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Genetic architecture and adaptation of flowering time among environments
Author(s) -
Yan Wenjie,
Wang Baosheng,
Chan Emily,
MitchellOlds Thomas
Publication year - 2021
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.17229
Subject(s) - genetic architecture , biology , pleiotropy , local adaptation , adaptation (eye) , quantitative trait locus , ecological genetics , genome wide association study , trait , evolutionary biology , population , phenology , natural selection , allele , association mapping , genetics , ecology , gene , phenotype , single nucleotide polymorphism , genotype , demography , neuroscience , sociology , programming language , computer science
Summary The genetic basis of flowering time changes across environments, and pleiotropy may limit adaptive evolution of populations in response to local conditions. However, little information is known about how genetic architecture changes among environments. We used genome‐wide association studies (GWAS) in Boechera stricta (Graham) Al‐Shehbaz, a relative of Arabidopsis, to examine flowering variation among environments and associations with climate conditions in home environments. Also, we used molecular population genetics to search for evidence of historical natural selection. GWAS found 47 significant quantitative trait loci (QTLs) that influence flowering time in one or more environments, control plastic changes in phenology between experiments, or show associations with climate in sites of origin. Genetic architecture of flowering varied substantially among environments. We found that some pairs of QTLs showed similar patterns of pleiotropy across environments. A large‐effect QTL showed molecular signatures of adaptive evolution and is associated with climate in home environments. The derived allele at this locus causes later flowering and predominates in sites with greater water availability. This work shows that GWAS of climate associations and ecologically important traits across diverse environments can be combined with molecular signatures of natural selection to elucidate ecological genetics of adaptive evolution.