It has long been assumed that lifespan and healthspan correlate strongly, yet the two can be clearly dissociated1,2,3,4,5,6. Although there has been a global increase in human life expectancy, increasing longevity is rarely accompanied by an extended healthspan4,7. Thus, understanding the origin of healthy behaviours in old people remains an important and challenging task. Here we report a conserved epigenetic mechanism underlying healthy ageing. Through genome-wide RNA-interference-based screening of genes that regulate behavioural deterioration in ageing Caenorhabditis elegans, we identify 59 genes as potential modulators of the rate of age-related behavioural deterioration. Among these modulators, we found that a neuronal epigenetic reader, BAZ-2, and a neuronal histone 3 lysine 9 methyltransferase, SET-6, accelerate behavioural deterioration in C. elegans by reducing mitochondrial function, repressing the expression of nuclear-encoded mitochondrial proteins. This mechanism is conserved in cultured mouse neurons and human cells. Examination of human databases8,9 shows that expression of the human orthologues of these C. elegans regulators, BAZ2B and EHMT1, in the frontal cortex increases with age and correlates positively with the progression of Alzheimer’s disease. Furthermore, ablation of Baz2b, the mouse orthologue of BAZ-2, attenuates age-dependent body-weight gain and prevents cognitive decline in ageing mice. Thus our genome-wide RNA-interference screen in C. elegans has unravelled conserved epigenetic negative regulators of ageing, suggesting possible ways to achieve healthy ageing.
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Guarente, L. Aging research—where do we stand and where are we going? Cell 159, 15–19 (2014).
Yin, J. A., Liu, X. J., Yuan, J., Jiang, J. & Cai, S. Q. Longevity manipulations differentially affect serotonin/dopamine level and behavioral deterioration in aging Caenorhabditis elegans. J. Neurosci. 34, 3947–3958 (2014).
Bansal, A., Zhu, L. J., Yen, K. & Tissenbaum, H. A. Uncoupling lifespan and healthspan in Caenorhabditis elegans longevity mutants. Proc. Natl Acad. Sci. USA 112, E277–E286 (2015).
Beard, J. R. et al. The world report on ageing and health: a policy framework for healthy ageing. Lancet 387, 2145–2154 (2016).
Hansen, M. & Kennedy, B. K. Does longer lifespan mean longer healthspan? Trends Cell Biol. 26, 565–568 (2016).
Yin, J. A. et al. Genetic variation in glia-neuron signalling modulates ageing rate. Nature 551, 198–203 (2017).
Crimmins, E. M. & Beltrán-Sánchez, H. Mortality and morbidity trends: is there compression of morbidity? J. Gerontol. B 66, 75–86 (2011).
Lu, T. et al. Gene regulation and DNA damage in the ageing human brain. Nature 429, 883–891 (2004).
Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153, 707–720 (2013).
Hedden, T. & Gabrieli, J. D. Insights into the ageing mind: a view from cognitive neuroscience. Nat. Rev. Neurosci. 5, 87–96 (2004).
Bäckman, L., Nyberg, L., Lindenberger, U., Li, S. C. & Farde, L. The correlative triad among aging, dopamine, and cognition: current status and future prospects. Neurosci. Biobehav. Rev. 30, 791–807 (2006).
Chowdhury, R. et al. Dopamine restores reward prediction errors in old age. Nat. Neurosci. 16, 648–653 (2013).
Calixto, A., Chelur, D., Topalidou, I., Chen, X. & Chalfie, M. Enhanced neuronal RNAi in C. elegans using SID-1. Nat. Methods 7, 554–559 (2010).
Mostafavi, S., Ray, D., Warde-Farley, D., Grouios, C. & Morris, Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 9 (Suppl 1), S4 (2008).
Benayoun, B. A., Pollina, E. A. & Brunet, A. Epigenetic regulation of ageing: linking environmental inputs to genomic stability. Nat. Rev. Mol. Cell Biol. 16, 593–610 (2015).
