ViniGWAS – towards the development of climate-resilient grapevine varieties

Abstract

One possible strategy to face the increasing challenges of climate change in viticulture is the breeding of new climate-resilient grapevine varieties using modern breeding techniques, e.g. marker-assisted-selection. The limiting factor in facilitating this is that the genetic background of the desired traits for climate-adaptation has not been sufficiently elucidated yet, like it has been for example for fungal resistance. To characterize these genomic regions, we are combining high coverage whole-genome sequencing (WGS) in a genome-wide association study (GWAS). Over 250 genotypes of the JKI Grapevine breeding institute have been genotyped with Illumina paired-end 150 bp WGS at IPK Gatersleben, yielding an average coverage of 30–35 ×. Several categories of phenotypic data have been collected: a) phenological data at different developmental stages, b) analysis of multiple grape must quality parameters at harvest time with FTIR and c) 3D-Scans of the grape clusters at harvest time. The phenotypic data has been collected for several years and exists for different traits from 2019 onwards. First calculations with the phenotypic data showed a high broad-sense heritability and a high correlation between the years. With the changing climate, developing grapevine varieties with later phenological development is more and more preferred. Hence the focus in this research is foremost the phenological development, mainly the time of budburst (H2 = 0.87), time of flowering (H2 = 0.85) and time of veraison (H2 = 0.92). Over the years, more and more GWAS models have been developed, each having its own advantage for detecting different kinds (e.g. single-locus vs. multi-locus) of traits. We used different models to combine the WGS genotypic data with the phenotypic data to investigate the traits of interest. Uncovering the genetics of these traits is needed to develop corresponding genetic markers to make breeding climate-resilient varieties possible.