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Age-associated changes in the skin transcriptome in Naked mole-rats

ABSTRACT: Age-associated changes in the skin transcriptome in Naked mole-rats

PROVIDER: PRJNA826455 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR18742787_1.fastq.gz	Fastqsanger.gz
	SRR18742787_2.fastq.gz	Fastqsanger.gz
	SRR18742788_1.fastq.gz	Fastqsanger.gz
	SRR18742788_2.fastq.gz	Fastqsanger.gz

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Project description:The naked mole-rat, Heterocephalus glaber (NMR), the longest-lived rodent with a maximum possible lifespan exceeding 33 years, is emerging as an important non-model organism for the study of longevity and healthspan. As such it is of significance and interest in the study of biomarkers for ageing in mammals. Recent breakthroughs in this field have indicated that ‘epigenetic clocks’ based on the temporal accumulation of DNA methylation at specific genomic sites can enable accurate age estimates for tissues across the lifespan of an individual. Here, we validate the hypothesis of an epigenetic clock in NMRs, and create a method for predicting the age of naked mole-rats based on changes in methylation of targeted CpG sites in regions known as ageing-associated differentially methylated positions (aDMPs). In the discovery phase, we performed a targeted analysis of 51 different CpGs in 24 different NMR livers spanning an age range from 39 weeks to 1,144 weeks. Of these 51 different sites, 23 were found to be significantly associated with age (p < 0.05). We then built a predictor of age using the 23 sites that showed an association with age. To test the accuracy of this model, we predicted age in an additional test set of 19 different livers spanning an age range 43 to 1,196 weeks. Our model was able to successfully predict age in the test with a root mean squared error (RMSE) of 166.11 weeks. We also profiled a 20 skin samples with the same age range and found a striking correlation between the predicted age of these samples versus their actual age (R=0.93). However, this correlation when compared to the liver samples showed a lower predicted age than actual age, suggesting that skin tissue ages slower than the liver in NMRs. Finally, we have produced freely available software tool that will take in raw sequencing data and produce an age prediction for new NMR samples. Our model will enable the prediction of age in wild caught naked mole-rats and captive animals of unknown age, and will be invaluable for further mechanistic studies of mammalian ageing.

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Age-associated changes in the skin transcriptome in Naked mole-rats

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