Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci

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作者
Abigail L. LaBella
Abin Abraham
Yakov Pichkar
Sarah L. Fong
Ge Zhang
Louis J. Muglia
Patrick Abbot
Antonis Rokas
John A. Capra
机构
[1] Vanderbilt University,Department of Biological Sciences
[2] Vanderbilt University,Vanderbilt Genetics Institute
[3] Vanderbilt University Medical Center,Department of Pediatrics
[4] Vanderbilt University,Department of Biomedical Informatics
[5] Division of Human Genetics,Departments of Biomedical Informatics and Computer Science, Vanderbilt Genetics Institute, Center for Structural Biology
[6] Cincinnati Children’s Hospital Medical Center,undefined
[7] The Center for Prevention of Preterm Birth,undefined
[8] Perinatal Institute,undefined
[9] Cincinnati Children’s Hospital Medical Center,undefined
[10] March of Dimes Prematurity Research Center Ohio Collaborative,undefined
[11] University of Cincinnati College of Medicine,undefined
[12] Vanderbilt University School of Medicine,undefined
[13] Vanderbilt University,undefined
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摘要
Currently, there is no comprehensive framework to evaluate the evolutionary forces acting on genomic regions associated with human complex traits and contextualize the relationship between evolution and molecular function. Here, we develop an approach to test for signatures of diverse evolutionary forces on trait-associated genomic regions. We apply our method to regions associated with spontaneous preterm birth (sPTB), a complex disorder of global health concern. We find that sPTB-associated regions harbor diverse evolutionary signatures including conservation, excess population differentiation, accelerated evolution, and balanced polymorphism. Furthermore, we integrate evolutionary context with molecular evidence to hypothesize how these regions contribute to sPTB risk. Finally, we observe enrichment in signatures of diverse evolutionary forces in sPTB-associated regions compared to genomic background. By quantifying multiple evolutionary forces acting on sPTB-associated regions, our approach improves understanding of both functional roles and the mosaic of evolutionary forces acting on loci. Our work provides a blueprint for investigating evolutionary pressures on complex traits.
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