P0223
Genetic Variation Across Australian Bread Wheat Varieties

Date: Monday, January 14, 2013
Room: Grand Exhibit Hall
Kaitao Lai , University of Queensland, Brisbane, Australia
Michał T. Lorenc , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Hong Lee , University of Queensland, Brisbane, Australia
Paul J. Berkman , CSIRO Plant Industry, St Lucia, Australia
Paul Visendi , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Philipp Emanuel Bayer , University of Queensland, Brisbane, Australia
Pradeep Ruperao , University of Queensland, Brisbane, Australia
Kenneth Chan , University of Queensland, Brisbane, Australia
Sahana Manoli , University of Queensland, Brisbane, Australia
Jiri Stiller , CSIRO Plant Industry, St Lucia, Australia
Satomi Hayashi , University of Queensland, Brisbane, Australia
Jacqueline Batley , University of Queensland, Brisbane, Australia
David Edwards , University of Queensland, Brisbane, Australia
We have applied a novel algorithm SGSautoSNP for the discovery of large numbers of genomic SNPs across 16 Australian diverse bread wheat varieties. More than 10x whole genome shotgun Illumina paired read sequence data was generated through a collaboration with Bioplatforms Australia, and the data mapped to the draft assemblies of chromosomes 7A, 7B and 7D. This identified more than 3 million SNPs with a validated accuracy of 93%. SNP density varied along the lengths chromosome syntenic builds as well as between genomes.

SNP density analysis provides insights into the evolution and breeding history of this important crop. Furthermore, this SNP resource permits the application of high resolution skim based genotyping by sequencing, trait association and analysis of structural variation in populations. All SNPs are publically available on a GBrowse genome viewer at www.wheatgenome.info.

Back to: Genome Mapping, Tagging & Characterization: Wheat, Barley, Oat, and related
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