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A Quantitative Proteome Map of the Human Body
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Abstract
SUMMARY Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.
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“Although transcriptomic profiling has provided insights into Tex cell biology, mRNA abundance is not always a faithful proxy of protein expression across various organisms18–22.”
From Proteotoxic stress response drives T cell exhaustion and immune evasion (2025) · cites this paper as [21]
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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 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 [83]
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Metadata
- Authors
- Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., Anand, S., Ardlie, K. G., Gabriel, S., Getz, G., Graubert, A., Hadley, K., Handsaker, R. E., Huang, K. H., Kashin, S., MacArthur, D. G., Meier, S. R., Nedzel, J. L., Nguyen, D. Y., Segrè, A. V., Todres, E., Balliu, B., Barbeira, A. N., Battle, A., Bonazzola, R., Brown, A., Brown, C. D., Castel, S. E., Conrad, D., Cotter, D. J., Cox, N., Das, S., de Goede, O. M., Dermitzakis, E. T., Engelhardt, B. E., Eskin, E., Eulalio, T. Y., Ferraro, N. M., Flynn, E., Fresard, L., Gamazon, E. R., Garrido-Martín, D., Gay, N. R., Guigó, R., Hamel, A. R., He, Y., Hoffman, P. J., Hormozdiari, F., Hou, L., Im, H. K., Jo, B., Kasela, S., Kellis, M., Kim-Hellmuth, S., Kwong, A., Lappalainen, T., Li, X., Liang, Y., Mangul, S., Mohammadi, P., Montgomery, S. B., Muñoz-Aguirre, M., Nachun, D. C., Nobel, A. B., Oliva, M., Park, Y., Park, Y., Parsana, P., Reverter, F., Rouhana, J. M., Sabatti, C., Saha, A., Skol, A. D., Stephens, M., Stranger, B. E., Strober, B. J., Teran, N. A., Viñuela, A., Wang, G., Wen, X., Wright, F., Wucher, V., Zou, Y., Ferreira, P. G., Li, G., Melé, M., Yeger-Lotem, E., Barcus, M. E., Bradbury, D., Krubit, T., McLean, J. A., Qi, L., Robinson, K., Roche, N. V., Smith, A. M., Sobin, L., Tabor, D. E., Undale, A., Bridge, J., Brigham, L. E., Foster, B. A., Gillard, B. M., Hasz, R., Hunter, M., Johns, C., Johnson, M., Karasik, E., Kopen, G., Leinweber, W. F., McDonald, A., Moser, M. T., Myer, K., Ramsey, K. D., Roe, B., Shad, S., Thomas, J. A., Walters, G., Washington, M., Wheeler, J., Jewell, S. D., Rohrer, D. C., Valley, D. R., Davis, D. A., Mash, D. C., Branton, P. A., Barker, L. K., Gardiner, H. M., Mosavel, M., Siminoff, L. A., Flicek, P., Haeussler, M., Juettemann, T., Kent, W. J., Lee, C. M., Powell, C. C., Rosenbloom, K. R., Ruffier, M., Sheppard, D., Taylor, K., Trevanion, S. J., Zerbino, D. R., Abell, N. S., Akey, J., Chen, L., Demanelis, K., Doherty, J. A., Feinberg, A. P., Hansen, K. D., Hickey, P. F., Jasmine, F., Kaul, R., Kibriya, M. G., Li, J. B., Li, Q., Linder, S. E., Pierce, B. L., Rizzardi, L. F., Smith, K. S., Stamatoyannopoulos, J., Tang, H., Carithers, L. J., Guan, P., Koester, S. E., Little, A. R., Moore, H. M., Nierras, C. R., Rao, A. K., Vaught, J. B., Volpi, S., & Snyder, M. P.
- Affiliations
- Stanford Medicine (US)
- University of Washington (US)
- Thermo Fisher Scientific (United States) (US)
- Corresponding author
- Snyder, Michael P.
- ORCID
- Jiang, Lihua
- Wang, Meng
- Lin, Shin
- Jian, Ruiqi
- Li, Xiao
- Chan, Joanne
- Dong, Guanlan
- Fang, Huaying
- Robinson, Aaron E.
- Aguet, François
- Anand, Shankara
- Ardlie, Kristin G.
- Gabriel, Stacey
- Getz, Gad
- Graubert, Aaron
- Hadley, Kane
- Handsaker, Robert E.
