RESUMO
Rice blast and bacterial leaf blight, are major disease, significantly threatens rice yield in all rice growing regions under favorable conditions and identification of resistance genes and their superior haplotypes is a potential strategy for effectively managing and controlling this devastating disease. In this study, we conducted a genome-wide association study (GWAS) using a diverse set of 147 rice accessions for blast and bacterial blight diseases in replications. Results revealed 23 (9 for blast and 14 for BLB) significant marker-trait associations (MTAs) that corresponded to 107 and 210 candidate genes for blast and BLB, respectively. The haplo-pheno analysis of the candidate genes led to the identification of eight superior haplotypes for blast, with an average SES score ranging from 0.00 to 1.33, and five superior haplotypes for BLB, with scores ranging from 1.52cm to 4.86cm superior haplotypes. Among these, superior haplotypes LOC_OS12G39700-H4 and LOC_Os06g30440-H33 were identified with the lowest average blast scores of 0.00-0.67, and superior haplotype LOC_Os02g12660-H39 exhibited the lowest average lesion length (1.88 - 2.06cm) for BLB. A total of ten accessions for blast and eight accessions for BLB were identified carrying superior haplotypes were identified. These haplotypes belong to aus and indx subpopulations of five countries (Bangladesh, Brazil, India, Myanmar, and Pakistan). For BLB resistance, eight accessions from six countries (Bangladesh, China, India, Myanmar, Pakistan, and Sri Lanka) and four subpopulations (aus, ind1A, ind2, and ind3) were identified carrying superior haplotypes. Interestingly, four candidate genes, LOC_Os06g21040, LOC_Os04g23960, LOC_Os12g39700, and LOC_Os01g24640 encoding transposon and retrotransposon proteins were among those with superior haplotypes known to play a crucial role in plant defense responses. These identified superior haplotypes have the potential to be combined into a single genetic background through haplotype-based breeding for a broader resistance spectrum against blast and bacterial blight diseases.
RESUMO
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/.
