Multiple molecular pathways to longevity with opposing gene expression programs defining distinct aging strategies in Caenorhabditis elegans
- Department of Neurology and Neurosurgery, McGill University, Canada
- Metabolic Disorders and Complications Program, and Brain Repair and Integrative Neuroscience Program, Research Institute of the McGill University Health Centre, Canada
- Bioinformatics Core, Harvard School of Public Health, Harvard Medical School, United States
- Laboratory of Aging and Neurodegenerative Disease, Center for Neurodegenerative Science, Van Andel Research Institute, United States
- Division of Experimental Medicine, Department of Medicine, McGill University, Canada
Figures
Figure 1 with 25 supplements
Long-lived mutants exhibit significantly extended lifespans of varying magnitudes.
The lifespan of nine different long-lived mutants was measured on NGM plates with no FUdR. All of the long-lived mutants exhibited significantly increased lifespan of varying magnitudes. The long-lived mutants included clk-1 (A), sod-2 (B), eat-2 (C), ife-2 (D), isp-1 (E), nuo-6 (F), osm-5 (G), daf-2 (H), and glp-1 (I) mutants. glp-1 worms were allowed to develop at 25°C then shifted to 20°C at adulthood. A minimum of three biological replicates were performed for each strain. Significance was assessed using the log-rank test. Three biological replicates were performed. Total n for each strain was as follows: N2 (244), clk-1 (174), sod-2 (174), eat-2 (108), ife-2 (214), isp-1 (94), nuo-6 (148), osm-5 (48), daf-2 (176), glp-1 (197), and N2-25°C (195).
Figure 1—figure supplement 1
Transcriptomic analysis of long-lived sod-2 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 2
Transcriptomic analysis of long-lived clk-1 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 3
Transcriptomic analysis of long-lived isp-1 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 4
Transcriptomic analysis of long-lived nuo-6 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 5
Transcriptomic analysis of long-lived daf-2 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 6
Transcriptomic analysis of long-lived glp-1 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 7
Transcriptomic analysis of long-lived eat-2 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 8
Transcriptomic analysis of long-lived osm-5 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 9
Transcriptomic analysis of long-lived ife-2 mutants.
(A) Principal component analysis plot. (B) Heatmap comparing gene expression to wild-type (WT) worms. (C) Mean average (MA) plot examining log fold change across all genes. (D) Volcano plot comparing adjusted p-value and log fold change across all genes.
Figure 1—figure supplement 10
Enrichment analysis of differentially expressed genes in long-lived sod-2 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 11
Enrichment analysis of differentially expressed genes in long-lived clk-1 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 12
Enrichment analysis of differentially expressed genes in long-lived isp-1 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 13
Enrichment analysis of differentially expressed genes in long-lived nuo-6 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 14
Enrichment analysis of differentially expressed genes in long-lived daf-2 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 15
Enrichment analysis of differentially expressed genes in long-lived glp-1 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 16
Enrichment analysis of differentially expressed genes in long-lived eat-2 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 17
Enrichment analysis of differentially expressed genes in long-lived osm-5 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 18
Enrichment analysis of differentially expressed genes in long-lived ife-2 mutants.
(A) Gene Ontology (GO) term enrichment of upregulated genes. (B) KEGG pathway enrichment for upregulated genes. (C) GO term enrichment for downregulated genes. (D) KEGG pathway enrichment for downregulated genes. Enrichment analysis was performed using ShingGo 0.85.1 (https://bioinformatics.sdstate.edu/go/).
Figure 1—figure supplement 19
Comparison of gene expression changes in clk-1 mutants in the current study to previously published gene expression results.
The published microarray data is from Cristina et al., 2009, PLoS Genetics Microarray: https://doi.org/10.1371/journal.pgen.1000450. The published RNA-seq data is from Dutta et al., 2025, PLoS Biology (https://doi.org/10.1371/journal.pbio.3003504).
Figure 1—figure supplement 20
Comparison of gene expression changes in isp-1 mutants in the current study to previously published gene expression results.
The published microarray data is from Cristina et al., 2009, PLoS Genetics (https://doi.org/10.1371/journal.pgen.1000450) and Yee et al., 2014, Cell (https://doi.org/10.1016/j.cell.2014.02.055).
Figure 1—figure supplement 21
Comparison of gene expression changes in nuo-6 mutants in the current study to previously published gene expression results.
