Revealing Genetic Diversity in the Rice Breeding Lines (Oryza sativa x O. rufipogon) Based on Whole Genome Sequencing Variants (SNPs/InDels)

Whole genome sequencing makes it possible to find a vast number of DNA polymorphisms, including SNPs and InDels, between cultivars. Genetic variation between cultivars and the genomic sites of heritable characteristics may be quickly identified due to these DNA polymorphisms. The whole genomes of four rice lines, comprising two offspring lines(YR13 and YR32) and their parents ( Oryza sativa cv. Yamuna and Oryza rufipogon ), were resequenced in order to determine the sequence diversity resulting from interspecific hybridization using Illumina next-generation sequencing. The range of sequencing coverage was 18.46× to 27.51×, and the mapping efficiency against the reference genome of O. sativa Nipponbare was high (98.21–98.73%). Variant discovery indicated 452,810–1,393,901 polymorphisms per line, with transition/transversion ratios of 2.43–2.50 and SNPs accounting for the majority (88–91%). Functional annotation showed that 7.8–9.6% of variants occurred in exonic regions, with missense mutations being the most frequent (52–54%), while high-impact coding mutations accounted for less than 1%.Unique variants ranged 973–4,041, whereas 15,137 were common to all lines. The progeny lines primarily carried SNPs from a number of agronomically significant genes and QTLs, such as NOG1 (grain number), qSH1 and SH4 (seed shattering), GS2 (grain size), Hd1/Hd6 (heading date), Badh2 (aroma), Saltol (salt tolerance), and Sub1A (submergence tolerance), indicating successful introgression of trait-associated alleles. The transcription, transport, signal transduction, and carbohydrate/lipid metabolism pathways were shown to be enriched by Gene ontology and KEGG analysis. Low to moderate differentiation across lines was revealed by genome-wide Fst analysis (mean SNP Fst = 0.012; InDel Fst = 0.017), which reflected both parental contributions and new recombination patterns in progeny. These findings provide a thorough genetic resource for functional genomics and marker-assisted breeding in rice improvement.