The effects of space radiation on the transcriptome of heart right ventricle tissue

Abstract

Deep space represents a challenging environment for human exploration and can be accompanied by harmful health-related risks. We aimed to assess the effect of simplified galactic cosmic ray simulated (simGCRsim) and gamma (γ) ionizing radiation (IR) on transcriptome changes in right ventricular (RV) tissue after a single low dose (0.5 Gy, 500 MeV/nucleon) full body exposure in C57BL/6J male and female mice. In females, no differentially expressed genes (DEGs) and only 2 upregulated genes in males exposed to γ-IR were revealed. In contrast, exposure to simGCRsim-IR resulted in 4 DEGs in females and 371 DEGs in males, suggesting longer-lasting and sex-biased DEGs after simGCRsim-IR. Overrepresentation analysis of DEGs in simGCRsim-IR males revealed significant enrichment in pathways related to muscle contraction, hypertrophic cardiomyopathy, oxytocin release, the regulation of cytoskeleton, and genes associated with Alzheimer's, Huntington's, and Parkinson's diseases. Our results suggested the RV transcriptome exhibits distinct responses after exposure based on both the IR and sex.

Fig. 1. Principal component analysis (PCA) of gene expression data.

Scatter plot of the first two principal components from PCA of normalized gene expression data. Each dot represents a sample colored by sex and radiation exposure type. The primary source of variability in gene expression is associated with sex differences. Male experimental groups (yellow, orange, and purple dots) are located in the upper right side of the plot and display a wider spread, indicating greater expression variability. In contrast, female groups (green, blue, and red dots) are more tightly clustered and located on the left side of the plot.

Fig. 2. Volcano plots showing differential expression across the comparison groups.

Volcano plots showing differentially expressed genes between the two irradiation (IR) groups (γ- and simGCRsim) for both females (A, C) and males (B, D). Each row in the plot grid corresponds to an IR type, and each column represents a specific gender. Red dots indicate genes with an adjusted p-value (FDR) < 0.05 and an average log₂ fold change > 0.5. Blue dots represent genes with an adjusted p-value (FDR) < 0.05 but with a log₂ fold change ≤ 0.5.

Fig. 3. Heatmap of DEGs expression across comparison groups.

Heatmap of normalized expression values of DEGs identified across all comparison groups (256 genes). The color bar at the top of the heatmap represents sample groups, with colors corresponding to the legend on the right side of the plot. Sample clustering was turned off to preserve the original sample order and facilitate direct comparison across experimental conditions.

Fig. 4. Overlap of DEGs between the IR groups of LV and RV.

Overlap between the groups is presented as upset plots for females (A) and males (B). Single dots in the matrix indicate group-specific DEGs, with the corresponding gene counts displayed in the top bar plots. Connected dots across matrix rows indicate overlapping genes shared between comparison groups. The total number of DEGs for each experimental group are shown in the horizontal bar plots on the left side of the matrix. A Overlapping and group-specific DEGs in female comparison groups. Only 2 overlapping genes were observed: one between the γ- and simGCRsim-IR groups in the LV, and the second between simGCRsim-IR groups of the LV and RV. B Overlapping and group-specific DEGs in male comparison groups. Overlap was observed only between the simGCRsim-IR groups of LV and RV tissues, with 12 genes in common.

Fig. 5. Schematic representation of study design.

A Experimental design. Male and female mice were exposed to γ- and simGCRsim-irradiation. RV tissues were collected for sequencing at two timepoints (440 days and 660/550 days, male/female, respectively). B Sequencing and analysis workflow. Total RNA was extracted and sequenced using Illumina technology. The resulting reads were aligned to the mouse reference genome, and raw read counts were used for differential gene expression analysis. The diagram and the Workflow in this figure were created by using BioRender for our earlier published paper on transcriptomic changes in the left ventricular tissue of the same set of mice used in this study for the transcriptome changes in right ventricular tissue. Therefore, Fig. 5 is being reused in this paper under the Creative Commons Attribution (CC-BY) license.