Dynamic directionality of cell states in Boolean gene regulatory networks; a model of structural constraints in cell development.
Date
2019-05-08
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Abstract
This project studies the dynamics of three Boolean gene regulatory
networks for B and T cell differentiation and proposes an original gene regulatory
network for larval fat body remodeling in Drosophila. The difference between the
limited number of attractors in the gene regulatory networks and the many transient
states that lead to the attractors can be seen as analogous to the finite number of
phenotypic traits and their underlying genetic variation. The entropy, self
transitioning probability, attractability and steady-state probability of the Markov
Chain simulation of transitions between the attractors was compared with the
experimentally observed phenotypic transformation of cells undergoing
differentiation in vitro and in vivo. The model was able to rank attractors bearing
markers of differentiation in a logical order. The reconstruction of the potential
transition graph revealed cyclic patterns of recurring attractor states. This supports
the hypothesis of an attractor of attractors: the Boolean version of canalization. The
construction of a gene regulatory network for larval fat body remodeling shed light
on components and combinations of components that instruct the system to
maintain its inherit canalization.
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Keywords
Boolean Network, Canalization, Entropy, Steady State Probability, Attractor