Extreme trait GWAS (Et-GWAS): Unraveling rare variants in the 3,000 rice genome.

Identifying high-impact, rare genetic variants associated with specific traits is crucial for crop improvement. The 3,010 rice genome (3K RG) dataset offers a valuable resource for discovering genomic regions with potential applications in crop breeding. We used Extreme Trait GWAS (Et-GWAS), employing bulk pooling and allele frequency measurement to efficiently extract rare variants from the 3K RG. This innovative approach facilitates the detection of associations between genetic variants and target traits, concentrating and quantifying rare alleles. In our study, on grain yield under drought stress, Et-GWAS successfully identified five key genes (OsPP2C11, OsK5.2, OsIRO2, OsPEX1, and OsPWA1) known for enhancing yield under drought. In addition, we examined the overlap of our results with previously reported qDTY-QTLs and observed that OsUCH1 and OsUCH2 genes were located within qDTY2.2 We compared Et-GWAS with conventional GWAS, finding it effectively capturing most candidate genes associated with the target trait. Validation with resistant starch showed similar results. To enhance user-friendliness, we developed a GUI for Et-GWAS; https://et-gwas.shinyapps.io/Et-GWAS/.

Codon Usage Provide Insights into the Adaptation of Rice Genes under Stress Condition.

Plants experience different stresses, i.e., abiotic, or biotic, and to combat them, plants re-program the expression of growth-, metabolism-, and resistance-related genes. These genes differ in their synonymous codon usage frequency and show codon usage bias. Here, we investigated the correlation among codon usage bias, gene expression, and underlying mechanisms in rice under abiotic and biotic stress conditions. The results indicated that genes with higher expression (up- or downregulated) levels had high GC content (≥60%), a low effective number of codon usage (≤40), and exhibited strong biases towards the codons with C/G at the third nucleotide position, irrespective of stress received. TTC, ATC, and CTC were the most preferred codons, while TAC, CAC, AAC, GAC, and TGC were moderately preferred under any stress (abiotic or biotic) condition. Additionally, downregulated genes are under mutational pressure (R2 ≥ 0.5) while upregulated genes are under natural selection pressure (R2 ≤ 0.5). Based on these results, we also identified the possible target codons that can be used to design an optimized set of genes with specific codons to develop climate-resilient varieties. Conclusively, under stress, rice has a bias towards codon usage which is correlated with GC content, gene expression level, and gene length.