Global genetic heterogeneity in adaptive traits

Please always quote using this URN: urn:nbn:de:bvb:20-opus-270410
  • Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling acrossUnderstanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.show moreshow less

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Metadaten
Author: William Andres Lopez-Arboleda, Stephan Reinert, Magnus Nordborg, Arthur KorteORCiD
URN:urn:nbn:de:bvb:20-opus-270410
Document Type:Journal article
Faculties:Fakultät für Biologie / Center for Computational and Theoretical Biology
Language:English
Parent Title (English):Molecular Biology and Evolution
Year of Completion:2021
Volume:38
Issue:11
Pagenumber:4822–4831
Source:Molecular Biology and Evolution (2021) 38:11, 4822–4831. https://doi.org/10.1093/molbev/msab208
DOI:https://doi.org/10.1093/molbev/msab208
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:GWAS; evolutionary genomics; genetic architecture; regulation of gene expression
Release Date:2022/05/05
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2021
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International