A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.
Vitis vinifera L
GWAS
candidate genes
genetic architecture
genomic prediction
genotyping-by-sequencing
grapevine
secondary metabolites
yield components
Journal
G3 (Bethesda, Md.)
ISSN: 2160-1836
Titre abrégé: G3 (Bethesda)
Pays: England
ID NLM: 101566598
Informations de publication
Date de publication:
06 07 2022
06 07 2022
Historique:
received:
21
01
2022
accepted:
21
04
2022
pubmed:
30
4
2022
medline:
9
7
2022
entrez:
29
4
2022
Statut:
ppublish
Résumé
To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed.
Identifiants
pubmed: 35485948
pii: 6575896
doi: 10.1093/g3journal/jkac103
pmc: PMC9258538
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.
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