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Quantification and discovery of sequence determinants of protein-per-mRNA amount in 29 human tissues
Tech Univ Munich, Dept Informat, Computat Biol, Munich, Germany;Ludwig Maximilians Univ Munchen, Grad Sch Quantitat Biosci QBM, Munich, Germany.
Tech Univ Munich, Chair Prote & Bioanalyt, Freising Weihenstephan, Germany.
Tech Univ Munich, Inst Human Genet, Munich, Germany;Helmholtz Zentrum Munchen, Inst Human Genet, Neuherberg, Germany.
Tech Univ Munich, Inst Human Genet, Munich, Germany;Helmholtz Zentrum Munchen, Inst Human Genet, Neuherberg, Germany.
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2019 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 15, no 2, article id e8513Article in journal (Refereed) Published
Abstract [en]

Despite their importance in determining protein abundance, a comprehensive catalogue of sequence features controlling protein-to-mRNA (PTR) ratios and a quantification of their effects are still lacking. Here, we quantified PTR ratios for 11,575 proteins across 29 human tissues using matched transcriptomes and proteomes. We estimated by regression the contribution of known sequence determinants of protein synthesis and degradation in addition to 45 mRNA and 3 protein sequence motifs that we found by association testing. While PTR ratios span more than 2 orders of magnitude, our integrative model predicts PTR ratios at a median precision of 3.2-fold. A reporter assay provided functional support for two novel UTR motifs, and an immobilized mRNA affinity competition-binding assay identified motif-specific bound proteins for one motif. Moreover, our integrative model led to a new metric of codon optimality that captures the effects of codon frequency on protein synthesis and degradation. Altogether, this study shows that a large fraction of PTR ratio variation in human tissues can be predicted from sequence, and it identifies many new candidate post-transcriptional regulatory elements.

Place, publisher, year, edition, pages
WILEY , 2019. Vol. 15, no 2, article id e8513
Keywords [en]
codon usage, mRNA sequence motifs, proteomics, transcriptomics, translational control
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-379280DOI: 10.15252/msb.20188513ISI: 000459628300004PubMedID: 30777893OAI: oai:DiVA.org:uu-379280DiVA, id: diva2:1296322
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EU, Horizon 2020, 633974Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-14Bibliographically approved

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