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利用机器人辅助表型平台揭示根系结构和生长动态的自然变异。

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform.

机构信息

Department of Biology, Stanford University, Stanford, United States.

Department of Plant Biology, Carnegie Institution for Science, Stanford, United States.

出版信息

Elife. 2022 Sep 1;11:e76968. doi: 10.7554/eLife.76968.

Abstract

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in , over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions' respective origins.

摘要

植物王国拥有令人惊叹的复杂形态,这些形态很容易在地上观察到,但在地下观察则更具挑战性。了解根系在土壤中的分布多样性(称为根系结构(RSA))的巨大程度,对于确定该特征如何有助于物种在当地环境中的适应至关重要。根系是土壤环境和地上系统之间的接口,因此在锚固、资源吸收和应激弹性方面发挥着关键作用。之前,我们提出了 GLO-Roots(根生长和发光观测站)系统,以研究从发芽到成熟的土壤生长的植物的 RSA(Rellán-Álvarez 等人,2015)。在本研究中,我们使用机器人自动化了 GLO-Roots,并开发了图像分析管道,以便检查 RSA 的时间动态调节以及随着时间的推移, 在 中 RSA 的更广泛的自然变异。这些数据集描述了两个独立的品系面板的发育动态,并揭示了高度复杂和多基因的 RSA 特征,这些特征与各自起源的品系的气候变量显示出显著的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e024/9499532/5e612c9ff9c5/elife-76968-fig1.jpg

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