Evidence map›Paper›PMID 26604142›Full record

ArticleHuman molecular genetics2016

Large-scale probabilistic 3D organization of human chromosome territories.

Nitasha Sehgal, Andrew J Fritz, Jaromira Vecerova, Hu Ding, Zihe Chen, Branislav Stojkovic, Sambit Bhattacharya, Jinhui Xu, Ronald Berezney

Open access · bronzeAbstract read
In one paragraph

Article in Human molecular genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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  5. Review
  6. Mitotic Antipairing of Homologous Chromosomes.Results and problems in cell differentiation · 2022
    Article
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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

9 authors at 2 institutions in 1 country.

Nitasha SehgalDepartment of Biological Sciences.
Andrew J FritzDepartment of Biological Sciences.
Jaromira VecerovaDepartment of Biological Sciences.
Hu DingDepartment of Computer Science and Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA and.
Zihe ChenDepartment of Computer Science and Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA and.
Branislav StojkovicDepartment of Computer Science and Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA and.
Sambit BhattacharyaDepartment of Mathematics and Computer Sciences, Fayetteville State University, Fayetteville, NC 28301, USA.
Jinhui XuDepartment of Computer Science and Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260, USA and.
Ronald BerezneyDepartment of Biological Sciences, berezney@buffalo.edu.
University at Buffalo, State University of New York · USFayetteville State University · US

Funding

Nuclear Matrix Structure and Genomic FunctionR01GM072131 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI BEREZNEY, RONALD · 2004 to 2007
$1.5M
NIGMS NIH HHS GM-072131NIGMS NIH HHS R01 GM072131
6 · The paper itself

Abstract

There is growing evidence that chromosome territories (CT) have a probabilistic non-random arrangement within the cell nucleus of mammalian cells including radial positioning and preferred patterns of interchromosomal interactions that are cell-type specific. While it is generally assumed that the three-dimensional (3D) arrangement of genes within the CT is linked to genomic regulation, the degree of non-random organization of individual CT remains unclear. As a first step to elucidating the global 3D organization (topology) of individual CT, we performed multi-color fluorescence in situ hybridization using six probes extending across each chromosome in human WI38 lung fibroblasts. Six CT were selected ranging in size and gene density (1, 4, 12, 17, 18 and X). In-house computational geometric algorithms were applied to measure the 3D distances between every combination of probes and to elucidate data-mined structural patterns. Our findings demonstrate a high degree of non-random arrangement of individual CT that vary from chromosome to chromosome and display distinct changes during the cell cycle. Application of a classic, well-defined data mining and pattern recognition approach termed the 'k-means' generated 3D models for the best fit arrangement of each chromosome. These predicted models correlated well with the detailed distance measurements and analysis. We propose that the unique 3D topology of each CT and characteristic changes during the cell cycle provide the structural framework for the global gene expression programs of the individual chromosomes.

Indexed as

AlgorithmsCell CycleCell LineCell NucleusChromosome MappingChromosomes, HumanData MiningFetusFibroblastsHumansIn Situ Hybridization, FluorescencePattern Recognition, Automated

Identifiers

PMID26604142
PMCPMC4731017
OpenAlexW2271272215

What OpenQuestion holds

Textmetadata
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.