Retrotransposable elements are deleterious at many levels, and the failure of host surveillance systems for these elements can thus have negative consequences. However, the contribution of retrotransposon activity to ageing and age-associated diseases is not known. Here we show that during cellular senescence, L1 (also known as LINE-1) retrotransposable elements become transcriptionally derepressed and activate a type-I interferon (IFN-I) response. The IFN-I response is a phenotype of late senescence and contributes to the maintenance of the senescence-associated secretory phenotype. The IFN-I response is triggered by cytoplasmic L1 cDNA, and is antagonized by inhibitors of the L1 reverse transcriptase. Treatment of aged mice with the nucleoside reverse transcriptase inhibitor lamivudine downregulated IFN-I activation and age-associated inflammation (inflammaging) in several tissues. We propose that the activation of retrotransposons is an important component of sterile inflammation that is a hallmark of ageing, and that L1 reverse transcriptase is a relevant target for the treatment of age-associated disorders.

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All Source Data and exact P values (if applicable) for every figure are included in the supporting information that accompanies the paper. RNA-seq data have been deposited in the Gene Expression Omnibus (GEO) with accession number GSE109700. Any other data or information relevant to this study are available from the corresponding author upon reasonable request.

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The following funding sources are acknowledged: M.D., Glenn/AFAR Postdoctoral Fellowship, NIH P20 GM119943 COBRE pilot award; T.I., NIH F31 AG043189; A.P.P. and A.E.E., NIH T32 AG041688; S.W.C., NIH F31 AG050365; A.C. and G.B., Biotechnology and Sport Medicine Fellowships, School of Pharmacy, University of Bologna, Bologna, Italy; E.M.A. and J.D.B., NIH P01 AG051449; C.B., Canadian Institute of Health Research MOP-102709; J.A., NIH DP1 GM114862, R01 EY022238, R01 EY024068, R01 EY028027, John Templeton Foundation Grant ID 60763; M.S., A.S. and V.G., NIH R01 AG046320, R01 AG027237, R01 AG047200, P01 AG051449, Life Extension Foundation; S.L.H., NIH R37 AG016667, R01 AG024353, P01 AG051449, Glenn-AFAR Breakthroughs in Gerontology Award; N.N., NIH R01 AG050582, P20 GM109035; J.M.S., NIH R37 AG016694, P01 AG051449. We are grateful to A. Maier, M. Waaijer, R. Westendorp and the participants of the Leiden Longevity Study (LLS) for assistance with the human specimens. We thank D. Baker for guidance with the glomerulosclerosis assay. The biomaterials collection of the LLS (P.E.S., principal investigator) was supported by the Netherlands Genomics Initiative of the Netherlands Organization for Scientific Research (NWO), within the framework of the Netherlands Consortium of Healthy Ageing (NCHA, 050-060-810) and the Leiden University Medical Center.

Reviewer information

Nature thanks D. Sinclair, J. van Deursen and the anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

    • Alberto Caligiana
    •  & Greta Brocculi

    Present address: Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy


  1. Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA

    • Marco De Cecco
    • , Takahiro Ito
    • , Anna P. Petrashen
    • , Amy E. Elias
    • , Nicholas J. Skvir
    • , Steven W. Criscione
    • , Alberto Caligiana
    • , Greta Brocculi
    • , Stephen L. Helfand
    • , Nicola Neretti
    •  & John M. Sedivy
  2. Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA

    • Emily M. Adney
    •  & Jef D. Boeke
  3. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    • Emily M. Adney
  4. Centre de Recherche CHU Ste-Justine, and Department of Pharmacology and Physiology, Université de Montréal, Montréal, Québec, Canada

    • Oanh Le
    •  & Christian Beauséjour
  5. Center for Advanced Vision Science and Department of Ophthalmology, University of Virginia School of Medicine, Charlottesville, VA, USA

    • Jayakrishna Ambati
    •  & Kameshwari Ambati
  6. Department of Biology, University of Rochester, Rochester, NY, USA

    • Matthew Simon
    • , Andrei Seluanov
    •  & Vera Gorbunova
  7. Department of Molecular Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands

    • P. Eline Slagboom
  8. Center for Computational Molecular Biology, Brown University, Providence, RI, USA

