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From Data to Knowledge: translating functional genomics data into information for livestock production

Friday, August 22, 2014: 5:00 PM
Bayshore Grand Ballroom E-F (The Westin Bayshore)
Fiona McCarthy , University of Arizona, Tucson, AZ
Cathy R Gresham , Mississippi State University, Starkville, MS
James E. Koltes , Iowa State University, Ames, IA
Mark T Arick , Mississippi State University, Starkville, MS
Eric Lyons , University of Arizona, Tucson, AZ
Matt W Vaughn , Texas Advance Computing Center, University of Texas, Austin, TX
Eric T Dawson , Texas Advanced Computing Center, Austin, TX
Nicole Hopkins , University of Arizona, Tucons, AZ
Shane C Burgess , University of Arizona, Tucson, AZ
Abstract Text: New sequencing technologies enable the generation of an increasing number of livestock genomes. However using this data to understand how changes in the genotype affect function is hindered by poor annotation. For example, the Gene Ontology (GO) is routinely used for analyzing functional genomics data, however the GO does not include all key aspects affecting agricultural production (e.g. does not capture information about disease states or tissue expression). Moreover, technologies such as RNASeq identify many novel genes that have no known function. We have integrated new and existing tools to rapidly provide a first pass functional annotation for transcriptome data based upon sequence analysis of conserved protein motifs and sequence homology to better annotate genes. The result of this pipeline is a set of GO and pathway annotations that can be used to determine functional enrichment in a set of differentially expressed genes.

Keywords:

bioinformatics

Gene Ontology

functional genomics