Evidence map›Paper›PMID 34035432›Full record

ArticleCommunications biology2021

A combined approach for single-cell mRNA and intracellular protein expression analysis.

Johan Reimegård, Marcel Tarbier, Marcus Danielsson, Jens Schuster, Sathishkumar Baskaran, Styliani Panagiotou, Niklas Dahl, Marc R Friedländer, Caroline J Gallant

Abstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

90 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Integration ofFrontiers in immunology · 2023
    Pooled it
  2. Review
  3. Unveiling the Immune Mechanisms of Hypertension With Single-Cell Transcriptome-Wide Mendelian Randomization.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Cell Growth and Division Shape mRNA-Protein Correlations.bioRxiv : the preprint server for biology · 2026
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

30 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

9 authors.

Johan Reimegård *National Bioinformatics Infrastructure Sweden, Uppsala University, Uppsala, Sweden.
Marcel Tarbier *Science for Life Laboratory, Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden.
Marcus Danielsson *Science for Life Laboratory, Uppsala University, Uppsala, Sweden.ORCID 0000-0003-4418-0165
Jens SchusterDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-4383-9880
Sathishkumar BaskaranDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Styliani PanagiotouDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Niklas DahlDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-8122-0800
Marc R FriedländerScience for Life Laboratory, Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden.
Caroline J GallantDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. caroline.gallant@10xgenomics.com.ORCID 0000-0002-1499-8444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combined measurements of mRNA and protein expression in single cells enable in-depth analysis of cellular states. We present SPARC, an approach that combines single-cell RNA-sequencing with proximity extension essays to simultaneously measure global mRNA and 89 intracellular proteins in individual cells. We show that mRNA expression fails to accurately reflect protein abundance at the time of measurement, although the direction of changes is in agreement during neuronal differentiation. Moreover, protein levels of transcription factors better predict their downstream effects than do their corresponding transcripts. Finally, we highlight that protein expression variation is overall lower than mRNA variation, but relative protein variation does not reflect the mRNA level. Our results demonstrate that mRNA and protein measurements in single cells provide different and complementary information regarding cell states. SPARC presents a state-of-the-art co-profiling method that overcomes current limitations in throughput and protein localization, including removing the need for cell fixation.

Indexed as

Gene Expression ProfilingHumansProteinsProteomicsRNA, MessengerSequence Analysis, RNASingle-Cell AnalysisTranscription, GeneticProteinsRNA, Messenger

Identifiers

PMID34035432
PMCPMC8149646

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.