The published microarray data is from Yee et al., 2014, Cell (https://doi.org/10.1016/j.cell.2014.02.055).
Figure 1—figure supplement 22
Comparison of gene expression changes in daf-2 mutants in the current study to previously published gene expression results.
The published RNA-seq data is from Zhang et al., 2022, Nature Communications (https://doi.org/10.1038/s41467-022-33850-4).
Figure 1—figure supplement 23
Comparison of gene expression changes in glp-1 mutants in the current study to previously published gene expression results.
The published RNA-seq data is from Chaturbedi and Lee, 2025 and Steinbaugh et al., 2015.
Figure 1—figure supplement 24
Comparison of gene expression changes in eat-2 mutants in the current study to previously published gene expression results.
The published RNA-seq data is from Dutta et al., 2025, PLoS Biology (https://doi.org/10.1371/journal.pbio.3003504) and Ng et al., 2020, npj Aging (https://doi.org/10.1038/s41514-020-0044-8).
Figure 1—figure supplement 25
Comparison of gene expression changes in osm-5 mutants in the current study to previously published gene expression results.
The published RNA-seq data is from Li et al., 2024.
Figure 2
Gene expression levels during young adulthood are highly correlated with lifespan.
(A) Throughout the genome there were 853 genes positively correlated with lifespan on plates containing no FUdR and 1459 genes positively correlated with lifespan on plates with 25 µM FUdR. Of these genes, there were 753 genes positively correlated with lifespan under both conditions. (B) There were much fewer genes that were negatively correlated with lifespan: 45 genes were negatively correlated with lifespan on plates containing no FUdR and 149 genes were negatively correlated with lifespan on plates with 25 µM FUdR. There were 32 genes negatively correlated with lifespan under both conditions. (C) Examples of genes showing a high positive correlation with lifespan. (D) Examples of genes showing a high negative correlation with lifespan. Combined, these results suggest that gene expression at young adulthood can be predictive of lifespan. For (C) and (D), blue = daf-2, purple = isp-1, red = nuo-6, orange = osm-5, green = glp-1, brown = eat-2, grey = clk-1, yellow = sod-2, and pink = ife-2.
Figure 3 with 2 supplements
Degree of overlap of differentially expressed genes between pairs of long-lived mutants is highly significant.
Genes upregulated in each of the nine different long-lived mutants were compared to genes upregulated in the other eight long-lived mutants in a pairwise manner. All of the long-lived mutants showed a significant degree of overlap with multiple other long-lived mutants, suggesting that shared common pathways are promoting longevity. eat-2 mutants showed the least overlap with other long-lived mutants, suggesting that the pathways promoting longevity in this mutant are relatively unique compared to other long-lived mutants. The percentage shown above each bar indicates the number of overlapping genes as a percentage of the total number of upregulated genes for the strain indicated in the graph title on top of each graph. Statistical significance was assessed using a Fisher’s exact test. **p<0.01, ***p<0.001, ****p<0.0001.
Figure 3—figure supplement 1
UpSetR plots showing degree of overlap between sets of long-lived mutants.
(A) Significantly upregulated genes. (B) Significantly downregulated genes. Black bars on the left indicate the size of each gene set (number of differentially expressed genes in each long-lived mutant). Height of colored bars indicates the number of genes in common between the strains indicated below. For example, the first column of the upregulated genes indicates the number of genes that are significantly upregulated in ife-2, osm-5, and eat-2 worms. The colors indicate the number of strains in each overlap: dark blue = 3, light blue = 4, orange = 5, pink = 6, and black = 7.
Figure 3—figure supplement 2
Degree of overlap of significantly downregulated genes between pairs of long-lived mutants is highly significant.
Significantly downregulated genes (p<0.01) were compared between each pair of long-lived mutants. For most long-lived mutants, there is a highly significant degree of overlap between genes that are significantly downregulated in each long-lived mutant. For eat-2 worms, there was only a significant overlap with osm-5 and ife-2 mutants. ife-2 and daf-2 mutants exhibited a significant degree of overlap with all of the other long-lived mutants. The percentage shown above each bar indicates the number of overlapping genes as a percentage of the total number of upregulated genes for the strain indicated in the graph title on top of each graph. Statistical significance was assessed using a Fisher’s exact test. ****p<0.0001.
Figure 4 with 1 supplement
Long-lived mutants segregate into three distinct longevity groups based on gene expression.
