Tissue-based map of the human proteome

Mathias Uhlén(Science for Life Laboratory), Linn Fagerberg(Science for Life Laboratory), Björn M. Hallström(Science for Life Laboratory), Cecilia Lindskog(Uppsala University), Per Oksvold(Science for Life Laboratory), Adil Mardinoğlu(Chalmers University of Technology), Åsa Sivertsson(Science for Life Laboratory), Caroline Kampf(Uppsala University), Evelina Sjöstedt(Uppsala University), Anna Asplund(Uppsala University), Ing‐Marie Olsson(Uppsala University), Karolina Edlund(TU Dortmund University), Emma Lundberg(Science for Life Laboratory), Sanjay Navani, Cristina Al‐Khalili Szigyarto(KTH Royal Institute of Technology), Jacob Odeberg(Science for Life Laboratory), Dijana Djureinovic(Uppsala University), Jenny Ottosson Takanen(KTH Royal Institute of Technology), Sophia Hober(KTH Royal Institute of Technology), Tove Alm(Science for Life Laboratory), Per-Henrik Edqvist(Uppsala University), Holger Berling(KTH Royal Institute of Technology), Hanna Tegel(KTH Royal Institute of Technology), Jan Mulder(Science for Life Laboratory), Johan Rockberg(KTH Royal Institute of Technology), Peter Nilsson(Science for Life Laboratory), Jochen M. Schwenk(Science for Life Laboratory), Marica Hamsten(KTH Royal Institute of Technology), Kalle von Feilitzen(Science for Life Laboratory), Mattias Forsberg(Science for Life Laboratory), Lukas Persson(Science for Life Laboratory), Fredric Johansson(Science for Life Laboratory), Martin Zwahlen(Science for Life Laboratory), Gunnar von Heijne(Stockholm University), Jens Nielsen(Novo Nordisk Foundation), Fredrik Pontén(Uppsala University)
Science
January 22, 2015
Cited by 15,816Open Access
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Abstract

Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.


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