Age estimation in fishes using epigenetic clocks: Applications to fisheries management and conservation biology

Abstract

The distribution of age classes is a key demographic parameter of populations and thus proper age estimation is crucial for fisheries management and for conservation biology. Age estimation in fishes has traditionally relied on the analysis of growth marks in hard structures such as otoliths. However, besides being lethal this method is time-consuming, can have low accuracy in some species and cannot be applied in others. Thus, there is a need for the development of new methods. DNA methylation is an epigenetic modification consisting in the addition of a methyl group in cytosine-guanine loci. Aging is associated with changes in DNA methylation. Among a background of global and weak genome hypomethylation, there are some loci in which age-associated DNA methylation changes are of a “clock-like” nature and thus predictable. Chronological age estimators built from DNA methylation are termed ‘epigenetic clocks’. Epigenetic clocks have been developed in the last ten years for many species, notably vertebrates, including already several fish species. Here, we review the piscine epigenetic clocks built so far and outline the major considerations to be taken into account for the development of new epigenetic clocks for additional species, which include the number of samples to be collected and tissues to be targeted. The steps on how to develop such a clock and the techniques available to do so are also discussed. Next, we focus on the features of epigenetic clocks as measuring devices, considering aspects such as accuracy, precision and reproducibility. Finally, we discuss the possibility of developing a multi-species piscine epigenetic clock and how processing automation can greatly reduce the cost per sample. One important knowledge gap is to determine how environmental changes, especially temperature and food availability, may affect the tick rate of piscine epigenetic clocks. Improved age prediction through the use of piscine epigenetic clocks can contribute to better fisheries management practices in a context of overexploited fish stocks worldwide, and in the estimation of age classes in endangered species.

DNA methylation markers of age(ing) in non‐model animals

“…Optimal sample size for calibration of epigenetic clocks estimated on the basis of simulations on human and zebra fish data revealed a minimum calibration population size of 70, but ideally, at least 134 samples are needed to infer accurate epigenetic clocks (Mayne et al, 2021). The same study also revealed that with larger sample sizes, the number of selected CpG sites per model also increased, which is in line with our findings (Figure 6), but not with the findings of a recent review on piscine epigenetic clocks (Piferrer & Anastasiadi, 2023). Possibly because of this positive association, in addition to more accurate estimates, it was found that a higher training sample size can significantly increase the accuracy of epigenetic clocks in humans (Bell et al, 2019; Zhang et al, 2019).…”

Bioinformatic analysis for age prediction using epigenetic clocks: Application to fisheries management and conservation biology

“…Oxford Nanopore Technology sequencing is expected to vary for the basic bioinformatics steps, however, the statistical analysis including machine learning model building will be essentially the same (section 3). The HTS methods used for epigenetic clocks in fish species until now include RRBS, bis-RAD-seq, MBS and BisPCR 2 (see Table 1, Piferrer and Anastasiadi, 2023).…”

“…The total number of samples should ensure covering the full age range of the species considered, and may vary between species in the extremes of lifespan. In the published literature of fish epigenetic clocks, the total number of samples range between 10 in Northern red snapper and red grouper (Weber et al, 2021) and 141 in Australian lungfish (Mayne et al, 2021b) with mean 46 samples (Piferrer and Anastasiadi, 2023). These numbers maybe suboptimal, since the minimum sample size according to simulations using human and zebrafish (Danio rerio) data is 70 (Mayne et al, 2021a).…”

“…Epigenetic clocks are considered valid if the correlation (R) is higher than 0.80 in large independent data covering a broad age range (Horvath and Raj, 2018). Piscine epigenetic clocks show a mean correlation of 0.93 (Piferrer and Anastasiadi, 2023), while higher values are also possible. reported as MAE is used with actual time units (days, months or years) and shows a mean of 0.87 years in piscine clocks, or an average of about 3.5% of the total lifespan (Piferrer and Anastasiadi, 2023).…”

“…To the best of our knowledge, epigenetic clocks have been developed for: European sea bass (Anastasiadi and Piferrer, 2020), zebrafish (Mayne et al, 2020), Australian lungfish (Mayne et al, 2021b), Mary river cod (Mayne et al, 2021b), Murray cod (Mayne et al, 2021b), medaka (Bertucci et al, 2021), northern red snapper (Weber et al, 2021) and red grouper (Weber et al, 2021). For details on piscine epigenetic clocks including accuracy, techniques, CpGs covered and biological aspects to consider for new clocks please see Piferrer and Anastasiadi (2023). However, a crucial aspect for epigenetic clock development is how DNA methylation data is actually used to build the age predictor.…”