Methylation clocks for age estimation in toothed whales and dolphins
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ABSTRACT:
PROVIDER: PRJNA725202 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:An Infinium microarray platform (GPL28271, HorvathMammalMethylChip40) was used to generate DNA methylation data from several tissues (skin, blood) in toothed whales and dolphins. Tissues: skin and blood.
2021-04-27 | GSE173330 | GEO
Project description:DNA methylation clocks as a predictor for ageing and age estimation in naked mole-rats, Heterocephalus glaber
| PRJNA573950 | ENA
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.
2020-04-07 | GSE137957 | GEO
Project description:Age is a key demographic in conservation biology where individual age classes show diffuse differences in terms of important population dynamics metrics such as morbidity and mortality. Furthermore, several traits including reproductive potential show clear senescence with aging. Thus, the ability to estimate the ages for the individuals of a population as part of age class assignment is critical in understanding both the current population structure as well as in modelling and predicting the future survival of species. This study explored the utility of age-related changes in methylation for six candidate genes, EDARADD, ELOVL2, FHL2, GRIA2, ITGA2B, and PENK, to create an age estimation model in captive cheetah. Gene orthologues between humans and cheetah were retrieved from NCBI containing a hundred CpG’s. Target regions were assayed for differential methylation and fragmentation patterns in fifty samples using mass array technology for a total of seventy-seven CpG clusters. Correlation analyses between CpG methylation and chronological age identified six CpG’s with an age relationship, of which four were hypomethylated and two were hypermethylated. Regression models, fitted for different combinations of CpG’s, indicated that age models using four and six CpG’s were most accurate, with the six CpG model having superior correlation and predictive power (R2 = 0.70, Mean Absolute Error = 25 months). This model was more accurate than previous attempts using methylation sensitive Polymerase Chain Reaction and performed similarly to models created using a candidate gene approach in several other mammal species, making methylation a promising tool of age estimation in cheetah.
2024-01-14 | GSE252541 | GEO
Project description:We assessed DNA methylation in whole blood samples from an Australian population across different age groups. Our study focused on evaluating the accuracy of DNA methylation age estimation using the Horvath 2018 and PhenoAge clocks. Additionally, we examined previously reported functional measures of aging in peripheral blood mononuclear cells (PBMCs). Our findings indicated that DNA methylation age effectively predicted donor age, while only a limited number of tested cell functions showed correlations with donor age.
2023-09-15 | GSE235717 | GEO
Project description:DNA methylation is a reaction that results in the formation of 5-methylcytosine when a methyl group is added to the cytosine’s C5 position. As organisms age, DNA methylation patterns change in a reproducible fashion. This phenomenon has established DNA methylation as a valuable biomarker in aging studies. Epigenetic clocks based on weighted combinations of methylation sites have been developed to accurately predict the age of an individual from their methylome. However, many epigenetic clocks, particularly those that utilize penalized regression, model the changes in methylation linearly with age. Moreover, these models, which use methylation levels as features, are not robust to missing data and do not account for the count-based nature of bisulfite sequence data. Additionally, the models are generally not interpretable. To overcome these challenges, we present BayesAge, an extension of the previously developed scAge approach that was developed for the analysis of single cell DNA methylation datasets. BayesAge utilizes maximum likelihood estimation (MLE) to infer ages, models count data using binomial distributions, and uses LOWESS smoothing to capture the non-linear dynamics between methylation and age. Our approach is designed for use with bulk bisulfite sequencing datasets. BayesAge outperforms scAge in several respects. Specifically, BayesAge’s age residuals are not age associated, thus providing a less biased representation of epigenetic age variation across populations. Moreover, BayesAge enables the estimation of error bounds on age inference and, when run on downsampled data, its coefficient of determination between predicted and actual ages surpasses both scAge and penalized regression.
2024-03-20 | GSE261769 | GEO
Project description:The development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.
| S-EPMC8167141 | biostudies-literature
Project description:Transcriptomics analysis of fats of toothed whales
| PRJDB11720 | ENA
Project description:The naked mole-rat, Heterocephalus glaber (NMR), the longest-lived rodent, is of significance and interest in the study of biomarkers for ageing. Recent breakthroughs in this field have revealed 'epigenetic clocks' that are based on the temporal accumulation of DNA methylation at specific genomic sites. Here, we validate the hypothesis of an epigenetic clock in NMRs based on changes in methylation of targeted CpG sites. We initially analysed 51 CpGs in NMR livers spanning an age range of 39-1,144 weeks and found 23 to be significantly associated with age (p<0.05). We then built a predictor of age using these sites. To test the accuracy of this model, we analysed an additional set of liver samples, and were successfully able to predict their age with a root mean squared error of 166 weeks. We also profiled skin samples with the same age range, finding a striking correlation between their predicted age versus their actual age (R=0.93), but which was lower when compared to the liver, suggesting that skin ages slower than the liver in NMRs. Our model will enable the prediction of age in wild-caught and captive NMRs of unknown age, and will be invaluable for further mechanistic studies of mammalian ageing.
| S-EPMC7093186 | biostudies-literature
Project description:<p>The age estimation of bloodstains measures the time-dependent changes in the levels of bloodstain biomolecules. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none has consider gender and age-related metabolomic differences or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 d and validate them through the MRM technique. Interestingly, adenosine 5′-monophosphate (5′-AMP), choline and pyroglutamic acid were selected as markers. We validated a total of 7 metabolites, including 5 previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan and pyroglutamic acid. Choline and hypoxanthine might be used to differentiate between day 0 and day 14 at weekly intervals, while L-isoleucine and L-tryptophan might help distinguish between 7 d before and 14 d after. Evaluation of the changes in the levels of metabolites according to gender and age, revealed that the average level of all 7 metabolites was higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in the elderly than the youth under all time conditions. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers, and provided a new perspective on metabolomic approaches linked to forensic science.</p>
2024-01-16 | MTBLS5208 | MetaboLights