Joint calls

Associative expression and systems analysis of complex traits in oilseed rape / canola

  • Acronym ASSYST
  • Duration 3 years
  • Project leader Rod Snowdon, University of Giessen, Germany
  • Other project participants Pierre Fobert, National Research Council - Plant Biotechnology Institute, Saskatoon, Canada
    Andy Sharpe, National Research Council - Plant Biotechnology Institute, Saskatoon, Canada
    Sue Abrams, National Research Council - Plant Biotechnology Institute, Saskatoon, Canada
    Isobel Parkin, Agriculture and Agri-Food Canada, Saskatoon Research Centre, Saskatoon, Canada
    Benjamin Stich, University of Hohenhem, Germany
    Ian Bancroft, John Innes Centre, Norwich, UK
  • Funding Agriculture and Agri-Food Canada (AAFC), National Research Council - Plant Biotechnology Institute (NRC-PBI), Canada
    The German Research Foundation (DFG), Germany
    Biotechnological and Biological Sciences Research Council (BBSRC), UK
  • Total Granted budget € 2,063,489

Abstract

This study will utilise quantitative gene expression data from well-defined populations of segregating Brassica napus genotypes, and integrate the segregating transcriptome data with quantitative metabolite and phenotype data using a systems-genetics approach that combines an analysis of gene co-expression networks with expression QTL approaches. Furthermore, a public B. napus SNP array will be developed and used for association analyses in a large genotype diversity set of B. napus accessions. The expression of putative regulatory genes (i) for which eQTL hotspots are observed in the linkage mapping populations, and (ii) which are identified as candidates by systems genetics approaches based on global gene expression and hormone profiles, will be examined in the genotype diversity set by quantitative real-time PCR. This data will then be used for associative expression mapping. The work will initially focus on seedling development traits and their relationship to heterosis as a case study for a highly complex interactive system that is genetically very poorly understood, but is agronomically extremely important. The network analysis tools will also be applied for a systems analysis of important seed quality characters to identify key regulatory factors involved in biosynthesis of oil, protein and fibre components. The project will incorporate the most recent technological developments in the field of next-generation sequencing for ultra-deep transcriptome profiling, and will integrate gene co-expression network analysis, classical QTL analysis, genetical genomics and association genetics concepts in a manner that to date has not been used for functional genomics of complex traits in a crop plant.

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