Dataset Information

MRMPath and MRMutation, Facilitating Discovery of Mass Transitions for Proteotypic Peptides in Biological Pathways Using a Bioinformatics Approach.

ABSTRACT: Quantitative proteomics applications in mass spectrometry depend on the knowledge of the mass-to-charge ratio (m/z) values of proteotypic peptides for the proteins under study and their product ions. MRMPath and MRMutation, web-based bioinformatics software that are platform independent, facilitate the recovery of this information by biologists. MRMPath utilizes publicly available information related to biological pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. All the proteins involved in pathways of interest are recovered and processed in silico to extract information relevant to quantitative mass spectrometry analysis. Peptides may also be subjected to automated BLAST analysis to determine whether they are proteotypic. MRMutation catalogs and makes available, following processing, known (mutant) variants of proteins from the current UniProtKB database. All these results, available via the web from well-maintained, public databases, are written to an Excel spreadsheet, which the user can download and save. MRMPath and MRMutation can be freely accessed. As a system that seeks to allow two or more resources to interoperate, MRMPath represents an advance in bioinformatics tool development. As a practical matter, the MRMPath automated approach represents significant time savings to researchers.

SUBMITTER: Crasto C

PROVIDER: S-EPMC3570921 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MRMPath and MRMutation, Facilitating Discovery of Mass Transitions for Proteotypic Peptides in Biological Pathways Using a Bioinformatics Approach.

Crasto Chiquito C Narne Chandrahas C Kawai Mikako M Wilson Landon L Barnes Stephen S

Advances in bioinformatics 20130129

Quantitative proteomics applications in mass spectrometry depend on the knowledge of the mass-to-charge ratio (m/z) values of proteotypic peptides for the proteins under study and their product ions. MRMPath and MRMutation, web-based bioinformatics software that are platform independent, facilitate the recovery of this information by biologists. MRMPath utilizes publicly available information related to biological pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. All the p ...[more]

PMID: 23424586

Similar Datasets

Project description:Long noncoding RNA (lncRNA) refers to the family of RNA transcripts with more than 200 nucleotides in length, but cannot encode proteins. lincRNA (long intergenic noncoding RNA) is a subset of lncRNA that do not overlap with known genes. Increasing evidences have shown that some of these transcripts do in fact contain open reading frames (ORFs) to code short peptides, and do have significant functional roles within the cells. However, many of these peptides remain unannotated and uncharacterized. This study proposes a workflow integrating proteomics, transcriptomics and bioinformatics specifically for lincRNA-encoded peptide discovery. The workflow was tested on the mouse kidney inner medulla (IM), a region that contains the collecting duct system responsible for regulated water transport. In brief, short peptides (from 2 to 20 kDa) were enriched by tricine protein gel and in-gel trypsinized into peptides, then analyzed using high resolution mass spectrometry. However, to match mass fragment ion spectra to peptide sequences requires a reference peptide sequence database which are not available for the noncoding transcripts, and must be generated de novo in the sample of interest. We modified the RNA-Seq mapping workflow by filtering out coding reads first to better quantitate the noncoding transcript expressions. Also, a rule-based ORF prediction was implemented to select one best predicted ORF per noncoding transcript to construct the peptide library. Candidates were further evaluated using several quality control criteria and bioinformatics tools. Three candidates, conserved in rat and human, passed all criteria, maybe truly novel coding genes. In summary, we present a workflow based on the modern transcriptomics and proteomics technologies for lincRNA-encoded peptide discovery. A computational challenge is to generate a hypothetical lincRNA-encoded peptide database for peptide-mass spectra matching. With this workflow, we discovered three previously unannotated peptides in the mouse kidney inner medulla. The same workflow can be applied in any cell or tissue type of interest to quickly advance this research field.

Dataset Information

MRMPath and MRMutation, Facilitating Discovery of Mass Transitions for Proteotypic Peptides in Biological Pathways Using a Bioinformatics Approach.

Publications

MRMPath and MRMutation, Facilitating Discovery of Mass Transitions for Proteotypic Peptides in Biological Pathways Using a Bioinformatics Approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets