Transcriptome sequencing from diverse human populations reveals differentiated regulatory architecture.

Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.

Positive selection in the chromosome 16 VKORC1 genomic region has contributed to the variability of anticoagulant response in humans.

VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2) is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK). This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8), and PRSS8) with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect.

Worldwide human relationships inferred from genome-wide patterns of variation.

Human genetic diversity is shaped by both demographic and biological factors and has fundamental implications for understanding the genetic basis of diseases. We studied 938 unrelated individuals from 51 populations of the Human Genome Diversity Panel at 650,000 common single-nucleotide polymorphism loci. Individual ancestry and population substructure were detectable with very high resolution. The relationship between haplotype heterozygosity and geography was consistent with the hypothesis of a serial founder effect with a single origin in sub-Saharan Africa. In addition, we observed a pattern of ancestral allele frequency distributions that reflects variation in population dynamics among geographic regions. This data set allows the most comprehensive characterization to date of human genetic variation.

Genotype, haplotype and copy-number variation in worldwide human populations.

Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected--including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas--the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.

Haplotype analysis of the HSD17B1 gene and risk of breast cancer: a comprehensive approach to multicenter analyses of prospective cohort studies.

The 17beta-hydroxysteroid dehydrogenase 1 gene (HSD17B1) encodes 17HSD1, which catalyzes the final step of estradiol biosynthesis. Despite the important role of HSD17B1 in hormone metabolism, few epidemiologic studies of HSD17B1 and breast cancer have been conducted. This study includes 5,370 breast cancer cases and 7,480 matched controls from five large cohorts in the Breast and Prostate Cancer Cohort Consortium. We characterized variation in HSD17B1 by resequencing and dense genotyping a multiethnic sample and identified haplotype-tagging single nucleotide polymorphisms (htSNP) that capture common variation within a 33.3-kb region around HSD17B1. Four htSNPs, including the previously studied SNP rs605059 (S312G), were genotyped to tag five common haplotypes in all cases and controls. Conditional logistic regression was used to estimate odds ratios (OR) for disease. We found no evidence of association between common HSD17B1 haplotypes or htSNPs and overall risk of breast cancer. The OR for each haplotype relative to the most common haplotype ranged from 0.98 to 1.07 (omnibus test for association: X2 = 3.77, P = 0.58, 5 degrees of freedom). When cases were subdivided by estrogen receptor (ER) status, two common haplotypes were associated with ER-negative tumors (test for trend, Ps = 0.0009 and 0.0076; n = 353 cases). HSD17B1 variants that are common in Caucasians are not associated with overall risk of breast cancer; however, there was an association among the subset of ER-negative tumors. Although the probability that these ER-negative findings are false-positive results is high, these findings were consistent across each cohort examined and warrant further study.

The heritage of pathogen pressures and ancient demography in the human innate-immunity CD209/CD209L region.

The innate immunity system constitutes the first line of host defense against pathogens. Two closely related innate immunity genes, CD209 and CD209L, are particularly interesting because they directly recognize a plethora of pathogens, including bacteria, viruses, and parasites. Both genes, which result from an ancient duplication, possess a neck region, made up of seven repeats of 23 amino acids each, known to play a major role in the pathogen-binding properties of these proteins. To explore the extent to which pathogens have exerted selective pressures on these innate immunity genes, we resequenced them in a group of samples from sub-Saharan Africa, Europe, and East Asia. Moreover, variation in the number of repeats of the neck region was defined in the entire Human Genome Diversity Panel for both genes. Our results, which are based on diversity levels, neutrality tests, population genetic distances, and neck-region length variation, provide genetic evidence that CD209 has been under a strong selective constraint that prevents accumulation of any amino acid changes, whereas CD209L variability has most likely been shaped by the action of balancing selection in non-African populations. In addition, our data point to the neck region as the functional target of such selective pressures: CD209 presents a constant size in the neck region populationwide, whereas CD209L presents an excess of length variation, particularly in non-African populations. An additional interesting observation came from the coalescent-based CD209 gene tree, whose binary topology and time depth (approximately 2.8 million years ago) are compatible with an ancestral population structure in Africa. Altogether, our study has revealed that even a short segment of the human genome can uncover an extraordinarily complex evolutionary history, including different pathogen pressures on host genes as well as traces of admixture among archaic hominid populations.

A 3.9-centimorgan-resolution human single-nucleotide polymorphism linkage map and screening set.

Recent advances in technologies for high-throughout single-nucleotide polymorphism (SNP)-based genotyping have improved efficiency and cost so that it is now becoming reasonable to consider the use of SNPs for genomewide linkage analysis. However, a suitable screening set of SNPs and a corresponding linkage map have yet to be described. The SNP maps described here fill this void and provide a resource for fast genome scanning for disease genes. We have evaluated 6,297 SNPs in a diversity panel composed of European Americans, African Americans, and Asians. The markers were assessed for assay robustness, suitable allele frequencies, and informativeness of multi-SNP clusters. Individuals from 56 Centre d'Etude du Polymorphisme Humain pedigrees, with >770 potentially informative meioses altogether, were genotyped with a subset of 2,988 SNPs, for map construction. Extensive genotyping-error analysis was performed, and the resulting SNP linkage map has an average map resolution of 3.9 cM, with map positions containing either a single SNP or several tightly linked SNPs. The order of markers on this map compares favorably with several other linkage and physical maps. We compared map distances between the SNP linkage map and the interpolated SNP linkage map constructed by the deCode Genetics group. We also evaluated cM/Mb distance ratios in females and males, along each chromosome, showing broadly defined regions of increased and decreased rates of recombination. Evaluations indicate that this SNP screening set is more informative than the Marshfield Clinic's commonly used microsatellite-based screening set.

Genetic structure of human populations.

We studied human population structure using genotypes at 377 autosomal microsatellite loci in 1056 individuals from 52 populations. Within-population differences among individuals account for 93 to 95% of genetic variation; differences among major groups constitute only 3 to 5%. Nevertheless, without using prior information about the origins of individuals, we identified six main genetic clusters, five of which correspond to major geographic regions, and subclusters that often correspond to individual populations. General agreement of genetic and predefined populations suggests that self-reported ancestry can facilitate assessments of epidemiological risks but does not obviate the need to use genetic information in genetic association studies.