Sen, P., Shah, P. P., Nativio, R. & Berger, S. L. Epigenetic mechanisms of longevity and aging. Cell 166, 822–839 (2016).
Lin, K., Dorman, J. B., Rodan, A. & Kenyon, C. daf-16: an HNF-3/forkhead family member that can function to double the life-span of Caenorhabditis elegans. Science 278, 1319–1322 (1997).
McKay, J. P., Raizen, D. M., Gottschalk, A., Schafer, W. R. & Avery, L. eat-2 and eat-18 are required for nicotinic neurotransmission in the Caenorhabditis elegans pharynx. Genetics 166, 161–169 (2004).
Ewbank, J. J. et al. Structural and functional conservation of the Caenorhabditis elegans timing gene clk-1. Science 275, 980–983 (1997).
Santoro, R., Li, J. & Grummt, I. The nucleolar remodeling complex NoRC mediates heterochromatin formation and silencing of ribosomal gene transcription. Nat. Genet. 32, 393–396 (2002).
Houtkooper, R. H. et al. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature 497, 451–457 (2013).
Mouchiroud, L. et al. The NAD(+)/sirtuin pathway modulates longevity through activation of mitochondrial UPR and FOXO signaling. Cell 154, 430–441 (2013).
Durieux, J., Wolff, S. & Dillin, A. The cell-non-autonomous nature of electron transport chain-mediated longevity. Cell 144, 79–91 (2011).
Merkwirth, C. et al. Two conserved histone demethylases regulate mitochondrial stress-induced longevity. Cell 165, 1209–1223 (2016).
Tian, Y. et al. Mitochondrial stress induces chromatin reorganization to promote longevity and UPR(mt). Cell 165, 1197–1208 (2016).
Yoneda, T. et al. Compartment-specific perturbation of protein handling activates genes encoding mitochondrial chaperones. J. Cell Sci. 117, 4055–4066 (2004).
Benedetti, C., Haynes, C. M., Yang, Y., Harding, H. P. & Ron, D. Ubiquitin-like protein 5 positively regulates chaperone gene expression in the mitochondrial unfolded protein response. Genetics 174, 229–239 (2006).
Haynes, C. M., Yang, Y., Blais, S. P., Neubert, T. A. & Ron, D. The matrix peptide exporter HAF-1 signals a mitochondrial UPR by activating the transcription factor ZC376.7 in C. elegans. Mol. Cell 37, 529–540 (2010).
Lin, M. T. & Beal, M. F. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443, 787–795 (2006).
Sarov, M. et al. A genome-scale resource for in vivo tag-based protein function exploration in C. elegans. Cell 150, 855–866 (2012).
Ohno, H., Shinoda, K., Ohyama, K., Sharp, L.Z. & Kajimura, S. EHMT1 controls brown adipose cell fate and thermogenesis through the PRDM16 complex. Nature 504, 163–167 (2013).
Hope, I.A. (ed.) C. Elegans: A Practical Approach (Oxford Univ. Press, 1999).
Sawin, E. R., Ranganathan, R. & Horvitz, H. R. C. elegans locomotory rate is modulated by the environment through a dopaminergic pathway and by experience through a serotonergic pathway. Neuron 26, 619–631 (2000).
Mukhopadhyay, A., Deplancke, B., Walhout, A. J. & Tissenbaum, H. A. Chromatin immunoprecipitation (ChIP) coupled to detection by quantitative real-time PCR to study transcription factor binding to DNA in Caenorhabditis elegans. Nat. Protocols 3, 698–709 (2008).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17.1, 10–12 (2011).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Ramírez, F., Dündar, F., Diehl, S., Grüning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–W191 (2014).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
Huang, da W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protocols 4, 44–57 (2009).
Dale, R. K., Matzat, L. H. & Lei, E. P. metaseq: a Python package for integrative genome-wide analysis reveals relationships between chromatin insulators and associated nuclear mRNA. Nucleic Acids Res. 42, 9158–9170 (2014).
