Evidence map›Paper›PMID 32350457›Full record

ArticleNature protocols2020

Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq.

Corina M Markodimitraki, Franka J Rang, Koos Rooijers, Sandra S de Vries, Alex Chialastri, Kim L de Luca, Silke J A Lochs, Dylan Mooijman, Siddharth S Dey, Jop Kind

Abstract read
In one paragraph

Article in Nature protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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.

Corina M Markodimitraki *Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.ORCID http://orcid.org/0000-0002-2683-755X
Franka J Rang *Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.ORCID http://orcid.org/0000-0001-5772-3283
Koos RooijersOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.ORCID http://orcid.org/0000-0002-0412-468X
Sandra S de VriesOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.
Alex ChialastriDepartment of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA, USA.
Kim L de LucaOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.
Silke J A LochsOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.
Dylan MooijmanOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.
Siddharth S DeyDepartment of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA, USA. sdey@ucsb.edu.ORCID http://orcid.org/0000-0002-1161-1654
Jop KindOncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands. j.kind@hubrecht.eu.ORCID http://orcid.org/0000-0001-7538-2638

Funding

A marker-free technology for mapping the epigenome of cell types in mammalian tissuesR01HG011013 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI DEY, SIDDHARTH SUBHAS · 2020 to 2024
$1.8M
EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 678423Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research) 016.161.339Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research) 016.181.013Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research) 824.15.019NHGRI NIH HHS R01 HG011013
6 · The paper itself

Abstract

Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.

Indexed as

AnimalsCell LineCell Line, TumorDNADNA MethylationEscherichia coliEscherichia coli ProteinsGene Expression ProfilingGenomicsHumansMiceProtein BindingProteinsRecombinant Fusion ProteinsSequence Analysis, DNASingle-Cell Analysisdam protein, E coliDNAEscherichia coli ProteinsProteinsRecombinant Fusion ProteinsSite-Specific DNA-Methyltransferase (Adenine-Specific)

Identifiers

PMID32350457
PMCPMC7779467

What OpenQuestion holds

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LicenceTDM
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.