    • Nicola Neretti


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J.M.S. conceived the study. J.M.S. and M.D. designed the experiments. M.D. and T.I. maintained cell cultures and performed lentiviral interventions. M.D. performed RT–qPCR in cell culture and mouse tissues with help from M.S. and G.B. T.I. and A.C. performed immunoblots. M.D. performed all immunofluorescence analyses. N.J.S., S.W.C. and A.E.E. did the bioinformatics and statistics. A.P.P. performed immunohistochemistry and tissue histology. E.M.A. generated and validated antibodies against mouse ORF1. O.L. irradiated mice and collected tissues. J.A. and K.A. provided NRTI analogues. P.E.S. provided human samples. J.D.B., C.B., J.A., K.A., A.S., V.G., P.E.S., S.L.H., N.N. and J.M.S. contributed to personnel supervision, data interpretation and critical analysis. J.M.S. and M.D. wrote the manuscript with feedback from all authors.

Competing interests

J.A. is a cofounder of iVeena Holdings, iVeena Delivery Systems, and Inflammasome Therapeutics, and has been a consultant for Allergan, Biogen, Boehringer-Ingelheim, Janssen, Olix Pharmaceuticals, and Saksin LifeSciences in a capacity unrelated to this work. J.A. and K.A. are named as inventors on patent applications on macular degeneration filed by the University of Kentucky or the University of Virginia. J.D.B. is a founder and Director of Neochromosome, Inc., the Center of Excellence for Engineering Biology, and CDI Labs, Inc. He serves on the Scientific Advisory Boards of Modern Meadow, Inc., Recombinetics, Inc., and Sample6, Inc.

Corresponding author

Correspondence to John M. Sedivy.

Extended data figures and tables

  1. Extended Data Fig. 1 Establishment of senescent cultures and analysis of L1 and IFN-I activation.

    a, Passaging regimen to obtain long-term replicatively senescent cells (details in Methods). Point ‘A’ was designated as zero for time in senescence. bd, Confirmation of the senescent status of cultures. A representative experiment is shown; other experiments were monitored in the same manner and generated data that met these benchmarks. b, Cells were labelled with BrdU for 6 h. BrdU incorporation67 and SA-β-Gal activity66 were determined as indicated. DNA damage foci were visualized using γ-H2AX antibodies and immunofluorescence microscopy34. c, Expression of p21 (CDKN1A) and p16 (CDKN2A) proteins was determined by immunoblotting. GAPDH was the loading control. For gel source data, see Supplementary Fig. 1. d, Expression of genes characteristic of the SASP was determined by RT–qPCR. e, L1 activation during senescence of IMR-90 and WI-38 strains of fibroblasts was assessed by RT–qPCR using poly(A)-purified RNA and primers for amplicon F (Fig. 1b). f, Long-range RT–PCR was performed with primers A (forward) and C (reverse) (amplicon G) and primers A (forward) and D (reverse) (amplicon H) (Fig. 1b, Supplementary Table 1) and the cDNAs were cloned and sequenced. Several attempts using the same protocol on early passage proliferating cells did not yield any L1 clones. Sequences were mapped to the unmasked reference genome demanding 100% identify. A total of 658 clones could be thus mapped, 51 additional clones contained at least 1 mismatch and thus probably represent elements that are polymorphic in the cell line, and 58 were cloning artefacts. Among the 658 mappable clones, 224 unique elements were represented (Supplementary Table 3). Intact elements are the subset of full-length elements annotated with no ORF-inactivating mutations. Size of the features corresponds to the number of times the element was represented among the 658 clones. g, Summary of long-range PCR data presented in f and Supplementary Table 3. h, Apparent genomic copy numbers of elements detected with our amplicons (see Fig. 1b for locations of amplicons and Methods for primer design strategy). ‘Predicted’ denotes in silico PCR (Methods); ‘observed’ denotes qPCR was performed on 1 ng of genomic DNA and normalized to a known single copy locus. i, Activation of IFNA and IFNB1 genes during senescence of WI-38 and IMR-90 cells was determined by RT–qPCR. j, Confirmation of the senescent status of cells in OIS (20 days, Fig. 1e) and SIPS (30 days, Fig. 1e) by SA-β-Gal activity. k, Confirmation of full-length L1 mRNA expression in all forms of senescence using RT–qPCR with primers for amplicons A and F on poly(A)-purified RNA. Late onset activation is shown by comparing days 9 and 20 for OIS, and days 12 and 30 for SIPS. n = 3 independent biological samples, repeated in two independent experiments (be, ik). Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, unpaired two-sided t-test. Exact P values can be found in the accompanying Source Data. Source Data

