Evidence map›Paper›PMID 30577869›Full record

ArticleEpigenetics & chromatin2018

Automated in situ chromatin profiling efficiently resolves cell types and gene regulatory programs.

Derek H Janssens, Steven J Wu, Jay F Sarthy, Michael P Meers, Carrie H Myers, James M Olson, Kami Ahmad, Steven Henikoff

Abstract read
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 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

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  13. In situ tools for chromatin structural epigenomics.Protein science : a publication of the Protein Society · 2022
    Article
  14. EWS::FLI1 and HOXD13 Control Tumor Cell Plasticity in Ewing Sarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
    Article
  15. Article
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  18. CUT&RUN Profiling of the Budding Yeast Epigenome.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  19. Article
  20. Article
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

8 authors.

Derek H JanssensBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
Steven J WuBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
Jay F SarthyBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
Michael P MeersBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
Carrie H MyersClinical Research Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
James M OlsonCancer and Blood Disorder Center, Seattle Children's Hospital, 4800 Sand Point Way, Seattle, WA, 98105, USA.
Kami AhmadBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA.
Steven HenikoffBasic Sciences Division, Fred Hutchinson Cancer Research Center, 1100 N. Fairview Ave, Seattle, WA, 98109, USA. steveh@fredhutch.org.

Funding

FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
Howard Hughes Medical InstituteNIH HHS S10 OD020069
6 · The paper itself

Abstract

backgroundOur understanding of eukaryotic gene regulation is limited by the complexity of protein-DNA interactions that comprise the chromatin landscape and by inefficient methods for characterizing these interactions. We recently introduced CUT&RUN, an antibody-targeted nuclease cleavage method that profiles DNA-binding proteins, histones and chromatin-modifying proteins in situ with exceptional sensitivity and resolution.

resultsHere, we describe an automated CUT&RUN platform and apply it to characterize the chromatin landscapes of human cells. We find that automated CUT&RUN profiles of histone modifications crisply demarcate active and repressed chromatin regions, and we develop a continuous metric to identify cell-type-specific promoter and enhancer activities. We test the ability of automated CUT&RUN to profile frozen tumor samples and find that our method readily distinguishes two pediatric glioma xenografts by their subtype-specific gene expression programs.

conclusionsThe easy, cost-effective workflow makes automated CUT&RUN an attractive tool for high-throughput characterization of cell types and patient samples.

Indexed as

Binding SitesChromatinChromatin ImmunoprecipitationDNA-Binding ProteinsEnhancer Elements, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticHigh-Throughput Screening AssaysHistone CodeHistonesHumansIn Situ HybridizationK562 CellsPromoter Regions, GeneticProtein BindingSoftwareChromatinDNA-Binding ProteinsHistonesTranscription FactorsChromatin regulatorsCUT&RUNHistone modificationsTranscription factors

Identifiers

PMID30577869
PMCPMC6302505

What OpenQuestion 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 OpenQuestion graph.