- Huang, Katherine H.
- Kashin, Seva
- MacArthur, Daniel G.
- Meier, Samuel R.
- Nedzel, Jared L.
- Segrè, Ayellet V.
- Todres, Ellen
- Balliu, Brunilda
- Barbeira, Alvaro N.
- Battle, Alexis
- Bonazzola, Rodrigo
- Brown, Andrew
- Brown, Christopher D.
- Castel, Stephane E.
- Cotter, Daniel J.
- Cox, Nancy
- Das, Sayantan
- Dermitzakis, Emmanouil T.
- Engelhardt, Barbara E.
- Eskin, Eleazar
- Eulalio, Tiffany Y.
- Ferraro, Nicole M.
- Flynn, Elise
- Gamazon, Eric R.
- Garrido-Martín, Diego
- Gay, Nicole R.
- Guigó, Roderic
- Hamel, Andrew R.
- He, Yuan
- Hormozdiari, Farhad
- Hou, Lei
- Im, Hae Kyung
- Jo, Brian
- Kasela, Silva
- Kellis, Manolis
- Kim-Hellmuth, Sarah
- Kwong, Alan
- Lappalainen, Tuuli
- Li, Xin
- Liang, Yanyu
- Mangul, Serghei
- Mohammadi, Pejman
- Montgomery, Stephen B.
- Muñoz-Aguirre, Manuel
- Nachun, Daniel C.
- Nobel, Andrew B.
- Oliva, Meritxell
- Park, YoSon
- Park, Yongjin
- Parsana, Princy
- Rouhana, John M.
- Sabatti, Chiara
- Saha, Ashis
- Skol, Andrew D.
- Stephens, Matthew
- Stranger, Barbara E.
- Strober, Benjamin J.
- Teran, Nicole A.
- Viñuela, Ana
- Wang, Gao
- Wen, Xiaoquan
- Wright, Fred
- Wucher, Valentin
- Zou, Yuxin
- Ferreira, Pedro G.
- Li, Gen
- Melé, Marta
- Smith, Anna M.
- Tabor, David E.
- Foster, Barbara A.
- Gillard, Bryan M.
- Hasz, Richard
- Johns, Christopher
- Johnson, Mark
- Moser, Michael T.
- Jewell, Scott D.
- Rohrer, Daniel C.
- Davis, David A.
- Mash, Deborah C.
- Branton, Philip A.
- Gardiner, Heather M.
- Mosavel, Maghboeba
- Siminoff, Laura A.
- Flicek, Paul
- Haeussler, Maximilian
- Juettemann, Thomas
- Lee, Christopher M.
- Rosenbloom, Kate R.
- Ruffier, Magali
- Sheppard, Dan
- Taylor, Kieron
- Trevanion, Stephen J.
- Zerbino, Daniel R.
- Abell, Nathan S.
- Akey, Joshua
- Chen, Lin
- Demanelis, Kathryn
- Doherty, Jennifer A.
- Feinberg, Andrew P.
- Hansen, Kasper D.
- Hickey, Peter F.
- Jasmine, Farzana
- Kaul, Rajinder
- Kibriya, Muhammad G.
- Li, Jin Billy
- Li, Qin
- Pierce, Brandon L.
- Rizzardi, Lindsay F.
- Smith, Kevin S.
- Stamatoyannopoulos, John
- Tang, Hua
- Guan, Ping
- Little, A. Roger
- Moore, Helen M.
- Volpi, Simona
- Snyder, Michael P.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 183
- Issue
- 1
- Pages
- 269-283.e19
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC7575058
- OpenAlex
- W3083820674
- Semantic Scholar
- 433ccfe1fc4a69e669d65b7624ab4341f13fa1a9
- Cited by
- 458
- References
- 72
- Citations by year
- 2026: 56 · 2025: 105 · 2024: 83 · 2023: 96 · 2022: 61 · 2021: 46 · 2020: 10
- FWCI
- 20.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Discovery Research Portal (University of Dundee) (submittedVersion)
- Funders
- National Institutes of Health
- 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 › Advanced Biosensing Techniques and Applications
- Keywords
- human proteome, tissue-specific proteins, protein abundance, transcriptome, RNA-protein correlation, secretome
- MeSH terms
- Humans, RNA, RNA, Messenger, Gene Expression, Proteome, Gene Expression Profiling, Proteomics, Transcriptome
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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