Identifying genetic determinants of forage sorghum [Sorghum bicolor (Moench)] adaptation through GWAS

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BackgroundForage sorghum is a highly valued crop in livestock feed production due to its versatility, adaptability, high productivity, and resilience under adverse environmental conditions, making it a crucial option for sustainable forage production. This study aimed to investigate ninety-five forage sorghum genotypes and identify the marker – trait associations (MTAs) in adaptive traits, including yield and flowering through genome-wide association studies (GWAS).ResultsUsing 41,854 polymorphic SNPs, a GWAS involving the GLM, MLM, and FarmCPU models was performed to analyse fourteen adaptive traits. The population structure revealed the presence of two subpopulation groups. Linkage disequilibrium (LD) plots showed varying degrees of LD decay across the chromosomes, with an average LD decay of 19.49 kbp. Twelve common significant QTNs, encoding 17 putative candidate genes, were simultaneously co-detected and studied by at least two or more GWAS methods. Three QTNs were associated to days to 50% flowering; two each to leaf-to-stem ratio and number of nodes per plant; and one each to plant height, leaf width, number of leaves per plant, stem girth, and internodal length. Six candidate genes were associated with days to 50% flowering, two each with leaf width, stem girth, leaf-to-stem ratio, and number of nodes per plant, and one each with plant height, number of leaves per plant, and internodal length.ConclusionFarmCPU was identified as the most suitable and effective among all the models for controlling both false positives and false negatives. Further in-depth analysis of the newly discovered QTNs may lead to the identification of new candidate genes for the trait of interest. These studies elucidate gene functions and could transform forage sorghum breeding through marker-assisted selection and transgenic approaches, accelerating the development of superior forage sorghum varieties and enhancing global food security.