Abstract
Thousands of scientific papers have described how plants responded to different levels of a given environmental factor, for a wide variety of physiological processes and morphological, anatomical or chemical characteristics. There is a clear need to summarize this information in a structured and comparable way through meta-analysis. This paper describes how to use relative trait responses from many independent experiments to create generalized dose-response curves. By applying the same methodology to a wide range of plant traits, varying from the molecular to the whole plant level, we can achieve an unprecedented view on the many ways that plants are affected by and acclimate to their environment. We illustrate this approach, which we refer to as ‘MetaPhenomics’, with a variety of previously published and unpublished dose-response curves of the effect of light intensity on 25 plant traits. Furthermore, we discuss the need and difficulties to expand this approach to the transcriptomics and metabolomics level, and show how the generalized dose-response curves can be used to improve simulation models as well as the communication between modelers and experimental plant biologists.
Original language | English |
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Pages (from-to) | 421-454 |
Number of pages | 34 |
Journal | Plant and Soil |
Volume | 476 |
Issue number | 1-2 |
Early online date | Jul 2022 |
DOIs | |
Publication status | Published - Jul 2022 |
Keywords
- Abiotic environment
- Dose-response curve
- Light intensity
- Modeling
- Normalization