  2. Extended Data Fig. 2 Mapping transcriptional start sites in L1 elements activated during cellular senescence.

    5′ RACE was performed with primers C and D (Fig. 1a, Supplementary Table 1) on late senescent cells (16 weeks, point D in Extended Data Fig. 1a), the products were cloned, and individual clones were Sanger sequenced (Methods). a, A multiple sequence alignment of the 50 mappable clones against the L1HS consensus was generated with MAFFT software. The L1HS consensus is shown. Blue shading of the aligned clones shows their degree of identity with the consensus. Green vertical line marks the start (position 1) of the L1HS consensus. Red vertical lines mark short gaps (1–4 nucleotides) opened in the L1HS consensus by individual clones. The consensus of the 50 clones is shown at the bottom and was generated with Jalview. The initiation of L1 transcription is known to be imprecise, with most start sites occurring ±50 bp of the consensus start site, and a subset as far down as +180 bp68. b, Summary of the mapping data and classification of clones to families of L1 elements. The relative start sites were calculated relative to the L1HS consensus start site. RepEnrich software55 was used to assign the clones to L1 families.

  3. Extended Data Fig. 3 Evolution of transcriptomic changes during progression of cellular senescence.

    RNA-seq was performed on early proliferating LF1 cells and cultures at 8 weeks (SEN-E) and 16 weeks (SEN-L) in senescence (points C and D, respectively, in Extended Data Fig. 1a). Data were analysed using a three-way comparison: EP versus SEN-E, EP versus SEN-L and SEN-E versus SEN-L (see Methods for details). a, Area-proportional generalized Venn diagrams depicting the intersections of the three comparisons for the following datasets. iii, Significantly upregulated and downregulated genes (row ‘2×’ in b). iiiiv, Significant KEGG pathways identified by gene set enrichment analysis (GSEA). Note the considerable evolution of the transcriptome in late senescence, exemplified by large changes (especially upregulated) in differentially expressed genes as well as pathways. vvi, Significantly changing genes in the IFN-I and SASP gene sets (see Supplementary Table 4 for annotation of gene sets). Note that most changes in SASP genes occur early, whereas a large component of IFN-I changes is specific for late senescence. b, Summary of significantly changing genes using a fixed false discovery rate (FDR) (<0.05) and variable fold-change cut offs (2×, 1.75× and 1.5×). c, GSEA analysis of KEGG pathways. Heat map representation shows significantly upregulated pathways in red (also see e) and downregulated pathways in blue. Non-significant comparisons are shown in black; vertical annotations refer to Venn diagrams in a, iiiiv. Note that the SASP gene set is upregulated early, whereas the IFN-I gene set is upregulated late. d, Heat maps of significantly changing genes in the IFN-I and SASP gene sets. Vertical annotations refer to Venn diagrams in a, vvi. e, List of significantly upregulated KEGG pathways identified using GSEA (see Supplementary Table 5 for a list of all pathways). NES, normalized enrichment scores. IFN-I and SASP gene sets are highlighted in yellow. Note the significant upregulation of IFN-I between early and late senescence. Red font identifies KEGG pathways indicative of cytosolic DNA sensing and a type I interferon response at late times. f, g, GSEA profiles of the IFN-I and SASP gene sets for all comparisons; FDR is highlighted in yellow. Note that the upregulation of IFN-I is significant for EP_SEN-L and SEN-E_SEN-L but not for EP_SEN-E, and that the upregulation of SASP is significant for EP_SEN-E and EP_SEN-L but not SEN-E_SEN-L. n = 3 independent biological samples. Differential expression data were analysed for significance using the GSEA GenePattern interface and the outputs were corrected for multiple comparisons by adjusting the nominal P values using the Benjamini–Hochberg method (see Methods for details).

