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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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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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“We found that a set of 2,647 genes expressed specifically in brain tissue23 was strongly enriched for dURVs (OR=1.17; 95% CI=1.11–1.23; P = 1.2 × 10−4), whereas sets of genes with expression specific to other tissues (including immune cells) were not (Fig. 3a and Supplementary Fig. 7).”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [23]
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Self-citation
Metadata
- 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
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2014-02
- Volume
- 13
- Issue
- 2
- Pages
- 397-406
- ISSN
- 1535-9476 (ISSN-L)
- 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
- 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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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