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A draft map of the human proteome.

Kim MS, Pinto SM, Getnet D, Nirujogi RS, Manda SS, Chaerkady R, Madugundu AK, Kelkar DS, Isserlin R, Jain S, Thomas JK, Muthusamy B, Leal-Rojas P, Kumar P, Sahasrabuddhe NA, Balakrishnan L, Advani J, George B, Renuse S, Selvan LD, Patil AH, Nanjappa V, Radhakrishnan A, Prasad S, Subbannayya T, Raju R, Kumar M, Sreenivasamurthy SK, Marimuthu A, Sathe GJ, Chavan S, Datta KK, Subbannayya Y, Sahu A, Yelamanchi SD, Jayaram S, Rajagopalan P, Sharma J, Murthy KR, Syed N, Goel R, Khan AA, Ahmad S, Dey G, Mudgal K, Chatterjee A, Huang TC, Zhong J, Wu X, Shaw PG, Freed D, Zahari MS, Mukherjee KK, Shankar S, Mahadevan A, Lam H, Mitchell CJ, Shankar SK, Satishchandra P, Schroeder JT, Sirdeshmukh R, Maitra A, Leach SD, Drake CG, Halushka MK, Prasad TS, Hruban RH, Kerr CL, Bader GD, Iacobuzio-Donahue CA, Gowda H, Pandey A - Nature (2014)

Bottom Line: However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet.In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans.A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames.

View Article: PubMed Central - PubMed

Affiliation: 1] McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA [2] Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.

ABSTRACT
The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

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Summary of proteome analysisa, Mass error in parts per million for precursor ions of all identified peptides. b, Number of peptides detected per gene binned as shown. c, Distribution of sequence coverage of identified proteins. d–f, %FDR with a q value of <0.01 plotted against peptide length in number of amino acids, charge state of peptide ion and number of cleavage sites missed by enzyme. p values computed from two-tailed t-test are shown. Error bars indicate s.d. calculated from FDRs of multiple fetal samples. g–h, A comparison of peptides identified in this study with PeptideAtlas and GPMDB. i, Mass error in parts per million for precursor ions identified from proteogenomics analysis.
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Figure 6: Summary of proteome analysisa, Mass error in parts per million for precursor ions of all identified peptides. b, Number of peptides detected per gene binned as shown. c, Distribution of sequence coverage of identified proteins. d–f, %FDR with a q value of <0.01 plotted against peptide length in number of amino acids, charge state of peptide ion and number of cleavage sites missed by enzyme. p values computed from two-tailed t-test are shown. Error bars indicate s.d. calculated from FDRs of multiple fetal samples. g–h, A comparison of peptides identified in this study with PeptideAtlas and GPMDB. i, Mass error in parts per million for precursor ions identified from proteogenomics analysis.

Mentions: To generate a baseline proteomic profile in humans, we studied 30 histologically normal human cell and tissue types, including 17 adult tissues, 7 fetal tissues, and 6 hematopoietic cell types (Fig. 1a). Pooled samples from three individuals per tissue type were processed and fractionated at the protein level by SDS-PAGE and at the peptide level by basic RPLC and analyzed on high resolution Fourier transform mass spectrometers (LTQ-Orbitrap Elite and LTQ-Orbitrap Velos ) (Fig. 1b). To generate a high quality dataset, both precursor ions and HCD-derived fragment ions were measured using the high resolution and high accuracy Orbitrap mass analyzer. Approximately 25 million high resolution tandem mass spectra, acquired from >2,000 LC-MS/MS runs, were searched against NCBI’s RefSeq15 human protein sequence database using MASCOT16 and SEQUEST17 search engines. The search results were rescored using the Percolator18 algorithm and a total of ~293,000 non-redundant peptides were identified at a q value <0.01 with a median mass measurement error of ~260 parts per billion (Extended Data Fig. 1a). The median number of peptides and corresponding tandem mass spectra identified per gene are 10 and 37, respectively, while the median protein sequence coverage was ~28% (Extended Data Fig. 1 b, c). It should be noted, however, that false positive rates for subgroups of peptide-spectrum matches can vary upon nature of peptides such as size, charge state of precursor peptide ions or missed enzymatic cleavage (Extended Data Fig. 1d–f and Supplementary Information).


A draft map of the human proteome.

