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Detalle de: Genetic variation and association analyses identify genes linked to fruit set-related traits in grapevine

Title Genetic variation and association analyses identify genes linked to fruit set-related traits in grapevine
Abstract

Grapevine is one of the most valuable fruit crops in the world. Adverse environmental conditions reduce fruit quality and crop yield, so understanding the genetic and molecular mechanisms determining crop yield components is essential to optimize grape production. The analysis of a diverse collection of grapevine cultivars allowed us to evaluate the relationship between fruit set-related components of yield, including the incidence of reproductive disorders such as coulure and millerandage. The collection displayed a great phenotypic variation that we surveyed in a genetics association study using 15,309 single nucleotide polymorphisms (SNPs) detected in the sequence of 289 candidate genes scattered across the 19 grapevine linkage groups. After correcting statistical models for population structure and linkage disequilibrium effects, 164 SNPs from 34 of these genes were found to associate with fruit set-related traits, supporting a complex polygenic determinism. Many of them were found in the sequence of different putative MADS-box transcription factors, a gene family related with plant reproductive development control. In addition, we observed an additive effect of some of the associated SNPs on the phenotype, suggesting that advantageous alleles from different loci could be pyramided to generate superior cultivars with optimized fruit production.

Apa Reference Zinelabidine, L.H., Torres-Pérez, R., Grimplet, J., Baroja, E., Ibáñez, S., Carbonell-Bejerano, P., Martínez-Zapater, J.M., Ibáñez, J. & Tello, J. (2021). Genetic variation and association analyses identify genes linked to fruit set-related traits in grapevine. Plant Science, 306, 110875. 10.1016/j.plantsci.2021.110875
Doi 10.1016/j.plantsci.2021.110875
Publication Date May 2021
Publication Type Article
Researcher Rafael Torres Pérez
Ontology Regulatory biology, Statistical Methods for Biology, Population genomics, Quantitative genetics
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