Population Structure, Genetic Diversity, and Genome-Wide Association Analysis of Eastern African Rice Landraces for Climate Resilience Breeding: The case of complete submergence tolerance

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Abstract

Rice landraces remain a crucial reservoir of novel alleles for stress-tolerance and climate-resilience breeding in Africa. East Africa harbors a rich diversity of Oryza sativa germplasm that is under investigated for their potential to improve stress tolerance. This study characterized a panel of 260 Oryza sativa landraces collected from East Africa using whole genome sequencing and phenotypic evaluation under complete submergence stress. Following a genotype-by-sequencing approach, the study identified 168,091 high-quality SNP markers revealing a panel with high genetic diversity, moderate heterozygosity of 0.062, and complex population structure. Population structure analysis of the panel displayed three major subpopulations with extensive admixture, indicating long-term gene flow and local adaptation of the landraces. Genome-wide linkage disequilibrium decay at r 2  = 0.2 is approximately 35kb, revealing moderate mapping resolution. To explore the breeding relevance of the panel, the study carried out a genome-wide association analysis (GWAS) for complete submergence tolerance following a linear mixed model (LMM). GWAS revealed 11 loci associated with submergence tolerance across chromosomes 2, 4, 6, 8, 9, 10, and 11. Candidate gene mining within a 10kb linkage disequilibrium (LD) window found genes involved in cytokinin and auxin signaling, transcription regulation under oxygen-deprived environment, stress signal transduction, and cellular maintenance activities. The study findings present the panel as a genetic resource for breeding strategies in the region and as a novel resource for improving abiotic stress, including submergence tolerance. The findings provide a foundation for functional validation and realistic targets for marker-assisted introgression to improve productivity in rice-producing regions of Africa.

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