Evidence map›Paper›PMID 33637709›Full record

ArticleNature communications2021

Chromatin information content landscapes inform transcription factor and DNA interactions.

Ricardo D'Oliveira Albanus, Yasuhiro Kyono, John Hensley, Arushi Varshney, Peter Orchard, Jacob O Kitzman, Stephen C J Parker

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 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

7 authors.

Ricardo D'Oliveira AlbanusDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.ORCID http://orcid.org/0000-0003-3651-0136
Yasuhiro KyonoDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.
John HensleyDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.
Arushi VarshneyDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.ORCID http://orcid.org/0000-0001-9177-9707
Peter OrchardDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.
Jacob O KitzmanDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.ORCID http://orcid.org/0000-0002-6145-882X
Stephen C J ParkerDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA. scjp@umich.edu.ORCID http://orcid.org/0000-0001-8122-0117

Funding

University of Michigan Training Program in Genomic ScienceT32HG000040 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sebastian Zoellner · 1995 to 2026
$16.4M
Context-specific and combinatorial genetic regulatory grammars in diabetesR01DK117960 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Stephen CJ Parker · 2018 to 2026
$2.8M
NHGRI NIH HHS T32 HG000040NIDDK NIH HHS R01 DK117960
6 · The paper itself

Abstract

Interactions between transcription factors and chromatin are fundamental to genome organization and regulation and, ultimately, cell state. Here, we use information theory to measure signatures of organized chromatin resulting from transcription factor-chromatin interactions encoded in the patterns of the accessible genome, which we term chromatin information enrichment (CIE). We calculate CIE for hundreds of transcription factor motifs across human samples and identify two classes: low and high CIE. The 10-20% of common and tissue-specific high CIE transcription factor motifs, associate with higher protein-DNA residence time, including different binding site subclasses of the same transcription factor, increased nucleosome phasing, specific protein domains, and the genetic control of both chromatin accessibility and gene expression. These results show that variations in the information encoded in chromatin architecture reflect functional biological variation, with implications for cell state dynamics and memory.

Indexed as

Binding SitesCell LineChromatinDNADNA-Binding ProteinsGene Expression RegulationHep G2 CellsHumansNucleosomesTranscription FactorsTranscription, GeneticChromatinDNADNA-Binding ProteinsNucleosomesTranscription Factors

Identifiers

PMID33637709
PMCPMC7910283

What Socratic 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 Socratic graph.