Sets of genes with significant up and down effects were tested for enrichment of Gene Ontology (GO Biological Process, Molecular Function and Cellular Component) terms. Sets of genes were either combined across time points (Figure 1I) or collected separately per time point (Figures S1F and S1G). The over-representation analysis (ORA) was performed using the enricher function of clusterProfiler package (version 3.12.0) in R with default parameters. The gene ontology terms were obtained from the c5 category of Molecular Signature Database (MSigDBv7.1) (Subramanian et al., 2005). Significant GO terms (adjusted p value < 0.01) were identified and further refined to select non-redundant terms. In order to select non-redundant gene sets, we first constructed a GO term tree based on distances (1-Jaccard Similarity Coefficients of shared genes in MSigDB) between the significant terms. The GO term tree was cut at a specific level (h = 0.99) to identify clusters of non-redundant gene sets. For results with multiple significant terms belonging to the same cluster, we selected the most significant term (i.e., lowest adjusted p value).