A genome-wide association study of plant height and primary branch number in rapeseed (Brassica napus)

Plant Sci. 2016 Jan:242:169-177. doi: 10.1016/j.plantsci.2015.05.012. Epub 2015 May 23.

Abstract

Crop plant architecture plays a highly important role in its agronomic performance. Plant height (PH) and primary branch number (PB) are two major factors that affect the plant architecture of rapeseed (Brassica napus). Previous studies have shown that these two traits are controlled by multiple quantitative trait loci (QTL); however, QTLs have not been delimited to regions less than 10cM. Genome-wide association study (GWAS) is a highly efficient approach for identifying genetic loci controlling traits at relatively high resolution. In this study, variations in PH and PB of a panel of 472 rapeseed accessions that had previously been analyzed by a 60k SNP array were investigated for three consecutive years and studied by GWAS. Eight QTLs on chromosome A03, A05, A07 and C07 were identified for PH, and five QTLs on A01, A03, A07 and C07 were identified for PB. Although most QTLs have been detected in previous studies based on linkage analyses, the two QTLs of PH on A05 and the QTL of PB on C07 were novel. In the genomic regions close to the GWAS peaks, orthologs of the genes involved in flower development, phytohormone biosynthesis, metabolism and signaling in Arabidopsis were identified.

Keywords: Association mapping; Brassica napus; Plant architecture; Plant height; Primary branch number; SNP.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Arabidopsis / genetics
  • Arabidopsis / growth & development
  • Arabidopsis / metabolism
  • Brassica napus / classification
  • Brassica napus / genetics*
  • Brassica napus / growth & development
  • Chromosome Mapping
  • Chromosomes, Plant / genetics
  • Genes, Plant / genetics
  • Genetic Association Studies / methods*
  • Genome, Plant / genetics*
  • Linkage Disequilibrium
  • Models, Genetic
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci / genetics*