Evidence map›Paper›PMID 24288372›Full record

ArticleNucleic acids research2014

Quantifying the role of steric constraints in nucleosome positioning.

H Tomas Rube, Jun S Song

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

2 authors.

H Tomas RubeInstitute for Human Genetics, University of California, 513 Parnassus Avenue, Box 0794, San Francisco, CA 94143-0794, USA, The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, 513 Parnassus Avenue, Box 0794, San Francisco, CA 94143-0794, USA, Department of Epidemiology and Biostatistics, University of California, 513 Parnassus Avenue, Box 0794, San Francisco, CA 94143-0794, USA and Department of Bioengineering and Therapeutic Sciences, University of California, 513 Parnassus Avenue, Box 0794, San Francisco, CA 94143-0794, USA.
Jun S Song

Funding

Predicting Transcriptional and Epigenetic Networks in Cancer from Sequencing DataR01CA163336 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Jun S Song · 2012 to 2026
$4.4M
NCI NIH HHS R01 CA163336NCI NIH HHS R01CA163336
6 · The paper itself

Abstract

Statistical positioning, the localization of nucleosomes packed against a fixed barrier, is conjectured to explain the array of well-positioned nucleosomes at the 5' end of genes, but the extent and precise implications of statistical positioning in vivo are unclear. We examine this hypothesis quantitatively and generalize the idea to include moving barriers as well as nucleosomes actively packed against a barrier. Early experiments noted a similarity between the nucleosome profile aligned and averaged across genes and that predicted by statistical positioning; however, we demonstrate that aligning random nucleosomes also generates the same profile, calling the previous interpretation into question. New rigorous results reformulate statistical positioning as predictions on the variance structure of nucleosome locations in individual genes. In particular, a quantity termed the variance gradient, describing the change in variance between adjacent nucleosomes, is tested against recent high-throughput nucleosome sequencing data. Constant variance gradients provide support for generalized statistical positioning in ∼ 50% of long genes. Genes that deviate from predictions have high nucleosome turnover and cell-to-cell gene expression variability. The observed variance gradient suggests an effective nucleosome size of 158 bp, instead of the commonly perceived 147 bp. Our analyses thus clarify the role of statistical positioning in vivo.

Indexed as

3' Flanking Region5' Flanking RegionData Interpretation, StatisticalGene ExpressionNucleosomesSaccharomyces cerevisiaeNucleosomes

Identifiers

PMID24288372
PMCPMC3936764

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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.