rDNA array length is a major determinant of replicative lifespan in budding yeast

Abstract

The complex processes and interactions that regulate aging and determine lifespan are not fully defined for any organism. Here, taking advantage of recent technological advances in studying aging in budding yeast, we discovered a previously unappreciated relationship between the number of copies of the ribosomal RNA gene present in its chromosomal array and replicative lifespan (RLS). Specifically, the chromosomal ribosomal DNA (rDNA) copy number (rDNA CN) positively correlated with RLS and this interaction explained over 70% of variability in RLS among a series of wild-type strains. In strains with low rDNA CN, SIR2 expression was attenuated and extrachromosomal rDNA circle (ERC) accumulation was increased, leading to shorter lifespan. Suppressing ERC formation by deletion of FOB1 eliminated the relationship between rDNA CN and RLS. These data suggest that previously identified rDNA CN regulatory mechanisms limit lifespan. Importantly, the RLSs of reported lifespan-enhancing mutations were significantly impacted by rDNA CN, suggesting that changes in rDNA CN might explain the magnitude of some of those reported effects. We propose that because rDNA CN is modulated by environmental, genetic, and stochastic factors, considering rDNA CN is a prerequisite for accurate interpretation of lifespan data.

Keywords: Saccharomyces cerevisiae; aging; machine learning; microfluidics; ribosomal DNA.

Fig. 1.

rDNA copy number explains a majority of the variability in RLS estimates. (A) Kaplan–Meier estimates for 13 wild-type strains derived from the same parent show significant variability (“spontaneous variation”; >400 observations per curve, median of ∼1,000 observations per curve, 95% confidence interval represented by shaded region). (B) Copy number variations in the rDNA locus correlate with RLS. Polymorphisms identified by whole-genome sequencing data are grouped into SNPs and CNVs of 2-kb genome bins. Forty-one polymorphisms occurring in at least two strains are shown. Strains are ordered by increasing median RLS from left to right. Color map for SNPs is gray (absent, REF) and black (present, VAR). Color map for CNVs is from low (dark blue) to high (yellow). (C) rDNA CN correlates with median RLS. Color map indicates rDNA CN and is maintained throughout the rest of the plots. Each point represents a unique lifespan experiment (microfluidic channel) with >400 cells. Ninety-five percent confidence intervals around median RLS estimate are represented as vertical bars. (D) Kaplan–Meier estimates for an extended panel of 54 wild-type strains with variable rDNA CN (“experimental variation”; >400 observations per curve, median ∼1,150 observations per curve). (E) Correlation of median RLS and rDNA CN for the same strains as in D (n = >319 per microfluidic channel, median 593 cells).

Fig. 2.

Chromosomal rDNA CN modulates lifespan via ERC levels. (A) Southern blots probed for rDNA and NPR2 (loading control). Samples were obtained from wild-type and fob1Δ strains with variable rDNA CN aged for 24 h. Arrows 1 to 4 highlight bands of ERCs, and arrow A highlights the chromosomal rDNA array. (Scale bar, 1 cm.) (B) Quantification of ERCs on blot from A shows anticorrelation between rDNA CN and ERC levels. ERC accumulation is suppressed by deletion of FOB1. Sum intensity of all four ERC bands is plotted. (C) Hazard estimates for 51 wild types and 20 fob1Δ strains derived from microfluidics experiments show increased hazard risk for cells in rDNA-dependent MoD with low rDNA CN. This effect is suppressed by fob1Δ. Color maps, indicating rDNA CN, are the same as in B ( >400 cells per hazard estimate; shaded regions represent 95% confidence interval). (D) fob1Δ eliminates the correlation between rDNA CN and RLS ( >400 cells per median lifespan estimate; vertical bars represent 95% confidence interval).

Fig. 3.

SIR2 accessibility and expression correlate with rDNA CN and RLS. (A) Chromatin accessibility at the SIR2 locus as derived by ATAC-Seq. The UAF-binding site upstream of SIR2 shows increased accessibility with decreasing rDNA CN. Color map is the same as in Fig 1. (B) Magnification of chromatin accessibility changes at the UAF-binding site from A. (C) Sir2 gene expression is strongly up-regulated with increasing RLS. Fold change of gene expression is plotted as a function of RLS (FC/RLS) vs. the adjusted P value [–log10(padj)].

Fig. 4.

rDNA CN affects the lifespan of known modulators of aging. (A–G) Correlation of median RLS and rDNA CN for wild-type and mutant strains as indicated ( >300 cells per lifespan estimate; median = 593). Vertical gray line indicates rDNA CN of 150. (H) Cox Proportional Hazard model testing the effect of mutations on the hazard at 150 rDNA CN (Left) and on the correlation between rDNA CN and RLS (Right). (H, Left) Negative coefficients indicate a reduction in hazard due to the mutation at an rDNA CN of 150. Vertical bars represent 95% confidence interval, and open circles indicate that the estimated range overlaps with 0. (H, Right) More positive interaction terms indicate a weaker correlation between rDNA CN and RLS in the indicated mutant background. Coefficients are measured per mutation or per unit change for rDNA CN.

Fig. 5.

rDNA CN affects lifespan through known regulation of established aging factors. Model shows how differences in rDNA CN affect lifespan. In cells with low rDNA CN, Sir2 expression is low due to repression by the UAF complex, which in turn causes ERC accumulation and shortens lifespan.