Genome-wide Association Study of Basic Fruit Chemistry in Cold Climate Winegrapes (Vitis spp.)
Venkateswara Rao Kadium, Ramesh Pillli, Andrej
Svyantek, John Stenger, Xuehui Li, Collin Auwarter, and Harlene
Hatterman-Valenti*
*North Dakota State University, NDSU Dept 7670, PO Box 6050 ,
Fargo, ND, 58108-6050 (h.hatterman.valenti@ndsu.edu)
Grapegrowers in North Dakota face multiple constraints such as winter injury, short growing season, frost damage, and poor fruit quality. To overcome some of these challenges, native North American Vitis-derived varieties have been used for production. Despite the advantageous environmental resilience provided by wild crosses, their fruit chemistry parameters such as acidity, sugar, and pH concentrations often deviate from traditional expectations. Identifying the role of genetics in the expression of these traits in interspecific hybrid populations will greatly benefit the process of new hybrid cultivar development. For this purpose, an incomplete diallel mapping population of ~1000 F1 individuals derived from three interspecific breeding lines from the North Dakota State University Grape Germplasm Enhancement Project was created in 2016 and field-planted in 2017 in Fargo, ND. The population is genotyped with ~36,000 GBS markers and ~2000 rhAmpSeq markers. Phenotypic data pertaining to three different traits, Brix, pH, and acidity, were measured during three consecutive growing seasons (2020 to 2022). Genome-wide association analysis was performed using the GAPIT3 package in R statistical software to identify associations between measured traits and the markers. A significant association was detected in the population on chromosomes 6 and 16 for all three traits measured during multiple years. Candidate gene scanning at the region of significant markers revealed several genes related to carbohydrate and acid metabolism. The stable significant markers identified in this study will serve as a resource in continued selection and development of new hybrid lines with improved fruit chemistry through marker-assisted selection and genomic prediction methods.
Funding Support: Specialty Crop Block Grant