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Gravity is a powerful element in shaping plant development, with gravitropism, the oriented growth response of plant organs to the direction of gravity, leading to each plant’s characteristic form both above and below ground. Despite being conceptually simple to follow, monitoring a plant’s directional growth responses can become complex as variation arises from both internal developmental cues as well as effects of the environment. In this protocol, we discuss approaches to gravitropism assays, focusing on automated analyses of root responses. For Arabidopsis, we recommend a simple 90􏰁 rotation using seedlings that are 5–8 days old. If images are taken at regular intervals and the environmental metadata is recorded during both seedling development and gravitropic assay, these data can be used to reveal quantitative kinetic patterns at distinct stages of the assay. The use of software that analyzes root system parameters and stores this data in the RSML format opens up the possibility for a host of root parameters to be extracted to characterize growth of the primary root and a range of lateral root phenotypes. 

Spaceflight presents a multifaceted environment for plants, combining the effects on growth of many stressors and factors including altered gravity, the influence of experiment hardware, and increased radiation exposure. To help understand the plant response to this complex suite of factors this study compared transcriptomic analysis of 15Arabidopsis thalianaspaceflight experiments deposited in the National Aeronautics and Space Administration’s GeneLab data repository. These data were reanalyzed for genes showing significant differential expression in spaceflight versus ground controls using a single common computational pipeline for either the microarray or the RNA-seq datasets. Such a standardized approach to analysis should greatly increase the robustness of comparisons made between datasets. This analysis was coupled with extensive cross-referencing to a curated matrix of metadata associated with these experiments. Our study reveals that factors such as analysis type (i.e., microarray versus RNA-seq) or environmental and hardware conditions have important confounding effects on comparisons seeking to define plant reactions to spaceflight. The metadata matrix allows selection of studies with high similarity scores, i.e., that share multiple elements of experimental design, such as plant age or flight hardware. Comparisons between these studies then helps reduce the complexity in drawing conclusions arising from comparisons made between experiments with very different designs.