C24
Using Wheat BLAST Database to Search for Mutations and Expression

Date: Wednesday, January 13, 2016
Time: 11:30 AM
Room: California
Hans Vasquez-Gross , University of California Davis, Davis, CA
Ksenia V Krasileva , The Genome Analysis Centre, The Sainsbury Laboratory, Norwich, United Kingdom
Tyson R. Howell , University of California Davis, Davis, CA
Paul C. Bailey , The Genome Analysis Centre, Norwich, United Kingdom of Great Britain and Northern Ireland
Sarah Ayling , The Genome Analysis Centre, Norwich, United Kingdom of Great Britain and Northern Ireland
Cristobal Uauy , John Innes Centre, Norwich, England
Stephen Pearce , University of California Davis, Davis, CA
Jorge Dubcovsky , University of California, Davis, CA
The exome sequencing of an EMS mutagenized tetraploid wheat population comprised of 1,500 mutant lines enables a valuable in silico targeting of induced local legions in genomes (TILLING) reverse genetics tool for wheat researchers and breeders. The database includes 3.7 million mutations in the coding regions of ~82,000 genes, resulting in a high probability of deleterious mutations or truncations in the two homoeologs of each gene. This computer demonstration will show how to use this new tool to rapidly identify wheat genes of interest, detect mutations, and request corresponding seed stocks.  During the session, we will cover performing a BLAST search for gene of interest, finding potential high quality hits, and visualizing the results on a reference genome browser (JBrowse).  For each annotated gene, we have identified silent synonymous and intergenic changes as well as non-synonymous and truncation mutations (premature stop codons and splice site mutations).  This resource is available upon request from the UCDavis - Dubcovsky Lab at:  http://dubcovskylab.ucdavis.edu/wheat-tilling

We have also developed a complementary tool that allows the user to visualize the expression profiles of the different homoeologs of the wheat gene of interest in published RNAseq experiments.  Using BLAST users can identify a gene of interest, select one or more resulting genes and compare expression profiles through multiple different tissue types.  For more information visit: http://dubcovskylab.ucdavis.edu/wheat-expression-database

The combination of expression and mutant databases has the potential to accelerate functional studies of most of the wheat genes.