14 NSFBIO: Bilateral NSF/BIO-BBSRC - Modeling the effects of intrinsic and extrinsic signaling on cellular differentiation in plants

尽管植物发育具有可塑性，但植物细胞的分化即使在受到干扰的情况下也是非常稳健的。因此，迫切需要更深入地了解控制细胞发育的复杂调控网络，以及它们如何运作、相互作用和响应细胞间和细胞外信号，以产生具有增加的生物量和胁迫耐受性的植物。我们提出，参与细胞分化的基因调控网络的涌现特性可以用从发育特异性转录组签名中获得的信息来表征和测试。为了验证这一假设，我们使用拟南芥根韧皮部筛管元件作为模型，为此我们开发了一套独特的分子、数学和生理学工具。因为去核的筛分子的完全分化是以一种非常压缩的方式发生的，在20个细胞内，SE提供了一种前所未有的细胞分辨率的细胞分化模型。我们的目标是整合开发特定的转录组学，molecularandimaging数据，与已知的关键监管机构使用常微分方程和代理的建模系统的信息。这种数学方法将使我们能够获得一个全面的和定量的角度来看，设计规则的进展，从干细胞到他们的最后阶段的分化。我们的目标是迭代提高我们的模型的准确性和强度，通过整合额外的数据后，暴露这个细胞过程的两个共同的扰动;共质体隔离和缺铁。

Despite the plasticity of plant development, cellular differentiation in plants is remarkablyrobust, even in the presence of perturbations. Thus, a greater understanding of the complexregulatory networks that control cellular development, and how they operate, interact, andrespond to intercellular and extracellular signals is urgently needed to generate plants withincreased biomass and stress-tolerance. We propose that emergent properties of gene regulatorynetworks involved in cellular differentiation can be represented and tested mathematicallyusing information gained from development-specific transcriptomic signatures in response tovarying conditions. To test this hypothesis we are using as a model the Arabidopsis root phloemsieve element, for which we have developed a unique set of molecular, mathematical, and physiologicaltools. Because complete differentiation of the enucleated sieve elements takes place in avery compressed manner, within 20 cells, SEs provide a cell differentiation model of unprecedentedcellular resolution. Our goal is to integrate development-specific transcriptomic, molecularand imaging data, with information about known key regulators using a system of ordinary differentialequations and agent based modeling. This mathematical approach will allow us to gain a comprehensiveand quantitative perspective of the design rules governing the progression from stem cellsto their final stage of differentiation. We aim to iteratively improve the accuracy and strengthof our models by integrating additional data after exposing this cellular process to two disparateperturbations; symplastic isolation and iron deficiency.