Molecular Breeding

, 35:143 | Cite as

Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches

  • Humberto A. Gajardo
  • Benjamin Wittkop
  • Braulio Soto-Cerda
  • Erin E. Higgins
  • Isobel A. P. Parkin
  • Rod J. Snowdon
  • Maria L. Federico
  • Federico L. Iniguez-LuyEmail author


Single nucleotide polymorphisms (SNPs) have rapidly become the molecular marker of choice in plant and animal association mapping (AM) studies. In this work, a genome-wide association study (GWAS) and candidate quantitative trait loci (cQTL) approaches were used to identify SNP markers associated with seed quality traits, in a Brassica napus L. association panel composed of 89 adapted winter oilseed rape accessions. Six seed quality traits (oil and protein content, linolenic acid, total glucosinolates, hemicellulose and cellulose content) were evaluated in two different locations for two seasons. For GWAS, 4025 SNP markers evenly distributed along the B. napus genome were genotyped using a 6K Illumina array platform. For cQTL, 100 SNP markers previously discovered in genomic regions underlying seed quality QTL were genotyped using a competitive allele-specific PCR (KASPar). Analysis of the population structure revealed the presence of two weakly differentiated subpopulations (F ST  = 0.037), with 82 % of the pairwise kinship comparisons ranging from 0 to 0.1. The GWAS approach resulted in the identification of 17 and 5 significant associations for seed glucosinolate content and seed hemicellulose content, respectively. The cQTL approach identified 4 significant associations for seed glucosinolate content and 6 significant associations for seed hemicellulose content. The associated SNPs were consistently identified across environments and were mapped to previously reported QTL. These results illustrate the suitability of AM to identify SNP markers associated with seed quality traits in B. napus.


Association mapping Brassica napus Seed quality SNP Glucosinolate Hemicellulose 



The authors would like to thank Katherine Andara for her technical assistance. We acknowledge Fondecyt 1100732, Proyecto Fortalecimiento R13F1001, Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) Regional Program and the Araucania Regional Government/CGNA/R10C1001 and INIA for its support providing laboratory infrastructure. HG was supported by Becas de Magíster Nacional—CONICYT No: 22121770.

Supplementary material

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Humberto A. Gajardo
    • 1
    • 2
  • Benjamin Wittkop
    • 3
  • Braulio Soto-Cerda
    • 1
  • Erin E. Higgins
    • 4
  • Isobel A. P. Parkin
    • 4
  • Rod J. Snowdon
    • 3
  • Maria L. Federico
    • 1
  • Federico L. Iniguez-Luy
    • 1
    Email author
  1. 1.Genomics and Bioinformatics UnitAgriaquaculture Nutritional Genomic Center (CGNA)TemucoChile
  2. 2.Faculty of Agricultural Science, Graduate SchoolUniversidad Austral de ChileValdiviaChile
  3. 3.Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and NutritionJustus Liebig UniversityGiessenGermany
  4. 4.Agriculture and Agri-Food CanadaSaskatoonCanada

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