Kim MS, Pinto SM, Getnet D, Nirujogi RS, Manda SS, Chaerkady R, Madugundu AK, Kelkar DS, Isserlin R, Jain S, Thomas JK, Muthusamy B, Leal-Rojas P, Kumar P, Sahasrabuddhe NA, Balakrishnan L, Advani J, George B, Renuse S, Selvan LD, Patil AH, Nanjappa V, Radhakrishnan A, Prasad S, Subbannayya T, Raju R, Kumar M, Sreenivasamurthy SK, Marimuthu A, Sathe GJ, Chavan S, Datta KK, Subbannayya Y, Sahu A, Yelamanchi SD, Jayaram S, Rajagopalan P, Sharma J, Murthy KR, Syed N, Goel R, Khan AA, Ahmad S, Dey G, Mudgal K, Chatterjee A, Huang TC, Zhong J, Wu X, Shaw PG, Freed D, Zahari MS, Mukherjee KK, Shankar S, Mahadevan A, Lam H, Mitchell CJ, Shankar SK, Satishchandra P, Schroeder JT, Sirdeshmukh R, Maitra A, Leach SD, Drake CG, Halushka MK, Prasad TS, Hruban RH, Kerr CL, Bader GD, Iacobuzio-Donahue CA, Gowda H, Pandey A - Nature (2014)

Summary of proteome analysisa, Mass error in parts per million for precursor ions of all identified peptides. b, Number of peptides detected per gene binned as shown. c, Distribution of sequence coverage of identified proteins. d–f, %FDR with a q value of <0.01 plotted against peptide length in number of amino acids, charge state of peptide ion and number of cleavage sites missed by enzyme. p values computed from two-tailed t-test are shown. Error bars indicate s.d. calculated from FDRs of multiple fetal samples. g–h, A comparison of peptides identified in this study with PeptideAtlas and GPMDB. i, Mass error in parts per million for precursor ions identified from proteogenomics analysis.
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Figure 6: Summary of proteome analysisa, Mass error in parts per million for precursor ions of all identified peptides. b, Number of peptides detected per gene binned as shown. c, Distribution of sequence coverage of identified proteins. d–f, %FDR with a q value of <0.01 plotted against peptide length in number of amino acids, charge state of peptide ion and number of cleavage sites missed by enzyme. p values computed from two-tailed t-test are shown. Error bars indicate s.d. calculated from FDRs of multiple fetal samples. g–h, A comparison of peptides identified in this study with PeptideAtlas and GPMDB. i, Mass error in parts per million for precursor ions identified from proteogenomics analysis.
Mentions: To generate a baseline proteomic profile in humans, we studied 30 histologically normal human cell and tissue types, including 17 adult tissues, 7 fetal tissues, and 6 hematopoietic cell types (Fig. 1a). Pooled samples from three individuals per tissue type were processed and fractionated at the protein level by SDS-PAGE and at the peptide level by basic RPLC and analyzed on high resolution Fourier transform mass spectrometers (LTQ-Orbitrap Elite and LTQ-Orbitrap Velos ) (Fig. 1b). To generate a high quality dataset, both precursor ions and HCD-derived fragment ions were measured using the high resolution and high accuracy Orbitrap mass analyzer. Approximately 25 million high resolution tandem mass spectra, acquired from >2,000 LC-MS/MS runs, were searched against NCBI’s RefSeq15 human protein sequence database using MASCOT16 and SEQUEST17 search engines. The search results were rescored using the Percolator18 algorithm and a total of ~293,000 non-redundant peptides were identified at a q value <0.01 with a median mass measurement error of ~260 parts per billion (Extended Data Fig. 1a). The median number of peptides and corresponding tandem mass spectra identified per gene are 10 and 37, respectively, while the median protein sequence coverage was ~28% (Extended Data Fig. 1 b, c). It should be noted, however, that false positive rates for subgroups of peptide-spectrum matches can vary upon nature of peptides such as size, charge state of precursor peptide ions or missed enzymatic cleavage (Extended Data Fig. 1d–f and Supplementary Information).

Bottom Line: However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet.In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans.A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames.

View Article: PubMed Central - PubMed

Affiliation: 1] McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA [2] Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.

ABSTRACT
The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Show MeSH
Related in: MedlinePlus