Meta-analysis of the space flight and microgravity response of the Arabidopsis plant transcriptome

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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 15 Arabidopsis thaliana spaceflight 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.
This work was coordinated through the GeneLab Plant Analysis Working Group and was supported by NASA grants 80NSSC19K0126, 80NSSC18K0132 and 80NSSC21K0577 to S.G. and R.B., through NASA 80NSSC19K1481 to S.W., NNX15AG55G to C.W., and NNX15AG56G to L.D. and N.L., from the Spanish Agencia Estatal de Investigación grant RTI2018-099309-B-I00 and ESA 1340112 4000131202/20/NL/PG/pt to R.H. Contributions from P.J. and P.G. were partially supported by funds from the Oregon State University, NSF awards 1127112 and 1340112 and the United States Department of Agriculture, Agriculture Research Service. The Qlik software used in this work is provided under a free-to-use educational license from Qlik Technologies Inc. GeneLab datasets were obtained from https://genelab-data.ndc.nasa.gov/genelab/projects/, maintained by NASA GeneLab, NASA Ames Research Center, Moffett Field, CA 94035.