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A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

机译:随机多细胞模型从自组织的叶序模式中识别疾病中的生物水印

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摘要

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems.>DOI:
机译:对发展机制的探索通常依赖于模式规律性的分析。由生物噪声引起的疾病是否可以携带有关发育系统构建原理的信息,这是一个有争议的重要问题。在这里,我们从理论上讲了使用植物轴器官的几何排列的叶轴作为模型系统的问题。音轴现象是由芽顶的侧向抑制驱动的再生器官发生。基于对叶序模式疾病的反复观察的启发,我们深入探讨了叶序模式的经典确定性观点。我们在茎尖建立了原基萌生的随机模型,在图案系统中整合了局部性和随机性。该随机模型概括了规则和不规则的叶序模式,并对由噪声引起的疾病的性质进行了定量预测。我们进一步表明,花序轴疾病指导我们有关花序轴动力学的参数,因此这些疾病可以揭示发育系统的生物学水印。> DOI:

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