(A) A heat map comparing eight of the nine long-lived mutants indicates that the mutants cluster into two groups based on gene expression. Group 1 contains daf-2, nuo-6, isp-1, glp-1, clk-1, and sod-2 mutants. Group 2 contains osm-5 and eat-2 mutants. (B) Diagram showing the percentage overlap of upregulated and downregulated genes in the nine long-lived mutants. The group 2 strains eat-2 and osm-5 show little overlap with group 1 strains. ife-2 worms exhibit overlap with both group 1 and group 2 strains. (C) Genes that are downregulated in group 2 worms (eat-2, osm-5) show a much greater overlap with genes upregulated in group 1 worms (daf-2, nuo-6, isp-1, glp-1) than with genes downregulated in group 1 worms. (D) Similarly, genes upregulated in group 2 worms show a much greater overlap with genes downregulated in group 1 worms than with genes upregulated in group 1 worms. Thus, for many genes, group 1 and group 2 worms exhibit changes in gene expression in the opposite direction.
Figure 4—figure supplement 1
Heat map demonstrates that long-lived mutants cluster into three groups by gene expression.
Group 1 contains daf-2, nuo-6, glp-1, sod-2, clk-1, and isp-1. Group 2 contains eat-2 and osm-5. Group 3 contains ife-2.
Figure 5 with 1 supplement
Group 1 longevity mutants exhibit upregulation of Class I DAF-16 target genes.
(A) Examination of expression of Class I DAF-16 target genes (genes activated by DAF-16) across group 1 (blue bars), group 2 (red bars), and group 3 (purple bars) longevity mutants reveals that DAF-16 target genes are upregulated in group 1 mutants but either unchanged or downregulated in group 2 mutants. (B) A heat map of the top 50 high-confidence DAF-16 target genes from Tepper et al., 2013 shows activation of the DAF-16 stress response pathway in group 1 and group 3 mutants but not in group 2 mutants. These results suggest that group 1 longevity mutants rely on the DAF-16 stress response pathway to promote longevity, while group 2 mutants utilize other pathways. Panel (A) includes RNA-seq data from six biological replicates per strain except for wild-type, which included 18 biological replicates. Statistical significance was assessed using a one-way ANOVA with Dunnett’s multiple comparisons test. **p<0.01, ***p<0.001, ****p<0.0001.
Figure 5—figure supplement 1
Group 1 longevity mutants exhibit downregulation of Class II DAF-16 target genes.
A heat map of the top 50 high-confidence Class II DAF-16 target genes (genes negatively regulated by DAF-16) from Tepper et al. Cell 2014 shows downregulation of genes that are negatively regulated by DAF-16 in group 1 mutants but not in group 2 or group 3 mutants.
Figure 6 with 3 supplements
Group 1 longevity mutants exhibit upregulation of ATFS-1 target genes.
(A) Examination of expression of ATFS-1 target genes across group 1 (blue bars), group 2 (red bars), and group 3 (purple bars) longevity mutants reveals that ATFS-1 target genes are upregulated in group 1 mutants but either unchanged or downregulated in group 2 and group 3 mutants. (B) A heat map of the top 61 high-confidence ATFS-1 target genes from Soo et al. Micropublication Biology 2021 shows activation of the mitochondrial unfolded protein response (mitoUPR) pathway in group 1 mutants but not in group 2 or group 3 mutants. These results suggest that group 1 longevity mutants rely on the mitoUPR pathway to promote longevity, while group 2 and group 3 mutants utilize other pathways. Panel (A) includes RNA-seq data from six biological replicates per strain except for wild-type, which included 18 biological replicates. Statistical significance was assessed using a one-way ANOVA with Dunnett’s multiple comparisons test. **p<0.01, ***p<0.001, ****p<0.0001.
Figure 6—figure supplement 1
Examples of genes upregulated in group 2 longevity mutants.
A number of genes were found to be significantly upregulated in group 2 longevity mutants eat-2 and osm-5 (red bars) but either unchanged or downregulated in group 1 longevity mutants (blue bars). These genes showed variable expression in the group 3 (purple bars) longevity mutant ife-2. Interestingly, among the genes that were specifically upregulated in group 2 longevity mutants were the PQM-1 target genes F55G11.2 and fat-7. Statistical significance was assessed using a one-way ANOVA with Dunnett’s multiple comparisons test. **p<0.01, ***p<0.001, ****p<0.0001.