Frezza, C., Cipolat, S. & Scorrano, L. Organelle isolation: functional mitochondria from mouse liver, muscle and cultured fibroblasts. Nat. Protocols 2, 287–295 (2007).
Viesselmann, C., Ballweg, J., Lumbard, D. & Dent, E. W. Nucleofection and primary culture of embryonic mouse hippocampal and cortical neurons. J. Vis. Exp. 47, 2373 (2011).
Lee, H. Y., Greene, L. A., Mason, C. A. & Manzini, M. C. Isolation and culture of post-natal mouse cerebellar granule neuron progenitor cells and neurons. J. Vis. Exp. 23, 990 (2009).
Patel, J. C., Rossignol, E., Rice, M. E. & Machold, R. P. Opposing regulation of dopaminergic activity and exploratory motor behavior by forebrain and brainstem cholinergic circuits. Nat. Commun. 3, 1172 (2012).
Patil, S. S., Sunyer, B., Höger, H. & Lubec, G. Evaluation of spatial memory of C57BL/6J and CD1 mice in the Barnes maze, the multiple T-maze and in the Morris water maze. Behav. Brain Res. 198, 58–68 (2009).
Wimmer, M. E., Hernandez, P. J., Blackwell, J. & Abel, T. Aging impairs hippocampus-dependent long-term memory for object location in mice. Neurobiol. Aging 33, 2220–2224 (2012).
Xu, X. et al. Modular genetic control of sexually dimorphic behaviors. Cell 148, 596–607 (2012).
We thank M-m. Poo and X. Shi for critical reading of the manuscript; Q. Sun, Y.-J. Cai and Y.-Z. Li for generating Baz2b-knockout mice; the C. elegans Genetics Center (funded by the National Institutes of Health (NIH) Office of Research Infrastructure Programs P40 OD010440) for providing strains; members of C.-y. Li’s laboratory for helping with mouse behavioural assays; M. Sun for helping to prepare the H3K9 ChIP–seq DNA libraries; and the Institute of Neuroscience Molecular and Cellular Biology Core Facility, the Optical Imaging Facility, and the Animal Facility (Chinese Academy of Sciences) for technical support. This work was supported by grants to S.-Q.C. (from the National Natural Science Foundation of China, grants 31925022, 91949206 and 81527901; and from the National Key R&D Program of China, grant 2018YFC2000400); the Strategic Priority Research Program of the Chinese Academy of Science (grant XDB32020100); the Shanghai Municipal Science and Technology Major Project (grant 2018SHZDZX05); and grants to L.J. (from the National Key R&D Program of China, grant 2018YFA0507300; and the National Natural Science Foundation of China, grant 31771455).
The authors declare no competing interests.
Peer review information Nature thanks Cole Haynes and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
a, Effects of representative positive clones on BAS-1 protein levels in Pbas-1::bas-1::gfp transgenic worms. White arrows indicate NSM neurons. Scale bar, 20 µm. Images are representative of three independent experiments. b, Effect of each screening hit on the expression of BAS-1::GFP. The GFP fluorescence in NSM neurons of worms individually treated with the 59 screening hits, also shown in Supplementary Table 1, was normalized to that in worms treated with the control RNAi. P values were determined by unpaired two-tailed t-test (see Supplementary Table 1 for numbers of tested worms and exact P values). c, Categories of genes corresponding to the 59 screening hits identified by RNAi. d, Coexpression network of screening hits and their partners. The network was constructed with GeneMANIA. Black and grey dots indicate screening hits and their partners, respectively. Blue and orange dots show screening hits whose human homologues are involved in age-related neurodegeneration and cell senescence, respectively. e, Pharyngeal pumping in TU3401 worms (which express a dsRNA channel, SID-1, in neurons) after RNAi treatment in the presence of 20 μM 2′-deoxy-5-fluorouridine (FUDR). The genes from the top 20 screening hits were examined. Numbers of tested worms are shown beneath the bars. Data shown are means ± s.e.m.; *P < 0.05; **P < 0.05; ***P < 0.001; ns, not significant (one-way ANOVA with Dunnett's test; see Supplementary Information for exact P values)Source Data.
