RNA sequencing counts how many copies of each gene's mRNA exist in a sample. The Inspiration4 mission used nanopore direct RNA sequencing (first ever from astronauts) plus single-nuclei RNA-seq from PBMCs (immune cells). This gives both bulk tissue-level and individual cell-type resolution.
Reading this chart
Y-axis shows log2 fold-change from baseline. The spike during flight (FD1-FD3) means stress-response genes were 2-4x more active. The dashed lines mark launch and return. Notice how expression peaks just after landing (R+1) then slowly returns to normal.
If a gene's expression increases in space, that biological process is being activated. For example, upregulated oxidative phosphorylation genes mean cells are under metabolic stress. The I4 data revealed a 'spaceflight transcriptional signature' enriched in UV response, immune function, and stress pathways.
Log2 fold-change between timepoints. A value of 1.0 means expression doubled; -1.0 means it halved. Z-scores normalize across genes. No complex statistics needed — with n=4, descriptive analysis is more appropriate than hypothesis testing.
All AP-level math. No differential equations, no ML required. With n=4, descriptive statistics are more honest than hypothesis testing.
Spaceflight signature enriched in oxidative phosphorylation and UV response
Cell-type-specific responses visible at single-cell level
TCF21 pathway activation (cardiovascular remodeling marker)
Most changes resolved within 3 months post-flight
Group genes by pathway (inflammation, oxidative stress, DNA repair) and compute average fold-changes per pathway per crew member. This becomes your per-domain 'activation score' on the dashboard.