C07
SNP Discovery in Complex Genomes using SGSautoSNP and autoSNPdb

Date: Sunday, January 13, 2013
Time: 3:50 PM
Room: California
Kaitao Lai , University of Queensland, Brisbane, Australia
Michał T. Lorenc , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Chris Duran , University of Melbourne, Melbourne, Australia
Satomi Hayashi , University of Queensland, Brisbane, Australia
Jiri Stiller , CSIRO Plant Industry, St Lucia, Australia
Hong Lee , University of Queensland, Brisbane, Australia
Paul Visendi , Australian Centre for Plant Functional Genomics, Brisbane, Australia
Pradeep Ruperao , University of Queensland, Brisbane, Australia
Sahana Manoli , University of Queensland, Brisbane, Australia
Manuel Zander , University of Queensland, Brisbane, Australia
Annaliese S. Mason , University of Queensland, Brisbane, Australia
Jacqueline Batley , University of Queensland, Brisbane, Australia
David Edwards , University of Queensland, Brisbane, Australia
SGSautoSNP is a pipeline for discovering SNPs from Illumina whole genome re-sequencing data. Read pairs are aligned to a reference and SNPs are called using an algorithm based on a modification of the original autoSNP method. Application in the complex genomes of wheat and canola led to the identification of several million SNPs with an accuracy of 93-95%. These predicted SNPs are suitable for high throughput genotyping by sequencing using the skim method.

The integrated AutoSNPdb pipeline identifies SNPs from assembled expressed gene sequence. The results are maintained in a custom relational database along with annotation information. User may identify sequences of interest through BLAST sequence comparison; keyword search of annotations derived from UniRef90, SwissProt, and GeneBank comparisons; GO annotations; or in genes corresponding to syntenic regions of reference genomes. SNP may also be browsed using a user-friendly graphical interface. The database currently hosts data for barley, Brassica, rice and wheat and is freely accessible at http://autosnpdb.appliedbioinformatics.com.au/.