Person: Sankararaman, Sriram
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Sankararaman
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Sriram
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Sankararaman, Sriram
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Publication The landscape of Neandertal ancestry in present-day humans(2014) Sankararaman, Sriram; Mallick, Swapan; Dannemann, Michael; Prüfer, Kay; Kelso, Janet; Pääbo, Svante; Patterson, Nick; Reich, DavidAnalyses of Neandertal genomes have revealed that Neandertals have contributed genetic variants to modern humans1–2. The antiquity of Neandertal gene flow into modern humans means that regions that derive from Neandertals in any one human today are usually less than a hundred kilobases in size. However, Neandertal haplotypes are also distinctive enough that several studies have been able to detect Neandertal ancestry at specific loci1,3–8. Here, we have systematically inferred Neandertal haplotypes in the genomes of 1,004 present-day humans12. Regions that harbor a high frequency of Neandertal alleles in modern humans are enriched for genes affecting keratin filaments suggesting that Neandertal alleles may have helped modern humans adapt to non-African environments. Neandertal alleles also continue to shape human biology, as we identify multiple Neandertal-derived alleles that confer risk for disease. We also identify regions of millions of base pairs that are nearly devoid of Neandertal ancestry and enriched in genes, implying selection to remove genetic material derived from Neandertals. Neandertal ancestry is significantly reduced in genes specifically expressed in testis, and there is an approximately 5-fold reduction of Neandertal ancestry on chromosome X, which is known to harbor a disproportionate fraction of male hybrid sterility genes20–22. These results suggest that part of the reduction in Neandertal ancestry near genes is due to Neandertal alleles that reduced fertility in males when moved to a modern human genetic background.Publication Leveraging population admixture to explain missing heritability of complex traits(2014) Zaitlen, Noah; Pasaniuc, Bogdan; Sankararaman, Sriram; Bhatia, Gaurav; Zhang, Jianqi; Gusev, Alexander; Young, Taylor; Tandon, Arti; Pollack, Samuela; Vilhjálmsson, Bjarni J; Assimes, Themistocles L.; Berndt, Sonja I.; Blot, William J.; Chanock, Stephen; Franceschini, Nora; Goodman, Phyllis G.; He, Jing; Hennis, Anselm JM; Hsing, Ann; Ingles, Sue A.; Isaacs, William; Kittles, Rick A.; Klein, Eric A.; Lange, Leslie A.; Nemesure, Barbara; Patterson, Nick; Reich, David; Rybicki, Benjamin A.; Stanford, Janet L.; Stevens, Victoria L; Strom, Sara S.; Whitsel, Eric A; Witte, John S.; Xu, Jianfeng; Haiman, Christopher; Wilson, James G.; Kooperberg, Charles; Stram, Daniel; Reiner, Alex P.; Tang, Hua; Price, AlkesDespite recent progress on estimating the heritability explained by genotyped SNPs (hg2), a large gap between hg2 and estimates of total narrow-sense heritability (h2) remains. Explanations for this gap include rare variants, or upward bias in family-based estimates of h2 due to shared environment or epistasis. We estimate h2 from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (hγ2). We show that hγ2 = 2FSTCθ(1−θ)h2, where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We examined 21,497 African Americans from three cohorts, analyzing 13 phenotypes. For height and BMI, we obtained h2 estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of hg2 in these and other data, but smaller than family-based estimates of h2.Publication The Simons Genome Diversity Project: 300 genomes from 142 diverse populations(Springer Nature, 2016) Mallick, Swapan; Li, Heng; Lipson, Mark; Mathieson, Iain; Gymrek, Melissa Ann; Racimo, Fernando; Zhao, Mengyao; Chennagiri, Niru; Nordenfelt, Susanne; Tandon, Arti; Skoglund, Pontus R; Lazaridis, Iosif; Sankararaman, Sriram; Fu, Qiaomei; Rohland-Pinello, Nadin; Renaud, Gabriel; Erlich, Yaniv; Willems, Thomas; Gallo, Carla; Spence, Jeffrey P.; Song, Yun; Poletti, Giovanni; Balloux, Francois; van Driem, George; de Knijff, Peter; Romero, Irene Gallego; Jha, Aashish R.; Behar, Doron M.; Bravi, Claudio M.; Capelli, Cristian; Hervig, Tor; Moreno-Estrada, Andres; Posukh, Olga L.; Balanovska, Elena; Balanovsky, Oleg; Karachanak-Yankova, Sena; Sahakyan, Hovhannes; Toncheva, Draga; Yepiskoposyan, Levon; Tyler-Smith, Chris; Xue, Yali; Abdullah, M. Syafiq; Ruiz-Linares, Andres; Beall, Cynthia M.; Di Rienzo, Anna; Jeong, Choongwon; Starikovskaya, Elena B.; Metspalu, Ene; Parik, Jüri; Villems, Richard; Henn, Brenna M.; Hodoglugil, Ugur; Mahley, Robert; Sajantila, Antti; Stamatoyannopoulos, George; Wee, Joseph T. S.; Khusainova, Rita; Khusnutdinova, Elza; Litvinov, Sergey; Ayodo, George; Comas, David; Hammer, Michael F.; Kivisild, Toomas; Klitz, William; Winkler, Cheryl A.; Labuda, Damian; Bamshad, Michael; Jorde, Lynn B.; Tishkoff, Sarah A.; Watkins, W. Scott; Metspalu, Mait; Dryomov, Stanislav; Sukernik, Rem; Singh, Lalji; Thangaraj, Kumarasamy; Pääbo, Svante; Kelso, Janet; Patterson, Nick; Reich, DavidWe report the Simons Genome Diversity Project (SGDP) dataset: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioral modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that in other non-Africans.Publication Inferring parental genomic ancestries using pooled semi-Markov processes(Oxford University Press, 2015) Zou, James Y.; Halperin, Eran; Burchard, Esteban; Sankararaman, SriramMotivation: A basic problem of broad public and scientific interest is to use the DNA of an individual to infer the genomic ancestries of the parents. In particular, we are often interested in the fraction of each parent’s genome that comes from specific ancestries (e.g. European, African, Native American, etc). This has many applications ranging from understanding the inheritance of ancestry-related risks and traits to quantifying human assortative mating patterns. Results: We model the problem of parental genomic ancestry inference