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

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.

We demonstrate the power of a stochastic model for quantifying selective pressure on expression and estimating evolutionary distributions of optimal gene expression.

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Additional Info

Field Value
Author Chen, Jenny
Last Updated November 20, 2019, 16:45 (UTC)
Created August 1, 2019, 10:27 (UTC)
Article Host Type publisher
Article Is Open Access true
Article License Type cc-by
Article Version Type publishedVersion
Citation Report https://scite.ai/reports/10.1101/229096
DOI 10.1101/229096
Date Last Updated 2019-06-07T00:54:08.017532
Evidence open (via page says license)
Funder code(s)
Journal Is Open Access false
Open Access Status hybrid
PDF URL https://www.biorxiv.org/content/biorxiv/early/2017/12/04/229096.full.pdf
Publisher URL https://doi.org/10.1101/229096