Inter-individual variability and temporal scaling in the aging transcriptome

Resumen

Thanks to extensive research efforts, our understanding of the physiological mechanisms underlying aging has immensely progressed. Recently, omics technologies have enabled the genome-wide study of age-related changes. Nevertheless, omics analyses often overlook the stochastic, dynamic, and complex nature of aging. Consequently, untangling cause-effect relationships has proven challenging. In this thesis, we analyze the effect of aging on the transcriptome in Caenorhabditis elegans, studying gene expression changes as they vary and covary between individuals, over time, and in response to multiple lifespan-modulating interventions. First, we developed a single individual RNA-seq protocol that allows us to measure inter-individual transcriptomic variability. We found that inter-individual differences in tissue size are the main contributor to inter-individual transcriptomic variability. After accounting for these differences, we utilized inter-individual covariability to reconstruct a gene co-expression network. This network allowed us to identify functional communities altered by insulin/IGF-1 signaling. Second, we used an auxin-inducible degron system to compare the temporal dynamics of aging and gene expression across nine differentially aging populations. We collected time-resolved transcriptomic measurements and found that only five percent of transcriptomic trajectories are temporally rescaled in the same way as lifespan. Third, we collaborated with a laboratory working on prohibitin, a mitochondrial protein that can extend or shorten lifespan depending on the context. We found coordinated changes in gene expression across multiple metabolically compromised strains that may explain context-dependent effects. To conclude, we present novel ways to relate lifespan and transcriptomic changes, thus providing insight on how lifespan-modulating interventions ultimately impact aging.