Genome Wide Single Locus Single Trait, Multi-Locus and Multi-Trait Association Mapping for Some Important Agronomic Traits in Common Wheat (T. aestivum L.)
Open Access
- 21 July 2016
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 11 (7) , e0159343
Abstract
Genome wide association study (GWAS) was conducted for 14 agronomic traits in wheat following widely used single locus single trait (SLST) approach, and two recent approaches viz. multi locus mixed model (MLMM), and multi-trait mixed model (MTMM). Association panel consisted of 230 diverse Indian bread wheat cultivars (released during 1910–2006 for commercial cultivation in different agro-climatic regions in India). Three years phenotypic data for 14 traits and genotyping data for 250 SSR markers (distributed across all the 21 wheat chromosomes) was utilized for GWAS. Using SLST, as many as 213 MTAs (p ≤ 0.05, 129 SSRs) were identified for 14 traits, however, only 10 MTAs (~9%; 10 out of 123 MTAs) qualified FDR criteria; these MTAs did not show any linkage drag. Interestingly, these genomic regions were coincident with the genomic regions that were already known to harbor QTLs for same or related agronomic traits. Using MLMM and MTMM, many more QTLs and markers were identified; 22 MTAs (19 QTLs, 21 markers) using MLMM, and 58 MTAs (29 QTLs, 40 markers) using MTMM were identified. In addition, 63 epistatic QTLs were also identified for 13 of the 14 traits, flag leaf length (FLL) being the only exception. Clearly, the power of association mapping improved due to MLMM and MTMM analyses. The epistatic interactions detected during the present study also provided better insight into genetic architecture of the 14 traits that were examined during the present study. Following eight wheat genotypes carried desirable alleles of QTLs for one or more traits, WH542, NI345, NI170, Sharbati Sonora, A90, HW1085, HYB11, and DWR39 (Pragati). These genotypes and the markers associated with important QTLs for major traits can be used in wheat improvement programs either using marker-assisted recurrent selection (MARS) or pseudo-backcrossing method.Keywords
This publication has 77 references indexed in Scilit:
- A mixed-model approach for genome-wide association studies of correlated traits in structured populationsNature Genetics, 2012
- An efficient multi-locus mixed-model approach for genome-wide association studies in structured populationsNature Genetics, 2012
- Genome-wide association studies of 14 agronomic traits in rice landracesNature Genetics, 2010
- Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred linesNature, 2010
- Mixed linear model approach adapted for genome-wide association studiesNature Genetics, 2010
- Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their ApplicationThe American Journal of Human Genetics, 2010
- Epistasis — the essential role of gene interactions in the structure and evolution of genetic systemsNature Reviews Genetics, 2008
- A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environmentsTheoretical and Applied Genetics, 2005
- Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein contentFunctional & Integrative Genomics, 2005
- A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.)Theoretical and Applied Genetics, 2004