a, Expression patterns of BAZ-2 and SET-6. Scale bar, 30 μm. Images are representative of three independent experiments. b, Representative fluorescence images (left) and quantitative analysis (right) of BAZ-2 and SET-6 expression. We quantified only those cells whose nuclear morphology was clearly visualized with DAPI. Scale bar, 10 μm. n = 14 and 18 worms for BAZ-2 and SET-6, respectively. c, d, Representative western blots (c) and quantitative analysis (d) of age-related changes in endogenous SET-6 and BAZ-2 protein levels in genome-edited baz-2GFP::FLAG;set-6GFP::HA worms. n = 5 independent experiments. Tubulin expression is used as a reference. For gel source data, see Supplementary Fig. 2. In d, each data point represents the result of one independent experiment. e, Fluorescence images (left) and quantitative analysis (right) of BAS-1 expression in baz-2 and set-6 mutant worms. Quantitative analysis of BAS-1 levels was performed by measuring GFP fluorescence intensity in the soma of NSM neurons. White arrows indicate NSM neurons. Scale bar, 15 μm. The numbers of tested worms are shown beneath the bars. All data shown are means ± s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001 (d, Kruskal–Wallis test; e, one-way ANOVA with Dunnett’s test; see Supplementary Information for exact P values). Source Data
Extended Data Fig. 3 Deletion of baz-2 or set-6 extends lifespan and enhances stress resistance via mechanisms related to dietary restriction and mitochondrial function.
a–c, Percentage survival of N2, baz-2, set-6, and baz-2;set-6 worms under oxidative (a), ultraviolet (b) and heat (c) stress. d, Lifespan curves of daf-16, daf-16;baz-2, and daf-16;set-6 mutant worms (left) and their abilities to resist to oxidative stress (right). e, Lifespan curves of eat-2, eat-2;baz-2, and eat-2;set-6 mutant worms (left) and their abilities to resist to oxidative stress (right). f, Lifespan curves of clk-1, clk-1;baz-2, and clk-1;set-6 mutant worms (left) and their abilities to resist to oxidative stress (right). In a–f, for oxidative-stress assays, data shown are means ± s.e.m.; one-way ANOVA with Dunnett’s test; numbers of independent experiments are shown beneath the bars. For heat-shock, ultraviolet-stress and lifespan assays, data represent the sum of animals in multiple experiments; two-sided log-rank test. The numbers of independent experiments and of tested hermaphrodites are indicated in parentheses. In all assays, *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant (see Supplementary Information for exact P values). Source Data
Extended Data Fig. 4 Epigenetic regulators BAZ-2 and SET-6 localize at the promoter region of target genes.
a, Co-immunoprecipitation of BAZ-2 and SET-6 using genome-edited baz-2GFP::FLAG;set-6GFP::HA worms (left) or transgenic worms expressing BAZ-2::FLAG and SET-6::HA (right). Images are representative of four independent experiments. For gel source data, see Supplementary Fig. 3. b, Representative western blots (left) and quantitative analysis (right) of H3K9 methylation levels in N2, baz-2, set-6 and baz-2;set-6 worms. Normalized H3K9 methylation levels were calculated by normalizing the ratio of H3K9 methylation and histone 3 levels to that of N2 worms. For gel source data, see Supplementary Fig. 4. c, Peaks of BAZ-2- and SET-6-binding sites in the region −1,000 bp to +1000 bp around the transcription start site (TSS). Only those peaks with a fold change of more than 2 are plotted. The y-axis indicates the average read coverage normalized to the number of uniquely mapped reads per million per genomic bin (bins = 1,000). d, Pie chart showing the distribution of overlapping BAZ-2- and SET-6-binding sites in genomic features. TTS, transcription termination site. e, f, ChIP-qPCR analysis of endogenous BAZ-2 (e) or SET-6 (f) enrichment at nuclear genes encoding mitochondrial proteins in genome-edited baz-2GFP::FLAG and set-6GFP::HA worms. ChIP-qPCR data from N2 worms were used as a control. In b, e, f, the numbers of independent experiments are shown beneath the bars; data are means ± s.e.m.; *P < 0.05; **P < 0.01; ***P < 0.001 (b, one-way ANOVA with Dunnett’s test; e, f, two-tailed t-test; see Supplementary Information for exact P values). Source Data
Extended Data Fig. 5 BAZ-2 and SET-6 regulate the expression of nuclear genes encoding mitochondrial proteins.
