The Equine PeptideAtlas: A resource for developing proteomics‐based veterinary research. Issue 6 (16th February 2014)

• Record Type: Journal Article
• Authors: Bundgaard, Louise; Jacobsen, Stine; Sørensen, Mette A.; Sun, Zhi; Deutsch, Eric W.; Moritz, Robert L.; Bendixen, Emøke
• Is Part Of: Proteomics. Volume 14:Issue 6(2014:Mar.)
• Page Start: 763
• Page End: 773
• Publication Date: 2014-02-16
• Subjects: Acute phase proteins -- Animal proteomics -- Equine -- PeptideAtlas -- Proteotypic peptides; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201300398
• Languages: English
• ISSNs: 1615-9853

Abstract

Abstract : Progress in MS‐based methods for veterinary research and diagnostics is lagging behind compared to the human research, and proteome data of domestic animals is still not well represented in open source data repositories. This is particularly true for the equine species. Here we present a first Equine PeptideAtlas encompassing high‐resolution tandem MS analyses of 51 samples representing a selection of equine tissues and body fluids from healthy and diseased animals. The raw data were processed through the Trans‐Proteomic Pipeline to yield high quality identification of proteins and peptides. The current release comprises 24 131 distinct peptides representing 2636 canonical proteins observed at false discovery rates of 0.2% at the peptide level and 1.4% at the protein level. Data from the Equine PeptideAtlas are available for experimental planning, validation of new datasets, and as a proteomic data mining resource. The advantages of the Equine PeptideAtlas are demonstrated by examples of mining the contents for information on potential and well‐known equine acute phase proteins, which have extensive general interest in the veterinary clinic. The extracted information will support further analyses, and emphasizes the value of the Equine PeptideAtlas as a resource for the design of targeted quantitative proteomic studies.