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Reshaping the epigenetic landscape during early flower development: induction of attractor transitions by relative differences in gene decay rates

Overview of attention for article published in BMC Systems Biology, May 2015
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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1 X user
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1 Wikipedia page

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Title
Reshaping the epigenetic landscape during early flower development: induction of attractor transitions by relative differences in gene decay rates
Published in
BMC Systems Biology, May 2015
DOI 10.1186/s12918-015-0166-y
Pubmed ID
Authors

Jose Davila-Velderrain, Carlos Villarreal, Elena R Alvarez-Buylla

Abstract

Gene regulatory network (GRN) dynamical models are standard systems biology tools for the mechanistic understanding of developmental processes and are enabling the formalization of the epigenetic landscape (EL) model. In this work we propose a modeling framework which integrates standard mathematical analyses to extend the simple GRN Boolean model in order to address questions regarding the impact of gene specific perturbations in cell-fate decisions during development. We systematically tested the propensity of individual genes to produce qualitative changes to the EL induced by modification of gene characteristic decay rates reflecting the temporal dynamics of differentiation stimuli. By applying this approach to the flower specification GRN (FOS-GRN) we uncovered differences in the functional (dynamical) role of their genes. The observed dynamical behavior correlates with biological observables. We found a relationship between the propensity of undergoing attractor transitions between attraction basins in the EL and the direction of differentiation during early flower development - being less likely to induce up-stream attractor transitions as the course of development progresses. Our model also uncovered a potential mechanism at play during the transition from EL basins defining inflorescence meristem to those associated to flower organs meristem. Additionally, our analysis provided a mechanistic interpretation of the homeotic property of the ABC genes, being more likely to produce both an induced inter-attractor transition and to specify a novel attractor. Finally, we found that there is a close relationship between a gene's topological features and its propensity to produce attractor transitions. The study of how the state-space associated with a dynamical model of a GRN can be restructured by modulation of genes' characteristic expression times is an important aid for understanding underlying mechanisms occurring during development. Our contribution offers a simple framework to approach such problem, as exemplified here by the case of flower development. Different GRN models and the effect of diverse inductive signals can be explored within the same framework. We speculate that the dynamical role of specific genes within a GRN, as uncovered here, might give information about which genes are more likely to link a module to other regulatory circuits and signaling transduction pathways.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Italy 1 2%
Unknown 62 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 23%
Student > Ph. D. Student 10 16%
Researcher 10 16%
Student > Master 6 9%
Student > Doctoral Student 3 5%
Other 8 13%
Unknown 12 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 41%
Biochemistry, Genetics and Molecular Biology 13 20%
Computer Science 4 6%
Engineering 3 5%
Physics and Astronomy 2 3%
Other 3 5%
Unknown 13 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 07 October 2018.
All research outputs
#7,215,016
of 22,805,349 outputs
Outputs from BMC Systems Biology
#296
of 1,142 outputs
Outputs of similar age
#86,409
of 264,546 outputs
Outputs of similar age from BMC Systems Biology
#5
of 23 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,546 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.