Evidence map›Paper›PMID 21179022›Full record

ArticleMolecular systems biology2010

Defining the transcriptome and proteome in three functionally different human cell lines.

Emma Lundberg, Linn Fagerberg, Daniel Klevebring, Ivan Matic, Tamar Geiger, Juergen Cox, Cajsa Algenäs, Joakim Lundeberg, Matthias Mann, Mathias Uhlen

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 206 papers.

0numbers the graph read from it
0cells of the map it votes in
206citing papers in PubMed
15.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

206 citing papers in PubMed, 380 citations in OpenAlex.

  1. Estimating protein isoform abundances with [Formula: see text].Proceedings of the National Academy of Sciences of the United States of America · 2026
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146 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Emma LundbergScience for Life Laboratory, Royal Institute of Technology, Stockholm, Sweden.
Linn Fagerberg
Daniel Klevebring
Ivan Matic
Tamar Geiger
Juergen Cox
Cajsa Algenäs
Joakim Lundeberg
Matthias Mann
Mathias Uhlen
AlbaNova · SEMax Planck Institute of Biochemistry · DEScience for Life Laboratory · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An essential question in human biology is how cells and tissues differ in gene and protein expression and how these differences delineate specific biological function. Here, we have performed a global analysis of both mRNA and protein levels based on sequence-based transcriptome analysis (RNA-seq), SILAC-based mass spectrometry analysis and antibody-based confocal microscopy. The study was performed in three functionally different human cell lines and based on the global analysis, we estimated the fractions of mRNA and protein that are cell specific or expressed at similar/different levels in the cell lines. A highly ubiquitous RNA expression was found with >60% of the gene products detected in all cells. The changes of mRNA and protein levels in the cell lines using SILAC and RNA ratios show high correlations, even though the genome-wide dynamic range is substantially higher for the proteins as compared with the transcripts. Large general differences in abundance for proteins from various functional classes are observed and, in general, the cell-type specific proteins are low abundant and highly enriched for cell-surface proteins. Thus, this study shows a path to characterize the transcriptome and proteome in human cells from different origins.

Indexed as

Gene Expression ProfilingGenome, HumanBase SequenceBlotting, WesternCell LineFluorescent Antibody TechniqueHumansMass SpectrometryMembrane ProteinsMicroscopy, ConfocalPolymerase Chain ReactionProteinsProteomeRNA, MessengerSequence Analysis, ProteinTranscription, GeneticMembrane ProteinsProteinsProteomeRNA, Messenger

Identifiers

PMID21179022
PMCPMC3018165
OpenAlexW2106806242

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.