W323 Finding Function in Complex Crop Genomes

Date: Sunday, January 15, 2012
Time: 1:50 PM
Room: Pacific Salon 2
Hong Lee , University of Queensland, Australia
Paul J. Berkman , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Kaitao Lai , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Michal Lorenc , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Mike Imelfort , University of Queensland, Australia
Sahana Manoli , University of Queensland, Australia
Pradeep Ruperao , University of Queensland, Australia
Chris Duran , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Emma Campbell , University of Queensland, Australia
Alice C Hayward , University of Queensland, St Lucia, Australia
Jessica Dalton-Morgan , University of Queensland, Australia
Jiri Stiller , University of Queensland, Australia
Jacqueline Batley , University of Queensland, Australia
David Edwards , Australian Centre for Plant Functional Genomics, Brisbane, Australia
The genome sequence of an organism provides the basis for gene discovery, the analysis of genetic variation and the association of genomic variation with heritable traits. Second generation sequencing technologies and applied bioinformatics tools can provide an unprecedented insight into genome structure, variation and function. This technology is still in its infancy, yet is already making a huge impact in our understanding of biological processes. We have developed and applied novel bioinformatics tools and approaches for Illumina second generation sequence data analysis with the aim of understanding functional components of complex crop genomes. We have identified more than 1 million SNPs across the amphidiploid canola (Brassica napus) genome, with a validation accuracy of 96%. This information has been integrated with mapped genetic marker and trait information within searchable databases. The resulting tools enable the association of candidate genes with trait associated genetic markers and the study of Brassica genome evolution under selection. We have also characterised SNP density variation across the Brassica genomes which highlights regions and genes which may have undergone selection during domestication and breeding.