Evidence map›Paper›PMID 35150617›Full record

ArticleBiophysical journal2022

Differences in nanoscale organization of regulatory active and inactive human chromatin.

Katharina Brandstetter, Tilo Zülske, Tobias Ragoczy, David Hörl, Miguel Guirao-Ortiz, Clemens Steinek, Toby Barnes, Gabriela Stumberger, Jonathan Schwach, Eric Haugen and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Biophysical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  8. Genome modeling: From chromatin fibers to genes.Current opinion in structural biology · 2023
    Review
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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

16 authors at 4 institutions in 2 countries.

Katharina BrandstetterHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Tilo ZülskeCompetence Center Bioinformatics, Institute for Applied Computer Science, Hochschule Stralsund, Stralsund, Germany.
Tobias RagoczyAltius Institute for Biomedical Sciences, Seattle, Washington.
David HörlHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Miguel Guirao-OrtizHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Clemens SteinekHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Toby BarnesBiomedical Center (BMC), Molecular Biology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Martinsried, Germany.
Gabriela StumbergerHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Jonathan SchwachHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Eric HaugenAltius Institute for Biomedical Sciences, Seattle, Washington.
Eric RynesAltius Institute for Biomedical Sciences, Seattle, Washington.
Philipp KorberBiomedical Center (BMC), Molecular Biology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Martinsried, Germany.
John A StamatoyannopoulosAltius Institute for Biomedical Sciences, Seattle, Washington; Department of Genome Sciences, University of Washington, Seattle, Washington; Department of Medicine, Division of Oncology, University of Washington, Seattle, Washington.
Heinrich LeonhardtHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany.
Gero WedemannCompetence Center Bioinformatics, Institute for Applied Computer Science, Hochschule Stralsund, Stralsund, Germany. Electronic address: gero.wedemann@hochschule-stralsund.de.
Hartmann HarzHuman Biology & BioImaging, Faculty of Biology, Ludwig-Maximilians-Universität München, Munich, Germany. Electronic address: harz@biologie.uni-muenchen.de.
Ludwig-Maximilians-Universität München · DEAltius Institute for Biomedical Sciences · USUniversity of Applied Sciences Stralsund · DEUniversity of Washington · US

Funding

Project-002RM1HG007743 · NHGRI · UNIVERSITY OF WASHINGTON · PI STAMATOYANNOPOULOS, JOHN A · 2015 to 2019
$10.1M
NHGRI NIH HHS RM1 HG007743
6 · The paper itself

Abstract

Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. Analyzing genome-wide data from 733 human cell and tissue samples, we identified 2 prototypical regions that exhibit high or absent hypersensitivity to deoxyribonuclease I, respectively. These regulatory active or inactive regions were examined in the lymphoblast cell line K562 by using high-throughput super-resolution microscopy. In both regions, we systematically measured the physical distance of 2 fluorescence in situ hybridization spots spaced by only 5 kb of DNA. Unexpectedly, the resulting distance distributions range from very compact to almost elongated configurations of more than 200-nm length for both the active and inactive regions. Monte Carlo simulations of a coarse-grained model of these chromatin regions based on published data of nucleosome occupancy in K562 cells were performed to understand the underlying mechanisms. There was no parameter set for the simulation model that can explain the microscopically measured distance distributions. Obviously, the chromatin state given by the strength of internucleosomal interaction, nucleosome occupancy, or amount of histone H1 differs from cell to cell, which results in the observed broad distance distributions. This large variability was not expected, especially in inactive regions. The results for the mechanisms for different distance distributions on this scale are important for understanding the contacts that mediate gene regulation. Microscopic measurements show that the inactive region investigated here is expected to be embedded in a more compact chromatin environment. The simulation results of this region require an increase in the strength of internucleosomal interactions. It may be speculated that the higher density of chromatin is caused by the increased internucleosomal interaction strength.

Indexed as

ChromatinNucleosomesDNAHumansIn Situ Hybridization, FluorescenceMolecular ConformationChromatinDNANucleosomes

Identifiers

PMID35150617
PMCPMC8943813
OpenAlexW4210969799

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.