a, Scatter plots of mRNA-seq data for N2 versus baz-2 mutant worms (left) and N2 versus set-6 mutant worms (right). The x- and y-axes represent the log10-transformed transcripts per million clean tags (TPM) expression values of N2 (x-axis), baz-2 (left, y-axis) and set-6 (right, y-axis) animals. Differentially expressed genes (DEGs) were defined through the parameters of false discovery rate (FDR) ≤ 0.001 and |log2Ratio| ≥ 1. b, RT–PCR analysis of changes in the expression of nuclear genes encoding mitochondrial proteins in baz-2 and set-6 mutant worms at day 1 (left) or day 7 (right) of adulthood. The numbers of independent experiments are shown beneath the bars. c, Western blots (left) and quantitative analysis (right) of nDNA-encoded ATP5A and mtDNA-encoded MTCO1 proteins. n = 3 independent experiments. For gel source data, see Supplementary Fig. 5. In b, c, data shown are means ± s.e.m.; *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant (one-way ANOVA with Dunnett’s test; see Supplementary Information for exact P values). Source Data
Extended Data Fig. 6 BAZ-2 and SET-6 repress gene expression by altering the H3K9me3 level of target genes.
a, Heatmaps showing gene expression (left) and occupation by BAZ-2 and SET-6 at DNA regions (middle and right) of 450 differentially expressed genes. The enrichment of genes was analysed at DAVID Bioinformatics Resources; a hypergeometric test was performed using mitochondrial and ribosome genes from cluster 2 for statistical analysis. b–d, Average-read-coverage profiles of the cluster-2 differentially expressed genes for ChIP analysis of H3K9me3 (b), H3K9me2 (c) and H3K9me1 (d) from N2, baz-2 and set-6 mutant worms at day 2 (A2) and day 7 (A7) of adulthood. RPM, reads per million mapped reads. e, ChIP–seq profiles of H3K9me1, H3K9me2 and H3K9me3 at the indicated DNA regions of representative cluster-2 genes, cyc-2.1 on chromosome (Chr.) IV and gst-36 on chromosome X. The ChIP–seq analysis of H3K9me3 was carried out twice, with averages shown. Source Data
a, Diagram showing the similarity between C. elegans BAZ-2 and SET-6 and their human homologues. aa, amino acids; ANK, ankyrin repeats; BROMO, bromo domain; DDT, ‘DNA-binding homeobox and different transcription factors’ domain; MBD, methyl-CpG binding domain; PHD, plant homeodomain; SET, Su(var.)3-9, Enhancer-of-zeste, Trithorax domain; b, Alignment of conserved domains in BAZ-2 or SET-6 with those in their mammalian homologues. Identical and conservative residues are highlighted in black and in grey, respectively.
