Dataset Information

A chromosome-centric human proteome project (C-HPP) to characterize the sets of proteins encoded in chromosome 17.

ABSTRACT: We report progress assembling the parts list for chromosome 17 and illustrate the various processes that we have developed to integrate available data from diverse genomic and proteomic knowledge bases. As primary resources, we have used GPMDB, neXtProt, PeptideAtlas, Human Protein Atlas (HPA), and GeneCards. All sites share the common resource of Ensembl for the genome modeling information. We have defined the chromosome 17 parts list with the following information: 1169 protein-coding genes, the numbers of proteins confidently identified by various experimental approaches as documented in GPMDB, neXtProt, PeptideAtlas, and HPA, examples of typical data sets obtained by RNASeq and proteomic studies of epithelial derived tumor cell lines (disease proteome) and a normal proteome (peripheral mononuclear cells), reported evidence of post-translational modifications, and examples of alternative splice variants (ASVs). We have constructed a list of the 59 "missing" proteins as well as 201 proteins that have inconclusive mass spectrometric (MS) identifications. In this report we have defined a process to establish a baseline for the incorporation of new evidence on protein identification and characterization as well as related information from transcriptome analyses. This initial list of "missing" proteins that will guide the selection of appropriate samples for discovery studies as well as antibody reagents. Also we have illustrated the significant diversity of protein variants (including post-translational modifications, PTMs) using regions on chromosome 17 that contain important oncogenes. We emphasize the need for mandated deposition of proteomics data in public databases, the further development of improved PTM, ASV, and single nucleotide variant (SNV) databases, and the construction of Web sites that can integrate and regularly update such information. In addition, we describe the distribution of both clustered and scattered sets of protein families on the chromosome. Since chromosome 17 is rich in cancer-associated genes, we have focused the clustering of cancer-associated genes in such genomic regions and have used the ERBB2 amplicon as an example of the value of a proteogenomic approach in which one integrates transcriptomic with proteomic information and captures evidence of coexpression through coordinated regulation.

SUBMITTER: Liu S

PROVIDER: S-EPMC4142220 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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A chromosome-centric human proteome project (C-HPP) to characterize the sets of proteins encoded in chromosome 17.

Liu Suli S Im Hogune H Bairoch Amos A Cristofanilli Massimo M Chen Rui R Deutsch Eric W EW Dalton Stephen S Fenyo David D Fanayan Susan S Gates Chris C Gaudet Pascale P Hincapie Marina M Hanash Samir S Kim Hoguen H Jeong Seul-Ki SK Lundberg Emma E Mias George G Menon Rajasree R Mu Zhaomei Z Nice Edouard E Paik Young-Ki YK Uhlen Mathias M Wells Lance L Wu Shiaw-Lin SL Yan Fangfei F Zhang Fan F Zhang Yue Y Snyder Michael M Omenn Gilbert S GS Beavis Ronald C RC Hancock William S WS

Journal of proteome research 20121221 1

We report progress assembling the parts list for chromosome 17 and illustrate the various processes that we have developed to integrate available data from diverse genomic and proteomic knowledge bases. As primary resources, we have used GPMDB, neXtProt, PeptideAtlas, Human Protein Atlas (HPA), and GeneCards. All sites share the common resource of Ensembl for the genome modeling information. We have defined the chromosome 17 parts list with the following information: 1169 protein-coding genes, t ...[more]

PMID: 23259914

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Project description:Alternative splicing allows a single gene to produce multiple transcript-level splice isoforms from which the translated proteins may show differences in their expression and function. Identifying the major functional or canonical isoform is important for understanding gene and protein functions. Identification and characterization of splice isoforms is a stated goal of the HUPO Human Proteome Project and of neXtProt. Multiple efforts have catalogued splice isoforms as "dominant", "principal", or "major" isoforms based on expression or evolutionary traits. In contrast, we recently proposed highest connected isoforms (HCIs) as a new class of canonical isoforms that have the strongest interactions in a functional network and revealed their significantly higher (differential) transcript-level expression compared to nonhighest connected isoforms (NCIs) regardless of tissues/cell lines in the mouse. HCIs and their expression behavior in the human remain unexplored. Here we identified HCIs for 6157 multi-isoform genes using a human isoform network that we constructed by integrating a large compendium of heterogeneous genomic data. We present examples for pairs of transcript isoforms of ABCC3, RBM34, ERBB2, and ANXA7. We found that functional networks of isoforms of the same gene can show large differences. Interestingly, differential expression between HCIs and NCIs was also observed in the human on an independent set of 940 RNA-seq samples across multiple tissues, including heart, kidney, and liver. Using proteomic data from normal human retina and placenta, we showed that HCIs are a promising indicator of expressed protein isoforms exemplified by NUDFB6 and M6PR. Furthermore, we found that a significant percentage (20%, p = 0.0003) of human and mouse HCIs are homologues, suggesting their conservation between species. Our identified HCIs expand the repertoire of canonical isoforms and are expected to facilitate studying main protein products, understanding gene regulation, and possibly evolution. The network is available through our web server as a rich resource for investigating isoform functional relationships (http://guanlab.ccmb.med.umich.edu/hisonet). All MS/MS data were available at ProteomeXchange Web site (http://www.proteomexchange.org) through their identifiers (retina: PXD001242, placenta: PXD000754).

Project description:Protein extraction and proteolytic digestion were performed using a Filter-Assisted Sample Preparation (FASP) protocol. In case of phosphopeptide enrichment immobilized Fe(III) affinity chromatography (Fe-IMAC) was performed. The peptides were fractionated using an HPLC system fitted with an SCX column. 10 sample datasets were used: 1. CRC_N: Normal tissue samples were obtained from 20 colorectal cancer patients, no quantification.Phosphopeptide enrichment was performed. 2. CRC_T: Human colorectal cancer tissue samples were obtained from 20 patients, no quantification. Phosphopeptide enrichment was performed. 3. CRC_iTRAQ: Human colorectal cancer tissue samples were obtained from 24 patients, iTRAQ quantification. 4. CRC_phospho_iTRAQ:Human colorectal cancer tissue samples were obtained from 24 patients, iTRAQ quantification.Phosphopeptide enrichment was performed. 5. HCT116_iTRAQ: Human colon cancer cell HCT116, iTRAQ quantification. 6. HCT116_phospho_iTRAQ: Human colon cancer cell HCT116, phosphopeptide enrichment, iTRAQ quantification. 7. SW_SILAC_HL: Human colon cancer cell SW480 and SW620, SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW480; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW620; heavy). 8. SW_SILAC_LH: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW620; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW480; heavy). 9. SW_phospho_SILAC_HL: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW480; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW620; heavy). Phosphopeptide enrichment was performed. 10. SW_phospho_SILAC_LH: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW620; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW480; heavy). Phosphopeptide enrichment was performed. For creation of xml and mgf files, Proteome Discoverer 1.3 and Mascot v2.3 software were used.

Dataset Information

A chromosome-centric human proteome project (C-HPP) to characterize the sets of proteins encoded in chromosome 17.

Publications

A chromosome-centric human proteome project (C-HPP) to characterize the sets of proteins encoded in chromosome 17.

Similar Datasets

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