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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Mapping QTLs controlling agronomic traits in the ‘attila’ × ‘CDC Go’ spring wheat population under organic management using 90K SNP array
Crop Science, Volume 57, No. 1, Year 2017
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Description
Our group previously reported five quantitative trait loci (QTL) associated with plant height, test weight, thousand-kernel weight, and grain protein content in a recombinant inbred line population derived from spring wheat (Triticum aestivum L.) cultivars ‘Attila’ and ‘CDC Go’, evaluated across three environments (2008–2010) under organic management and genotyped with 579 diversity arrays technology and Rht-B1 markers. No QTL was identified for flowering time, maturity, grain yield, and number of tillers across all three environments. In the present study, we reanalyzed the same phenotypic data with a subset of 1200 informative single-nucleotide polymorphic (SNP) markers out of the 90K SNP array and three gene-specific markers (Ppd-D1, Vrn-A1, and Rht-B1) to investigate if high marker density improves QTL detection. Here, five moderateand eleven minor-effect QTLs were detected across all three organic environments using the new genotypic data, including 13 QTLs that were not previously detected. Up to five QTLs were detected for each trait, except grain protein content, which individually accounted for 5.5 to 18.8% of phenotypic variance. For each trait, the total phenotypic and genetic variance explained by all detected QTLs varied from 9.3 to 39.4 and from 24.6 to 96.8%, respectively, which was much greater than in our previous study. One of the moderate-effect QTLs on 5A was coincidental for flowering time and maturity and mapped close to the Vrn- A1 gene, while the second moderate-effect coincidental QTL on 4B was associated with both plant height and maturity but was 27 cM from the Rht-B1 gene. Results from this study provide additional information for wheat researchers and organic wheat breeders. © Crop Science Society of America.
Authors & Co-Authors
Zou, Jun
Canada, Edmonton
University of Alberta
Semagn, Kassa
Canada, Edmonton
University of Alberta
Iqbal, Muhammad Arslan
Canada, Edmonton
University of Alberta
Pakistan, Islamabad
National Agricultural Research Center
N’Diaye, Amidou
United States, Manhattan
Kansas State University
Chen, Hua
Canada, Edmonton
University of Alberta
Asif, Muhammad S.
United States, Manhattan
Kansas State University
Navabi, Alireza
Canada, Saskatoon
University of Saskatchewan
Canada, Guelph
University of Guelph
Pozniak, Curtis Jerry
United States, Manhattan
Kansas State University
Canada, Saskatoon
University of Saskatchewan
Randhawa, Harpinder Singh
Canada, Ottawa
Agriculture and Agri-food Canada
Spaner, Dean M.
Canada, Edmonton
University of Alberta
Statistics
Citations: 27
Authors: 10
Affiliations: 7
Identifiers
Doi:
10.2135/cropsci2016.06.0459
ISSN:
0011183X
Research Areas
Genetics And Genomics
Study Design
Cross Sectional Study
Study Approach
Quantitative