4 PCA
4.1 PCA switch mice
Principal component analysis (PCA) of variance-stabilized RNA-seq counts from the switch cohort revealed that tissue type was the dominant driver of transcriptional variance. The first principal component (PC1), accounting for 98% of the total variance, clearly separated liver and brain samples, indicating strong tissue-specific expression profiles. The second component (PC2), explaining about 1% of the variance, captured minor within-tissue variability associated primarily with sex, with male and female samples forming partially distinct subclusters.
No obvious outliers were detected, and samples from independent batches overlapped within each tissue cluster, suggesting minimal batch-related effects. Together, these data confirm that tissue identity overwhelmingly dominates the transcriptional landscape in the switch mice.
4.1.1 All mice
4.1.2 PCA by tissue and sex
Within each tissue–sex subgroup, Cre-AAV and GFP control mice formed partially overlapping clusters, suggesting that the switch introduced subtle transcriptomic changes relative to the global tissue effect.
Importantly, samples from independent experimental batches overlapped extensively, indicating that batch effects were minimal after normalization.
4.2 PCA TR mice
4.2.1 All TR mice
As occurred with switch mice, PCA of variance-stabilized RNA-seq counts from ApoE targeted-replacement (TR) mice revealed a strong separation of samples by tissue type, with liver and brain samples clearly segregating along the first principal component (PC1), which accounted for 98% of the total variance .
4.2.2 PCA by tissue with possible outliers labeled
Within the liver cluster, separation along the second principal component (PC2) distinguished ApoE2/E2 mice from the ApoE3/E3 and ApoE4/E4 groups . These data suggest that ApoE2 expression has a more pronounced impact on liver transcriptomes compared with the other ApoE isoforms, while tissue identity (liver vs. brain) remains the dominant source of variance across the dataset.
