Dissecting quantitative trait variation in the resequencing era: Complementarity of bi-parental, multi-parental and association panels - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Journal Articles Plant Science Year : 2016

Dissecting quantitative trait variation in the resequencing era: Complementarity of bi-parental, multi-parental and association panels

Abstract

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloningidentified several QTL. However linkage mapping is limited to the analysis of traits differing betweentwo lines and the impact of the genetic background on QTL effect has been underlined. Genome-wideassociation studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shownthat GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impactof population structure. Nevertheless, GWAs success might be limited due to the low decay of linkagedisequilibrium, which varies along the genome in this species.Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditionallinkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC popula-tion by crossing eight tomato lines whose genomes were resequenced. We showed the potential of theMAGIC population when coupled with whole genome sequencing to detect candidate single nucleotidepolymorphisms (SNPs) underlying the QTL. QTL for fruit quality traits were mapped and related to thevariations detected at the genome sequence and expression levels. The advantages and limitations of thethree types of population, in the context of the available genome sequence and resequencing facilities,are discussed

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Vegetal Biology
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hal-02635859 , version 1 (24-04-2024)

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Laura Pascual, Elise Albert, Christopher Sauvage, Janejira Duangjit, Jean-Paul Bouchet, et al.. Dissecting quantitative trait variation in the resequencing era: Complementarity of bi-parental, multi-parental and association panels. Plant Science, 2016, 242, pp.120-130. ⟨10.1016/j.plantsci.2015.06.017⟩. ⟨hal-02635859⟩
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