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Title: | Genome Wide Single Locus Single Trait, Multi-Locus and Multi-Trait Association Mapping for Some Important Agronomic Traits in Common Wheat (T. aestivum L.) |
Other Titles: | Not Available |
Authors: | Vandana Jaiswal Vijay Gahlaut Prabina Kumar Meher Reyazul Rouf Mir Jai Prakash Jaiswal Atmakuri Ramakrishna Rao Harindra Singh Balyan Pushpendra Kumar Gupta |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute Plant Molecular Biology Lab, CSIR-National Botanical Research Institute, Lucknow, India Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, India Division of Plant Breeding & Genetics, Shere-Kashmir University of Agricultural Sciences & Technology of Jammu (SKUAST-J), Chatha, India Dept of Genetics & Plant Breeding, G.B. Pant University of Agriculture & Technology, Pantnagar, India |
Published/ Complete Date: | 2016-07-21 |
Project Code: | Not Available |
Keywords: | Genome wide association study (GWAS) multi-trait mixed model SSR markers QTLs |
Publisher: | Not Available |
Citation: | Jaiswal V, Gahlaut V, Meher PK, Mir RR, Jaiswal JP, Rao AR, et al. (2016) Genome Wide Single Locus Single Trait, Multi-Locus and Multi-Trait Association Mapping for Some Important Agronomic Traits in Common Wheat (T. aestivum L.). PLoS ONE 11(7): e0159343. https://doi.org/10.1371/journal.pone.0159343 |
Series/Report no.: | Not Available; |
Abstract/Description: | 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. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | PLOS One |
NAAS Rating: | 9.24 |
Impact Factor: | 3.24 |
Volume No.: | 11 |
Page Number: | 7 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | https://doi.org/10.1371/journal.pone.0159343 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/73738 |
Appears in Collections: | AEdu-IASRI-Publication AEdu-IASRI-Publication |
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