Location: Horticultural Crops Production and Genetic Improvement Research Unit
Project Number: 2072-21000-060-019-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2025
End Date: Jul 31, 2028
Objective:
The Pacific Northwest (PNW) produces over 90% of the processed red raspberry crop harvested annually in the U.S., with a strong focus on machine harvestable red raspberry cultivars whose berries can withstand the significant bruising and damage brought about during mechanized harvest, and with suitable color and quality for processing. This requires improved red raspberry genetics that yield fruit with rich internal coloring and increased durability with regard to firmness, skin toughness, and lack of drupelet crumbling.
The USDA-ARS-HCPGIRU (Horticultural Crops Production and Genetic Improvement Research Unit) caneberry breeding program is collaborating with the Oregon State University Endowed Professor for Northwest Berry Production and Management, to modernize approaches to breeding and trialing caneberries in the Northwest. As trailing efforts shift toward full mechanization of caneberry production, our objective is to conduct studies necessary to elucidate the underlying genetic control of raspberry fruit quality, particularly for traits impacting suitability for machine harvest. The results of these studies will enable generation of genetic markers that can be deployed within breeding programs for more rapid selection of breeding material with increased fruit durability.
Objective 1: Collect data on fruit quality related traits, including color, firmness, texture, drupelet cohesion, post-harvest durability, in a population of 400 red raspberry breeding lines.
Objective 2: Perform high-throughput sequencing and identify genome-wide single nucleotide polymorphisms (SNPs) in the red raspberry breeding population.
Objective 3: Utilize SNPs and trait data to perform a genome-wide association study identifying loci within the red raspberry genome controlling traits of interest, and convert predictive SNPs into genetic marker assays for marker-assisted breeding.
Approach:
Red raspberry breeding populations are maintained at Oregon State University's Lewis Brown Farm (Corvallis, OR) and North Willamette Research and Extension Center (OSU-NWREC; Aurora, OR). A population of red raspberries consisting of 400 full-sib progeny from 25 bi-parental families will provide the basis for a genome-wide association study (GWAS) to investigate the genomic loci underlying fruit size, drupelet count, firmness, skin toughness, drupelet cohesion, post-harvest durability, and internal chemistry. In 2025 and 2026, we will harvest fruit from these breeding populations and capture the range of quantitative variation for these critical traits within the USDA germplasm. We will implement multiple approaches for investigating fruit firmness and texture in red raspberry, including testing compression force, penetration force, skin elasticity, and force required to separate drupelets. We will assess the relationships between data generated with these different approaches to understand which tools for measuring fruit firmness are most predictive of fruit crumbling as well as fruit leakage in post-harvest. Other traits to be considered will include prickle size and density on raspberry plants, early-/mid-/late-season flowering and ripening, and primocane vs floricane flowering habit.
We will generate high-throughput sequencing datasets for the 400 progeny and parents comprising the GWAS population. Individuals will be sequenced to average 10x genome coverage. Sequence data will be aligned to the red raspberry 'Finnberry' genome assembly and used to predict single nucleotide polymorphism (SNP) genomic variants. After QC and filtering of the SNP set, SNPs will be further processed into a subset of maximally informative loci using linkage disequilibrium pruning. The resulting set of SNPs will be fed into the GAPIT software for identifying statistically significant relationships between SNP marker genotypes and quantitative variation for specific raspberry traits that were measured. The 'Finnberry' genome and its corresponding structural and functional annotations will be used to identify genes putatively associated with these traits, and highly predictive SNP markers will be converted to single-marker assays (KASP, HRM) for implementing marker-assisted selection for fruit quality within the caneberry breeding program.