Transcriptional drift in aging cells: A global de-controller

Abstract

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the upregulated genes code for sensory proteins upstream of stress responses and downregulated genes are growth- and metabolism-related. We propose a simple mechanistic model for how such global coordination of multi-protein expression levels may be achieved by the binding of a single ligand that concentrates with age. A key implication is that a cell's own responses are part of its aging process, so unlike for wear-and-tear processes, intervention might be able to modulate these effects.

Figure 1:. The relative changes of the two archetypes of genes with age.

Using normalized nonnegative matrix factorization, we identified two key archetypes: one that increases with age (red) and one that decreases (green).

Figure 2:. Much of the transcriptome changes with age.

(A) Pearson correlation coefficient of all genes vs the two archetypes. Genes with high positive $R^2$ are strongly monotonically increasing whereas genes with high negative $R^2$ are monotonically decreasing. Genes selected as archetype centers are to the left and right of the purple lines. (b) Rescaled expression data for genes with correlation coefficients ≥ 0.9 (top) and ≤ −0.9 (bottom).

Figure 3:. The Cumulative Factor model captures the linear increase in upregulated expressions and the Michaelis-Menten decrease in downregulated expressions.

. Best-fit regressions to the data using the equations in the text. The average value of the percentage change in $\text{cpm}$ across all genes in each subset is plotted in blue. Plot A models the sensory genes with an $R^2$ of 0.9999 and plot B models the growth genes with an $R^2$ of 0.9964.