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

Linn Fagerberg(Science for Life Laboratory), Björn M. Hallström(Science for Life Laboratory), Per Oksvold(Science for Life Laboratory), Caroline Kampf(Uppsala University), Dijana Djureinovic(Uppsala University), Jacob Odeberg(Science for Life Laboratory), Masato Habuka(Science for Life Laboratory), Simin Tahmasebpoor(Uppsala University), Angelika Danielsson(Uppsala University), Karolina Edlund(Uppsala University), Anna Asplund(Uppsala University), Evelina Sjöstedt(Uppsala University), Emma Lundberg(Science for Life Laboratory), Cristina Al‐Khalili Szigyarto(Science for Life Laboratory), Marie Skogs(Science for Life Laboratory), Jenny Ottosson Takanen(KTH Royal Institute of Technology), Holger Berling(KTH Royal Institute of Technology), Hanna Tegel(Science for Life Laboratory), Jan Mulder(Science for Life Laboratory), Peter Nilsson(Science for Life Laboratory), Jochen M. Schwenk(Science for Life Laboratory), Cecilia Lindskog(Uppsala University), Frida Danielsson(Science for Life Laboratory), Adil Mardinoğlu(Chalmers University of Technology), Åsa Sivertsson(Science for Life Laboratory), Kalle von Feilitzen(KTH Royal Institute of Technology), Mattias Forsberg(Science for Life Laboratory), Martin Zwahlen(Science for Life Laboratory), Ing‐Marie Olsson(Uppsala University), Sanjay Navani, Mikael Huss(Science for Life Laboratory), Jens Nielsen(Uppsala University), Fredrik Pontén(Uppsala University), Mathias Uhlén(Science for Life Laboratory)
Molecular & Cellular Proteomics
December 5, 2013
Cited by 3,795Open Access
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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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