  4. Extended Data Fig. 4 Characterization of L1 effectors and the IFN-I response.

    a, Expression of TREX1 was determined by RT–qPCR and immunoblotting. For gel source data, see Supplementary Fig. 1. b, Expression of RB family genes was compared by RT–qPCR. Primer pairs for all genes were verified to be of equivalent efficiency. c, Enrichment of H3K9me3 and H3K27me3 on L1 elements was examined by ChIP–qPCR (PCR primers illustrated in Fig. 1b were used: 5′ UTR, amplicon A; ORF1, amplicon E; ORF2, amplicon F). d, ChIP–seq data from ENCODE were investigated for transcription factors that bind to the L1 consensus sequence. The fold change, log2(enrichment), relative to input controls is shown for the indicated cell lines. The binding of YY1 to the L1 promoter has been documented69 and was used as a positive control. CEBPB was used as a negative control. A schematic illustrating L1 coordinates and relevant features is shown above. Amplicons A–E are the same as shown in Fig. 1b. e, Transcriptional activity of the intact L1 5′ UTR or a UTR lacking the FOXA1-binding site (UTR−Δ) was determined using sense and antisense reporters cotransfected into early passage LF1 cells either with a FOXA1 expression plasmid or empty vector. f, FOXA1 was knocked down in senescent cells with shFOXA1 (a) (see also Fig. 2e and Extended Data Fig. 5a) and binding to the L1 5′ UTR (amplicon B) was determined by ChIP–qPCR. g, Knockdown of RB1, TREX1 and ectopic expression of FOXA1 were performed in early passage cells in all single (1×), double (2×) and triple (3×) combinations and assessed by RT–qPCR using poly(A)-purified RNA for activation of L1, IFNA and IFNB1 expression (primers for amplicon F). Three controls are shown: cells infected with irrelevant shRNA (shGFP), expression construct (LacZ), or uninfected early passage cells. h, L1 5′ UTR occupancy of RB1 and FOXA1 in 3× cells was determined by ChIP–qPCR performed as in Fig. 2a, b. Primers for amplicons A and B were used for RB1 and FOXA1, respectively. For comparison, single interventions in early passage cells with shRB1 (a) or FOXA1 cDNA expression (EP FOXA1-OE) are also shown. i, Confirmation of full-length L1 mRNA expression in 3× cells using RT–qPCR with primers for amplicons A and F on poly(A)-purified RNA. CTR, cells infected with irrelevant shRNA (shGFP). j, Heat map representation showing all biological replicates for the 67 genes significantly changing expression in SEN and/or 3× cells (Fig. 2h, Supplementary Table 6). Column clustering was calculated as 1 − Pearson correlation. Rows have been grouped into functional subsets of the IFN-I response. k, Venn diagram showing the overlap between the 67 significantly changing genes. n = 3 independent biological samples, repeated in two independent experiments (af, h); n = 3 independent experiments (g, i).) Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, unpaired two-sided t-test. Exact P values can be found in the accompanying Source Data. Source Data

