Alon Keinan

Integrating common and rare genetic variation in diverse human populations.

Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called ‘HapMap 3’, includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of ≤5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.

Recent Explosive Human Population Growth Has Resulted in an Excess of Rare Genetic Variants

Exponential Growth Effects Humans are an extraordinarily successful species, as measured by our large population size—approximately 7 billion—much of which can be put down to recent explosive growth. Leveraging human genomic data, Keinan and Clark (p. 740) examined the effects of population growth on our ability to detect rare genetic variants, those hypothesized to be most likely associated with disease. It appears that rapid recent growth increases the load of rare variants and is likely to play an important role in the individual genetic burden of complex disease risk. Genetic models that incorporate recent human population growth can better identify mutations in large samples. Human populations have experienced recent explosive growth, expanding by at least three orders of magnitude over the past 400 generations. This departure from equilibrium skews patterns of genetic variation and distorts basic principles of population genetics. We characterized the empirical signatures of explosive growth on the site frequency spectrum and found that the discrepancy in rare variant abundance across demographic modeling studies is mostly due to differences in sample size. Rapid recent growth increases the load of rare variants and is likely to play a role in the individual genetic burden of complex disease risk. Hence, the extreme recent human population growth needs to be taken into consideration in studying the genetics of complex diseases and traits.

Measurement of the human allele frequency spectrum demonstrates greater genetic drift in East Asians than in Europeans

Large data sets on human genetic variation have been collected recently, but their usefulness for learning about history and natural selection has been limited by biases in the ways polymorphisms were chosen. We report large subsets of SNPs from the International HapMap Project that allow us to overcome these biases and to provide accurate measurement of a quantity of crucial importance for understanding genetic variation: the allele frequency spectrum. Our analysis shows that East Asian and northern European ancestors shared the same population bottleneck expanding out of Africa but that both also experienced more recent genetic drift, which was greater in East Asians.

Host genetic variation impacts microbiome composition across human body sites

BackgroundThe composition of bacteria in and on the human body varies widely across human individuals, and has been associated with multiple health conditions. While microbial communities are influenced by environmental factors, some degree of genetic influence of the host on the microbiome is also expected. This study is part of an expanding effort to comprehensively profile the interactions between human genetic variation and the composition of this microbial ecosystem on a genome- and microbiome-wide scale.ResultsHere, we jointly analyze the composition of the human microbiome and host genetic variation. By mining the shotgun metagenomic data from the Human Microbiome Project for host DNA reads, we gathered information on host genetic variation for 93 individuals for whom bacterial abundance data are also available. Using this dataset, we identify significant associations between host genetic variation and microbiome composition in 10 of the 15 body sites tested. These associations are driven by host genetic variation in immunity-related pathways, and are especially enriched in host genes that have been previously associated with microbiome-related complex diseases, such as inflammatory bowel disease and obesity-related disorders. Lastly, we show that host genomic regions associated with the microbiome have high levels of genetic differentiation among human populations, possibly indicating host genomic adaptation to environment-specific microbiomes.ConclusionsOur results highlight the role of host genetic variation in shaping the composition of the human microbiome, and provide a starting point toward understanding the complex interaction between human genetics and the microbiome in the context of human evolution and disease.

The History of African Gene Flow into Southern Europeans, Levantines, and Jews

Previous genetic studies have suggested a history of sub-Saharan African gene flow into some West Eurasian populations after the initial dispersal out of Africa that occurred at least 45,000 years ago. However, there has been no accurate characterization of the proportion of mixture, or of its date. We analyze genome-wide polymorphism data from about 40 West Eurasian groups to show that almost all Southern Europeans have inherited 1%–3% African ancestry with an average mixture date of around 55 generations ago, consistent with North African gene flow at the end of the Roman Empire and subsequent Arab migrations. Levantine groups harbor 4%–15% African ancestry with an average mixture date of about 32 generations ago, consistent with close political, economic, and cultural links with Egypt in the late middle ages. We also detect 3%–5% sub-Saharan African ancestry in all eight of the diverse Jewish populations that we analyzed. For the Jewish admixture, we obtain an average estimated date of about 72 generations. This may reflect descent of these groups from a common ancestral population that already had some African ancestry prior to the Jewish Diasporas.

