Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)

Grain quality is the key concern for rice breeders and is paramount to consumer acceptability. We characterized a diverse subset of 198 rice accessions of 3 K Rice Genome Project (RGP) for grain quality attributes, specifically glycemic index %, total dietary fibre, oil %, protein, amylose, moisture...

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Autores principales: Sachdeva, Supriya, Singh, Rakesh, Bharadwaj, Rakesh, Jain, Antil, Singh, Vikas K., Singh, Uma Maheshwar, Kumar, Arvind, Singh, Gyanendra Pratap
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier Ltd. 2025
Materias:
Acceso en línea:https://hdl.handle.net/10568/179455
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author Sachdeva, Supriya
Singh, Rakesh
Bharadwaj, Rakesh
Jain, Antil
Singh, Vikas K.
Singh, Uma Maheshwar
Kumar, Arvind
Singh, Gyanendra Pratap
author_browse Bharadwaj, Rakesh
Jain, Antil
Kumar, Arvind
Sachdeva, Supriya
Singh, Gyanendra Pratap
Singh, Rakesh
Singh, Uma Maheshwar
Singh, Vikas K.
author_facet Sachdeva, Supriya
Singh, Rakesh
Bharadwaj, Rakesh
Jain, Antil
Singh, Vikas K.
Singh, Uma Maheshwar
Kumar, Arvind
Singh, Gyanendra Pratap
author_sort Sachdeva, Supriya
collection Repository of Agricultural Research Outputs (CGSpace)
description Grain quality is the key concern for rice breeders and is paramount to consumer acceptability. We characterized a diverse subset of 198 rice accessions of 3 K Rice Genome Project (RGP) for grain quality attributes, specifically glycemic index %, total dietary fibre, oil %, protein, amylose, moisture %, phytate, phenol, and starch content. A set of 5,53,229 single nucleotide polymorphism (SNP) markers obtained from the 3 K RG 1 M filtered SNP dataset used for genome wide association studies (GWAS). Consequently, we discovered 200 Quantitative trait nucleotides (QTNs) associated with the traits mentioned above distributed across the genome. These QTNs were grouped into 26 Quantitative Trait Loci (QTL) clusters, of which 20 clusters validated with at least three GWAS methods were considered reliable. Furthermore, 869 putative candidate genes were identified, many of which overlapped between quality traits. Integrating the GWAS, RNA-seq and qRT-PCR results, we finally identified two important genes (LOC_Os11g303700 and LOC_Os11g30500) associated with rice quality, and they may affect the grain quality by regulating the textural properties, appearance and eating quality. The findings of our study highlighted the role of molecular machinery in future rice breeding.
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spelling CGSpace1794552026-01-08T02:15:07Z Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.) Sachdeva, Supriya Singh, Rakesh Bharadwaj, Rakesh Jain, Antil Singh, Vikas K. Singh, Uma Maheshwar Kumar, Arvind Singh, Gyanendra Pratap rice genome-wide association studies grain quality candidate genes molecular genetics Grain quality is the key concern for rice breeders and is paramount to consumer acceptability. We characterized a diverse subset of 198 rice accessions of 3 K Rice Genome Project (RGP) for grain quality attributes, specifically glycemic index %, total dietary fibre, oil %, protein, amylose, moisture %, phytate, phenol, and starch content. A set of 5,53,229 single nucleotide polymorphism (SNP) markers obtained from the 3 K RG 1 M filtered SNP dataset used for genome wide association studies (GWAS). Consequently, we discovered 200 Quantitative trait nucleotides (QTNs) associated with the traits mentioned above distributed across the genome. These QTNs were grouped into 26 Quantitative Trait Loci (QTL) clusters, of which 20 clusters validated with at least three GWAS methods were considered reliable. Furthermore, 869 putative candidate genes were identified, many of which overlapped between quality traits. Integrating the GWAS, RNA-seq and qRT-PCR results, we finally identified two important genes (LOC_Os11g303700 and LOC_Os11g30500) associated with rice quality, and they may affect the grain quality by regulating the textural properties, appearance and eating quality. The findings of our study highlighted the role of molecular machinery in future rice breeding. 2025-10-08 2026-01-07T08:39:03Z 2026-01-07T08:39:03Z Journal Article https://hdl.handle.net/10568/179455 en Open Access application/pdf Elsevier Ltd. Sachdeva, Supriya, Rakesh Singh, Harshita Singh, Rakesh Bharadwaj, Antil Jain, Vikas K. Singh, Uma Maheshwar Singh, Arvind Kumar, and Gyanendra Pratap Singh. "Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)." Food Chemistry: Molecular Sciences 11 (2025): 100313.
spellingShingle rice
genome-wide association studies
grain quality
candidate genes
molecular genetics
Sachdeva, Supriya
Singh, Rakesh
Bharadwaj, Rakesh
Jain, Antil
Singh, Vikas K.
Singh, Uma Maheshwar
Kumar, Arvind
Singh, Gyanendra Pratap
Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title_full Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title_fullStr Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title_full_unstemmed Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title_short Genome-wide association studies for identification of QTLs and key candidate genes to improve grain quality in rice (Oryza sativa L.)
title_sort genome wide association studies for identification of qtls and key candidate genes to improve grain quality in rice oryza sativa l
topic rice
genome-wide association studies
grain quality
candidate genes
molecular genetics
url https://hdl.handle.net/10568/179455
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