  5. Extended Data Fig. 5 Efficacy of genetic and pharmacological interventions.

    a, b, Knockdowns with two distinct shRNAs (a or b) (a) or ectopic cDNA expression (b) were performed in senescent cells as described in Fig. 2d, e, g (also see Methods). The effectiveness of these manipulations on their targets was assessed by RT–qPCR and immunoblotting. For gel source data, see Supplementary Fig. 1. c, RB1, TREX1 and FOXA1 mRNA and protein expression after the triple (3×) intervention (Fig. 2f). d, The effect of 3TC treatment on the relative abundance of L1HS sequences in senescent cells was determined by multiplex TaqMan qPCR on total DNA (primer set 6, Supplementary Table 1). SEN entry, 0 weeks in senescence (Fig. 1a; point A in Extended Data Fig. 1a). 3TC was administered continuously from SEN entry until collection 16 weeks later. e, The dual luciferase L1 reporter system52 was used to determine the effect of 3TC dosing on retrotransposition. L1 reporters were introduced into early passage cells using lentivirus vectors (Methods) and cells were treated with 3TC for 4 days before collection and assay. JM111, a defective reporter carrying mutations in ORF1 (absence of 3TC); L1RP, a retrotransposition competent reporter. f, The effect of 3TC dosing on the IFN-I response. The experiment in d was processed by RT–qPCR to determine the expression of IFNA and IFNB1. g, Knockdowns of L1 elements were performed with two distinct shRNAs (a and b) in senescent cells (as in Fig. 2d, e, g) or 3× cells (as in Fig. 2f). The effectiveness on L1 expression was assessed by RT–qPCR using poly(A)-purified RNA and primers F. h, Cells in the experiment in g were examined for levels of ORF1 protein by immunofluorescence. Image analysis was performed with CellProfiler software (Methods). More than 200 cells were examined for each condition (a.f.u., arbitrary fluorescence units). i, The L1 shRNA treatment in the experiment in g was substituted with 3TC treatment (10 μM) for the same period of time. j, Five different NRTIs (or combinations) were tested for effects on the IFN-I response. AZT (zidovudine, 15 μM), ABC (abacavir, 15 μM), FTC (emtricitabine, 10 μM), 3TC (10 μM) and TZV (Trizivir, a combination of 15 μM AZT, 15 μM ABC and 7.5 μM 3TC). Cells were treated for 4 weeks between 12 and 16 weeks in senescence (Fig. 1a; points D and E in Extended Data Fig. 1a). 3× cells (Fig. 2f) were treated with 3TC for 48 h after the completion of the last drug selection. IFNA expression was determined by RT–qPCR. k, A native L1 reporter (pLD143)53 was co-transfected with shRNA plasmid vectors into HeLa cells (Methods). Retrotransposition was scored as GFP-positive cells, and shL1 knockdowns were normalized to a shLuc negative control. The absolute average retrotransposition frequency (percentage of GFP-positive cells) was 4.1, which matches the published values for the reporter used (pLD143)53. l, Knockdowns of cGAS and STING were performed in senescent or 3× cells as with the other shRNAs (as in a, g, and Fig. 2d, e, g). m, Downregulation of interferon signalling after CRISPR-mediated inactivation of IFNAR1 and IFNAR2 genes was verified by the absence of IRF9 nuclear translocation and STAT2 phosphorylation in response to interferon stimulation. Cells were infected with lentivirus vectors expressing Cas9 and gRNAs to both IFNAR1 and IFNAR2 (ΔIFNAR, Methods). After the infection, cells were reseeded on coverslips, treated with interferon for 2 h, and examined by immunofluorescence microscopy. The experiment was repeated three times with similar results. n = 3 independent experiments (aj, l), n = 3 independent biological samples, repeated in two independent experiments (k). Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, unpaired two-sided t-test. Exact P values can be found in the accompanying Source Data. Source Data

  6. Extended Data Fig. 6 Characterization of cytoplasmic DNA in senescent cells.

    a, Left, quiescent and senescent cells were treated with BrdU as in Fig. 3c and the cellular localization of BrdU incorporation was visualized by immunofluorescence microscopy. Proliferating cells (EP (Prol)) are shown as a positive control for nuclear BrdU incorporation. Right, the signals were quantified using CellProfiler software (Methods). More than 200 cells were examined for each condition. b, Senescent (and early passage control) cells (neither labelled with BrdU) were fractionated into nuclear and cytoplasmic fractions, and the representation of L1 sequences in these compartments (as well as whole cells) was assessed with qPCR as in Fig. 3c (TaqMan multiplex qPCR assay16, amplicon F, Fig. 1b). Note that the y-axis units differ by tenfold between the left and right panels. c, Cells were examined by immunofluorescence microscopy for the presence of ORF1 protein, RNA–DNA hybrids, and ssDNA. See Methods and Supplementary Table 2 for antibodies. The RNA–DNA signal in senescent cells largely colocalized with the ORF1 signal and was lost after RNase A treatment. The ssDNA signal also colocalized with the ORF1 signal and was exposed by RNase treatment. The experiment was repeated three times with similar results. d, The pulled-down BrdU-containing DNA (a and Fig. 3c; Methods) was cloned and Sanger sequenced. Of the 96 total clones examined, 37 mapped to L1. Red boxes represent the relative positions of these clones on the L1 consensus sequence. e, Senescent cells labelled with BrdU (a and Fig. 3c) were immunoprecipitated with anti-BrdU antibodies, and the representation of L1 sequences in the pulled-down DNA was assessed using qPCR with primers spanning the entirety of L1 elements (Fig. 1b, c). f, Senescent cells were treated with L1 shRNA (using lentiviral vectors as described in Extended Data Fig. 5g) between 12 and 16 weeks of senescence, and expression of SASP genes was determined. g, Transcription throughout mouse L1 elements was assessed in a strand-specific manner using the same strategy as was applied to human L1 elements (Fig. 1b, c). The amplicons (designated W–Z to distinguish them from the human-specific primers) correspond to the 5′ UTR (W), ORF1 (X), ORF2 (Y) and 3′UTR (Z). See Methods and Supplementary Table 1 for primer sequences (primer sets 37 and 48–50). Poly(A) RNA was prepared from male white adipose tissue. A total of 12 mice were assessed (3 pools of 4 mice each) in 3 independent experiments. h, Expression of the three currently active families of mouse L1 elements (MdA, MdN and Tf). Primers were designed to distinguish 5′ UTR polymorphisms of the MdA, MdN and Tf families (Methods, Supplementary Table 1 primer sets 51–53). RT–qPCR was performed as in f (non-strand-specific). n = 3 independent biological samples, repeated in two independent experiments (a, b, e); n = 3 independent experiments (f). Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, one-way ANOVA with Tukey’s multiple comparisons test (a), unpaired two-sided t-test (b, eh). Exact P values can be found in the accompanying Source Data. Source Data

