Stochastic Turing patterns of trichomes in Arabidopsis leaves
Published in Proceedings of the National Academy of Sciences (PNAS), 2023
In this work, we investigate the interplay between high-precision biological patterns and cellular-scale demographic noise using the trichome patterns of Arabidopsis thaliana as a model system. We demonstrate that the power spectra of these patterns exhibit signatures of noise-driven stochastic Turing patterns, which differ significantly from deterministic instabilities.
By developing a theoretical model that incorporates birth-death processes of genetic regulators, we provide both analytical insights and stochastic simulations that capture the experimental features of leaf trichomes. This study highlights how biological systems can leverage molecular fluctuations to generate robust spatial configurations.
Recommended citation: Di Patti, F., Ugartechea Chirino, Y., Arbel-Goren, R., Sharon, T., Castillo, A., Alvarez–Buylla, E., ... & Stavans, J. (2023). Stochastic Turing patterns of trichomes in Arabidopsis leaves. Proceedings of the National Academy of Sciences, 120(42), e2309616120.
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