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Body plan evolvability: The role of variability in gene regulatory networks.

Authors :
Spirov, Alexander V.
Myasnikova, Ekaterina M.
Holloway, David M.
Source :
Journal of Bioinformatics & Computational Biology. Jun2024, Vol. 22 Issue 3, p1-24. 24p.
Publication Year :
2024

Abstract

Recent computational modeling of early fruit fly (Drosophila) development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression. Gap genes are expressed with greater spatial precision than the maternal patterns. Computational modeling of the gap–gap regulatory interactions provides a mechanistic understanding for this robustness to maternal variability in wild-type (WT) patterning. A long-standing question in evolutionary biology has been how a system which is robust, such as the developmental program creating any particular species' body plan, is also evolvable, i.e. how can a system evolve or speciate, if the WT form is strongly buffered and protected? In the present work, we use the WT model to explore the breakdown of such Waddington-type 'canalization'. What levels of variability will push the system out of the WT form; are there particular pathways in the gene regulatory mechanism which are more susceptible to losing the WT form; and when robustness is lost, what types of forms are most likely to occur (i.e. what forms lie near the WT)? Manipulating maternal effects in several different pathways, we find a common gap 'peak-to-step' pattern transition in the loss of WT. We discuss these results in terms of the evolvability of insect segmentation, and in terms of experimental perturbations and mutations which could test the model predictions. We conclude by discussing the prospects for using continuum models of pattern dynamics to investigate a wider range of evo-devo problems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02197200
Volume :
22
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Bioinformatics & Computational Biology
Publication Type :
Academic Journal
Accession number :
178652397
Full Text :
https://doi.org/10.1142/S0219720024500112