A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs

Abstract

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 (QTLs) in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in five 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 (SNPs) by combining an 18K microarray and genotyping-by-sequencing (GBS). The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via GBS markedly increased the proportion of genetic variance explained by SNPs, and two multi-SNP models identified QTLs not found by a SNP-by-SNP model. Overall, 489 reliable QTLs were detected for 41% more response variables than by a SNP-by-SNP model with microarray-only SNPs, many new ones compared to 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 QTL and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed.

Genetic dissection of QTLs for starch content in four maize DH populations

“…Molecular markers are useful tools to efficiently facilitate the selection process. SNP markers are the most frequent variations in genomes, and the application of SNP markers in plant breeding has guaranteed the precision of QTL mapping and genetic analysis (Bhattramakki et al, 2002 ; Mammadov et al, 2012 ; Flutre et al, 2022 ; Kaur et al, 2022 ). In the present study, a total of 13 QTLs were distributed on chromosomes 1, 3, 4, 5, 7, 8, and 9.…”

The phased diploid genome assembly ofVitis vinifera cv. Shiraz

“…Previously published RAD-Seq lllumina paired-end reads from cultivars Dureza and Mondeuse Blanche [41] were mapped to the Shiraz primary assembly using Minimap2 v. 2.24 [42]. Mapped reads had their variants called (MQ>20) and were filtered (DP>5, GQ>20, F_MISS=0) using BCFtools v1.16 [43].…”

“…As SSR data was previously used to suggest that Mondeuse Blanche and Dureza comprise the parents of Shiraz [1], existing RAD-Seq data from these two cultivars [41] was utilized to provide further support to their relationship to Shiraz. Whole genome variant calling was performed using the RAD-Seq data of Mondeuse Blanche and Dureza against the Shiraz genome sequence, producing a space of 81,551 variants for analysis.…”

Biotechnologies and Strategies for Grapevine Improvement

“…sativa (cultivated grapevine), to reveal synonymies, homonymies, as well as inter and intra-specific genetic variations and phylogenetic relationships among wild and cultivated grapevines [27,[57][58][59][60][61][62]. In recent years, SNP markers have also gained high popularity for evaluating allelic variations throughout grapevine genomes and dissecting complex traits via QTL (quantitative trait loci) for breeding programs [63,64]. SNPs are highly abundant across plant genomes and offer higher reproducibility than microsatellite data, facilitating the integration and interpretation of genotyping data throughout grape gene banks and databases [65,66].…”