MI-PVT: A Tool for Visualizing the Chromosome-Centric Human Proteome.

We have developed the web-based Michigan Proteome Visualization Tool (MI-PVT) to visualize and compare protein expression and isoform-level function across human chromosomes and tissues (http://guanlab.ccmb.med.umich.edu/mipvt). As proof of principle, we have populated the tool with Human Proteome Map (HPM) data. We were able to observe many biologically interesting features. From the vantage point of our chromosome 17 team, for example, we found more than 300 proteins from chromosome 17 expressed in each of the 30 tissues and cell types studied, with the highest number of expressed proteins being 685 in testis. Comparisons of expression levels across tissues showed low numbers of proteins expressed in esophagus, but esophagus had 12 cytoskeletal proteins coded on chromosome 17 with very high expression (>1000 spectral counts). This customized MI-PVT should be helpful for biologists to browse and study specific proteins and protein data sets across tissues and chromosomes. Users can upload any data of interest in MI-PVT for visualization. Our aim is to integrate extensive mass-spectrometric proteomic data into the tool to facilitate finding chromosome-centric protein expression and correlation across tissues.

[1]  E. Lundberg,et al.  A global view of protein expression in human cells, tissues, and organs , 2009, Molecular systems biology.

[2]  Yuanfang Guan,et al.  A new class of protein cancer biomarker candidates: differentially expressed splice variants of ERBB2 (HER2/neu) and ERBB1 (EGFR) in breast cancer cell lines. , 2014, Journal of proteomics.

[3]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[4]  William S. Hancock,et al.  Distinct splice variants and pathway enrichment in the cell-line models of aggressive human breast cancer subtypes. , 2014, Journal of proteome research.

[5]  Amos Bairoch,et al.  Metrics for the Human Proteome Project 2013-2014 and strategies for finding missing proteins. , 2014, Journal of proteome research.

[6]  Y. Guan,et al.  The emerging era of genomic data integration for analyzing splice isoform function. , 2014, Trends in genetics : TIG.

[7]  Eleanor Howe,et al.  RNA-Seq analysis in MeV , 2011, Bioinform..

[8]  P. Friedl,et al.  Tumour-cell invasion and migration: diversity and escape mechanisms , 2003, Nature Reviews Cancer.

[9]  Dan Xie,et al.  Variation and Genetic Control of Protein Abundance in Humans , 2013, Nature.

[10]  Christopher M. Fife,et al.  Movers and shakers: cell cytoskeleton in cancer metastasis , 2014, British journal of pharmacology.

[11]  Hongdong Li,et al.  Systematically Differentiating Functions for Alternatively Spliced Isoforms through Integrating RNA-seq Data , 2013, PLoS Comput. Biol..

[12]  H. Tojo,et al.  Full-length transcriptome-based H-InvDB throws a new light on chromosome-centric proteomics. , 2013, Journal of proteome research.

[13]  S. Hanash,et al.  A chromosome-centric human proteome project (C-HPP) to characterize the sets of proteins encoded in chromosome 17. , 2013, Journal of proteome research.

[14]  Dan Wang,et al.  CAPER: a chromosome-assembled human proteome browsER. , 2013, Journal of proteome research.

[15]  Xinlei Zhang,et al.  CAPER 3.0: A Scalable Cloud-Based System for Data-Intensive Analysis of Chromosome-Centric Human Proteome Project Data Sets. , 2015, Journal of proteome research.

[16]  Ying Zhang,et al.  The neXtProt knowledgebase on human proteins: current status , 2014, Nucleic Acids Res..

[17]  Y. Guan,et al.  Revisiting the identification of canonical splice isoforms through integration of functional genomics and proteomics evidence , 2014, Proteomics.

[18]  A. Paulus,et al.  The chromosome-centric human proteome project: a call to action. , 2013, Journal of proteome research.

[19]  Xinlei Zhang,et al.  CAPER 2.0: an interactive, configurable, and extensible workflow-based platform to analyze data sets from the Chromosome-centric Human Proteome Project. , 2014, Journal of proteome research.

[20]  C. Overall,et al.  Proteolytic Post-translational Modification of Proteins: Proteomic Tools and Methodology* , 2013, Molecular & Cellular Proteomics.

[21]  Robertson Craig,et al.  Open source system for analyzing, validating, and storing protein identification data. , 2004, Journal of proteome research.

[22]  William S Hancock,et al.  The proteome browser web portal. , 2013, Journal of proteome research.

[23]  Johannes Griss,et al.  The Proteomics Identifications (PRIDE) database and associated tools: status in 2013 , 2012, Nucleic Acids Res..

[24]  Hsien-Da Huang,et al.  dbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications , 2012, Nucleic Acids Res..

[25]  L. Franke,et al.  Proteomic studies related to genetic determinants of variability in protein concentrations. , 2014, Journal of proteome research.

[26]  Erik K. Malm,et al.  A Human Protein Atlas for Normal and Cancer Tissues Based on Antibody Proteomics* , 2005, Molecular & Cellular Proteomics.

[27]  B. Kuster,et al.  Mass-spectrometry-based draft of the human proteome , 2014, Nature.

[28]  Y. L. Ramachandra,et al.  Human Proteinpedia enables sharing of human protein data , 2008, Nature Biotechnology.

[29]  Hongdong Li,et al.  MIsoMine: a genome-scale high-resolution data portal of expression, function and networks at the splice isoform level in the mouse , 2015, Database J. Biol. Databases Curation.

[30]  A. Nesvizhskii,et al.  Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification. , 2015, Journal of proteome research.

[31]  Mathias Wilhelm,et al.  A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets , 2015, Molecular & Cellular Proteomics.

[32]  T. Ideker,et al.  Genome wide proteomics of ERBB2 and EGFR and other oncogenic pathways in inflammatory breast cancer. , 2013, Journal of proteome research.

[33]  S. Hanash,et al.  Standard guidelines for the chromosome-centric human proteome project. , 2012, Journal of proteome research.

[34]  G. von Heijne,et al.  Tissue-based map of the human proteome , 2015, Science.

[35]  Gary D Bader,et al.  A draft map of the human proteome , 2014, Nature.

[36]  William S Hancock,et al.  Protannotator: a semiautomated pipeline for chromosome-wise functional annotation of the "missing" human proteome. , 2014, Journal of proteome research.

[37]  P. Hoen,et al.  Alternative mRNA transcription, processing, and translation: insights from RNA sequencing , 2015 .

[38]  Hoguen Kim,et al.  GenomewidePDB, a proteomic database exploring the comprehensive protein parts list and transcriptome landscape in human chromosomes. , 2013, Journal of proteome research.

[39]  Lennart Martens,et al.  PRIDE: The proteomics identifications database , 2005, Proteomics.

[40]  William S Hancock,et al.  Genome-wide proteomics, Chromosome-Centric Human Proteome Project (C-HPP), part II. , 2014, Journal of Proteome Research.

[41]  Nichole L. King,et al.  The PeptideAtlas Project , 2010, Proteome Bioinformatics.