bioRxivGenomicsPreprint
Reference-guided comparative genomics of seven Indonesian rice cultivars identifies conserved gene space and trait-associated sequence candidates
Yekti Asih PurwestriiD, Adhityo WicaksonoiD, Siti NurbaitiiD, Nada Tazkia PurbaiD, Dewi RetnaningatiiD, Ratih RestianiiD, Nirma Kumalasari, Tri Rini NuringtyasiD, Valentina Dwi Suci HandayaniiD
Abstract
Indonesian rice cultivars represent valuable genetic resources, yet many remain poorly characterized at the genomic level. Here, we generated 95.40 Gb of PacBio HiFi sequence data from seven Indonesian rice cultivars and constructed cultivar-specific consensus genomes using the telomere-to-telomere Nipponbare reference AGIS1.0. Sequencing coverage ranged from 27.92x to 41.58x, and the resulting consensus genomes spanned 387.93-390.54 Mb, with BUSCO completeness of approximately 98.3-98.5%. OrthoFinder assigned 99.1% of predicted proteins to 40,737 orthogroups, including 27,514 core orthogroups represented across all seven cultivars, indicating a highly conserved predicted gene space within the reference-guided framework. Targeted analysis recovered 278 of 280 cultivar-by-locus combinations representing 40 genes or gene family entries associated with grain pigmentation, nitrogen and amino-acid metabolism, and starch properties. Comparative predicted protein analysis prioritized ANS1, SBE2b, SSIIa/ALK, Wx/GBSSI, OsAAP6/qPC1, and SSI as candidates for further investigation. Among 269 completed AGIS1.0-anchored promoter comparisons, 159 passed quality-control criteria, whereas 110 were flagged for gene-model, boundary, synteny, or structural concerns. Notably, these flagged comparisons accounted for more than 90% of the alignment-derived sequence variation, emphasizing the importance of rigorous quality control when interpreting apparent promoter divergence. Collectively, these reference-guided genomic resources provide a standardized framework for investigating sequence variation in Indonesian rice germplasm and prioritize testable coding and regulatory candidates for functional validation and future genomics-assisted crop improvement.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: variant calling
- research focus: database / resource
- approach: statistical model
- approach: matrix factorization
- Citations
- 0
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