Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population
Author(s) -
Isidore Diouf,
Laurent Derivot,
Shai Koussevitzky,
Yolande Carretero,
Frédérique Bitton,
Laurence Moreau,
Mathilde Causse
Publication year - 2020
Publication title -
journal of experimental botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.616
H-Index - 242
eISSN - 1460-2431
pISSN - 0022-0957
DOI - 10.1093/jxb/eraa265
Subject(s) - biology , quantitative trait locus , phenotypic plasticity , genetic architecture , solanum , population , gene–environment interaction , candidate gene , context (archaeology) , trait , genotype , genetics , microbiology and biotechnology , evolutionary biology , gene , botany , paleontology , demography , sociology , computer science , programming language
Deciphering the genetic basis of phenotypic plasticity and genotype × environment interactions (G×E) is of primary importance for plant breeding in the context of global climate change. Tomato (Solanum lycopersicum) is a widely cultivated crop that can grow in different geographical habitats and that displays a great capacity for expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore G×E and plasticity for multiple traits measured in a multi-environment trial (MET) comprising optimal cultural conditions together with water deficit, salinity, and heat stress over 12 environments. Substantial G×E was observed for all the traits measured. Different plasticity parameters were estimated by employing Finlay-Wilkinson and factorial regression models and these were used together with genotypic means for quantitative trait loci (QTL) mapping analyses. In addition, mixed linear models were also used to investigate the presence of QTL × environment interactions. The results highlighted a complex genetic architecture of tomato plasticity and G×E. Candidate genes that might be involved in the occurrence of G×E are proposed, paving the way for functional characterization of stress response genes in tomato and for breeding climate-adapted cultivars.
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