Evidence map›Paper›PMID 30181316›Full record

ReviewThe Journal of cell biology2019

Interchromosomal interactions: A genomic love story of kissing chromosomes.

Philipp G Maass, A Rasim Barutcu, John L Rinn

Abstract readReview
In one paragraph

Review in The Journal of cell biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.

0numbers the graph read from it
0cells of the map it votes in
90citing 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

90 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Differential analysis of image-based chromatin tracing data with Dory.bioRxiv : the preprint server for biology · 2026
    Article
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  13. Review
  14. Article
  15. Article
  16. Article
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  20. Article

30 more citing papers are in PubMed but not listed here.

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

3 authors.

Philipp G MaassDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA.ORCID 0000-0002-2742-8301
A Rasim BarutcuDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA.ORCID 0000-0002-4838-8695
John L RinnDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA john.rinn@colorado.edu.ORCID 0000-0002-6113-0381

Funding

Deciphering the function and mechanisms of lncRNA-mediated organization of nuclear compartmentsU01DA040612 · NIDA · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI GUTTMAN, MITCHELL, RINN, JOHN LOUIS · 2015 to 2019
$4.1M
Howard Hughes Medical InstituteNIDA NIH HHS U01 DA040612
6 · The paper itself

Abstract

Nuclei require a precise three- and four-dimensional organization of DNA to establish cell-specific gene-expression programs. Underscoring the importance of DNA topology, alterations to the nuclear architecture can perturb gene expression and result in disease states. More recently, it has become clear that not only intrachromosomal interactions, but also interchromosomal interactions, a less studied feature of chromosomes, are required for proper physiological gene-expression programs. Here, we review recent studies with emerging insights into where and why cross-chromosomal communication is relevant. Specifically, we discuss how long noncoding RNAs (lncRNAs) and three-dimensional gene positioning are involved in genome organization and how low-throughput (live-cell imaging) and high-throughput (Hi-C and SPRITE) techniques contribute to understand the fundamental properties of interchromosomal interactions.

Indexed as

Chromosome AberrationsGenomeAnimalsCCCTC-Binding FactorCell NucleusChromosomesDNAGene Expression RegulationGene Regulatory NetworksHumansMolecular ImagingNucleic Acid ConformationRNA, Long NoncodingCCCTC-Binding FactorCTCF protein, humanDNAlong noncoding RNA Firre, humanRNA, Long Noncoding

Identifiers

PMID30181316
PMCPMC6314556

What OpenQuestion holds

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LicenceCC BY-NC-SA
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.