4.5 Article

Genome-Wide Association Study Dissects the Genetic Architecture of Seed Weight and Seed Quality in Rapeseed (Brassica napus L.)

期刊

DNA RESEARCH
卷 21, 期 4, 页码 355-367

出版社

OXFORD UNIV PRESS
DOI: 10.1093/dnares/dsu002

关键词

Brassica napus; association mapping; SNP; seed quality; seed weight

资金

  1. Chinese National Basic Research and Development Program [2011CB109302]
  2. National Natural Science Foundation of China [31301360]
  3. Strategic Japanese-Chinese Cooperative Program on 'Climate Change' [2012DFG90290]
  4. National Science and Technology Pillar Program during the Twelfth Five-year Plan Period [2011BAD35B09]
  5. Chengguang Program for Young Scientists of Wuhan Municipal Government [2013070104010031]
  6. Biotechnology and Biological Sciences Research Council [BB/H004351/1, BB/E017363/1] Funding Source: researchfish
  7. BBSRC [BB/E017363/1, BB/H004351/1] Funding Source: UKRI

向作者/读者索取更多资源

Association mapping can quickly and efficiently dissect complex agronomic traits. Rapeseed is one of the most economically important polyploid oil crops, although its genome sequence is not yet published. In this study, a recently developed 60K Brassica Infinium (R) SNP array was used to analyse an association panel with 472 accessions. The single-nucleotide polymorphisms (SNPs) of the array were in silico mapped using 'pseudomolecules' representative of the genome of rapeseed to establish their hypothetical order and to perform association mapping of seed weight and seed quality. As a result, two significant associations on A8 and C3 of Brassica napus were detected for erucic acid content, and the peak SNPs were found to be only 233 and 128 kb away from the key genes BnaA.FAE1 and BnaC.FAE1. BnaA.FAE1 was also identified to be significantly associated with the oil content. Orthologues of Arabidopsis thaliana HAG1 were identified close to four clusters of SNPs associated with glucosinolate content on A9, C2, C7 and C9. For seed weight, we detected two association signals on A7 and A9, which were consistent with previous studies of quantitative trait loci mapping. The results indicate that our association mapping approach is suitable for fine mapping of the complex traits in rapeseed.

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