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In silico evo-devo: reconstructing stages in the evolution of animal segmentation

Overview of attention for article published in EvoDevo, August 2016
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Title
In silico evo-devo: reconstructing stages in the evolution of animal segmentation
Published in
EvoDevo, August 2016
DOI 10.1186/s13227-016-0052-8
Pubmed ID
Authors

Renske M. A. Vroomans, Paulien Hogeweg, Kirsten H. W. J. ten Tusscher

Abstract

The evolution of animal segmentation is a major research focus within the field of evolutionary-developmental biology. Most studied segmented animals generate their segments in a repetitive, anterior-to-posterior fashion coordinated with the extension of the body axis from a posterior growth zone. In the current study we ask which selection pressures and ordering of evolutionary events may have contributed to the evolution of this specific segmentation mode. To answer this question we extend a previous in silico simulation model of the evolution of segmentation by allowing the tissue growth pattern to freely evolve. We then determine the likelihood of evolving oscillatory sequential segmentation combined with posterior growth under various conditions, such as the presence or absence of a posterior morphogen gradient or selection for determinate growth. We find that posterior growth with sequential segmentation is the predominant outcome of our simulations only if a posterior morphogen gradient is assumed to have already evolved and selection for determinate growth occurs secondarily. Otherwise, an alternative segmentation mechanism dominates, in which divisions occur in large bursts through the entire tissue and all segments are created simultaneously. Our study suggests that the ancestry of a posterior signalling centre has played an important role in the evolution of sequential segmentation. In addition, it suggests that determinate growth evolved secondarily, after the evolution of posterior growth. More generally, we demonstrate the potential of evo-devo simulation models that allow us to vary conditions as well as the onset of selection pressures to infer a likely order of evolutionary innovations.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 18%
Student > Bachelor 7 18%
Researcher 6 15%
Student > Master 4 10%
Other 2 5%
Other 7 18%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 48%
Biochemistry, Genetics and Molecular Biology 11 28%
Unspecified 1 3%
Philosophy 1 3%
Earth and Planetary Sciences 1 3%
Other 0 0%
Unknown 7 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 September 2016.
All research outputs
#6,014,322
of 8,317,445 outputs
Outputs from EvoDevo
#156
of 182 outputs
Outputs of similar age
#167,489
of 259,532 outputs
Outputs of similar age from EvoDevo
#6
of 7 outputs
Altmetric has tracked 8,317,445 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 182 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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