  7. Extended Data Fig. 7 Effects of ablating L1 activation, the cytoplasmic DNA sensing pathway, or interferon signalling on expression of the IFN-I and SASP responses.

    a, 3× cells were treated with L1 shRNA or with 3TC for 48 h as described in Extended Data Fig. 5g,i. Effects on the IFN-I response were determined by RT–qPCR, ELISA or immunoblotting. For gel source data, see Supplementary Fig. 1. b, Cells were serially passaged into replicative senescence with 3TC (10 μM) present throughout, as in Fig. 3f, and expression of the CDK inhibitors p21 and p16 was assessed by RT–qPCR. c, Senescent cells were treated with shRNAs against CGAS or STING between 12 and 16 weeks of senescence (as described in Extended Data Fig. 5l), and expression of IFN-I response genes (IFNA, IRF7 and OAS1) was determined. d, cGAS and STING knockdowns were performed with shRNAs in 3× cells (as in c), and expression of IFN-I genes was examined by RT–qPCR. e, cGAS and STING were knocked down in senescent cells with shRNAs (as in c), and expression of SASP response genes (IL1B, CCL2, IL6 and MMP3) was assayed by RT–qPCR. f, g, The activity of K-9 was compared with 3TC in senescent and 3× cells. Senescent cultures were treated between 12 and 16 weeks (as in Fig. 3b) and 3× cultures for 48 h (as in a). Effects on the expression of IFN-I genes (IFNA, IRF7 and OAS1) and SASP genes (IL1B, IL6 and MMP3) was assessed by RT–qPCR. n = 3 independent experiments. Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, unpaired two-sided t-test. Exact P values can be found in the accompanying Source Data. Source Data

  8. Extended Data Fig. 8 Assessment of p16, L1 ORF1 and pSTAT1 expression in senescent cells and skin specimens from aged humans.

    a, Immunofluorescence (IF) detection of p16 and ORF1 in early passage, 3× and senescent cells. b, Representative images of combinatorial ORF1 and p16 or ORF1 and phosphorylated STAT1 (pSTAT1) staining in human dermis. The experiments in a and b were repeated three times independently with similar results. c, Cells were plated on coverslips, stained and quantified as described in the Methods. A total of 200 cells in several fields were scored for each condition. Insets show the percentage of cells found in each quadrant. d, e, Abundance of ORF1 and p16 or pSTAT1 cells in human skin. Skin biopsies were cryosectioned and stained as described in the Methods. A total of 200 dermal fibroblast cells in several fields were scored for each subject. Aggregated data for 4 subjects (800 cells) are shown. f, Data in c and d were recalculated to show the relative abundance of p16+ cells among all cells, and ORF1+ cells in the p16+ pool of cells. g, Data in e were recalculated as in f. h, Characteristics of the human subjects used in the analysis of dermal fibroblasts. These specimens were collected as part of the ongoing Leiden Longevity Study62. The specimens used here were chosen randomly from leftover material. The telomere dysfunction-induced foci (TIF) assay34 relies on a two-parameter (colour) visualization of telomeres (using a FISH probe) and immunofluorescent detection of DNA damage foci (using antibody to 53BP1). Because of limiting material, it was not possible to combine detection of p16 with TIFs in a three-colour experiment.

