Editorial: Genetic association studies in oilseeds

Crop improvement traits that are significant for agriculture are genetically complex and regulated by polygenes. These polygenes are spread across crop genomes and mapped as genomic targets known as quantitative trait loci (QTLs). Genome-Wide Association (GWA) mapping is an effective plant breeding...

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Main Authors: Shobhana, V.G., Kirubakaran, Silvas J. P., Li, Song, Parthiban, T.P.
Format: Journal Article
Language:Inglés
Published: Frontiers Media 2024
Subjects:
Online Access:https://hdl.handle.net/10568/163812
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author Shobhana, V.G.
Kirubakaran, Silvas J. P.
Li, Song
Parthiban, T.P.
author_browse Kirubakaran, Silvas J. P.
Li, Song
Parthiban, T.P.
Shobhana, V.G.
author_facet Shobhana, V.G.
Kirubakaran, Silvas J. P.
Li, Song
Parthiban, T.P.
author_sort Shobhana, V.G.
collection Repository of Agricultural Research Outputs (CGSpace)
description Crop improvement traits that are significant for agriculture are genetically complex and regulated by polygenes. These polygenes are spread across crop genomes and mapped as genomic targets known as quantitative trait loci (QTLs). Genome-Wide Association (GWA) mapping is an effective plant breeding strategy for detecting natural allelic variations and associating haplotype polymorphisms with valuable agronomic traits such as yield, (a) biotic resistance, and nutritional quality traits. GWA has gained momentum over traditional mapping by documenting alleles/QTLs with a higher resolution by addressing the population structure and linkage disequilibrium (LD). The success of GWA relies on the germplasm choice, population size and diversity, molecular marker density, accurate phenotypic data, and appropriate statistical analyses. The biological value of the genomic regions identified by QTL or GWA warrants validation through diverse functional genomic approaches that drive crop improvement in commercial crops. Combining mapping and functional genomic strategies will enhance the use of genetic variation to improve economically valuable traits of crop plants. Association mapping studies in oilseed crops are at an early stage and are accelerating at a faster pace. Association mapping would unquestionably find genomic solutions to mitigate losses caused by both biotic and abiotic factors, with the success of identifying true associations depending on the marker with higher association signals and their positions within LD.
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spelling CGSpace1638122025-12-08T10:29:22Z Editorial: Genetic association studies in oilseeds Shobhana, V.G. Kirubakaran, Silvas J. P. Li, Song Parthiban, T.P. oilseeds yields quantitative trait loci Crop improvement traits that are significant for agriculture are genetically complex and regulated by polygenes. These polygenes are spread across crop genomes and mapped as genomic targets known as quantitative trait loci (QTLs). Genome-Wide Association (GWA) mapping is an effective plant breeding strategy for detecting natural allelic variations and associating haplotype polymorphisms with valuable agronomic traits such as yield, (a) biotic resistance, and nutritional quality traits. GWA has gained momentum over traditional mapping by documenting alleles/QTLs with a higher resolution by addressing the population structure and linkage disequilibrium (LD). The success of GWA relies on the germplasm choice, population size and diversity, molecular marker density, accurate phenotypic data, and appropriate statistical analyses. The biological value of the genomic regions identified by QTL or GWA warrants validation through diverse functional genomic approaches that drive crop improvement in commercial crops. Combining mapping and functional genomic strategies will enhance the use of genetic variation to improve economically valuable traits of crop plants. Association mapping studies in oilseed crops are at an early stage and are accelerating at a faster pace. Association mapping would unquestionably find genomic solutions to mitigate losses caused by both biotic and abiotic factors, with the success of identifying true associations depending on the marker with higher association signals and their positions within LD. 2024-05-08 2024-12-19T12:53:02Z 2024-12-19T12:53:02Z Journal Article https://hdl.handle.net/10568/163812 en Open Access Frontiers Media Shobhana, V. G.; Kirubakaran, Silvas J. P.; Li, Song and Parthiban, T. P. 2024. Editorial: Genetic association studies in oilseeds. Front. Genet., Volume 15
spellingShingle oilseeds yields quantitative trait loci
Shobhana, V.G.
Kirubakaran, Silvas J. P.
Li, Song
Parthiban, T.P.
Editorial: Genetic association studies in oilseeds
title Editorial: Genetic association studies in oilseeds
title_full Editorial: Genetic association studies in oilseeds
title_fullStr Editorial: Genetic association studies in oilseeds
title_full_unstemmed Editorial: Genetic association studies in oilseeds
title_short Editorial: Genetic association studies in oilseeds
title_sort editorial genetic association studies in oilseeds
topic oilseeds yields quantitative trait loci
url https://hdl.handle.net/10568/163812
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AT kirubakaransilvasjp editorialgeneticassociationstudiesinoilseeds
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