Figure 6—figure supplement 2
Activity of specific transcription factors are modulated in multiple long-lived mutants.
The Venn diagram shows the overlap between transcription factors found to be modulated in group 1, group 2, and group 3 longevity mutants. There were 33 transcription factors that were found to be significantly modulated in all three longevity groups. Of those 33 transcription factors, 25 are modulated in opposite directions in group 1 and group 2 longevity mutants, while only 5 are modulated in the same direction. The direction of transcription factor modulation in ife-2 worms is most similar to group 1 longevity mutants.
Figure 6—figure supplement 3
Comparison of gene expression changes in long-lived mutants to gene expression changes during aging.
The gene expression changes in each of the nine long-lived mutants were compared to genes that are differentially expressed during aging. In each long-lived mutant, there were genes that were modulated in the same direction as changes that take place during aging (e.g., upregulated in long-lived mutant and upregulated during aging or downregulated in long-lived mutant and downregulated during aging) and genes that were modulated in opposite directions (upregulated in long-lived mutant and downregulated during aging or downregulated in long-lived mutant and upregulated during aging). Interestingly, in group 1 longevity mutants, there were a greater number of genes modulated in the same direction as genes that are differentially expressed with age, while in group 2 longevity mutants, there were a greater number of genes modulated in the opposite direction as genes that are differentially expressed with age. This was primarily due to genes that are downregulated during aging being upregulated in group 2 longevity mutants.
Figure 7 with 2 supplements
Genes that are commonly upregulated in the majority of long-lived mutants are involved in metabolism, defense, and innate immunity.
(A) Comparing differentially expressed genes across the panel of long-lived mutants revealed that very few genes are commonly regulated across seven or more strains. (B) Among the 196 genes that are upregulated in six or more long-lived mutants, there was an enrichment for genes involved in various metabolic processes, defense response, and innate immunity. (C) Among the 362 genes that are downregulated in five or more long-lived mutants, there was an enrichment for genes involved in translation, ribosome, and gene expression.
Figure 7—figure supplement 1
Genes upregulated in multiple long-lived mutants are involved in various metabolic processes, defense responses and innate immunity.
Figure 7—figure supplement 2
Genes downregulated in multiple long-lived mutants are involved in translation and various metabolic processes.
Figure 8 with 4 supplements
Targeted RNA interference screen identifies differentially expressed genes that can individually affect longevity.
To identify differentially expressed genes that can affect lifespan individually, genes that were found to be upregulated in six or more long-lived mutants were knocked down in daf-2 or nuo-6 mutants, and the resulting effect on lifespan was quantified. An overview of this screen is provided in panel A. While the majority of these RNAi clones did not affect longevity, we found that there were RNAi clones that both increased and decreased lifespan. Three genes were selected to study further: C08F11.7, ugt-62, and K05C4.9. (B) We confirmed that these genes decrease lifespan in nuo-6 worms. (C) Knocking down these genes was also found to decrease wild-type lifespan. Total n per treatment was as follows: nuo-6 EV (47), nuo-6 daf-16 RNAi (91), nuo-6 C08F11.7 RNAi (62), nuo-6 ugt-62 RNAi (64), nuo-6 K05C4.9 RNAi (45), WT EV (86), WT daf-16 RNAi (69), WT C08F11.7 RNAi (61), WT ugt-62 RNAi (40), and WT K05C4.9 RNAi (75). Statistical significance was assessed using the log-rank test.
Figure 8—figure supplement 1
Survival plots for targeted RNAi screen in daf-2 mutants.
RNAi was initiated at the egg stage. daf-16 RNAi was included as a positive control. Statistical significance was assessed using a log-rank test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
Figure 8—figure supplement 2
Survival plots for targeted RNAi screen in nuo-6 mutants.
RNAi was initiated at the egg stage. daf-16 RNAi was included as a positive control. Statistical significance was assessed using a log-rank test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
Figure 8—figure supplement 3
Summary of weighted mortality for targeted RNAi screen.
RNAi was initiated at the egg stage. daf-16 RNAi was included as a positive control. To compare the results of the RNAi lifespan screen across trials, weighted mortality was calculated as (mortality – mortality of EV)/(mortality of daf-16 RNAi – mortality of EV). Black dots indicate data points from the initial screen. Blue dots indicate data from re-screening hits.
Figure 8—figure supplement 4
Repeat testing of RNAi clones that decreased nuo-6 lifespan in initial screen.
