Evidence map›Paper›PMID 28957653›Full record

ArticleCell systems2017

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.

Luca Mariani, Kathryn Weinand, Anastasia Vedenko, Luis A Barrera, Martha L Bulyk

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

25 citing papers in PubMed, 47 citations in OpenAlex.

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  12. Computational biology approaches for mapping transcriptional regulatory networks.Computational and structural biotechnology journal · 2021
    Review
  13. Article
  14. Article
  15. Article
  16. LIN28B regulates transcription and potentiates MYCN-induced neuroblastoma through binding to ZNF143 at target gene promotors.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  17. Article
  18. Article
  19. 6mA-RicePred: A Method for Identifying DNAFrontiers in plant science · 2020
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Luca MarianiDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Kathryn WeinandDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Anastasia VedenkoDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Luis A BarreraDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Harvard-MIT Division of Health Sciences and Technology (HST), Harvard Medical School, Boston, MA 02115, USA; Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA.
Martha L BulykDivision of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Harvard-MIT Division of Health Sciences and Technology (HST), Harvard Medical School, Boston, MA 02115, USA; Committee on Higher Degrees in Biophysics, Harvard University, Cambridge, MA 02138, USA; Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. Electronic address: mlbulyk@genetics.med.harvard.edu.
Brigham and Women's Hospital · US

Funding

Center for Cell CircuitsP50HG006193 · NHGRI · BROAD INSTITUTE, INC. · PI REGEV, AVIV · 2011 to 2015
$15.6M
Universal, Compact Combinatorial Microarrays for DNA Binding Site DiscoveryR01HG003985 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI BULYK, MARTHA L · 2006 to 2017
$4.9M
High-Throughput Identification of Tissue/Cell-Type-Specific Cis Regulatory ModuleR01HG005287 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI BULYK, MARTHA L · 2010 to 2016
$3.4M
NHGRI NIH HHS P50 HG006193NHGRI NIH HHS R01 HG003985NHGRI NIH HHS R01 HG005287
6 · The paper itself

Abstract

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs.

Indexed as

Binding SitesChromatin ImmunoprecipitationComputational BiologyDNA-Binding ProteinsGene Regulatory NetworksGenomicsHumansProtein BindingRegulatory Sequences, Nucleic AcidSequence Analysis, RNATranscriptional ActivationTranscription FactorsTranscription, GeneticDNA-Binding ProteinsTranscription Factorsbackground constructionChIP-seq analysisDNA binding specificityENCODEmotif enrichmenttranscription factors

Identifiers

PMID28957653
PMCPMC5657590
OpenAlexW2760584685

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.