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

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.
Statistics
Citations: 27
Authors: 10
Affiliations: 7
Research Areas
Genetics And Genomics
Study Design
Cross Sectional Study
Study Approach
Quantitative