Version 1
: Received: 14 August 2024 / Approved: 15 August 2024 / Online: 15 August 2024 (10:45:32 CEST)
How to cite:
Subedi, M.; Bagwell, J. W.; Lopez, B.; Baik, B.-K.; Babar, M. A.; Mergoum, M. A Gwas Approach to Identify Novel Major-Effect Qtls for End-Use Quality Traits in Soft Red Winter Wheat. Preprints2024, 2024081141. https://doi.org/10.20944/preprints202408.1141.v1
Subedi, M.; Bagwell, J. W.; Lopez, B.; Baik, B.-K.; Babar, M. A.; Mergoum, M. A Gwas Approach to Identify Novel Major-Effect Qtls for End-Use Quality Traits in Soft Red Winter Wheat. Preprints 2024, 2024081141. https://doi.org/10.20944/preprints202408.1141.v1
Subedi, M.; Bagwell, J. W.; Lopez, B.; Baik, B.-K.; Babar, M. A.; Mergoum, M. A Gwas Approach to Identify Novel Major-Effect Qtls for End-Use Quality Traits in Soft Red Winter Wheat. Preprints2024, 2024081141. https://doi.org/10.20944/preprints202408.1141.v1
APA Style
Subedi, M., Bagwell, J. W., Lopez, B., Baik, B. K., Babar, M. A., & Mergoum, M. (2024). A Gwas Approach to Identify Novel Major-Effect Qtls for End-Use Quality Traits in Soft Red Winter Wheat. Preprints. https://doi.org/10.20944/preprints202408.1141.v1
Chicago/Turabian Style
Subedi, M., Md Ali Babar and Mohamed Mergoum. 2024 "A Gwas Approach to Identify Novel Major-Effect Qtls for End-Use Quality Traits in Soft Red Winter Wheat" Preprints. https://doi.org/10.20944/preprints202408.1141.v1
Abstract
Wheat is used for making many food products due to its diverse quality profile found among different wheat classes. Since laboratory analysis of these end-use quality traits is costly and time-consuming, genetic dissection of the traits is preferential. This study used a genome-wide association study (GWAS) of 10 end-use quality traits, including kernel protein, flour protein, flour yield, softness equivalence, solvent’s retention capacity, cookie diameter, and top-grain, in soft red winter wheat (SRWW) adapted to US southeast. The GWAS study included 266 SRWW genotypes that were evaluated in two locations over two years (2020-2022). A total of 27,466 single nucleotide markers were used and a total of 80 significant marker-trait associations were identified. There were 13 major effect quantitative trait loci (QTLs) explaining > 10% phenotypic variance out of which 12 were considered as novel. Five of the major effect QTLs were found to be stably expressed across multiple datasets, and four showed associations with multiple traits. Candidate genes were identified for eight of the major-effect QTLs including genes associated with starch biosynthesis and nutritional homeostasis in plants. These findings increase genetic comprehension of these end-use quality traits and could potentially be used for improving the quality of SRWW.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
