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QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management

Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP) array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1) markers on quantitative trait loci (QTL) detection in a recombinant inbred lines (RILs) population derived from a cross between two spring wheat (Tritic...

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Autores principales: Zou, Jun, Semagn, Kassa, Iqbal, Muhammad, Chen, Hua, Asif, Mohammad, N’Diaye, Amidou, Navabi, Alireza, Perez-Lara, Enid, Pozniak, Curtis, Yang, Rong-Cai, Randhawa, Harpinder, Spaner, Dean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291526/
https://www.ncbi.nlm.nih.gov/pubmed/28158253
http://dx.doi.org/10.1371/journal.pone.0171528
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author Zou, Jun
Semagn, Kassa
Iqbal, Muhammad
Chen, Hua
Asif, Mohammad
N’Diaye, Amidou
Navabi, Alireza
Perez-Lara, Enid
Pozniak, Curtis
Yang, Rong-Cai
Randhawa, Harpinder
Spaner, Dean
author_facet Zou, Jun
Semagn, Kassa
Iqbal, Muhammad
Chen, Hua
Asif, Mohammad
N’Diaye, Amidou
Navabi, Alireza
Perez-Lara, Enid
Pozniak, Curtis
Yang, Rong-Cai
Randhawa, Harpinder
Spaner, Dean
author_sort Zou, Jun
collection PubMed
description Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP) array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1) markers on quantitative trait loci (QTL) detection in a recombinant inbred lines (RILs) population derived from a cross between two spring wheat (Triticum aestivum L.) cultivars, ‘Attila’ and ‘CDC Go’, and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering), flowering time, maturity, plant height, test weight (grain volume weight), 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM) on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers), we identified a total of 14 QTLs associated with flowering time (1), maturity (2), plant height (1), grain yield (1), test weight (2), kernel weight (4), tillering (1) and grain protein content (2). Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61–66 cM), 4B (80–82 cM) and 5A (296–297 cM) harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r(2) ≤ 0.75) with SNP markers that mapped within the QTL confidence interval. Six of the 14 QTLs (one for flowering time and plant height each, and two for maturity and kernel weight each) were common between the conventional and organic management systems, which suggests issues in directly utilizing gene discovery results based on conventional management to make in detail selection (decision) for organic management.
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spelling pubmed-52915262017-02-17 QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management Zou, Jun Semagn, Kassa Iqbal, Muhammad Chen, Hua Asif, Mohammad N’Diaye, Amidou Navabi, Alireza Perez-Lara, Enid Pozniak, Curtis Yang, Rong-Cai Randhawa, Harpinder Spaner, Dean PLoS One Research Article Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP) array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1) markers on quantitative trait loci (QTL) detection in a recombinant inbred lines (RILs) population derived from a cross between two spring wheat (Triticum aestivum L.) cultivars, ‘Attila’ and ‘CDC Go’, and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering), flowering time, maturity, plant height, test weight (grain volume weight), 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM) on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers), we identified a total of 14 QTLs associated with flowering time (1), maturity (2), plant height (1), grain yield (1), test weight (2), kernel weight (4), tillering (1) and grain protein content (2). Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61–66 cM), 4B (80–82 cM) and 5A (296–297 cM) harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r(2) ≤ 0.75) with SNP markers that mapped within the QTL confidence interval. Six of the 14 QTLs (one for flowering time and plant height each, and two for maturity and kernel weight each) were common between the conventional and organic management systems, which suggests issues in directly utilizing gene discovery results based on conventional management to make in detail selection (decision) for organic management. Public Library of Science 2017-02-03 /pmc/articles/PMC5291526/ /pubmed/28158253 http://dx.doi.org/10.1371/journal.pone.0171528 Text en © 2017 Zou et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zou, Jun
Semagn, Kassa
Iqbal, Muhammad
Chen, Hua
Asif, Mohammad
N’Diaye, Amidou
Navabi, Alireza
Perez-Lara, Enid
Pozniak, Curtis
Yang, Rong-Cai
Randhawa, Harpinder
Spaner, Dean
QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title_full QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title_fullStr QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title_full_unstemmed QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title_short QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management
title_sort qtls associated with agronomic traits in the attila × cdc go spring wheat population evaluated under conventional management
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291526/
https://www.ncbi.nlm.nih.gov/pubmed/28158253
http://dx.doi.org/10.1371/journal.pone.0171528
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