Evidence map›Paper›PMID 33431919›Full record

ArticleScientific reports2021

Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin.

Javier Arpòn, Kaori Sakai, Valérie Gaudin, Philippe Andrey

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.6field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Javier ArpònInstitut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France.
Kaori SakaiInstitut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France.
Valérie GaudinInstitut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France. valerie.gaudin@inrae.fr.
Philippe AndreyInstitut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France. philippe.andrey@inrae.fr.
AgroParisTech · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions.

Indexed as

Models, BiologicalArabidopsisHeterochromatinHeterochromatin

Identifiers

PMID33431919
PMCPMC7801681
OpenAlexW3119693300

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.