Modeling of genetic regulatory networks in the differentiation of neural crest stem cells to sensory neurons by means of boolean networks

Abstract

In the present study we have generated a GRN comprising the process by which neural crest stem cells develop to two types of sensory neurons (Propioceptors and Nocioceptors). We have also been able to find patterns of regulation (motifs) that act cooperatively to control such process. Surprisingly, these motifs take place in similar stages during the development of erythrocytes from hematopoietic stem cells. Regarding the complexity of the GRN found, we then used Random Boolean Networks (RBN) for this purpose, which showed key components as well as the dynamics of the process through changes in initial conditions. Finally, the motifs were reflected in the model, suggesting insights for further studies.