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Mol Syst Biol. 2016 Apr 4;12(4):862. doi: 10.15252/msb.20155865.

Transcriptomics resources of human tissues and organs.

Author information

1
Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden Department of Proteomics, KTH - Royal Institute of Technology, Stockholm, Sweden Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark mathias.uhlen@scilifelab.se.
2
Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden Department of Proteomics, KTH - Royal Institute of Technology, Stockholm, Sweden.
3
Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
4
Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
5
Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.

Abstract

Quantifying the differential expression of genes in various human organs, tissues, and cell types is vital to understand human physiology and disease. Recently, several large-scale transcriptomics studies have analyzed the expression of protein-coding genes across tissues. These datasets provide a framework for defining the molecular constituents of the human body as well as for generating comprehensive lists of proteins expressed across tissues or in a tissue-restricted manner. Here, we review publicly available human transcriptome resources and discuss body-wide data from independent genome-wide transcriptome analyses of different tissues. Gene expression measurements from these independent datasets, generated using samples from fresh frozen surgical specimens and postmortem tissues, are consistent. Overall, the different genome-wide analyses support a distribution in which many proteins are found in all tissues and relatively few in a tissue-restricted manner. Moreover, we discuss the applications of publicly available omics data for building genome-scale metabolic models, used for analyzing cell and tissue functions both in physiological and in disease contexts.

KEYWORDS:

genome‐scale metabolic models; proteomics; transcriptomics

PMID:
27044256
PMCID:
PMC4848759
DOI:
10.15252/msb.20155865
[Indexed for MEDLINE]
Free PMC Article

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