Project Number: 1910-21220-005-03
Project Type: Specific Cooperative Agreement

Start Date: Sep 22, 2008
End Date: Sep 21, 2013

Objective:
The objective of this research is to characterize trait variation of the USDA-ARS Vitis germplasm collections. The phenotypic trait information collected from this study, in combination with the genotypic information generated from the grape SNP discovery project led by Dr. Ed Buckler at ARS, will significantly advance our knowledge and capability in identifying useful allelic variation in the Vitis germplasm for grape improvement. In addition, one mapping population relevant to winegrape breeding will also be characterized to examine how well the research results of trait variation from Vitis germplasm can be extended to practical breeding material.

Approach:
Phenotype USDA-ARS Vitis germplasm collections: 1. Phenotyping berry shape, berry color, berry length and width, and cluster size per Standard Biodiversity International Descriptors for all non-hybrid Vitis germplasm accessions (about 700) from the USDA-ARS Geneva Vitis Clonal Repository. This work will be closely coordinated with the ongoing phenotyping effort at the USDA-ARS Davis Vitis Clonal Repository and the ARS grape SNP discovery project of Dr. Ed Buckler et al. 2. Analyzing key primary and secondary metabolites of 600 Vitis germplasm accessions from the USDA-ARS Vitis Clonal Repositories at Davis, CA and Geneva, NY. A total of 3,600 samples (3 replicates x 2 years x 600 accessions) will be analyzed. Phenotype one mapping population relevant to winegrape breeding: 1. Analyzing key primary and secondary metabolites of the Horizon x Illinois 547-1 mapping population developed by Dr. Bruce Reisch at Cornell. A total of 400 samples (2 replicates x 2 years x 100 lines) will be analyzed. Analyze phenotypic data and carry out marker-trait association analysis: 1. Characterizing properties of the phenotypic trait variation investigated. 2. Collaborating with Dr. Ed Buckler and his group to carry out marker-trait association analysis. 3. Validating association analysis results with linkage mapping data.