Accelerated genetic drift on chromosome X during the human dispersal out of Africa

Comparisons of chromosome X and the autosomes can illuminate differences in the histories of males and females as well as shed light on the forces of natural selection. We compared the patterns of variation in these parts of the genome using two datasets that we assembled for this study that are both genomic in scale. Three independent analyses show that around the time of the dispersal of modern humans out of Africa, chromosome X experienced much more genetic drift than is expected from the pattern on the autosomes. This is not predicted by known episodes of demographic history, and we found no similar patterns associated with the dispersals into East Asia and Europe. We conclude that a sex-biased process that reduced the female effective population size, or an episode of natural selection unusually affecting chromosome X, was associated with the founding of non-African populations.

Extensive pathogenicity of mitochondrial heteroplasmy in healthy human individuals

Significance There are hundreds to thousands of copies of mitochondrial DNA (mtDNA) in each human cell in contrast to only two copies of nuclear DNA. High-frequency pathogenic mtDNA mutations have been found in patients with classic mitochondrial diseases, premature aging, cancers, and neurodegenerative diseases. In this study we investigated the distribution of heteroplasmic mutations, their pathogenic potential, and their underlying evolutionary forces using genome sequence data from the 1000 Genomes Project. Our results demonstrated the prevalence of low-frequency high-pathogenic-potential mtDNA mutations in healthy human individuals. These deleterious mtDNA mutations, when reaching high frequency, could provide a likely source of mitochondrial dysfunction. Managing the expansion of deleterious mtDNA mutations could be a promising means of preventing disease progression. A majority of mitochondrial DNA (mtDNA) mutations reported to be implicated in diseases are heteroplasmic, a status with coexisting mtDNA variants in a single cell. Quantifying the prevalence of mitochondrial heteroplasmy and its pathogenic effect in healthy individuals could further our understanding of its possible roles in various diseases. A total of 1,085 human individuals from 14 global populations have been sequenced by the 1000 Genomes Project to a mean coverage of ∼2,000× on mtDNA. Using a combination of stringent thresholds and a maximum-likelihood method to define heteroplasmy, we demonstrated that ∼90% of the individuals carry at least one heteroplasmy. At least 20% of individuals harbor heteroplasmies reported to be implicated in disease. Mitochondrial heteroplasmy tend to show high pathogenicity, and is significantly overrepresented in disease-associated loci. Consistent with their deleterious effect, heteroplasmies with derived allele frequency larger than 60% within an individual show a significant reduction in pathogenicity, indicating the action of purifying selection. Purifying selection on heteroplasmies can also be inferred from nonsynonymous and synonymous heteroplasmy comparison and the unfolded site frequency spectra for different functional sites in mtDNA. Nevertheless, in comparison with population polymorphic mtDNA mutations, the purifying selection is much less efficient in removing heteroplasmic mutations. The prevalence of mitochondrial heteroplasmy with high pathogenic potential in healthy individuals, along with the possibility of these mutations drifting to high frequency inside a subpopulation of cells across lifespan, emphasizes the importance of managing mitochondrial heteroplasmy to prevent disease progression.

Fair attribution of functional contribution in artificial and biological networks

This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation virtual lesions, as well as in providing insight into the inner workings of computational models of neurophysiological systems.

Population Genetic Inference from Personal Genome Data: Impact of Ancestry and Admixture on Human Genomic Variation

Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas-70% of the European ancestry in todays African Americans dates back to European gene flow happening only 7-8 generations ago.

Combining Evidence of Natural Selection with Association Analysis Increases Power to Detect Malaria-Resistance Variants

Statistical power to detect disease variants can be increased by weighting candidates by their evidence of natural selection. To demonstrate that this theoretical idea works in practice, we performed an association study of 10 putative resistance variants in 471 severe malaria cases and 474 controls from the Luo in Kenya. We replicated associations at HBB (P=.0008) and CD36 (P=.03) but also showed that the same variants are unusually differentiated in frequency between the Luo and Yoruba (who historically have been exposed to malaria) and the Masai and Kikuyu (who have not been exposed). This empirically demonstrates that combining association analysis with evidence of natural selection can increase power to detect risk variants by orders of magnitude--up to P=.000018 for HBB and P=.00043 for CD36.