• Treffer 1 von 4
Zurück zur Trefferliste

Global genetic heterogeneity in adaptive traits

Zitieren Sie bitte immer diese 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.zeige mehrzeige weniger

Volltext Dateien herunterladen

Metadaten exportieren

Weitere Dienste

Teilen auf Twitter Suche bei Google Scholar Statistik - Anzahl der Zugriffe auf das Dokument
Metadaten
Autor(en): William Andres Lopez-Arboleda, Stephan Reinert, Magnus Nordborg, Arthur KorteORCiD
URN:urn:nbn:de:bvb:20-opus-270410
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Biologie / Center for Computational and Theoretical Biology
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Molecular Biology and Evolution
Erscheinungsjahr:2021
Band / Jahrgang:38
Heft / Ausgabe:11
Seitenangabe:4822–4831
Originalveröffentlichung / Quelle:Molecular Biology and Evolution (2021) 38:11, 4822–4831. https://doi.org/10.1093/molbev/msab208
DOI:https://doi.org/10.1093/molbev/msab208
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Freie Schlagwort(e):GWAS; evolutionary genomics; genetic architecture; regulation of gene expression
Datum der Freischaltung:05.05.2022
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2021
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International