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Identifying genomic regions associated with key agro-morphological traits in soft red winter wheat using genome-wide association study

Madhav Subedi

Madhav Subedi

Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Griffin Campus, Griffin, Georgia, USA

Contribution: Conceptualization, Data curation, Formal analysis, ​Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

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John W. Bagwell

John W. Bagwell

Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Griffin Campus, Griffin, Georgia, USA

Contribution: Data curation, Writing - review & editing

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Bikash Ghimire

Bikash Ghimire

Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Griffin Campus, Griffin, Georgia, USA

Department of Plant Pathology, University of Georgia, Griffin Campus, Griffin, Georgia, USA

Contribution: Formal analysis, Writing - review & editing

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Benjamin Lopez

Benjamin Lopez

Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin Campus, Griffin, Georgia, USA

Contribution: Data curation, Writing - review & editing

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Suraj Sapkota

Suraj Sapkota

USDA-ARS, Small Grains and Potato Germplasm Research Unit, Aberdeen, Idaho, USA

Contribution: Conceptualization, Writing - review & editing

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Md. Ali Babar

Md. Ali Babar

Department of Agronomy, University of Florida, Gainesville, Florida, USA

Contribution: Writing - review & editing

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Mohamed Mergoum

Corresponding Author

Mohamed Mergoum

Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Griffin Campus, Griffin, Georgia, USA

Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin Campus, Griffin, Georgia, USA

Correspondence

Mohamed Mergoum, Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Griffin Campus, Griffin, GA 30223, USA. Email: [email protected]

Contribution: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing - review & editing

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First published: 19 May 2024

Assigned to Associate Editor Alexander Lipka.

Abstract

Agro-morphological traits play a significant role in the adaptation of wheat to diverse agroecosystems. Genetic understanding of these traits is crucial to develop cultivars adapted to specific environments and maximize their productivity. This is a comprehensive genome-wide association study (GWAS) of 230 diverse lines of soft red winter wheat for identifying quantitative trait loci (QTLs) related to eight key agro-morphological traits. The diversity panel was evaluated in two locations for three consecutive years (2020–2023). A total of 150 significant marker–trait associations were detected, including 65 for three flag leaf traits, 35 for peduncle length, 33 for plant height, 16 for heading date, and one for plant vigor using 27,466 single nucleotide polymorphism (SNP) markers. Eleven high-confidence major-effect QTLs explaining greater than 10% phenotypic variance were detected, of which seven were stable, and one showed an association with plant height and peduncle length. QTLs possibly allelic for important dwarfing (Rht23) and vernalization (Vrn-B1) genes were identified. Six QTLs, QFlw.uga-1A, QPdl.uga-1A, QFlw.uga-2B.2, QPdl.uga-5A, QPdl.uga-7A, and QPht.uga-7B, are presumed to be novel, and nearby candidate gene(s) were identified for all except QPdl.uga-1A. The pyramiding of favorable alleles from major-effect QTLs was found to have significant improvement in peduncle length (shortened by 5 cm), flag leaf width (increased by 0.18 cm), and plant height (shortened by 11 cm). This study has improved our genetic understanding of important agro-morphological traits. These results, upon further validation, can be used in breeding for desirable plant architecture to improve wheat yield potential.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

DATA AVAILABILITY STATEMENT

The phenotype and genotype data are available in Tables S1 and S3, respectively. The GBS SRA data generated for this panel can be accessed at NCBI using accession number PRJNA578088 (https://www.ncbi.nlm.nih.gov//bioproject/PRJNA578088). The R-codes utilized for this study can be publicly accessed in a GitHub repository (https://github.com/beingmadhav/GWAS-Agro-morpho-traits).