We collected 60 age-dependent transcriptomes for C. elegans strains including four exceptionally long-lived mutants (mean adult lifespan extended 2.2- to 9.4-fold) and three examples of lifespan-increasing RNAi treatments. Principal Component Analysis (PCA) reveals aging as a transcriptomic drift along a single direction, consistent across the vastly diverse biological conditions and coinciding with the first principal component, a hallmark of the criticality of the underlying gene regulatory network. We therefore expected that the organism’s aging state could be characterized by a single number closely related to vitality deficit or biological age. The “aging trajectory”, i.e. the dependence of the biological age on chronological age, is then a universal stochastic function modulated by the network stiffness; a macroscopic parameter reflecting the network topology and associated with the rate of aging. To corroborate this view, we used publicly available datasets to define a transcriptomic biomarker of age and observed that the rescaling of age by lifespan simultaneously brings together aging trajectories of transcription and survival curves. In accordance with the theoretical prediction, the limiting mortality value at the plateau agrees closely with the mortality rate doubling exponent estimated at the cross-over age near the average lifespan. Finally, we used the transcriptomic signature of age to identify possible life-extending drug compounds and successfully tested a handful of the top-ranking molecules in C. elegans survival assays and achieved up to a +30% extension of mean lifespan.

A quantitative trait locus (QTL) in the nematode C. elegans, “lsq4,” was recently implicated by mapping longevity genes. QTLs for lifespan and three stress-resistance traits coincided within a span of <300 kbp, later narrowed to <200 kbp. A single gene in this interval is now shown to modulate all lsq4-associated traits. Full-genome analysis of transcript levels indicates that lsq4 contains a dimorphic gene governing the expression of many sperm-specific genes, suggesting an effect on spermatogenesis. Quantitative analysis of allele-specific transcripts encoded within the lsq4 interval revealed significant, 2- to 15-fold expression differences for 10 of 33 genes. Fourteen “dual-candidate” genes, implicated by both position and expression, were tested for RNA-interference effects on QTL-linked traits. In a strain carrying the shorter-lived allele, knockdown of rec-8 (encoding a meiotic cohesin) reduced its transcripts 4-fold, to a level similar to the longer-lived strain, while extending lifespan 25–26%, whether begun before fertilization or at maturity. The short-lived lsq4 allele also conferred sensitivity to oxidative and thermal stresses, and lower male frequency (reflecting X-chromosome non-disjunction), traits reversed uniquely by rec-8 knockdown. A strain bearing the longer-lived lsq4 allele, differing from the short-lived strain at <0.3% of its genome, derived no lifespan or stress-survival benefit from rec-8 knockdown. We consider two possible explanations: high rec-8 expression may include increased “leaky” expression in mitotic cells, leading to deleterious destabilization of somatic genomes; or REC-8 may act entirely in germ-line meiotic cells to reduce aberrations such as non-disjunction, thereby blunting a stress-resistance response mediated by innate immunity. Replicative lifespan was extended 20% in haploid S. cerevisiae (BY4741) by deletion of REC8, orthologous to nematode rec-8, implying that REC8 disruption of mitotic-cell survival is widespread, exemplifying antagonistic pleiotropy (opposing effects on lifespan vs. reproduction), and/or balancing selection wherein genomic disruption increases genetic variation under harsh conditions.

To detect overlap or convergence among the diverse genetic pathways that can extend lifespan, we collected a dataset of 60 C.elegans age-dependent transcriptomes by RNA-seq technique for worm strains with vastly different lifespans. We selected four exceptionally long-lived mutants and three examples of the most successful life-extending RNAi treatments (which increased mean lifespan by 35% rather than 120% as reported). We used the dataset augmented with publicly available gene expression datasets to produce a transcriptomic signature of biological age. We introduced a transcriptomic measure of biological age and observed that its dependence on chronological age is modulated by a single parameter, the rate of aging. We hypothesized that the scaling revealed in the gene expression kinetics underlies the recently observed scaling of the survival curves in C.elegans, and the stochasticity in gene expressions leads to deceleration of mortality with age, reaching a plateau at advanced ages. Using experimental survival data, we confirm that the plateau mortality agrees closely with the estimate of Gompertz exponent at the cross-over age near the mean lifespan. The genes associated with aging in our data are enriched with the targets of transcription factors such as DAF-16, ELT-2, ELT-6, NHR-10, ZTF-9, NHR-86, and miRNAs including miR-57, -59, and -244, which is in agreement with previous studies. Overall, our meta-analysis results are consistent with a concept of aging based on critical dynamics of molecular level variables (e.g., gene expression), and support our view of aging as arising from dynamic instability of a single (critical) mode.