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Biology subjects

Connally, N. J.

Publications and source records attributed to Connally, N. J..

2 recordsLinked to original sources

Farm animal evolution demonstrates hidden molecular basis of human traits

Most human variants identified by genome-wide association studies are believed to affect traits by altering gene expression. This belief is supported by considerable circumstantial evidence, but statistical methods are unable to link most trait-associated variants to gene expression--a problem we refer to as "missing regulation." Many explanations have been proposed, including the possibility that natural selection on gene expression limits power. Here, we take a novel approach to the question of missing regulation, beginning with the observation that the majority of trait-associated variants alter gene expression in two non-human species: cattle and pigs. We explain this discrepancy by comparing the species evolutionary histories. The observed differences in regulatory variants are consistent with selection on human gene regulation and increased genetic drift due to agricultural breeding. The differences are not limited to specific genes and reflect increased ascertainment of regulatory variants that are distal to genes. Additionally, we show that trait-associated gene regulation in cattle and pigs matches observed patterns from complex-trait genetics in humans, and may reflect currently unobserved trait-associated regulation in humans.

genetics↗

Genetic association data are broadly consistent with stabilizing selection shaping human common diseases and traits

Results from genome-wide association studies (GWAS) enable inferences about the balance of evolutionary forces maintaining genetic variation underlying common diseases and other genetically complex traits. Natural selection is a major force shaping variation, and understanding it is necessary to explain the genetic architecture and prevalence of heritable diseases. Here, we analyze data for 27 traits, including anthropometric traits, metabolic traits, and binary diseases--both early-onset and post-reproductive. We develop an inference framework to test existing population genetics models based on the joint distribution of allelic effect sizes and frequencies of trait-associated variants. A majority of traits have GWAS results that are inconsistent with neutral evolution or long-term directional selection (selection against a trait or against disease risk). Instead, we find that most traits show consistency with stabilizing selection, which acts to preserve an intermediate trait value or disease risk. Our observations also suggest that selection may reflect pleiotropy, with each variant influenced by associations with multiple selected traits.

genomics↗