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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Cereal Crops Improvement Research » Research » Research Project #447538

Research Project: Increasing Genetic Gain in Spring Oat Using Genetics and Genomics

Location: Cereal Crops Improvement Research

Project Number: 3060-21000-046-039-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Dec 1, 2024
End Date: Nov 30, 2025

Objective:
Oats are annual grasses that represent a diversity of species and ploidy levels. The most notable, spring oat (A. sativa L.), is a small grain food crop that is grown worldwide as a source of food, feed, and cosmetics products. Oat provides numerous health benefits that include lowering LDL cholesterol levels, reducing cardiovascular disease risks, and increasing satiety and glycemic index stability. In the past decade, global oat production has been increasingly challenged by environmental changes and its economic value has suffered due to competition with other high-value grain crops. Oat acreage has significantly declined in the U.S. and research into breeding of new cultivars has been limited. Fortunately, there is renewed interest for human consumption, and modern cultivars with superior yield and quality are required to meet this new need. To rapidly develop new oat varieties with enhanced disease resistance, high quality and high yield, modern breeding tools need to be developed, evaluated, and executed. This project aims to modernize oat breeding for the Upper Great Plains by collaborating on population development that enable genomic selection for the purpose of increasing genetic gain. Recent genomics-assisted breeding methods, like genomic selection (GS), have been demonstrated to reduce labor, space, and time associated with cultivar development. Today, traditional breeding and selection methods are most common in oat, with few active examples of GS because of limited genomics resources. Most molecular marker assays developed for oat are to target major-effect genes that confer resistance to single rust isolates. However, most traits important for yield, seed composition and quality, and durable disease resistance are quantitative. Selection on these traits requires repeated measurements of large segregating populations evaluated across multiple environments and years. GS bypasses early evaluation trials by utilizing prior observations of a training population to predict the performance of unobserved lines based on genome-wide markers (kinship). Compared to molecular markers developed from high-effect QTL, genomic estimated breeding values (GEBVs) are sensitive to minor QTL, which are important to consider when breeding for complex traits. The objectives of this research project are to develop, genotype, and evaluate new oat populations segregating for economically important traits, identify regions of the oat genome that influence yield, quality, and disease resistance, and use genomic prediction methods to identify parents for new crosses for the purpose of increasing genetic gain.

Approach:
The first objective of this study is to develop segregating populations in the greenhouse and advance progeny to the F4 generation using speed breeding techniques and advanced to the F5 in larger pots to scale-up seed. At this stage, all lines will be genotyped using a high-throughput marker set developed in-house by ARS Fargo. Single panicles from F5 individuals will be harvested in the greenhouse and planted in hill plots in the field for early evaluation and scale-up for early performance field trials. At this early stage, lines will be evaluated for grain yield, disease resistance, milling quality, and chemical composition traits. Seed will be harvested using ARS owned plot combine, cleaned and de-awned using ARS threshing equipment, and stored. Throughout the breeding cycle, genomic relationships of reference lines will be used to guide the selection of parents and progeny for these traits. Genome-wide markers will be used for genomic prediction in previously evaluated breeding material, segregating populations, and diverse oat germplasm. Reference population lines with insufficient seed will be scaled-up in the greenhouse and field nurseries for use in multi-environment yield trials, evaluated for important field traits, and grain harvested for measurement of quality traits. In addition, genome-wide association studies (GWAS) and linkage mapping will be performed to identify molecular markers associated with oat traits that can aid in breeding and selection efforts. All genetic and phenotypic data will be stored on password-protected drives and copied to the online database server, Breeding Insight (Oat), an ARS-funded project through Cornell University. All data generated from this project will be made publicly-available.