A whole lifespan mouse multi-tissue DNA methylation clock
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ABSTRACT:
PROVIDER: PRJNA495834 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8032930_1.fastq.gz | Fastqsanger.gz | |||
| SRR8032930_2.fastq.gz | Fastqsanger.gz | |||
| SRR8032940_1.fastq.gz | Fastqsanger.gz | |||
| SRR8032940_2.fastq.gz | Fastqsanger.gz | |||
| SRR8032950_1.fastq.gz | Fastqsanger.gz |
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Project description:Age predictors based on DNA methylation levels at a small set of CpG sites, DNAm clocks, have been developed for humans and extended to several other species. Three currently available versions of mouse DNAm clocks were either created for individual tissues or tuned towards young ages. Here, we constructed a robust multi-tissue age predictor based on 435 CpG sites, which covers the entire mouse lifespan and remains unbiased with respect to any particular age group. It can successfully detect the effects of several lifespan-modulating interventions on biological age as well as the rejuvenation effect related to the transition from fibroblasts to iPSCs. We have carried out comparative analyses of available mouse DNAm clocks, which revealed their broad applicability, but also certain limitations to the use of tissue-specific and multi-tissue age predictors. Together, these tools should help address diverse questions in aging research.
2018-11-20 | GSE121141 | GEO
Project description:Age predictors based on DNA methylation levels at a small set of CpG sites, DNAm clocks, have been developed for humans and extended to several other species. Three currently available versions of mouse DNAm clocks were either created for individual tissues or tuned toward young ages. Here, we constructed a robust multi-tissue age predictor based on 435 CpG sites, which covers the entire mouse lifespan and remains unbiased with respect to any particular age group. It can successfully detect the effects of certain lifespan-modulating interventions on DNAm age as well as the rejuvenation effect related to the transition from fibroblasts to iPSCs. We have carried out comparative analyses of available mouse DNAm clocks, which revealed their broad applicability, but also certain limitations to the use of tissue-specific and multi-tissue age predictors. Together, these tools should help address diverse questions in aging research.
| S-EPMC6287945 | biostudies-literature
Project description:A multi-tissue full lifespan epigenetic clock for mice
| PRJNA491717 | ENA
Project description:A multi-tissue full lifespan epigenetic clock for mice [I]
| PRJNA491712 | ENA
Project description:Background: DNA-methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing programme. It has also not been shown whether this ‘epigenetic clock’ is unique to humans or conserved in other animals such as the experimentally tractable mouse. Results: We have generated a comprehensive set of whole genome base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. A large number of CpG sites show significant tissue independent correlations with age and allowed us to develop a multi-tissue predictor of age in the mouse (‘mouse epigenetic clock’). The predictor, which estimates age based on DNA methylation at 644 unique CpG sites, is highly accurate (mean absolute error of 4.09 weeks) and has similar properties to the recently described human epigenetic clock. Using publicly available datasets from various biological manipulations in mice, we found that the mouse clock also measures biological age. While females and males showed no significant differences in predicted DNA methylation age, ovariectomy resulted in significant age acceleration in females. Furthermore we found significant differences in age-acceleration dependent on the lipid content of the maternal or offspring diet. Conclusions: Here we identify and characterise a highly accurate epigenetic predictor of age in mice, the ‘mouse epigenetic clock’. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ‘ticking’ rate and resetting the clock in vivo to study the impact on biological age.
2017-03-28 | GSE93957 | GEO
Project description:Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.
2018-11-29 | GSE120136 | GEO
Project description:Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.
2018-11-29 | GSE120132 | GEO
Project description:Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.
| S-EPMC6224226 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-11-29 | GSE120137 | GEO
Project description:Here, we analyzed 76 ecologically diverse wild yeast isolates and discovered a wide diversity of replicative lifespan. Phylogenetic analyses pointed to genes and environmental factors that strongly interact to modulate the observed aging patterns. We then identified genetic networks causally associated with natural variation in replicative lifespan across wild yeast isolates, as well as genes, metabolites and pathways, many of which have never been associated with yeast lifespan in laboratory settings. In addition, a combined analysis of lifespan-associated metabolic and transcriptomic changes revealed unique adaptations to interconnected amino acid biosynthesis, glutamate metabolism and mitochondrial function in long-lived strains. Overall, our multi-omic and lifespan analyses across diverse isolates of the same species shows how gene-environment interactions shape cellular processes involved in phenotypic variation such as lifespan.
2021-11-07 | GSE188294 | GEO