2017/10/10 by Michäel Dougoud, Christian Mazza, Dougoud, Michael +5
Biochemistry, Genetics and Molecular Biology · Computer Science · #FOS: Biological sciences #Gene Regulatory Network Analysis #Nonlinear Dynamics and Pattern Formation #Tissues and Organs (q-bio.TO)
paper · pdf · doi:10.48550/arxiv.1710.03563
openalex publication_date 2017/10/10 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
Piebaldism usually manifests as white areas of fur, hair or skin due to the\nabsence of pigment-producing cells in those regions. The distribution of the\nwhite and colored zones does not follow the classical Turing patterns. Here we\npresent a modeling framework for pattern formation that enables to easily\nmodify the relationship between three factors with different feedback\nmechanisms. These factors consist of two diffusing factors and a\ncell-autonomous immobile transcription factor. Globally the model allowed to\ndistinguishing four different situations. Two situations result in the\nproduction of classical Turing patterns; regularly spaced spots and labyrinth\npatterns. Moreover, an initial slope in the activation of the transcription\nfactor produces straight lines. The third situation does not lead to patterns,\nbut results in different homogeneous color tones. Finally, the fourth one sheds\nnew light on the possible mechanisms leading to the formation of piebald\npatterns exemplified by the random patterns on the fur of some cow strains and\nDalmatian dogs. We demonstrate that these piebald patterns are of transient\nnature, develop from random initial conditions and rely on a system's\nbi-stability. The main novelty lies in our finding that the presence of a\ncell-autonomous factor not only expands the range of reaction diffusion\nparameters in which a pattern may arise, but also extends the pattern-forming\nabilities of the reaction-diffusion equations.\n