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Cited by 750Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic NetworksGenomics and Phylogenetic Studies

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

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Wang, Dongxue, Eraslan, Basak, Wieland, Thomas, Hallström, Björn, Hopf, Thomas, Zolg, Daniel Paul, Zecha, Jana, Asplund, Anna +11 more·2019·Molecular Systems Biology
DOI 10.15252/msb.20188503PMC PMC6379049

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Abstract

Genome‐, transcriptome‐ and proteome‐wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein‐level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue‐specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

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  • Correlation between the mRNAs for the paired RNA-Seq relative to the global proteomics datasets showed lower positive Pearson correlation values ranging from 0.333 - 0.378 for all genotypes tested.

    “Correlation between the mRNAs for the paired RNA-Seq relative to the global proteomics datasets showed lower positive Pearson correlation values ranging from 0.333 – 0.378 for all genotypes tested which is consistent with prior studies on transcriptome / proteome correlation82–84.”

    From EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery (2026) · cites this paper as [84]

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Authors
Wang, D., Eraslan, B., Wieland, T., Hallström, B., Hopf, T., Zolg, D. P., Zecha, J., Asplund, A., Li, L., Meng, C., Frejno, M., Schmidt, T., Schnatbaum, K., Wilhelm, M., Ponten, F., Uhlen, M., Gagneur, J., Hahne, H., & Kuster, B.
Affiliations
  • Technical University of Munich (DE)
  • Science for Life Laboratory (SE)
  • Uppsala University (SE)
  • JPT Peptide Technologies (Germany) (DE)
Corresponding author
  • Gagneur, Julien
  • Hahne, Hannes
ORCID
Venue
Molecular Systems Biology
Publisher
Springer Science and Business Media LLC
Published
2019-02-01
Volume
15
Issue
2
Pages
e8503-e8503
ISSN
1744-4292 (ISSN-L)
DOI
10.15252/msb.20188503
PMC
PMC6379049
OpenAlex
W2950512597
Cited by
750
References
12
Citations by year
2026: 64 · 2025: 97 · 2024: 100 · 2023: 125 · 2022: 122 · 2021: 117 · 2020: 92 · 2019: 29 · 2018: 2
FWCI
35.95
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Systems Biology (publishedVersion, other-oa)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
  • mediaTUM (Technical University of Munich) (submittedVersion)
Funders
  • Center for Integrated Protein Analysis Munich
  • Knut and Alice Wallenberg Foundation
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
human tissue proteome, protein abundance, mRNA-protein correlation, tissue-specific gene expression, proteogenomics, amino acid variants, testis, Human Protein Atlas, biomarker specificity, gene expression regulation
MeSH terms
Gene Expression Regulation, Humans, RNA, Messenger, Mass Spectrometry, Tissue Distribution, Genome, Human, Sequence Analysis, RNA, Proteome, Proteomics, Transcriptome

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