Global Genetic Heterogeneity in Adaptive Traits
| Autor: | Stephan Reinert, Arthur Korte, Magnus Nordborg, William Andres Lopez-Arboleda |
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| Rok vydání: | 2021 |
| Předmět: |
Genetic heterogeneity
Arabidopsis AcademicSubjects/SCI01130 evolutionary genomics Genetic Variation Reproducibility of Results Genome-wide association study Biology AcademicSubjects/SCI01180 Phenotype Polymorphism Single Nucleotide genetic architecture Human genetics Genetic architecture Genetic Heterogeneity Evolutionary biology ddc:570 GWAS Adaptation regulation of gene expression Gene Discoveries Genetic association Genome-Wide Association Study |
| Zdroj: | Molecular Biology and Evolution |
| ISSN: | 1537-1719 |
| Popis: | 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 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 for a variety of phenotypes in the model plant species Arabididopsis 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, while 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 incredibly sensitive to sampling and population structure. |
| Databáze: | OpenAIRE |
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