Iterative Genome Correction Largely Improves Proteomic Analysis Of Non

With the implementation and development of human genome project, researchersare paying more and more attention to the proteomic studies. Liquid chromatographytandem mass spectrometry at present stage has become the core technique of theprotein identification. However, highly dependent on the existing protein database, itis difficult to apply to the discovery and research of new proteins. Therefore, thismethod severely impede the investigations of the genome and proteome of non-modelorganisms. To deal with this situation, we developed a new strategy, which can utilizeexisting genome database and annotation for further subsequent proteomic analysisand research.The new strategy implements our stable, accurate and error-tolerant FANSe (Fastand Accurate mapping tool for Nucleotide Sequencing datasets) mapping algorithm tocorrect genome sequences in an iterative manner. In the experiment, we extract anenvironmental of Bacillus pumilus strain and performed whole genome DNAsequencing as well as mass spectrometry of total proteins. In order to effectivelyassess the effect of the revised genome on the proteomic study, we examined twoprotein database before and after correction to perform MASCOT identification ofmass spectrometry spectra. Compared to the original database, the corrected databasecan improve11.5%protein identification rate and14.2%peptides identification rate.The results showed that the corrected protein sequence database by iterativegenome corrections significantly facilitates peptide/protein identification. Thisstrategy can also help to detect novel peptide variants. We believe that the strategywill play a significant role in promoting the development of functional proteomics innon-model organisms.