|FORD, D - Mississippi Valley State University|
|Arias De Ares, Renee|
|NEWSOME, A - Mississippi Valley State University|
Submitted to: Meeting Proceedings
Publication Type: Other
Publication Acceptance Date: 10/17/2010
Publication Date: 12/9/2010
Citation: Ford, D., Arias, R.S., Ballard, L.L., Scheffler, B.E., Duke, M.V., Simpson, S.A., Newsome, A. 2010. UPIC + GO: Zeroing in on informative markers. Eighth Annual Rocky Mountain Bioinformatics Conference, International Society of Computational Biology (ISCB), December 09-11, 2010, Aspen, CO. Meeting Proceedings.
Interpretive Summary: not required
Technical Abstract: Microsatellites/SSRs (simple sequence repeats) have become a powerful tool in genomic biology because of their broad range of applications and availability. An efficient method recently developed to generate microsatellite-enriched libraries used in combination with high throughput DNA pyrosequencing with Roche 454 allow isolation of large number of microsatellites. Although very effective, screening hundreds of microsatellites on large number of samples can be expensive. We introduce UPIC + GO as a cost-effective tool that will zero in on informative markers with discrimination power. This approach is an extension of UPIC, Unique Pattern Informative Combinations, which provides users with a more economical plan for choosing which markers to run in an experiment based on the obtainable information and UPIC scores . We used as a model system Macrophomina phaseolina, a soilborne fungus that causes charcoal rot in numerous plant species. Sequences were assembled into contigs and primers were designed on repeat regions. Blast2GO was used to annotate sequences, and primers were screened on 24 isolates of M. phaseolina. DNA fingerprinting provided amplicon distinction which was validated with GeneMapper analysis. UPIC scores were calculated and used in association with the annotation to make biological inferences about the isolates. Incorporating a priori knowledge about the function of a discriminative marker will enhance the selection process in experiments in a cost-effective manner.