JUMPg: An Integrative Proteogenomics Pipeline Identifying Unannotated Proteins in Human Brain and Cancer Cells

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• 作者：Yuxin Li ; Xusheng Wang ; Ji-Hoon Cho ; Timothy I. Shaw ; Zhiping Wu ; Bing Bai ; Hong Wang ; Suiping Zhou ; Thomas G. Beach ; Gang Wu ; Jinghui Zhang ; Junmin Peng
• 刊名：Journal of Proteome Research
• 出版年：2016
• 出版时间：July 1, 2016
• 年：2016
• 卷：15
• 期：7
• 页码：2309-2320
• 全文大小：843K
• 年卷期：0
• ISSN：1535-3907

文摘

Proteogenomics is an emerging approach to improve gene annotation and interpretation of proteomics data. Here we present JUMPg, an integrative proteogenomics pipeline including customized database construction, tag-based database search, peptide-spectrum match filtering, and data visualization. JUMPg creates multiple databases of DNA polymorphisms, mutations, splice junctions, partially trypticity, as well as protein fragments translated from the whole transcriptome in all six frames upon RNA-seq de novo assembly. We use a multistage strategy to search these databases sequentially, in which the performance is optimized by re-searching only unmatched high-quality spectra and reusing amino acid tags generated by the JUMP search engine. The identified peptides/proteins are displayed with gene loci using the UCSC genome browser. Then, the JUMPg program is applied to process a label-free mass spectrometry data set of Alzheimer’s disease postmortem brain, uncovering 496 new peptides of amino acid substitutions, alternative splicing, frame shift, and “non-coding gene” translation. The novel protein PNMA6BL specifically expressed in the brain is highlighted. We also tested JUMPg to analyze a stable-isotope labeled data set of multiple myeloma cells, revealing 991 sample-specific peptides that include protein sequences in the immunoglobulin light chain variable region. Thus, the JUMPg program is an effective proteogenomics tool for multiomics data integration.