Cited by 3,665Bioinformatics and Genomic NetworksGene expression and cancer classificationAdvanced Proteomics Techniques and Applications

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Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics

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Fagerberg, Linn, Hallström, Björn M., Oksvold, Per, Kampf, Caroline, Djureinovic, Dijana, Odeberg, Jacob, Habuka, Masato, Tahmasebpoor, Simin, Danielsson, Angelika, Edlund, Karolina, Asplund, Anna, Sjöstedt, Evelina, Lundberg, Emma, Szigyarto, Cristina Al-Khalili, Skogs, Marie, Takanen, Jenny Ottosson, Berling, Holger, Tegel, Hanna, Mulder, Jan, Nilsson, Peter, Schwenk, Jochen M., Lindskog, Cecilia, Danielsson, Frida, Mardinoglu, Adil, Sivertsson, Åsa, von Feilitzen, Kalle, Forsberg, Mattias, Zwahlen, Martin, Olsson, IngMarie, Navani, Sanjay, Huss, Mikael, Nielsen, Jens, Ponten, Fredrik, Uhlén, Mathias·2014·Molecular & Cellular Proteomics

DOI 10.1074/mcp.m113.035600PMC PMC3916642

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Abstract

Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ∼80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

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Authors: Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., Asplund, A., Sjöstedt, E., Lundberg, E., Szigyarto, C. A.-K., Skogs, M., Takanen, J. O., Berling, H., Tegel, H., Mulder, J., Nilsson, P., Schwenk, J. M., Lindskog, C., Danielsson, F., Mardinoglu, A., Sivertsson, Å., von Feilitzen, K., Forsberg, M., Zwahlen, M., Olsson, I., Navani, S., Huss, M., Nielsen, J., Ponten, F., & Uhlén, M.
Affiliations: Science for Life Laboratory (SE)
Uppsala University (SE)
KTH Royal Institute of Technology (SE)
Corresponding author: Uhlén, Mathias
ORCID: Fagerberg, Linn
Oksvold, Per
Djureinovic, Dijana
Odeberg, Jacob
Habuka, Masato
Edlund, Karolina
Sjöstedt, Evelina
Lundberg, Emma
Szigyarto, Cristina Al-Khalili
Tegel, Hanna
Mulder, Jan
Nilsson, Peter
Schwenk, Jochen M.
Lindskog, Cecilia
Sivertsson, Åsa
Zwahlen, Martin
Huss, Mikael
Nielsen, Jens
Uhlén, Mathias
Venue: Molecular & Cellular Proteomics
Publisher: Elsevier BV
Published: 2014-02
Volume: 13
Issue: 2
Pages: 397-406
ISSN: 1535-9476 (ISSN-L)
DOI: 10.1074/mcp.m113.035600
PMC: PMC3916642
OpenAlex: W2167898988
Cited by: 3,665
References: 28
Citations by year: 2026: 163 · 2025: 292 · 2024: 458 · 2023: 422 · 2022: 438 · 2021: 474 · 2020: 528 · 2019: 387 · 2018: 255 · 2017: 105 · 2016: 43 · 2015: 64 · 2014: 28
FWCI: 20.19
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor, 2434 d)
Locations: Molecular & Cellular Proteomics (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Chalmers Research (Chalmers University of Technology) (submittedVersion)
Chalmers Publication Library (Chalmers University of Technology) (submittedVersion)
Funders: Knut och Alice Wallenbergs Stiftelse
Science for Life Laboratory
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords: tissue-specific gene expression, spatial expression patterns, Human Protein Atlas, RNA-seq, antibody-based proteomics, protein-coding genes, human organs, gene expression atlas
MeSH terms: Antibodies, Female, Humans, Male, Organ Specificity, Proteins, Gene Expression, Systems Integration, Proteome, Gene Expression Profiling, Genomics, Proteomics, Tissue Array Analysis, Gene Regulatory Networks, Transcriptome

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Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics

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