W453 Automated, High-Throughput Mutation Detection in Plants: Scanning Small to Large Gene Sizes with Fragment Analyzerô Technology

Date: Saturday, January 14, 2012
Time: 12:00 PM
Room: Pacific Salon 1
Deepak Dibya , Advanced Analytical Technologies, Inc., Ames, IA
Steve Siembieda , Advanced Analytical Technologies, Inc., Ames, IA
Jeremy Kenseth , Advanced Analytical Technologies, Inc., Ames, IA
TILLING® (Targeting Induced Local Lesions IN Genomes) is a well known reverse genetics technique designed to detect unknown SNPs (single nucleotide polymorphisms) in genes of interest using an enzymatic digestion, and is widely employed in plant and animal genomics. We present herein a new platform that offers a high-throughput, simplified modification of the assay methodology for mutation detection in pooled samples. The improved method requires less time, cost and is far more amenable to automation than most methods for TILLING® used presently. The new process eliminates the need for laborious slab gel preparations, use of labeled primers, and typically employed desalting cleanup steps. In addition, the new process accommodates a large dynamic range for the post PCR DNA concentration and combines a robust scoring capability with substantially reduced overall analysis times. The improved mutation detection process was evaluated using the Fragment Analyzer™ parallel capillary electrophoresis technology, to separate enzymatically cleaved DNA fragments in various ratios of mutant to wild type DNA in a 96-well high-throughput format. Various parameters critical to the optimization of the assay will be presented in detail. To verify the optimized method, several test and real samples have been evaluated on the Fragment Analyzer™ system. The samples comprised different plant species, various ploidy levels, a range of DNA concentrations and multiple pooling ratios. The results obtained with the Fragment Analyzer™ system were found to be in agreement with the expected results, confirming the efficacy of the new platform at identifying SNPs. Possibilities of using the developed heteroduplex methodologies for screening mutations in the human genome as well as for scanning large gene sizes will be discussed.