Evidence map›Paper›PMID 30414612›Full record

ArticleEpigenetics & chromatin2018

Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.

Fatemeh Behjati Ardakani, Kathrin Kattler, Karl Nordström, Nina Gasparoni, Gilles Gasparoni, Sarah Fuchs, Anupam Sinha, Matthias Barann, Peter Ebert, Jonas Fischer and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Epigenetics & chromatin, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Molecular models of bidirectional promoter regulation.Current opinion in structural biology · 2024
    Review
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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

21 authors.

Fatemeh Behjati ArdakaniExcellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.
Kathrin KattlerDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Karl NordströmDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Nina GasparoniDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Gilles GasparoniDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Sarah FuchsDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Anupam SinhaInstitute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany.
Matthias BarannInstitute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany.
Peter EbertDepartment of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.
Jonas FischerExcellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany.
Barbara HutterApplied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany.
Gideon ZipprichData Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
Charles D ImbuschApplied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany.
Bärbel FelderData Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
Jürgen EilsData Management and Genomics IT, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
Benedikt BrorsApplied Bioinformatics, Deutsches Krebsforschungszentrum, Berliner-Str. 41, Heidelberg, 69120, Germany.
Thomas LengauerDepartment of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics, Campus E 4, Saarbrücken, 66123, Germany.
Thomas MankeMax Planck Institute of Immunobiology and Epigenetics, Stübeweg 51, Freiburg, 79108, Germany.
Philip RosenstielInstitute of Clinical Molecular Biology, Christian-Albrechts-University, Rosalind-Franklin-Str. 12, Kiel, 24105, Germany.
Jörn WalterDepartment of Genetics, University of Saarland, Campus A2 4, Saarbrücken, 66123, Germany.
Marcel H SchulzExcellence Cluster for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Campus E1 7, Saarbrücken, 66123, Germany. marcel.schulz@em.uni-frankfurt.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs.

resultsWe performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.

conclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

Indexed as

Epigenesis, GeneticPromoter Regions, GeneticTranscriptional ActivationChromatin Assembly and DisassemblyDNA MethylationHep G2 CellsHistone CodeHumansSingle-Cell AnalysisTranscription FactorsTranscription FactorsBidirectional genesEpigeneticsSingle-cell RNA-seq

Identifiers

PMID30414612
PMCPMC6230222

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Registered trials

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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.