  9. Extended Data Fig. 9 Effects of 3TC or K-9 treatment on L1, p16, IFN-I and SASP gene expression in mouse tissues.

    ac, Mice at the indicated ages were treated with 3TC continuously for two weeks (see also Fig. 4c, e, Extended Data Fig. 10d–f and Methods). For all conditions, the expression of L1 mRNA, p16, three representative IFN-I response genes (Ifna, Irf7 and Oas1) and three representative SASP genes (Il6, Mmp3 and Pai1) were assessed by RT–qPCR. In no instance was expression at 5 months plus 3TC significantly different from the no-drug control, therefore these data are not shown in the figure (for all collected data, see Supplementary Table 7). Each point represents one animal. a, Visceral white adipose, male mice. n = 8 mice at 5 month; n = 12 mice at 26 months; n = 12 mice at 26 months + 3TC. b, Visceral white adipose, female mice. n = 8 mice at 5 months; n = 12 mice at 26 months; n = 12 mice at 26 months + 3TC. c, Liver, male mice. n = 8 mice at 5 months; n = 10 mice at 26 months; n = 10 mice at 26 months + 3TC. d, Mice at the age of 26 months were treated with K-9 or 3TC in drinking water for two weeks and analysed by RT–qPCR as above. NT, not treated. Visceral white adipose, male mice, n = 7 mice for each group. Box plots as in Fig. 4. Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, one-way ANOVA with Tukey’s multiple comparisons test. Exact P values can be found in the accompanying Source Data. Source Data

  10. Extended Data Fig. 10 Combinatorial assessment of senescence, IFN-I, SASP and L1 markers and effects of 3TC on age-associated phenotypes in mouse tissues.

    a, b, Whole-mount immunofluorescence was performed on white adipose of 5- and 26-month-old male mice (with and without 2 weeks of 3TC treatment). a, Loss of lamin B1 (senescence marker) was colocalized with IL-6 (SASP marker). b, pSTAT1 (IFN-I marker) was colocalized with ORF1 (L1 marker). c, Quantification of the experiments in a and b. Four mice and at least 200 cells per animal were scored for each condition. d, Neutral lipids were stained with BODIPY to visualize mature adipocytes in whole-mount preparations, and macrophages were detected by immunofluorescence using the F4/80 antibody. e, The effects of 2 weeks of 3TC treatment on adipogenesis were assessed by measuring mean adipocyte size (left), and by RT–qPCR to determine the expression of key adipogenic genes (right; Acaca, acetyl-CoA carboxylase 1; Cebpa, CCAAT/enhancer-binding protein alpha; Fasn, fatty acid synthase; Srebf1, sterol regulatory element-binding protein 1). Adipocyte size (BODIPY-stained area) was calculated using CellProfiler; aggregated data for 5 mice and 500 total cells are shown. For RT–qPCR data, each point represents one animal; n = 6 mice. f, Expression of the Ucp1 gene (thermogenin) in brown adipose tissue was determined by RT–qPCR and is represented as in e. n = 5 mice. g, Expression of L1 mRNA was determined by RT–qPCR and is represented as in e. n = 8 mice at 5 months; n = 12 mice at 26 months; n = 6 mice at 29 months. Box plots as in Fig. 4. Data are mean ± s.d. *P ≤ 0.05, **P ≤ 0.01, one-way ANOVA with Tukey’s multiple comparisons test (c, e, left, f, g), or unpaired two-sided t-test (e, right). Exact P values can be found in the accompanying Source Data. Source Data

Supplementary information

  1. Supplementary Information

    This file contains Supplementary Figure 1 and Supplementary Tables 1, 2 and 6

  2. Reporting Summary

  3. Supplementary Table 3

    A list of expressed L1 elements identified by long range RT-PCR

  4. Supplementary Table 4

    The gene list used in GSEA for SASP (85 genes) and the gene list used in GSEA for IFN-I (50 genes)

  5. Supplementary Table 5

    This table contains: a, GSEA analysis of KEGG pathways comparing early passage with early senescence; b, GSEA analysis of KEGG pathways comparing early passage with late senescence; and c, GSEA analysis of KEGG pathways comparing early senescence with late senescence

  6. Supplementary Table 7

    A summary of mouse tissue RT-qPCR data for L1, p16, IFN-I and SASP genes

Source data

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