All four RNAi clones were found to decrease lifespan in both nuo-6 and wild-type worms. Statistical significance was assessed using the log-rank test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
Figure 9
Knockdown of C08F11.7, ugt-62, and K05C4.9 decreases lifespan in multiple long-lived mutants.
(A) The expression of C08F11.7, ugt-62, and K05C4.9 is increased in group 1 longevity mutants, but either unchanged or decreased in group 2 and group 3 mutants. (B) Knockdown of C08F11.7, ugt-62, or K05C4.9 did not decrease the longevity of group 1 daf-2 mutants. (C) Knockdown of C08F11.7 or ugt-62 but not K05C4.9 decreased lifespan in group 2 eat-2 mutants. (D) Knockdown of C08F11.7, ugt-62, or K05C4.9 decreased the longevity of group 3 ife-2 mutants. 25 µM FUdR was used in the lifespan studies. Two biological replicates were performed. The total n for each group was as follows: daf-2 EV (87), daf-2 daf-16 RNAi (72), daf-2 C08F11.7 RNAi (95), daf-2 ugt-62 RNAi (87), daf-2 K05C4.9 RNAi (93), eat-2 EV (92), eat-2 daf-16 RNAi (95), eat-2 C08F11.7 RNAi (95), eat-2 ugt-62 RNAi (91), eat-2 K05C4.9 RNAi (76), ife-2 EV (92), ife-2 daf-16 RNAi (106), ife-2 C08F11.7 RNAi (81), ife-2 ugt-62 RNAi (56), and ife-2 K05C4.9 RNAi (64). Statistical significance was assessed using a one-way ANOVA with Dunnett’s multiple comparisons test in panel (A) and a log-rank test in panels (B–D).
Figure 10
Overexpression of individual genes that are differentially expressed in long-lived mutant strains can increase lifespan and resistance to stress.
(A) Overexpression (OE) of C08F11.7 significantly increased lifespan, while overexpression of ugt-62 (B) or K05C4.9 (C) decreased longevity. (D) Overexpression of C08F11.7 and ugt-62 combined increased lifespan to a greater extent than either gene alone. (E) Resistance to heat stress (35°C) was enhanced in worms overexpressing C08F11.7 or ugt-62. (F) C08F11.7 OE worms also showed enhanced resistance to bacterial pathogens (P. aeruginosa strain PA14). (G) Resistance to oxidative stress (4 mM paraquat) was increased in C07F11.7 OE and ugt-62 OE worms. There was no increase in resistance to osmotic stress (450 mM, 500 mM; H) or anoxia (72 hour; I) in any of the overexpression strains. Three biological replicates were performed for each lifespan study. The total number of animals per strain for lifespan studies was as follows: WT (159), C08F11.7 OE (130), ugt-62 OE (146), K05C4.9 OE (133), C08F11.7 OE; ugt-62 OE (173). Statistical significance was assessed with a log-rank test in panels (A–G) and a one-way ANOVA with Dunnett’s multiple comparisons test in panels (H) and (I). ***p<0.001. The full genotypes of the overexpression strains are: sybIs6868[rpl-28p::C08F11.7, myo-2p::mCherry], sybIs6945[rpl-2p::ugt-62, myo-3p::mCherry] and sybIs6925[eft-3p::K05C4.9, ges-1p::mCherry].
Additional files
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Supplementary file 1
Differentially expressed genes in each long-lived mutant strain.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp1-v1.xlsx
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Supplementary file 2
Overlapping differentially expressed genes with previous gene expression Studies.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp2-v1.xlsx
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Supplementary file 3
Genes correlated with lifespan.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp3-v1.xlsx
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Supplementary file 4
Genes modulated in opposite directions in Group 1 and Group 2 longevity mutants.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp4-v1.xlsx
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Supplementary file 5
Transcription factor analysis.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp5-v1.xlsx
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Supplementary file 6
Comparison to genes that are differenetially expressed during aging.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp6-v1.xlsx
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Supplementary file 7
Genes that are differentially expressed in multiple long-lived mutants.
- https://cdn.elifesciences.org/articles/112139/elife-112139-supp7-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/112139/elife-112139-mdarchecklist1-v1.docx
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Multiple molecular pathways to longevity with opposing gene expression programs defining distinct aging strategies in Caenorhabditis elegans
eLife 15:RP112139.
https://doi.org/10.7554/eLife.112139.3
