Project Number: 2072-22000-046-019-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 1, 2022
End Date: Aug 31, 2025
1. Implement and validate genomic prediction as a plant breeding tool to increase the resistance of raspberry cultivars to the root lesion nematode (RLN), Pratylenchus penetrans.
Field experiment. Prior to project years, a panel of 300 genotypes will be assembled by the BC, USDA/OSU, and WSU plant breeding programs representing the Rubus germplasm diversity of each program, as well as diverse named varieties from the National Clonal Germplasm Repository. A set of 10 seedling populations of Northwest material will also be developed. In Spring 2022, the 300 genotypes in four single-plant replicates and seedling populations will be established in a field at WSU NWREC, Mount Vernon, WA. Half of the clonal replicates and seedlings will be inoculated with mixed stage RLN individuals, obtained by mist collection from raspberry roots from an infested field. The inoculum delivered will be approximately 1,000 nematodes/plant in 5 ml of water into the root system. This planting will be maintained for at least three seasons, through Fall of 2024. Phenotype data collection. Phenotyping to determine RLN parasitism and level of resistance and/or tolerance to RLN will occur by two main methods: plant aboveground biomass and RLN quantification. Plants will be pruned during the fall to remove and measure all aboveground biomass. The difference between plant biomass of inoculated replicates and non-inoculated replicates represents the plant response to RLN. The plants will also be visually rated for vigor. In the fall of each year we will quantify the plant RLN populations. Roots will be dug with a shovel on either side of the plant. In the lab, roots will be rinsed for RLN extraction under intermittent mist for 5 days. Roots from each sample will be placed in a drier for 7 days prior to measuring dry root weight. RLN will be counted using a microscope and RLN resistance phenotypes expressed as the number of RLN/g root mass. Genotyping and Genomic Prediction. In the first year, immature leaf tissue will be collected from each plant for DNA extraction. DNA samples will be submitted for molecular marker genotyping using a single-nucleotide polymorphism (SNP) array containing roughly 8,000 red raspberry marker probes. We will use the resulting molecular marker genotypes and RLN phenotypes to calculate genomic estimated breeding values (GEBVs) for non-genotyped individuals using the whole-genome regression methods employed by Pincot et al. (2020). We will determine the accuracy of the genomic prediction models using Monte Carlo cross-validation (MCCV) by randomly splitting accessions into training (80%) and validation (20%) subsets and comparing GEBVs to phenotypic data collected in the field. We will also perform a genome-wide association analysis to identify any potential large-effect resistance genes in the clonally replicated genotypes.