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A quantitative model for characterizing the evolutionary history of mammalian gene expression

By Jenny Chen, Ross Swofford, Jeremy Johnson, Beryl B. Cummings, Noga Rogel, Kerstin Lindblad-Toh, Wilfried Haerty, Federica di Palma, Aviv Regev

Posted 04 Dec 2017
bioRxiv DOI: 10.1101/229096 (published DOI: 10.1101/gr.237636.118)

Characterizing the evolutionary history of a gene's expression profile is a critical component for understanding the relationship between genotype, expression, and phenotype. However, it is not well-established how best to distinguish the different evolutionary forces acting on gene expression. Here, we use RNA-seq across 7 tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein- Uhlenbeck (OU) process. This stochastic process models expression trajectories across time as Gaussian distributions whose variance is parameterized by the rate of genetic drift and strength of stabilizing selection. We use these mathematical properties to identify expression pathways under neutral, stabilizing, and directional selection, and quantify the extent of selective pressure on a gene's expression. We further detect deleterious expression levels outside expected evolutionary distributions in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.

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