The position of cells during development is constantly subject to noise, i.e. cell-level noise. We do not yet fully understand how cell-level noise coming from processes such as cell division or movement leads to morphological noise, i.e. morphological differences between genetically identical individuals developing in the same environment. To address this question we constructed a large ensemble of random genetic networks regulating cell behaviors (contraction, adhesion, etc.) and cell signaling. We simulated them with a general computational model of development, EmbryoMaker. We identified and studied the dynamics, under cell-level noise, of those networks that lead to the development of animal-like morphologies from simple blastula-like initial conditions. We found that growth by cell division is a major contributor to morphological noise. Self-activating gene network loops also amplified cell-level noise into morphological noise while long-range signaling and epithelial stiffness tended to reduce morphological noise.
Inglés
51 - Matemáticas
Synaptic plasticity; Fluctuations; Network connectivity; Perceptual learning
31 p.
Springer
Journal of Computational Neuroscience
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