Geometrical constraints in a gene network model and pattern formation

Abstract

A fundamental task in developmental biology is to identify the mechanisms which drive morphogenesis. In many cases, pattern formation is driven by the positional information determined by both the gradient of maternal factors and hard-wired mechanisms embedded in the genome. Alternative mechanisms of positional information that contribute to patterning are the influence of signals derived from surrounding tissues. In this paper, we show that the interplay of geometrical constraints imposed by tissue shapes and hard-wired mechanisms, computationally implemented by a gene network model, can able to induce stable complex patterns. The rise of these patterns depends strongly on the geometrical constraints such as the shape of the surrounding tissues.