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ARS Home » Midwest Area » St. Paul, Minnesota » Plant Science Research » Research » Publications at this Location » Publication #404510
Research Project: Functional Genomics for Improving Nutrients and Quality in Alfalfa and Soybean

Location: Plant Science Research

Title: Multi-trait Genome-wide Association Studies of Sorghum bicolor regarding resistance to anthracnose, downy mildew, grain mold and head smut

Author
item Ahn, Ezekiel
item Prom, Louis
item MAGILL, CLINT - Texas A&M University

Submitted to: Pathogens
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/29/2023
Publication Date: 5/30/2023
Citation: Ahn, E.J., Prom, L.K., Magill, C.W. 2023. Multi-trait genome-wide association studies of sorghum bicolor regarding resistance to anthracnose, downy mildew, grain mold and head smut. Pathogens. 12(6). Article 779. https://doi.org/10.3390/pathogens12060779.
DOI: https://doi.org/10.3390/pathogens12060779

Interpretive Summary: Sorghum is an important cereal that supplies the daily needs of millions of people worldwide, but the crop is affected by many fungal diseases, costing millions of dollars each year. To minimize yield loss, it is essential to identify novel sources of resistance genes, and by applying a new statistical approach, we aim to identify novel resistance genes. In this study, multiple traits that cause resistance to fungal pathogens in sorghum were co-analyzed in contrast to previous studies that analyzed one trait at a time. By this approach, novel candidate resistance genes that haven't previously been reported were identified. The work is significant as it will provide more options of resistance sources to economically important sorghum diseases that can be applied to breeding programs to minimize yield loss in sorghum.

Technical Abstract: Sorghum is the fifth most important crop globally. Researching interactions between sorghum and fungal pathogens is essential to further elucidate plant defense mechanisms to biotic stress, which allows breeders to employ genetic resistance to disease. Multivariate linear mixed model (mvLMM) is widely applied for GWAS to detect genetic variants that affect multiple traits with correlations and/or different growth stages in plants. Multiple sorghum populations, including Sorghum Association Panel (SAP), Sorghum Mini Core Collection and Senegalese sorghum population, have been screened against various sorghum diseases such as anthracnose, downy mildew, grain mold and head smut, but the studies are generally performed in univariate framework. In this study, we performed GWAS based on the top principal components of defense-related multi-traits against fungal pathogens, resulting in the identification of new potential SNPs (S04_51771351, S02_66200847, S09_47938177, S08_7370058, S03_72625166, S07_17951013, S04_66666642 and S08_51886715) associated with sorghum's defense against these pathogens.