Stochastic Turing patterns of trichomes in Arabidopsis leaves

Francesca Di Patti, Yamel Ugartechea Chirino, Rinat Arbel-Gore, Tom Sharon, Aaron Castillo, Elena Alvarez-Buyll, Duccio Fanelli, Joel Stavans

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article numbere2309616120
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number42
Early online date12 Oct 2023
StatePublished - 17 Oct 2023

All Science Journal Classification (ASJC) codes

  • General


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