as a pooled semi-Markov process. We develop a general mathematical framework for pooled semi-Markov processes and construct efficient inference algorithms for these models. Applying our inference algorithm to genotype data from 231 Mexican trios and 258 Puerto Rican trios where we have the true genomic ancestry of each parent, we demonstrate that our method accurately infers parameters of the semi-Markov processes and parents’ genomic ancestries. We additionally validated the method on simulations. Our model of pooled semi-Markov process and inference algorithms may be of independent interest in other settings in genomics and machine learning. Contact: jazo@microsoft.comPublication Calibrating the Human Mutation Rate via Ancestral Recombination Density in Diploid Genomes(Public Library of Science, 2015) Lipson, Mark; Loh, Po-Ru; Sankararaman, Sriram; Patterson, Nick; Berger, Bonnie; Reich, DavidThe human mutation rate is an essential parameter for studying the evolution of our species, interpreting present-day genetic variation, and understanding the incidence of genetic disease. Nevertheless, our current estimates of the rate are uncertain. Most notably, recent approaches based on counting de novo mutations in family pedigrees have yielded significantly smaller values than classical methods based on sequence divergence. Here, we propose a new method that uses the fine-scale human recombination map to calibrate the rate of accumulation of mutations. By comparing local heterozygosity levels in diploid genomes to the genetic distance scale over which these levels change, we are able to estimate a long-term mutation rate averaged over hundreds or thousands of generations. We infer a rate of 1.61 ± 0.13 × 10−8 mutations per base per generation, which falls in between phylogenetic and pedigree-based estimates, and we suggest possible mechanisms to reconcile our estimate with previous studies. Our results support intermediate-age divergences among human populations and between humans and other great apes.Publication Phylogenetic Inference via Sequential Monte Carlo(Oxford University Press, 2012) Bouchard-Côté, Alexandre; Sankararaman, Sriram; Jordan, Michael I.Bayesian inference provides an appealing general framework for phylogenetic analysis, able to incorporate a wide variety of modeling assumptions and to provide a coherent treatment of uncertainty. Existing computational approaches to Bayesian inference based on Markov chain Monte Carlo (MCMC) have not, however, kept pace with the scale of the data analysis problems in phylogenetics, and this has hindered the adoption of Bayesian methods. In this paper, we present an alternative to MCMC based on Sequential Monte Carlo (SMC). We develop an extension of classical SMC based on partially ordered sets and show how to apply this framework—which we refer to as PosetSMC—to phylogenetic analysis. We provide a theoretical treatment of PosetSMC and also present experimental evaluation of PosetSMC on both synthetic and real data. The empirical results demonstrate that PosetSMC is a very promising alternative to MCMC, providing up to two orders of magnitude faster convergence. We discuss other factors favorable to the adoption of PosetSMC in phylogenetics, including its ability to estimate marginal likelihoods, its ready implementability on parallel and distributed computing platforms, and the possibility of combining with MCMC in hybrid MCMC–SMC schemes. Software for PosetSMC is available at http://www.stat.ubc.ca/ bouchard/PosetSMC.Publication Evidence of Widespread Selection on Standing Variation in Europe at Height-Associated SNPs(Nature Publishing Group, 2012) Turchin, Michael C.; Chiang, Charleston W. K.; Palmer, Cameron Douglas; Sankararaman, Sriram; Reich, David; Hirschhorn, Joel; GIANT ConsortiumStrong signatures of positive selection at newly arising genetic variants are well-documented in humans, but this form of selection may not be widespread in recent human evolution. Because many human traits are highly polygenic and partly determined by common, ancient genetic variation, an alternative model for rapid genetic adaptation has been proposed: weak selection acting on many pre-existing (standing) genetic variants, or polygenic adaptation. By studying height, a classic polygenic trait, we demonstrate the first human signature of widespread selection on standing variation. We show that frequencies of alleles associated with increased height, both at known loci and genome-wide, are systematically elevated in Northern Europeans compared with Southern Europeans \((p<4.3×10^{−4})\). This pattern mirrors intra-European height differences and is not confounded by ancestry or other ascertainment biases. The systematic frequency differences are consistent with the presence of widespread weak selection (selection coefficients \(~10^{−3}–10^{−5}\) per allele) rather than genetic drift alone \((p<10^{−15})\).Publication The Date of Interbreeding between Neandertals and Modern Humans(Public Library of Science, 2012) Sankararaman, Sriram; Patterson, Nick; Li, Heng; Pääbo, Svante; Reich, DavidComparisons of DNA sequences between Neandertals and present-day humans have shown that Neandertals share more genetic variants with non-Africans than with Africans. This could be due to interbreeding between Neandertals and modern humans when the two groups met subsequent to the emergence of modern humans outside Africa. However, it could also be due to population structure that antedates the origin of Neandertal ancestors in Africa. We measure the extent of linkage disequilibrium (LD) in the genomes of present-day Europeans and find that the last gene flow from Neandertals (or their relatives) into Europeans likely occurred 37,000–86,000 years before the present (BP), and most likely 47,000–65,000 years ago. This supports the recent interbreeding hypothesis and suggests that interbreeding may have occurred when modern humans carrying Upper Paleolithic technologies encountered Neandertals as they expanded out of Africa.