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Updated: Aug 8, 2026

Analysis of Chromosome Segregation, Histone Acetylation, and Spindle Morphology in Horse Oocytes
Published on: May 11, 2017
Characterization of oat chromosome rearrangements in advanced breeding lines and implications for genetic improvement
Guilherme Oliveira1, Wubishet Bekele2, Françoise Dalprá Dariva1
1Department of Agronomy, Horticulture, and Plant Science, South Dakota State University (SDSU), Brookings, SD, USA.
Abstract:
Large-scale chromosomal rearrangements or structural variants (SVs) have shaped the evolution of Avena species, driving domestication and adaptation in oats (Avena sativa L.). The legacy of these reorganizations, including translocations and inversions, remains evident, yet their frequency and impact on phenotypic and genotypic variability in oat breeding populations remain unclear. The objective of this study was to characterize chromosome rearrangements in 1230 oat breeding lines using genotyping-by-sequencing and to utilize this information in genomic loci discovery and 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 distribution of the clusters of the four rearrangements in the genome-wide diversity space of our panel confirmed the role of SVs in population structure, with 1A/1C showing the most significant divergence. Suppression of recombination due to SVs was shown by higher linkage disequilibrium (LD) observed in all samples compared to lines within individual SV clusters. Genome-wide association studies (GWAS) identified markers for grain yield and agronomic traits, with some differences among cluster-based populations. Genomic prediction accuracies improved when cross-validation was performed within SV clusters rather than across the entire dataset. However, using SV clusters as covariates did not improve GWAS and prediction accuracies. These results suggest that SVs cause population stratification, reduce recombination rates, hinder gene discovery, and affect genomic prediction accuracy. Characterizing oat germplasm for SVs can improve breeding decisions, from optimizing parental selection to enhancing genomic predictions, accelerating genetic gains for key traits.
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