LaRue, Therese; Lindner, Heike; Srinivas, Ankit; Exposito-Alonso, Moises; Lobet, Guillaume; Dinneny, José R (2022). Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform. eLife, 11 eLife Sciences Publications 10.7554/eLife.76968
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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 Arabidopsis thaliana 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 Arabidopsis, 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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) |
UniBE Contributor: |
Lindner, Heike |
Subjects: |
500 Science > 580 Plants (Botany) |
ISSN: |
2050-084X |
Publisher: |
eLife Sciences Publications |
Language: |
English |
Submitter: |
Peter Alfred von Ballmoos-Haas |
Date Deposited: |
11 Oct 2022 08:38 |
Last Modified: |
05 Dec 2022 16:26 |
Publisher DOI: |
10.7554/eLife.76968 |
PubMed ID: |
36047575 |
BORIS DOI: |
10.48350/173631 |
URI: |
https://boris.unibe.ch/id/eprint/173631 |
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