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Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops
Since the inception of the theory and conceptual framework of genomic selection (GS), extensive research has been done on evaluating its efficiency for utilization in crop improvement. Though, the marker-assisted selection has proven its potential for improvement of qualitative traits controlled by...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864149/ https://www.ncbi.nlm.nih.gov/pubmed/35222548 http://dx.doi.org/10.3389/fgene.2022.832153 |
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author | Budhlakoti, Neeraj Kushwaha, Amar Kant Rai, Anil Chaturvedi, K K Kumar, Anuj Pradhan, Anjan Kumar Kumar, Uttam Kumar, Rajeev Ranjan Juliana, Philomin Mishra, D C Kumar, Sundeep |
author_facet | Budhlakoti, Neeraj Kushwaha, Amar Kant Rai, Anil Chaturvedi, K K Kumar, Anuj Pradhan, Anjan Kumar Kumar, Uttam Kumar, Rajeev Ranjan Juliana, Philomin Mishra, D C Kumar, Sundeep |
author_sort | Budhlakoti, Neeraj |
collection | PubMed |
description | Since the inception of the theory and conceptual framework of genomic selection (GS), extensive research has been done on evaluating its efficiency for utilization in crop improvement. Though, the marker-assisted selection has proven its potential for improvement of qualitative traits controlled by one to few genes with large effects. Its role in improving quantitative traits controlled by several genes with small effects is limited. In this regard, GS that utilizes genomic-estimated breeding values of individuals obtained from genome-wide markers to choose candidates for the next breeding cycle is a powerful approach to improve quantitative traits. In the last two decades, GS has been widely adopted in animal breeding programs globally because of its potential to improve selection accuracy, minimize phenotyping, reduce cycle time, and increase genetic gains. In addition, given the promising initial evaluation outcomes of GS for the improvement of yield, biotic and abiotic stress tolerance, and quality in cereal crops like wheat, maize, and rice, prospects of integrating it in breeding crops are also being explored. Improved statistical models that leverage the genomic information to increase the prediction accuracies are critical for the effectiveness of GS-enabled breeding programs. Study on genetic architecture under drought and heat stress helps in developing production markers that can significantly accelerate the development of stress-resilient crop varieties through GS. This review focuses on the transition from traditional selection methods to GS, underlying statistical methods and tools used for this purpose, current status of GS studies in crop plants, and perspectives for its successful implementation in the development of climate-resilient crops. |
format | Online Article Text |
id | pubmed-8864149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88641492022-02-24 Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops Budhlakoti, Neeraj Kushwaha, Amar Kant Rai, Anil Chaturvedi, K K Kumar, Anuj Pradhan, Anjan Kumar Kumar, Uttam Kumar, Rajeev Ranjan Juliana, Philomin Mishra, D C Kumar, Sundeep Front Genet Genetics Since the inception of the theory and conceptual framework of genomic selection (GS), extensive research has been done on evaluating its efficiency for utilization in crop improvement. Though, the marker-assisted selection has proven its potential for improvement of qualitative traits controlled by one to few genes with large effects. Its role in improving quantitative traits controlled by several genes with small effects is limited. In this regard, GS that utilizes genomic-estimated breeding values of individuals obtained from genome-wide markers to choose candidates for the next breeding cycle is a powerful approach to improve quantitative traits. In the last two decades, GS has been widely adopted in animal breeding programs globally because of its potential to improve selection accuracy, minimize phenotyping, reduce cycle time, and increase genetic gains. In addition, given the promising initial evaluation outcomes of GS for the improvement of yield, biotic and abiotic stress tolerance, and quality in cereal crops like wheat, maize, and rice, prospects of integrating it in breeding crops are also being explored. Improved statistical models that leverage the genomic information to increase the prediction accuracies are critical for the effectiveness of GS-enabled breeding programs. Study on genetic architecture under drought and heat stress helps in developing production markers that can significantly accelerate the development of stress-resilient crop varieties through GS. This review focuses on the transition from traditional selection methods to GS, underlying statistical methods and tools used for this purpose, current status of GS studies in crop plants, and perspectives for its successful implementation in the development of climate-resilient crops. Frontiers Media S.A. 2022-02-09 /pmc/articles/PMC8864149/ /pubmed/35222548 http://dx.doi.org/10.3389/fgene.2022.832153 Text en Copyright © 2022 Budhlakoti, Kushwaha, Rai, Chaturvedi, Kumar, Pradhan, Kumar, Kumar, Juliana, Mishra and Kumar. 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 | Genetics Budhlakoti, Neeraj Kushwaha, Amar Kant Rai, Anil Chaturvedi, K K Kumar, Anuj Pradhan, Anjan Kumar Kumar, Uttam Kumar, Rajeev Ranjan Juliana, Philomin Mishra, D C Kumar, Sundeep Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title | Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title_full | Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title_fullStr | Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title_full_unstemmed | Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title_short | Genomic Selection: A Tool for Accelerating the Efficiency of Molecular Breeding for Development of Climate-Resilient Crops |
title_sort | genomic selection: a tool for accelerating the efficiency of molecular breeding for development of climate-resilient crops |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864149/ https://www.ncbi.nlm.nih.gov/pubmed/35222548 http://dx.doi.org/10.3389/fgene.2022.832153 |
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