Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L

Li, Lun, Long, Yan, Zhang, Libin, Dalton-Morgan, Jessica, Batley, Jacqueline, Yu, Longjiang, Meng, Jinling and Li, Maoteng (2015) Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L. PLoS One, 10 3: . doi:10.1371/journal.pone.0119425


Author Li, Lun
Long, Yan
Zhang, Libin
Dalton-Morgan, Jessica
Batley, Jacqueline
Yu, Longjiang
Meng, Jinling
Li, Maoteng
Title Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2015-03-19
Year available 2015
Sub-type Article (original research)
DOI 10.1371/journal.pone.0119425
Open Access Status DOI
Volume 10
Issue 3
Total pages 18
Place of publication San Francisco, CA United States
Publisher Public Library of Science
Language eng
Formatted abstract
The prediction of the flowering time (FT) trait in Brassica napus based on genome-wide markers and the detection of underlying genetic factors is important not only for oilseed producers around the world but also for the other crop industry in the rotation system in China. In previous studies the low density and mixture of biomarkers used obstructed genomic selection in B. napus and comprehensive mapping of FT related loci. In this study, a high-density genome-wide SNP set was genotyped from a double-haploid population of B. napus. We first performed genomic prediction of FT traits in B. napus using SNPs across the genome under ten environments of three geographic regions via eight existing genomic predictive models. The results showed that all the models achieved comparably high accuracies, verifying the feasibility of genomic prediction in B. napus. Next, we performed a large-scale mapping of FT related loci among three regions, and found 437 associated SNPs, some of which represented known FT genes, such as AP1 and PHYE. The genes tagged by the associated SNPs were enriched in biological processes involved in the formation of flowers. Epistasis analysis showed that significant interactions were found between detected loci, even among some known FT related genes. All the results showed that our large scale and high-density genotype data are of great practical and scientific values for B. napus. To our best knowledge, this is the first evaluation of genomic selection models in B. napus based on a high-density SNP dataset and large-scale mapping of FT loci.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Agriculture and Food Sciences
Official 2016 Collection
 
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