Extended Data Fig. 8 Mammalian Baz2b and Ehmt1 have a conserved role in repressing mitochondrial function.
a, b, Transcription levels of BAZ2A and EHMT2 in the prefrontal cortex of human brains at different ages. Expression values in a (n = 30 samples) are from the dataset GSE1572 (see ref. 8), and in b (n = 145 samples) are from brain samples without neurodegenerative disease in the dataset GSE44772 (see ref. 9). Pearson’s r correlation coefficient was used for statistical testing. c, Co-immunoprecipitation of BAZ2B and EHMT1 in HEK293T cells. Images are representative of three independent experiments. For gel source data, see Supplementary Fig. 6. d, ChIP-qPCR analysis of BAZ2B or EHMT1 enrichment at nuclear genes encoding mitochondrial proteins in HEK293T cells. Immunoglobulin G (IgG) antibody was used as a control. e–g, Effects of downregulation of mouse Baz2b or Ehmt1 by short hairpin RNAs (shRNAs) on the transcription of mitochondria-related genes (e), ATP level (f) and oxygen-consumption rate (g) in primary mouse cerebellar neurons. F, carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP); NC, negative control; O, oligomycin; R, rotenone. h, i, Oxygen-consumption rate (h) and ATP content (i) in primary mouse cortical neurons overexpressing (OE) mouse Baz2b or Ehmt1. Graphical OCR data are representative of three independent experiments. In d–i, sample numbers are shown beneath the bars. Data shown are means ± s.e.m.; *P < 0.05; **P < 0.01; ***P < 0.001 (d, two-tailed t-test, e–h, one-way ANOVA with Dunnett’s test; i, Kruskal–Wallis test; see Supplementary Information for exact P values). Source Data
a, Diagram showing the generation of Baz2b−/− (KO) mice. UTR, untranslated repeat; WT, wild-type. Protospacer-adjacent motif (PAM) sequences are highlighted in green; the substitution site is highlighted in red. b, Western blot analysis of Baz2b protein level in samples from WT, Baz2b+/− and Baz2b−/− mice. Images are representative of three independent experiments. For gel source data, see Supplementary Fig. 7. c, Oxygen-consumption rates (OCRs) of mitochondria isolated from 12-month-old WT, Baz2b+/− and Baz2b−/− male mice. A, antimycin; F, carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP); O, oligomycin; R, rotenone. n = 4 mice per group. P values were determined by one-way ANOVA with Dunnett’s test. d, e, Spontaneous locomotion of old (d) and young (e) mice in an open field test. The numbers of tested mice are shown beneath the bars. f, Escape latency in Barnes maze trials during training days for young WT, Baz2b+/− and Baz2b−/− mice. Numbers of tested mice are indicated in parentheses. In all assays, data shown are means ± s.e.m. Source Data
Extended Data Fig. 10 Expression level of BAZ2B and EHMT1 correlates positively with the progression of Alzheimer’s disease in humans.
a, Expression level of BAZ2B (left) and EHMT1 (right) at different Braak stages in the prefrontal cortex of brains with Alzheimer’s disease. b, Expression level of BAZ2B (left) and EHMT1 (right) at different stages of frontal atrophy in the prefrontal cortex of brains with Alzheimer’s disease. c–e, Correlations between the expression levels of BAZ2B (x-axes) and selected nuclear genes (encoding mitochondrial proteins; y-axes) in the prefrontal cortex of brains with Alzheimer’s disease. f–h, Correlations between the expression levels of EHMT1 (x-axes) and selected nuclear genes (encoding mitochondrial proteins; y-axes) in the prefrontal cortex of brains with Alzheimer’s disease. In a–h, expression values (n = 390 samples) of examined genes are from the dataset GSE44772, using Pearson’s r correlation coefficient for statistical testing. i, Proposed working model for the epigenetic regulation of mitochondrial function and healthy ageing. Source Data
This file contains statistical test results, lists of RT-PCR primers and uncropped gel images.
Positive genes obtained by the RNAi screen.
Overlapping genes that bind to BAZ-2 and SET-6.
Common differentially expressed genes in baz-2 and set-6 mutant worms.
The efficiency of Baz2b and Ehmt1 shRNAs in primary mouse neurons.
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Yuan, J., Chang, S., Yin, S. et al. Two conserved epigenetic regulators prevent healthy ageing. Nature 579, 118–122 (2020). https://doi.org/10.1038/s41586-020-2037-y
Nature Reviews Genetics (2020)