Location: Cereal Crops Improvement Research
Title: Can GWAS information from oat breeding programs be used to develop higher-yield oat varieties? A case study in the SDSU Oat Breeding ProgramAuthor
OLIVEIRA, GUILHERME - South Dakota State University | |
BAZZER, SUMANDEEP - South Dakota State University | |
AYANA, GIRMA - South Dakota State University | |
Fiedler, Jason | |
Nandety, Raja Sekhar | |
CAFEE, MELANIE - South Dakota State University |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 7/10/2024 Publication Date: 7/21/2024 Citation: Oliveira, G., Bazzer, S., Ayana, G., Fiedler, J.D., Nandety, R., Cafee, M. 2024. Can GWAS information from oat breeding programs be used to develop higher-yield oat varieties? A case study in the SDSU Oat Breeding Program. Meeting Abstract. Interpretive Summary: Technical Abstract: Genome-wide association studies (GWAS) have been executed to identify regions controlling complex traits in oats (Avena sativa L.). Most studies have targeted traits related to grain yield to help oat breeders in the selection process to obtain varieties with higher productivity. However, GWAS research often employs diversity panels, and despite the benefits, applying these findings to breeding populations can be challenging due to interpopulation disparities, creating barriers to incorporating genomic knowledge into practical breeding routines. This study aimed to identify genomic regions associated with grain yield and grain yield-related traits through GWAS in breeding populations from the SDSU oat breeding program. We also explored whether this type of genetic information could be directly applied to breeding through incorporation into genomic prediction models for oat grain yield. Association mapping was conducted to investigate genetic associations for grain yield, plant height, heading date, lodging severity, snapback, and crown rust severity in six advanced oat breeding populations evaluated in multiple environments in six different years. We identified 156 significant SNPs associated with these traits, spanning 38 genomic regions across 18 oat chromosomes, highlighting a broad abundance of significant markers in the oat genome. Some genomic regions were novel, while others had been previously identified by other researchers, reinforcing the positive side to conducting GWAS studies in breeding populations, tracking which genomic information can be useful for these populations. Incorporating specific markers from significant genomic regions as fixed effects in a linear and additive genomic selection model increased prediction accuracies for grain yield. Nevertheless, these markers were not always positively associated with all grain yield-related traits. Our results demonstrated that molecular markers identified by GWAS in breeding populations can be incorporated as fixed effects into genomic selection models. However, careful consideration is essential to avoid selection for undesired phenotypes in other targeted traits. |