1. Genome-wide association study of a diverse grapevine panel: example of berry weight
- Author
-
Valérie Laucou, L. Le Cunff, Charles Romieu, Agnes Doligez, Gilles Berger, Agota Fodor, Jean Michel Boursiquot, Jean-Pierre Péros, Roberto Bacilieri, I. Becavin, Patrice This, Thierry Lacombe, Yves Bertrand, Amandine Launay, and Timothée Flutre
- Subjects
Evolutionary biology ,Genetic variation ,Trait ,food and beverages ,SNP ,Single-nucleotide polymorphism ,Genome-wide association study ,Horticulture ,Biology ,Quantitative trait locus ,DNA sequencing ,Genetic architecture - Abstract
Breeding new cultivars is an important lever to cope with the various challenges facing viticulture. As a prerequisite, it is necessary to assess how much genetic variation is available for the traits of interest, and to understand their genetic architecture. To go beyond quantitative trait locus (QTL) mapping in biparental crosses, we exploited the panel of 279 cultivars capturing most of the genetic and phenotypic diversity of Vitis vinifera L. present within the French collection of genetic resources (INRA Vassal). This panel was planted in the vineyard in five randomized complete blocks and numerous traits (berry weight, cluster weight, length and compactness, organic acids, δ13C, polyphenols, etc.) were phenotyped over several years. In parallel, the panel was genotyped with the GrapeReSeq microarray as well as with restriction-assisted DNA sequencing. This allowed us to conduct a genome-wide association study per trait, either by testing each single-nucleotide polymorphism (SNP) separately or by modeling all SNPs jointly. Focusing here on berry weight, we showed that genotyping by sequencing provided enough SNPs to explain most of the genetic variance, and that, compared with SNP-by-SNP approaches, a multi-SNP statistical model led to a gain in power. Several significant associations were detected, some being new compared with the QTLs detected in biparental crosses. Future prospects include setting up an international consortium to plant the panel on various sites to help to decipher genotype-environment interactions.
- Published
- 2019