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Updated: Jun 9, 2025

Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
Published on: January 3, 2025
Genetic diversity, population structure, and a genome-wide association study of sorghum lines assembled for breeding
Faizo Kasule1,2,3, Boris M E Alladassi2, Charles John Aru3
1Interdepartmental Genetics and Genomics (IGG), Iowa State University, Ames, IA, United States.
Abstract:
Sorghum is an important source of food and feed worldwide. Developing sorghum core germplasm collections improves our understanding of the evolution and exploitation of genetic diversity in breeding programs. Despite its significance, the characterization of the genetic diversity of local germplasm pools and the identification of genomic loci underlying the variation of critical agronomic traits in sorghum remains limited in most African countries, including Uganda. In this study, we evaluated a collection of 543 sorghum accessions actively used in Ugandan breeding program across two cropping seasons at NaSARRI, Uganda, under natural field conditions. Phenotypic data analysis revealed significant (p<0.01) variation among accessions for days to 50% flowering, plant height, panicle exsertion, and grain yield, with broad-sense heritability (H²) estimates of 0.54, 0.9, 0.81, and 0.48, respectively, indicating a high genetic variability for these traits. We used a newly developed genomic resource of 7,156 single nucleotide polymorphism (SNP) markers to characterize the genetic diversity and population structure of this collection. On average, the SNP markers exhibited moderately high polymorphic information content (PIC = 0.3) and gene diversity (He = 0.3), while observed heterozygosity (Ho = 0.07) was low, typical for self-pollinating crops like sorghum. Admixture-based models, PCA, and cluster analysis all grouped the accessions into two subpopulations with relatively low genetic differentiation. Genome-wide association study (GWAS) identified candidate genes linked to key agronomic traits using a breeding diversity panel from Uganda. GWAS analysis using three different mixed models identified 12 genomic regions associated with days to flowering, plant height, panicle exsertion, grain yield, and glume coverage. Five core candidate genes were co-localized with these significant SNPs. The SNP markers and candidate genes discovered provide valuable insights into the genetic regulation of key agronomic traits and, upon validation, hold promise for genomics-driven breeding strategies in Uganda.
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