Figure 5. Age-related transcripts and metabolites follow similar trajectories and show a delayed response under lifespan-extending dietary conditions.
One way repeated measures ANOVA was used to identify transcripts with age-related changes at p<0.0013. A total of 1171 features showed significance in both diets. (A) Normalization and clustering were performed according to the procedures described for Figure 3C legend. Each box represents individual clusters trimmed from hierarchically clustered tree using hclust algorithm in R. The number of genes contributing to each cluster is provided in the bottom left corner. (B) ClusterProfiler (Yu et al., 2012) package in R (Yu et al., 2012) was used to test for enrichment for Biological Process ontology in Clusters 1–12 in (A). Clusters 3, 10, and 12 did not enrich and therefore are not present. (C) Comparison of diet-dependent and diet-independent frequencies in gene and metabolite expression data. Frequencies of diet-dependent to diet-independent changes in gene expression and metabolites were obtained from signals provided by clusters 112 in panel A and Figure 4D, respectively. Differences that were continuous across lifespan were categorized as progressive, and those that were not as intermittent. (D) Average trajectories of upregulated (solid lines) and downregulated (dashed lines) signals in gene (top panel) and metabolite (bottom panel) expression datasets. For gene expression, the upregulated trajectories are averages of all signals from Clusters 1–5 shown in panel A, while all downregulated signals were derived from Clusters 6–8. Similarly, the global increases and decreases in metabolite levels were generated by averaging signals in Clusters 2–4 and Clusters 5–8, respectively, from Figure 4D. Plots show normalized trajectories' values, which were obtained using quadratic polynomial fit through sample replicates. Points indicate sampled ages.