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Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗

NASA NTRS2018

Space Radiation Induces Long Term Impact on the Cardiovascular System by the Activation of FYN Through Reactive Oxygen Species

Space radiation can damage the cardiovascular system and thus is an important health risk factor for astronauts during long-term space missions. We utilized publicly available transcriptomic data through NASA's GeneLab platform (genelab.nasa.gov) to determine cardiovascular system response to space radiation. GeneLab is an open repository that houses all NASA related omics experiments including on the International Space Station (ISS) and related radiation ground studies. We analyzed 3 datasets from GeneLab: GLDS-117 and GLDS-109, which are ground studies of cardiomyocytes followed-up for 28 days after exposure to 90cGy of proton at 1GeV and 15cGy of 56Fe at 1GeV; and GLDS-52, human endothelial cells (HUVECs) that were cultured for 10 days on the ISS. The ground studies were designed to characterize the long-term impact following space irradiation on cardiomyocytes for 5 different time points up to 28 days after irradiation. Our analysis was guided by the hypothesis that there are common persistent molecules affecting the cardiovascular system due to radiation effects during spaceflight. Endothelial cells are known to directly regulate the development and activity of cardiomyocytes, and thus their response to spaceflight should be highly correlated with cardiomyocytes. To investigate our hypothesis, we identified the molecular pathways that were modified for all time points compared across both radiation on the ground and the pathways found in HUVECs flown in the ISS. We found the following key results related to the cardiovascular systems: 1) space radiation downregulate ROS functions; and 2) the key/driving genes: FYN, LCK, AKT1 are upregulated and LYN and FOS are downregulated with FYN being the central driver/hub for the cardiovascular response to space radiation. It is worth noting the activation of FYN is a key event which prevents cardiac cell death and ROS production. From our study we thus hypothesize that a feedback loop occurs from the oxidative stress caused by space radiation that upregulates FYN which in turn reduces ROS levels and thus ROS pathways, preventing cardiomyocyte and endothelial cell death and thus protecting the cardiovascular systems. We believe that this is a novel mechanism for space radiation induced cardiovascular risk directly linking radiation ground studies to spaceflight

Beheshti, Afshin↗

NASA NTRS2007

Comparative MicroRNA Expression Patterns in Fibroblasts after Low and High Doses of Low-LET Radiation Exposure

Exposure to ionizing radiation causes DNA damage to cells, and provokes a plethora of cellular responses controlled by unique gene-directed signaling pathways. MicroRNAs (miRNAs) are small (~22-nucleotide), non-coding RNAs which functionally silence gene expression by either degrading the messages or inhibiting translation. Here we investigate radiation-dependent changes in these negative regulators by comparing the expression patterns of all 462 known human miRNAs in fibroblasts, after exposure to low (0.1 Gy) or high (2 Gy) doses of X-rays at 30 min, 2, 6 and 24 hrs post-treatment. The expression patterns of microRNAs after low and high doses of radiation show a similar qualitative down-regulation trend at early (0.5 hr) and late (24 hr) time points, with a quantitatively steeper slope following the 2 Gy exposures. Interestingly, an interruption of this downward trend is observed after the 2 Gy exposure, i.e. a significant up-regulation of microRNAs at 2 hrs, then reverting to the downward trend by 6 hrs; this interruption at the intermediate time point was not observed with the 0.1 Gy exposure. At the early time point (0.5 hr), candidate gene targets of selected down-regulated microRNAs, common to both 0.1 and 2 Gy exposures, were those functioning in chromatin remodeling. Candidate target genes of unique up-regulated microRNAs seen at a 2 hr intermediate time point, after the 2 Gy exposure only, are those involved in cell death signaling. Finally, putative target genes of down-regulated microRNAs seen at the late (24 hr) time point after either doses of radiation are those involved in the up-regulation of DNA repair, cell signaling and homeostasis. Thus we hypothesize that after radiation exposure, microRNAs acting as hub negative regulators for unique signaling pathways needed to be down-regulated so as to de-repress their target genes for the proper cellular responses, including DNA repair and cell maintenance. The unique microRNAs up-regulated at 2 hr after 2 Gy suggest the cellular response to functionally suppress the apoptotic death signaling reflex after exposure to high dose radiation. Further analyses with transcriptome and global proteomic profiling will validate the reciprocal expression of signature microRNAs selected in our radiation-exposed cells, and their candidate target gene families, and test our hypothesis that unique radiation-specific microRNAs are keys in governing signaling responses for damage control of this environmental hazard.

Maes, Olivier C.↗