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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Cereal Crops Improvement Research » Research » Publications at this Location » Publication #429572

Research Project: Improvement of Disease and Pest Resistance in Barley, Durum, Oat, and Wheat Using Genetics and Genomics

Location: Cereal Crops Improvement Research

Title: Characterization of oat chromosome rearrangements in advanced breeding lines and implications for genetic improvement

Author
item OLVEIRA, GUILHERME - South Dakota State University
item BEKELE, WUBISHET - Agriculture And Agri-Food Canada
item DARIVA, FRANCOIS DALPRA - South Dakota State University
item BAZZER, SUMANDEEP - South Dakota State University
item TINKER, NICHOLAS - Agriculture And Agri-Food Canada
item Fiedler, Jason
item Nandety, Raja Sekhar
item Jannink, Jean Luc
item CAFFE, MELANIE - South Dakota State University

Submitted to: Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/22/2026
Publication Date: 8/6/2026
Citation: Olveira, G., Bekele, W., Dariva, F., Bazzer, S., Tinker, N., Fiedler, J.D., Nandety, R., Jannink, J., Caffe, M. 2026. Characterization of oat chromosome rearrangements in advanced breeding lines and implications for genetic improvement. Theoretical and Applied Genetics. 139. Article 224. https://doi.org/10.1007/s00122-026-05332-4.
DOI: https://doi.org/10.1007/s00122-026-05332-4

Interpretive Summary: Oat is an important cereal crop that provides healthy food and feed grain and has a positive impact on soil health. The genome of oat has been shown to be quite variable, with many large rearrangements. In this study, we investigated the four major known arrangements variations in the breeding germplasm from South Dakota State University. We found that a single variation that previously conferred crown-rust resistance dictates a large portion of the overall genetic variation in the entire population. Additionally, we found an overall lack of genetic diversity around these rearrangements indicating that they were limiting genetic mixing after crossing. We also validated several gene regions found in previous studies that influenced traits such as grain yield and crown rust resistance. Genome-wide prediction models for these same traits could be improved when the large rearrangements were taken into account. Overall this information is useful to breeding programs becuase it identifies an important determinant of crossing outcomes and should be characterized to maximise genetic gain and cultivar development.

Technical Abstract: Large-scale chromosome rearrangements have shaped the evolution of Avena species, driving domestication and adaptation in cultivated oats (Avena sativa L.). The legacy of these reorganizations, including translocations and inversions, remain evident in oats, yet their frequency and impact on phenotypic and genotypic variability in breeding populations remains unclear. The objective of this study was to characterize chromosome rearrangements in 1,230 oat breeding lines using genotyping-by-sequencing and exploit this information in genomic regions’ discovery and genomic prediction. Principal component analysis (PCA) based on single-nucleotide polymorphisms (SNPs) identified distinct clusters at the known locations of 1A/1C translocation, 3C inversion, 4C inversion, and 7D inversion. The 1A/1C translocation clusters differentiated lines at this region and revealed broader genomic divergence in genome-wide PCA. Linkage disequilibrium (LD) was higher within rearranged regions across all lines but decreased within individual clusters. Genome-wide association studies identified markers for grain yield and adaptation traits, with some differences among cluster-based populations. Genomic prediction accuracies improved when cross-validation was performed within structural variant clusters rather than across the entire dataset. These results suggest that chromosome rearrangements are indicators of population stratification, reduce recombination rates, hinder gene discovery in significant genomic regions while affecting genomic prediction accuracy. Characterizing oat germplasm for structural variants can improve breeding decisions, from parental selection to genomic prediction optimization, ultimately accelerating genetic gains for key traits.