Submitted to: Joint Abstracts of the American Dairy Science and Society of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: March 12, 2007
Publication Date: July 8, 2007
Citation: Sonstegard, T.S., Keele, J.W., Harhay, G.P., Smith, T.P., Matukumalli, L.K., Van Tassell, C.P., Liu, G., Alexander, L.J. 2007. Creation of a Gene Atlas in cattle using sequence-based transcriptional profiling. [abstract] Joint Abstracts of the American Dairy Science and Society of Animal Science.
Numerous opportunities to advance the understanding of how heritable variation affects economically important traits are being provided through resources generated from the Bovine Genome Sequencing project. Success in these investigations relies upon the depth in which the draft sequence assembly is annotated. In humans and biomedical model species, extensive annotation to identify genes and report relative levels of expression in various tissues has been accomplished by creation of “Gene Atlas” databases that provide researchers instant access to the expression profile of a gene under study. Similarly, we are constructing a Bovine Gene Atlas (BGA) database that will house transcript profiles from 100 different tissues of the cow used to generate the draft genome sequence and her offspring. The transcript profiles are being derived from a “next generation” sequencing platform that is well-suited to underpin this effort. In the first five tissues sampled, an average of more than 5 million 20 bp cDNA sequence “tags” for each total RNA sample were generated. To assign identities and account for potential errors in tag sequence, a clustering pipeline was constructed using a modified version of Sagenhaft. The tag clusters derived from testes, two stages of uterus development, muscle, and placentome have mapped to more than 60,000 genome positions. This initial data indicated that relative levels of expression for nearly all genes, even those for rare and species-specific transcripts, can be determined. Such a framework of data will allow determination of regional transcriptional control, tissue phylogeny and interconnected gene networks. This data will be provided through a Web accessible, query-based database.