Evidence map›Paper›PMID 25878130›Full record

ArticleJournal of the Royal Society, Interface2015

Localized auxin peaks in concentration-based transport models of the shoot apical meristem.

Delphine Draelants, Daniele Avitabile, Wim Vanroose

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Scaling relations for auxin waves.Journal of mathematical biology · 2022
    Article
  3. Computational Models of Auxin-Driven Patterning in Shoots.Cold Spring Harbor perspectives in biology · 2022
    Review
  4. Modeling Plant Tissue Development Using VirtualLeaf.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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.

Delphine DraelantsDepartment of Mathematics and Computer Science, Universiteit Antwerpen, Middelheimlaan 1, 2020 Antwerpen, Belgium delphine.draelants@uantwerpen.be.
Daniele AvitabileCentre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK daniele.avitabile@nottingham.ac.uk.
Wim VanrooseDepartment of Mathematics and Computer Science, Universiteit Antwerpen, Middelheimlaan 1, 2020 Antwerpen, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We study the formation of auxin peaks in a generic class of concentration-based auxin transport models, posed on static plant tissues. Using standard asymptotic analysis, we prove that, on bounded domains, auxin peaks are not formed via a Turing instability in the active transport parameter, but via simple corrections to the homogeneous steady state. When the active transport is small, the geometry of the tissue encodes the peaks' amplitude and location: peaks arise where cells have fewer neighbours, that is, at the boundary of the domain. We test our theory and perform numerical bifurcation analysis on two models that are known to generate auxin patterns for biologically plausible parameter values. In the same parameter regimes, we find that realistic tissues are capable of generating a multitude of stationary patterns, with a variable number of auxin peaks, that can be selected by different initial conditions or by quasi-static changes in the active transport parameter. The competition between active transport and production rate determines whether peaks remain localized or cover the entire domain. In particular, changes in the auxin production that are fast with respect to the cellular life cycle affect the auxin peak distribution, switching from localized spots to fully patterned states. We relate the occurrence of localized patterns to a snaking bifurcation structure, which is known to arise in a wide variety of nonlinear media, but has not yet been reported in plant models.

Indexed as

Models, BiologicalComputer SimulationDiffusionIndoleacetic AcidsMembrane Transport ProteinsMeristemModels, ChemicalPlant ProteinsProtein TransportTissue DistributionIndoleacetic AcidsMembrane Transport ProteinsPlant Proteinsauxin patternsauxin transport modellocalized patternsnumerical bifurcation analysissnaking

Identifiers

PMID25878130
PMCPMC4424673

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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.