Equivalent genetic regulatory networks in different contexts recover contrasting spatial cell patterns that resemble those in Arabidopsis root and leaf epidermis: a dynamic model

• Published in: The International journal of developmental biology Vol. 51; no. 2; pp. 139 - 155
• Main Authors: Benitez, Mariana, Espinosa-Soto, Carlos, Padilla-Longoria, Pablo, Diaz, Jose, Alvarez-Buylla, Elena R.
• Format: Journal Article
• Language: English
• Published: Spain 2007
• Subjects: Arabidopsis - genetics; Arabidopsis - growth & development; Arabidopsis thaliana; Helix-Loop-Helix Motifs - genetics; Models, Biological; Plant Epidermis - cytology; Plant Epidermis - physiology; Plant Leaves - physiology; Plant Roots - physiology; Signal Transduction
• ISSN: 0214-6282
• DOI: 10.1387/ijdb.062183mb

In Arabidopsis thaliana, leaf and root epidermis hairs exhibit contrasting spatial arrangements even though the genetic networks regulating their respective cell-fate determination have very similar structures and components. We integrated available experimental data for leaf and root hair patterning in dynamic network models which may be reduced to activator-inhibitor models. This integration yielded expected results for these kinds of dynamic models, including striped and dotted cell patterns which are characteristic of root and leaf epidermis, respectively. However, these formal tools have led us to novel insights on current data and to put forward precise hypotheses which can be addressed experimentally. In particular, despite subtle differences in the root and leaf networks, these have equivalent dynamical behaviors. Our simulations also suggest that only when a biasing signal positively affects an activator in the network, the system recovers striped cellular patterns similar to those of root epidermis. We also postulate that cell shape may affect pattern stability in the root. Our results thus support the idea that in this and other cases, contrasting spatial cell patterns and other evolutionary morphogenetic novelties originate from conserved genetic network modules subject to divergent contextual traits.