基于模型的全器官生长动力学重建揭示了叶片形态发生的不变模式。

Quantitative Plant Biology Pub Date : 2023-02-03 eCollection Date: 2023-01-01 DOI:10.1017/qpb.2022.23
Mohamed Oughou, Eric Biot, Nicolas Arnaud, Aude Maugarny-Calès, Patrick Laufs, Philippe Andrey, Jasmine Burguet
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引用次数: 0

摘要

植物器官的形态发生在时间和空间上跨越了几个数量级。由于活体成像的局限性,分析器官从起始阶段到成熟阶段的整个生长过程通常依赖于从不同时间点和个体采样的静态数据。我们引入了一种基于模型的新策略,用于确定器官的生长时间,并根据静态数据重建无限时间窗内的形态发生轨迹。利用这种方法,我们发现拟南芥的叶片是以 1 天的固定时间间隔萌发的。尽管成叶形态各异,但不同等级的叶片表现出共同的生长动态,生长参数根据叶片等级呈线性渐变。在亚器官尺度上,来自相同或不同叶片的连续锯齿也遵循共同的生长动态,这表明叶片的整体和局部生长模式是分离的。对形态改变的突变体叶片进行分析,突显了成体形状与形态发生轨迹之间的不相关性,从而强调了我们的方法在确定器官形态发生过程中的决定因素和关键时间点方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis.

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis.

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis.

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis.

Plant organ morphogenesis spans several orders of magnitude in time and space. Because of limitations in live-imaging, analysing whole organ growth from initiation to mature stages typically rely on static data sampled from different timepoints and individuals. We introduce a new model-based strategy for dating organs and for reconstructing morphogenetic trajectories over unlimited time windows based on static data. Using this approach, we show that Arabidopsis thaliana leaves are initiated at regular 1-day intervals. Despite contrasted adult morphologies, leaves of different ranks exhibited shared growth dynamics, with linear gradations of growth parameters according to leaf rank. At the sub-organ scale, successive serrations from same or different leaves also followed shared growth dynamics, suggesting that global and local leaf growth patterns are decoupled. Analysing mutants leaves with altered morphology highlighted the decorrelation between adult shapes and morphogenetic trajectories, thus stressing the benefits of our approach in identifying determinants and critical timepoints during organ morphogenesis.

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