate that the extreme clustering of highly differentiated SNPs on the X chromosome is not an artifact of ascertainment bias, nor is it specific to the populations genotyped in the HapMap Project. Rather, additional analyses and resequencing data suggest that these five regions have been substrates of recent and strong adaptive evolution. Finally, we discuss the implications that patterns of X-linked population structure have on the evolutionary history of African populations.     

Haplotype diversity in 11 candidate genes across four populations

Analysis of haplotypes based on multiple single-nucleotide polymorphisms (SNP) is becoming common for both candidate gene and fine-mapping studies. Before embarking on studies of haplotypes from genetically distinct populations, however, it is important to consider variation both in linkage disequilibrium (LD) and in haplotype frequencies within and across populations, as both vary. Such diversity will influence the choice of "tagging" SNPs for candidate gene or whole-genome association studies because some markers will not be polymorphic in all samples and some haplotypes will be poorly represented or completely absent. Here we analyze 11 genes, originally chosen as candidate genes for oral clefts, where multiple markers were genotyped on individuals from four populations. Estimated haplotype frequencies, measures of pairwise LD, and genetic diversity were computed for 135 European-Americans, 57 Chinese-Singaporeans, 45 Malay-Singaporeans, and 46 Indian-Singaporeans. Patterns of pairwise LD were compared across these four populations and haplotype frequencies were used to assess genetic variation. Although these populations are fairly similar in allele frequencies and overall patterns of LD, both haplotype frequencies and genetic diversity varied significantly across populations. Such haplotype diversity has implications for designing studies of association involving samples from genetically distinct populations.     

Linkage disequilibrium and allele-frequency distributions for 114 single-nucleotide polymorphisms in five populations

Single-nucleotide polymorphisms (SNPs) may be extremely important for deciphering the impact of genetic variation on complex human diseases. The ultimate value of SNPs for linkage and association mapping studies depends in part on the distribution of SNP allele frequencies and intermarker linkage disequilibrium (LD) across populations. Limited information is available about these distributions on a genomewide scale, particularly for LD. Using 114 SNPs from 33 genes, we compared these distributions in five American populations (727 individuals) of African, European, Chinese, Hispanic, and Japanese descent. The allele frequencies were highly correlated across populations but differed by >20% for at least one pair of populations in 35% of SNPs. The correlation in LD was high for some pairs of populations but not for others (e.g., Chinese American or Japanese American vs. any other population). Regardless of population, average minor-allele frequencies were significantly higher for SNPs in noncoding regions (20%-25%) than for SNPs in coding regions (12%-16%). Interestingly, we found that intermarker LD may be strongest with pairs of SNPs in which both markers are nonconservative substitutions, compared to pairs of SNPs where at least one marker is a conservative substitution. These results suggest that population differences and marker location within the gene may be important factors in the selection of SNPs for use in the study of complex disease with linkage or association mapping methods.     

Perspectives on human genetic variation from the HapMap Project

The completion of the International HapMap Project marks the start of a new phase in human genetics. The aim of the project was to provide a resource that facilitates the design of efficient genome-wide association studies, through characterising patterns of genetic variation and linkage disequilibrium in a sample of 270 individuals across four geographical populations. In total, over one million SNPs have been typed across these genomes, providing an unprecedented view of human genetic diversity. In this review we focus on what the HapMap project has taught us about the structure of human genetic variation and the fundamental molecular and evolutionary processes that shape it.     

Implications of inter-population linkage disequilibrium patterns on the approach to a disease association study in the human MHC class III

There is presently much interest in utilizing patterns of linkage disequilibrium (LD) to further genetic association studies. This is particularly pertinent in the class III region of the human major histocompatibility complex (MHC), which has been extensively studied as a disease susceptibility locus in a number of ethnic groups. To date, however, few studies of LD in the MHC have considered non-Caucasian populations. With the advent of large-scale haplotyping of the human genome, the question of utilizing LD patterns across populations has come to the fore. We have previously used LD mapping to direct an MHC class III association study in a UK Caucasian population. As an extension of this, we sought to determine to what extent the pattern of LD observed in that study could be used to conduct a similar study in a West African Gambian population. We found that broad patterns of LD were similar in the two populations, resulting in similar candidate region delineations, but at a higher resolution, marker-specific patterns of LD and population-dependent allele frequencies confounded the choice of regional tagging SNPs. Our results have implications for the applicability of large-scale haplotype maps such as the HapMap to complex regions like the MHC.Electronic Supplementary Material Supplementary material is available for this article at .     

Type 2 diabetes risk alleles demonstrate extreme directional differentiation among human populations, compared to other diseases

Many disease-susceptible SNPs exhibit significant disparity in ancestral and derived allele frequencies across worldwide populations. While previous studies have examined population differentiation of alleles at specific SNPs, global ethnic patterns of ensembles of disease risk alleles across human diseases are unexamined. To examine these patterns, we manually curated ethnic disease association data from 5,065 papers on human genetic studies representing 1,495 diseases, recording the precise risk alleles and their measured population frequencies and estimated effect sizes. We systematically compared the population frequencies of cross-ethnic risk alleles for each disease across 1,397 individuals from 11 HapMap populations, 1,064 individuals from 53 HGDP populations, and 49 individuals with whole-genome sequences from 10 populations. Type 2 diabetes (T2D) demonstrated extreme directional differentiation of risk allele frequencies across human populations, compared with null distributions of European-frequency matched control genomic alleles and risk alleles for other diseases. Most T2D risk alleles share a consistent pattern of decreasing frequencies along human migration into East Asia. Furthermore, we show that these patterns contribute to disparities in predicted genetic risk across 1,397 HapMap individuals, T2D genetic risk being consistently higher for individuals in the African populations and lower in the Asian populations, irrespective of the ethnicity considered in the initial discovery of risk alleles. We observed a similar pattern in the distribution of T2D Genetic Risk Scores, which are associated with an increased risk of developing diabetes in the Diabetes Prevention Program cohort, for the same individuals. This disparity may be attributable to the promotion of energy storage and usage appropriate to environments and inconsistent energy intake. Our results indicate that the differential frequencies of T2D risk alleles may contribute to the observed disparity in T2D incidence rates across ethnic populations.     

ArchiLD: Hierarchical Visualization of Linkage Disequilibrium in Human Populations

Linkage disequilibrium (LD) is an essential metric for selecting single-nucleotide polymorphisms (SNPs) to use in genetic studies and identifying causal variants from significant tag SNPs. The explosion in the number of polymorphisms that can now be genotyped by commercial arrays makes the interpretation of triangular correlation plots, commonly used for visualizing LD, extremely difficult in particular when large genomics regions need to be considered or when SNPs in perfect LD are not adjacent but scattered across a genomic region. We developed ArchiLD, a user-friendly graphical application for the hierarchical visualization of LD in human populations. The software provides a powerful framework for analyzing LD patterns with a particular focus on blocks of SNPs in perfect linkage as defined by r². Thanks to its integration with the UCSC Genome Browser, LD plots can be easily overlapped with additional data on regulation, conservation and expression. ArchiLD is an intuitive solution for the visualization of LD across large or highly polymorphic genomic regions. Its ease of use and its integration with the UCSC Genome Browser annotation potential facilitates the interpretation of association results and enables a more informed selection of tag SNPs for genetic studies.