Chromosome-level genome assembly of IR64 near-isogenic line harboring Saltol reveals novel genomic regions associated with salinity tolerance in rice (Oryza sativa L.)
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Elsevier
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Climate change-induced sea level rise significantly exacerbates soil and groundwater salinization, posing a substantial threat to global agriculture, particularly impacting salt-sensitive crops like rice (Oryza sativa L.). Significant advancements have been made in identifying the genetic factors that influence salinity tolerance. A well-studied quantitative trait locus (QTL), known as Saltol, is located on chromosome 1 and provides notable salinity tolerance during the seedling stage by maintaining low ratios of Na+ to K+ in the shoots. Although considerable progress has been made in identifying genetic factors of salinity tolerance, Saltol QTL does not fully account for phenotypic variability under saline conditions. This study aims to comprehensively characterize additional genomic regions associated with salinity tolerance by using a high-quality genome assembly of the IR64 rice variety, a high-yielding and quality. We will also analyze its near-isogenic line (NIL), IR64-Saltol, which harbors Saltol QTL. Comparative genomic analyses identified 228 introgression segments from FL478, prominently on chromosomes 1, 2, 8, and 12, spanning a total of 7.04 Mb. Integrated QTL mapping highlighted 137 previously reported salinity tolerance loci from Pokkali populations, with significant overlaps observed in the introgression segments. Within these genomic regions, we identified 175 candidate genes, including transcription factors (MYB2, MYBY1), ion transporters (CCC2, CNGC17), and stress-responsive regulators (TPS10, IAA10), which implicates complex physiological networks in salinity adaptation. Our findings substantially expand the genetic framework available for breeding salt-tolerant rice varieties, providing critical resources to address agricultural challenges posed by salinization under ongoing climate change.
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salt tolerance, candidate genes, climate change, transcription factors, genomes, quantitative trait loci, marker-assisted selection, genetic resources, rice