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

By Linn Fagerberg, B. Hallström, P. Oksvold, C. Kampf, D. Djureinovic, J. Odeberg, Masato Habuka, Simin Tahmasebpoor, Angelika Danielsson, K. Edlund and 24 more. 2014

1,209 citations recorded by the source corpus.

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.

Subfields: Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

Predicting multicellular function through multi-layer tissue networks (2017, background): “…functions of proteins frequently depend on the tissue, and different proteins can have different cellular functions in different tissues (Lois et al. , 2002; Rakyan et al. , 2008; Magger et al. , 2012; Guan et al. , 2012; Fagerberg et al. , 2014; Yeger-Lotem and Sharan, 2015; Hu et al. , 2016).”
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues (2018, methodology): “Tissues were collected by the Human Protein Atlas project (Fagerberg et al. 2014) and adjacent cryo-sections were used for paired (allele specific) transcriptome and proteome analysis.”
A benchmark of gene expression tissue-specificity metrics (2015, methodology): “(Fagerberg et al. 2013) downloaded from their Supplementary Materials, 22 mouse tissues (GSE36025) from the ENCODE project (The ENCODE Project Consortium 2011; Lin et al.”