ArticleFrontiers in plant science2022
Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 14 citations in OpenAlex.
- Genome-wide association studies for identifying SNPs and candidate genes associated with grain quality traits in rice (Oryza sativa L.).The plant genome · 2026Article
- GWAS and Regularised Regression Identify SNPs Associated with Candidate Genes for Stage-Specific Salinity Tolerance in Rice.Plants (Basel, Switzerland) · 2026Article
- Article
- Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Food chemistry. Molecular sciences · 2025Article
- Uncovering genetic determinants of antioxidant properties in Thai landrace rice through genome-wide association analysis.Scientific reports · 2025Article
- Molecular breeding approaches for sustainable rice blast management: recent advances and challenges.Frontiers in plant science · 2025Review
- Genome-wide association study and fine-mapping identify a major quantitative trait locus controlling hundred-seed weight in soybean.Frontiers in plant science · 2025Article
- Article
- Hybrid Rice Production: A Worldwide Review of Floral Traits and Breeding Technology, with Special Emphasis on China.Plants (Basel, Switzerland) · 2024Review
- New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study.BMC plant biology · 2024Article
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14 authors at 1 institution in 1 country.
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Abstract
Background: Basmati is a speciality segment in the rice genepool characterised by explicit grain quality. For the want of suitable populations, genome-wide association study (GWAS) in Basmati rice has not been attempted. Materials: To address this gap, we have performed a GWAS on a panel of 172 elite Basmati multiparent population comprising of potential restorers and maintainers. Phenotypic data was generated for various agronomic and grain quality traits across seven different environments during two consecutive crop seasons. Based on the observed phenotypic variation, three agronomic traits namely, days to fifty per cent flowering, plant height and panicle length, and three grain quality traits namely, kernel length before cooking, length breadth ratio and kernel length after cooking were subjected to GWAS. Genotyped with 80K SNP array, the population was subjected to principal component analysis to stratify the underlying substructure and subjected to the association analysis using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model. Results: We identified 32 unique MTAs including 11 robust MTAs for the agronomic traits and 25 unique MTAs including two robust MTAs for the grain quality traits. Six out of 13 robust MTAs were novel. By genome annotation, six candidate genes associated with the robust MTAs were identified. Further analysis of the allelic combinations of the robust MTAs enabled the identification of superior allelic combinations in the population. This information was utilized in selecting 77 elite Basmati rice genotypes from the panel. Conclusion: This is the first ever GWAS study in Basmati rice which could generate valuable information usable for further breeding through marker assisted selection, including enhancing of heterosis.
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