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A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
Tech Univ Munich, Chair Prote & Bioanalyt, Freising Weihenstephan, Germany.
Tech Univ Munich, Dept Informat, Computat Biol, Garching, Germany;Ludwig Maximilians Univ Munchen, Gene Ctr, Dept Biochem, Quantitat Biosci Munich, Munich, Germany.
OmicScouts GmbH, Freising Weihenstephan, Germany.
KTH Royal Inst Technol, Sci Life Lab, Stockholm, Sweden.
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2019 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 15, no 2, article id e8503Article in journal (Refereed) Published
Abstract [en]

Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein-level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue-specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.

Place, publisher, year, edition, pages
WILEY , 2019. Vol. 15, no 2, article id e8503
Keywords [en]
human proteome, human transcriptome, proteogenomics, quantitative mass spectrometry, RNA-Seq
National Category
Biochemistry and Molecular Biology Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:uu:diva-379281DOI: 10.15252/msb.20188503ISI: 000459628300002PubMedID: 30777892OAI: oai:DiVA.org:uu-379281DiVA, id: diva2:1296318
Funder
Knut and Alice Wallenberg FoundationEU, Horizon 2020Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-14Bibliographically approved

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