PARALLEL MINING OF NEW PEPTIDES FROM WHOLE PROTEOMES

点击翻译按钮获取中文摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Protein isoforms are an essential component for expanding functional complexity of the eukaryotic genomes. Current high-throughput studies of protein isoforms take advantage of advances in EST sequencing, exon array, exon-exon junction array, and next-generation sequencing at the mRNA transcript level. Systematic, proteome-scale characterization of protein isoforms directly at the protein/peptide level has not yet been reported. Compared with the indirect transcriptome-level characterizations, direct proteome-level characterization of protein isoforms can address the wide-spread concern that mRNA-level expressions and protein-level expression do not correlate well in a dynamical biological system. This project is motivated by the need for direct proteome-level characterization of protein isoforms to answer the following questions: 1) what genes can these new peptides be mapped to? 2) what are the patterns of alternative splicing or mis-splicing in the proteins found in biological samples of different species? and 3) what are the different gene regulatory mechanism or biological context that caused differential detection of panels of such new peptides? In this project, we propose to comprehensively catalog all hypothetical and functional new peptides characterized for each target proteome available from proteomics raw data in the ProteoCommons.org database (totaling around 21TB).We request approximately 50,000 SUs on Blacklight of PSC, to search for new peptides from these raw proteomics spectral data.