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Gene-specific correlation of RNA and protein levels in human cells and tissues
KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-7692-1100
KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-5689-9797
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2016 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 12, no 10, 883Article in journal (Refereed) Published
Abstract [en]

An important issue for molecular biology is to establish whether transcript levels of a given gene can be used as proxies for the corresponding protein levels. Here, we have developed a targeted proteomics approach for a set of human non-secreted proteins based on parallel reaction monitoring to measure, at steady-state conditions, absolute protein copy numbers across human tissues and cell lines and compared these levels with the corresponding mRNA levels using transcriptomics. The study shows that the transcript and protein levels do not correlate well unless a gene-specific RNA-to-protein (RTP) conversion factor independent of the tissue type is introduced, thus significantly enhancing the predictability of protein copy numbers from RNA levels. The results show that the RTP ratio varies significantly with a few hundred copies per mRNA molecule for some genes to several hundred thousands of protein copies per mRNA molecule for others. In conclusion, our data suggest that transcriptome analysis can be used as a tool to predict the protein copy numbers per cell, thus forming an attractive link between the field of genomics and proteomics.

Place, publisher, year, edition, pages
Blackwell Publishing, 2016. Vol. 12, no 10, 883
Keyword [en]
gene expression, protein quantification, targeted proteomics, transcriptomics
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-196993DOI: 10.15252/msb.20167144ISI: 000386948100001ScopusID: 2-s2.0-84992562628OAI: oai:DiVA.org:kth-196993DiVA: diva2:1055905
Note

QC 20161213

Available from: 2016-12-13 Created: 2016-11-28 Last updated: 2016-12-13Bibliographically approved

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Edfors, FredrikDanielsson, FridaHallström, Björn M.Käll, LukasLundberg, EmmaForsström, BjörnUhlén, Mathias
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Proteomics and NanobiotechnologyScience for Life Laboratory, SciLifeLabGene Technology
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