Characterizing the genetic architecture of gene expression variation in wild baboons via RNA sequencing. X. Zhou1,2, J. Tung3, S. Alberts4, J. Altmann5, M. Stephens1,2, Y. Gilad1 1) Department of Human Genetics, University of Chicago, Chicago, IL; 2) Department of Statistics, University of Chicago, Chicago, IL; 3) Department of Evolutionary Anthropology, Duke University, Durham, NC; 4) Department of Biology, Duke University, Durham, NC; 5) Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ.

   Gene expression variation is well documented in human populations and its genetic architecture has been extensively explored in recent large-scale studies. However, we still know little about the genetic architecture of gene expression variation in other species, particularly our closest living relatives, the nonhuman primates. To address this gap, we performed an RNA sequencing (RNA-seq)-based study in 63 wild baboons, members of the intensively studied Amboseli baboon population in Kenya. Our study design allowed us to measure gene expression levels and call genetic variants using the same data set, enabling us to subsequently map cis-eQTLs (expression quantitative loci). We validated our approach using an existing human HapMap RNA-seq data set. We detected more than one thousand variants affecting gene expression levels in baboons, which is approximately four times more eQTLs than detectable using the same approach on a HapMap human data set of comparable size. This increase in power appears to stem from a combination of increased genetic variation, enrichment of SNPs with high minor allele frequencies, and longer-range linkage disequilibrium in the baboon data set relative to the human data set. As observed in humans, baboon eQTLs are enriched inside genes and near transcription start sites and associated with allelic specific expression in heterozygotes. eQTL effect sizes in the baboons were negatively correlated with minor allele frequency, consistent with arguments that negative selection often acts on gene expression variation to reduce the impact of the regulatory variation. Further, genes with large effect eQTL in baboons overlapped significantly with genes with large effect eQTL in humans. This set of overlapping genes was significantly less conserved across vertebrates at the sequence level than genes with large effect eQTL in only one species, which were in turn less conserved than genes with no detectable eQTL in either species. Finally, using a Bayesian sparse linear mixed model, we estimate that the cis-regulatory variants in baboons together explain approximately half of the genetic variance for gene expression levels, which is comparable to the results obtained in the same tissue in a human population. Together, our comparative eQTL mapping study represents an important first step towards understanding the genetic architecture of gene expression variation in natural primate populations.

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