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  • Title: Stochastic Turing patterns of trichomes in Arabidopsis leaves.
    Author: Di Patti F, Ugartechea Chirino Y, Arbel-Goren R, Sharon T, Castillo A, Alvarez-Buylla E, Fanelli D, Stavans J.
    Journal: Proc Natl Acad Sci U S A; 2023 Oct 17; 120(42):e2309616120. PubMed ID: 37824528.
    Abstract:
    Biological patterns that emerge during the morphogenesis of multicellular organisms can display high precision at large scales, while at cellular scales, cells exhibit large fluctuations stemming from cell-cell differences in molecular copy numbers also called demographic noise. We study the conflicting interplay between high precision and demographic noise in trichome patterns on the epidermis of wild-type Arabidopsis thaliana leaves, as a two-dimensional model system. We carry out a statistical characterization of these patterns and show that their power spectra display fat tails-a signature compatible with noise-driven stochastic Turing patterns-which are absent in power spectra of patterns driven by deterministic instabilities. We then present a theoretical model that includes demographic noise stemming from birth-death processes of genetic regulators which we study analytically and by stochastic simulations. The model captures the observed experimental features of trichome patterns.
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