Evidence map›Paper›PMID 21698124›Full record

ArticlePLoS computational biology2011

Generation of diverse biological forms through combinatorial interactions between tissue polarity and growth.

Richard Kennaway, Enrico Coen, Amelia Green, Andrew Bangham

Abstract read
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Quantitative plant biology · 2021
    Article
  6. Review
  7. Multiscale integration of environmental stimuli in plant tropism produces complex behaviors.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  8. Floral organ development goes live.Journal of experimental botany · 2020
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Growth patterns for shape-shifting elastic bilayers.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  17. Article
  18. Enhancer evolution and the origins of morphological novelty.Current opinion in genetics & development · 2017
    Review
  19. Flower development: from morphodynamics to morphomechanics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
    Article
  20. 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

4 authors.

Richard KennawaySchool of Computing Sciences, University of East Anglia, Norwich, UK.
Enrico Coen
Amelia Green
Andrew Bangham

Funding

Biotechnology and Biological Sciences Research Council BB/F005555/1Biotechnology and Biological Sciences Research Council BB/F005997/1Biotechnology and Biological Sciences Research Council BBS/E/J/00000152
6 · The paper itself

Abstract

A major problem in biology is to understand how complex tissue shapes may arise through growth. In many cases this process involves preferential growth along particular orientations raising the question of how these orientations are specified. One view is that orientations are specified through stresses in the tissue (axiality-based system). Another possibility is that orientations can be specified independently of stresses through molecular signalling (polarity-based system). The axiality-based system has recently been explored through computational modelling. Here we develop and apply a polarity-based system which we call the Growing Polarised Tissue (GPT) framework. Tissue is treated as a continuous material within which regionally expressed factors under genetic control may interact and propagate. Polarity is established by signals that propagate through the tissue and is anchored in regions termed tissue polarity organisers that are also under genetic control. Rates of growth parallel or perpendicular to the local polarity may then be specified through a regulatory network. The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. This constraint leads to the emergence of features such as curvature that were not directly specified by the regulatory networks. Resultant growth feeds back to influence spatial arrangements and local orientations of tissue, allowing complex shapes to emerge from simple rules. Moreover, asymmetries may emerge through interactions between polarity fields. We illustrate the value of the GPT-framework for understanding morphogenesis by applying it to a growing Snapdragon flower and indicate how the underlying hypotheses may be tested by computational simulation. We propose that combinatorial intractions between orientations and rates of growth, which are a key feature of polarity-based systems, have been exploited during evolution to generate a range of observed biological shapes.

Indexed as

Models, BiologicalAnisotropyAntirrhinumCell PolarityComputational BiologyComputer SimulationGene Expression Regulation, PlantMorphogenesis

Identifiers

PMID21698124
PMCPMC3116900

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.