The response of plants to the spaceflight environment and microgravity is still not well understood, although research has increased in this area. Even less is known about plants’ response to partial or reduced gravity levels. In the absence of the directional cues provided by the gravity vector, the plant is especially perceptive to other cues such as light. Here, we investigate the response of Arabidopsis thaliana 6-day-old seedlings to microgravity and the Mars partial gravity level during spaceflight, as well as the effects of red-light photostimulation by determining meristematic cell growth and proliferation. These experiments involve microscopic techniques together with transcriptomic studies. We demonstrate that microgravity and partial gravity trigger differential responses. The microgravity environment activates hormonal routes responsible for proliferation/growth and upregulates plastid/mitochondrial-encoded transcripts, even in the dark. In contrast, the Mars gravity level inhibits these routes and activates responses to stress factors to restore cell growth parameters only when red photostimulation is provided. This response is accompanied by upregulation of numerous transcription factors such as the environmental acclimation-related WRKY-domain family. In the long term, these discoveries can be applied in the design of bioregenerative life support systems and space farming.

During the Advanced Plant Habitat experiment 2, radish plants were grown in two successive grow-outs on the International Space Station (ISS) for 27 days each. On days 10, 18, and 24, leaf punch (LP) samples were collected and frozen. At harvest, bulb tissue was sampled with oligo-dT functionalized Solid Phase Gene Extraction (SPGE) probes. The space samples were compared with samples from ground controls (GC) grown at the Kennedy Space Center (KSC) under the same conditions as on the ISS, with notably elevated CO₂ (about 2500 ppm), and from lab plants grown under atmospheric CO₂ but with light and temperature conditions similar to the KSC control. Genes corresponding to peroxidase (RPP), glucosinolate biosynthesis (GIS), protein binding (CBP), myrosinase (RMA), napin (RSN), and ubiquitin (UBQ) were measured by qPCR. LP from day 24 and bulb samples collected at harvest were compared with RNA-seq data from material that was harvested, frozen, and analyzed after return to Earth. The results showed stable transcription in LP samples in GC but decreasing values in ISS samples during both grow-outs, possibly indicative of stress. SPGE results were similar between GC and ISS samples. However, the RNA-seq analyses showed different transcription profiles than SPGE or LP results, possibly related to localized sampling. RNA-seq of leaf samples showed greater variety than LP data, possibly because of different sampling times. RSN and RPP showed the lowest transcription regardless of method. Temporal analyses showed relatively small changes during plant development in space and in ground controls. This is the first study that compares developmental changes in space-grown plants with ground controls based on a comparison between RNA-seq and qPCR analyses.

Summary: With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility and reusability of pipeline data, to provide a template for data processing of future spaceflight-relevant datasets, and to encourage cross-analysis of data from other databases with the data available in GeneLab.