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Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement

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 elit...

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Autores principales: Abhijith, Krishnan P., Gopala Krishnan, S., Ravikiran, Kuram Tirumala, Dhawan, Gaurav, Kumar, Pankaj, Vinod, Kunnummal Kurungara, Bhowmick, Prolay Kumar, Nagarajan, Mariappan, Seth, Rakesh, Sharma, Ritesh, Badhran, Sourav Kumar, Bollinedi, Haritha, Ellur, Ranjith Kumar, Singh, Ashok Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760805/
https://www.ncbi.nlm.nih.gov/pubmed/36544876
http://dx.doi.org/10.3389/fpls.2022.994447
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author Abhijith, Krishnan P.
Gopala Krishnan, S.
Ravikiran, Kuram Tirumala
Dhawan, Gaurav
Kumar, Pankaj
Vinod, Kunnummal Kurungara
Bhowmick, Prolay Kumar
Nagarajan, Mariappan
Seth, Rakesh
Sharma, Ritesh
Badhran, Sourav Kumar
Bollinedi, Haritha
Ellur, Ranjith Kumar
Singh, Ashok Kumar
author_facet Abhijith, Krishnan P.
Gopala Krishnan, S.
Ravikiran, Kuram Tirumala
Dhawan, Gaurav
Kumar, Pankaj
Vinod, Kunnummal Kurungara
Bhowmick, Prolay Kumar
Nagarajan, Mariappan
Seth, Rakesh
Sharma, Ritesh
Badhran, Sourav Kumar
Bollinedi, Haritha
Ellur, Ranjith Kumar
Singh, Ashok Kumar
author_sort Abhijith, Krishnan P.
collection PubMed
description 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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spelling pubmed-97608052022-12-20 Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement Abhijith, Krishnan P. Gopala Krishnan, S. Ravikiran, Kuram Tirumala Dhawan, Gaurav Kumar, Pankaj Vinod, Kunnummal Kurungara Bhowmick, Prolay Kumar Nagarajan, Mariappan Seth, Rakesh Sharma, Ritesh Badhran, Sourav Kumar Bollinedi, Haritha Ellur, Ranjith Kumar Singh, Ashok Kumar Front Plant Sci Plant Science 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. Frontiers Media S.A. 2022-12-05 /pmc/articles/PMC9760805/ /pubmed/36544876 http://dx.doi.org/10.3389/fpls.2022.994447 Text en Copyright © 2022 Abhijith, Gopala Krishnan, Ravikiran, Dhawan, Kumar, Vinod, Bhowmick, Nagarajan, Seth, Sharma, Badhran, Bollinedi, Ellur and Singh https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Abhijith, Krishnan P.
Gopala Krishnan, S.
Ravikiran, Kuram Tirumala
Dhawan, Gaurav
Kumar, Pankaj
Vinod, Kunnummal Kurungara
Bhowmick, Prolay Kumar
Nagarajan, Mariappan
Seth, Rakesh
Sharma, Ritesh
Badhran, Sourav Kumar
Bollinedi, Haritha
Ellur, Ranjith Kumar
Singh, Ashok Kumar
Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title_full Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title_fullStr Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title_full_unstemmed Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title_short Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement
title_sort genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for basmati rice improvement
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9760805/
https://www.ncbi.nlm.nih.gov/pubmed/36544876
http://dx.doi.org/10.3389/fpls.2022.994447
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