Evidence map›Paper›PMID 33526904›Full record

ArticleCommunications biology2021

Bisulfite-free epigenomics and genomics of single cells through methylation-sensitive restriction.

Christoph Niemöller, Julius Wehrle, Julian Riba, Rainer Claus, Nathalie Renz, Janika Rhein, Sabine Bleul, Juliane M Stosch, Justus Duyster, Christoph Plass and 4 more

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 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Computational Methods for Single-cell DNA Methylome Analysis.Genomics, proteomics & bioinformatics · 2023
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Article
  16. Pathways of DNA Demethylation.Advances in experimental medicine and biology · 2022
    Article
  17. Review
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

14 authors.

Christoph Niemöller *Department of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Julius Wehrle *Department of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.ORCID 0000-0001-6514-4230
Julian RibaLaboratory for MEMS Applications, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, Germany.
Rainer ClausDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Nathalie RenzDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Janika RheinDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Sabine BleulDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Juliane M StoschDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Justus DuysterDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Christoph PlassDivision of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Pavlo LutsikDivision of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Daniel B LipkaSection Translational Cancer Epigenomics, Division of Translational Medical Oncology, German Cancer Research Center (DKFZ) & National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany.
Michael LübbertDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany.
Heiko BeckerDepartment of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany. heiko.becker@uniklinik-freiburg.de.ORCID 0000-0002-6919-4048

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell multi-omics are powerful means to study cell-to-cell heterogeneity. Here, we present a single-tube, bisulfite-free method for the simultaneous, genome-wide analysis of DNA methylation and genetic variants in single cells: epigenomics and genomics of single cells analyzed by restriction (epi-gSCAR). By applying this method, we obtained DNA methylation measurements of up to 506,063 CpGs and up to 1,244,188 single-nucleotide variants from single acute myeloid leukemia-derived cells. We demonstrate that epi-gSCAR generates accurate and reproducible measurements of DNA methylation and allows to differentiate between cell lines based on the DNA methylation and genetic profiles.

Indexed as

DNA MethylationEpigenesis, GeneticEpigenomeEpigenomicsSingle-Cell AnalysisCell Line, TumorCpG IslandsGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansLeukemia, Myeloid, AcutePolymerase Chain ReactionPolymorphism, Single NucleotideReproducibility of ResultsRNA-Seq

Identifiers

PMID33526904
PMCPMC7851132

What OpenQuestion holds

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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.