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Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs

Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associa...

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Autores principales: Kumar, Pawan, Nimbal, Somveer, Sangwan, Rajvir Singh, Budhlakoti, Neeraj, Singh, Varsha, Mishra, Dwijesh Chandra, Sagar, Choudhary, Raju Ram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187916/
https://www.ncbi.nlm.nih.gov/pubmed/34122477
http://dx.doi.org/10.3389/fpls.2021.653270
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author Kumar, Pawan
Nimbal, Somveer
Sangwan, Rajvir Singh
Budhlakoti, Neeraj
Singh, Varsha
Mishra, Dwijesh Chandra
Sagar,
Choudhary, Raju Ram
author_facet Kumar, Pawan
Nimbal, Somveer
Sangwan, Rajvir Singh
Budhlakoti, Neeraj
Singh, Varsha
Mishra, Dwijesh Chandra
Sagar,
Choudhary, Raju Ram
author_sort Kumar, Pawan
collection PubMed
description Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker–trait associations for six different environments separately. A total of 38 significant marker–trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker–trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding.
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spelling pubmed-81879162021-06-10 Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs Kumar, Pawan Nimbal, Somveer Sangwan, Rajvir Singh Budhlakoti, Neeraj Singh, Varsha Mishra, Dwijesh Chandra Sagar, Choudhary, Raju Ram Front Plant Sci Plant Science Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker–trait associations for six different environments separately. A total of 38 significant marker–trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker–trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding. Frontiers Media S.A. 2021-05-26 /pmc/articles/PMC8187916/ /pubmed/34122477 http://dx.doi.org/10.3389/fpls.2021.653270 Text en Copyright © 2021 Kumar, Nimbal, Sangwan, Budhlakoti, Singh, Mishra, Sagar and Choudhary. 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
Kumar, Pawan
Nimbal, Somveer
Sangwan, Rajvir Singh
Budhlakoti, Neeraj
Singh, Varsha
Mishra, Dwijesh Chandra
Sagar,
Choudhary, Raju Ram
Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title_full Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title_fullStr Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title_full_unstemmed Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title_short Identification of Novel Marker–Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs
title_sort identification of novel marker–trait associations for lint yield contributing traits in upland cotton (gossypium hirsutum l.) using ssrs
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187916/
https://www.ncbi.nlm.nih.gov/pubmed/34122477
http://dx.doi.org/10.3389/fpls.2021.653270
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