Meeting Abstract
P1.136 Wednesday, Jan. 4 Automatic Transcriptome Analysis and Quest for Signaling Molecules In Basal Metazoans GIRARDO, D.O.*; CITARELLA, M.R.; KOHN, A.B.; MOROZ , L.L.; Whitney Lab for Marine Bioscience, University of Florida, St Augustine, FL; Whitney Lab for Marine Bioscience, University of Florida, St Augustine, FL; Whitney Lab for Marine Bioscience, University of Florida, St Augustine, FL; Whitney Laboratory for Marine Bioscience Dept of Neuroscience, Univ. of Florida, Florida abkohn@msn.com
Ctenophores and sponges are one of the most basally branched lineages of Metazoa. Their unique organization, development, cellular structures and simpler behaviors make them useful for understanding the origins and evolution of nervous systems. We hypothesize that secretory peptides can be the earliest intercellular signaling molecules. The 1st step in our analysis, we developed an automated transcriptome analysis pipeline fully integrated with a signaling peptide prediction system. Our pipeline is a “zero-click” analysis package for transforming sets of raw reads from next-generation sequencing platforms into a fully assembled, annotated, quantified, and visualized transcriptome project with minimal manual operation. The zero-click pipeline greatly reduces the complexity and time requirements of working with next-generation sequencing data by integrating a number of publicly-available software packages, including MIRA, Newbler, mpiBLAST, annot8r, and a suite of neuropeptide prediction programs, into a completely autonomous system. The pipeline actively monitors a relational database of jobs created by our next-generation sequencing platforms (including 454 and Ion Torrent), selects projects for analysis, submits raw reads for assembly, transforms intermediate files, and uploads the resulting assembly and annotation data without any work on the part of researchers. In the work presented here, this has allowed our lab to transform raw sequence data into a fully functional transcriptome database complete with predicted signaling molecules, within one to two days.
