4 | Discussion
In this study, we found a significant correlation between age and methylation rate in the gene regions, GRIA2 and CDKN2Ausing a DNA extracted from a non-invasive fecal sample. Although sex was not affected by the correlation between age and methylation rate, the methylation rate decreased for the females in nursing states. We also succeeded in constructing an age estimation model using the methylation rates of both genes. This study is the first to report the use of multiple genes and DNA extracted from fecal samples to develop an age estimation model. We estimated the ages of 19 unknown-age individuals using our model (Table. S2). The error between the estimated age from our model and the assigned age based on the year of first birth or weaning exceeded the MAE after LOOCV was performed. On the other hand, only one of the five individuals (individual number: #068FA), had a high residual error, while the average error among the other four individuals was 6.37 years (range: 4.58–8.53), which is closer to the MAE after LOOCV. The reasons for the high estimation errors in the individual is unknown. However, considering that fecal sample collection was conducted underwater, it is plausible that feces from a different individual, outside the camera’s field of view might have been mistakenly collected. Indo-Pacific bottlenose dolphins are known to swim in groups of 20-50 individuals (Wang, 2018), which increases the likelihood of accidentally collecting fecal samples from a different individual. To enhance the accuracy of age estimation using this method, it is preferable to collect fecal samples multiple times from the same individual and estimate the age based on those replicated samples.
The age estimation model which exhibited the highest accuracy and precision were from the methylation rates of GRIA2 andCDKN2A (model 1), with an MAE of 5.08 years. This is 10–13% (percentage error) of the life span of a Indo-Pacific bottlenose dolphin which is 40–50 years (Wang, 2018) and it provides a sufficient level of accuracy for ecological and conservation studies. In a study focusing on Bechstein’s bats, a similar approach using multiple genes, includingGRIA2 from wing tissues, achieved an age estimation with a standard deviation of 1.52 years (Wright et al ., 2018). Assuming a lifespan of 20 years for this species, the error corresponds to 7.6% of the lifespan. In the case of blood samples of domestic cats, an age estimation error of 3.83 years has been reported (Qi et al ., 2021). Assuming a lifespan of 12 years for domestic cats, the error accounts for approximately 31.9% of its total lifespan. Notably, despite the use of fecal samples, which are associated with lower precision, the range of error to lifespan was comparable to studies conducted on other species. However, our model shows lower accuracy compared to other cetaceans using skin samples (humpback whale: MAE = 3.575, Polanowski et al ., 2014; common bottlenose dolphin: RMSE = 5.14, Beal et al ., 2019; fin whale: MAE = 4.264, García‐Vernetet al ., 2021). In contrast to previous studies that used pyrosequencing to measure methylation rates with DNA extracted from skin samples, we used MS-HRM with DNA extracted from fecal samples. The accuracy of MS-HRM was reported to be similar to that of pyrosequencing (Migheli et al ., 2013), thus, the differences in detection limits between the methods is not considered to be the cause of lower accuracy. However, pyrosequencing allows for the estimation of methylation rate at individual CpG sites, and only the most strongly correlated sites can be selected for the estimation model. MS-HRM quantifies the methylation rate within a certain range that encompasses multiple CpG sites. Depending on the target regions, it may include several CpG sites with varying degrees of correlation to age which can potentially lead to a decrease in accuracy. Previous studies have also reported variations in the correlation between methylation rates at individual CpG sites with age (e.g. GRIA2 : 0.48–0.75, CDKN2A : 0–0.44, Bealet al ., 2019). In addition, the fecal samples used in this study may also include not only the target dolphin’s DNA (Kita et al.,2017), but could also include DNA of intestinal bacteria (Suzukiet al., 2021), and prey species (Kita et al., 2018). The low concentration of the target DNA may have caused low estimation accuracy. As mentioned above, as samples were collected underwater, there is a risk of mixing feces from other individuals that have defecated nearby. In the future, when similar analyses are conducted using DNA extracted from fecal samples, it may be possible to solve this problem by using multiple replicated samples obtained from the same individual to then detect and discard samples with relatively high concentrations of target DNA or contamination from other individuals’ feces.
No significant sex differences were reported in the results of the age estimation model that included GRIA2 for the common bottlenose dolphins, which is closely related to our target species (Beal et al ., 2019). Similarly, we did not find significant sex differences between methylation rate and age in GRIA2 and CDKN2A(Table 3). Comparisons between the models also showed that the model which excluded sex as an explanatory variable, demonstrated the highest precision and accuracy. The results suggest that sex may not be necessary for age estimation. It has been reported that on average, females tended to have lower epigenetic age than males, and this association strengthened over the course of human life (Simpkin et al ., 2016). The sex differences in the rate of aging are consistent with higher mortality rates and shorter average life expectancy in males (Crimmins et al . 2019). The tendency for males to have a shorter lifespan is a common phenomenon observed in mammals (Lemaítre et al., 2020). In non-human mammals, a small number of species have reported sex differences between DNA methylation rate and age in the epigenetic clock (common bottlenose dolphin: Beal et al ., 2019; domestic cat: Qi et al ., 2021). While many other mammalian species have reported that there were no significant sex differences found (humpback whale: Polanowski et al ., 2014; fin whale: García-Varnet et al., 2020; beluga: Bors et al., 2021; brown bear: Nakamura et al ., 2023). Most of these studies often do not investigate sex differences in DNA methylation rates for each gene but rather examine the significance of sex as one of the explanatory variables in age estimation formulas that utilize multiple genes. As a result of formulating estimation models with multiple genes, the impact of sex may be concealed and overlooked. To address this issue, further research focusing on the relationship between sex differences and methylation rate for each gene is needed.
This is the first study to suggest the effect of female nursing states on methylation rate and age in GRIA2 , and CDKN2A .GRIA2 are family of receptors (Henley & Wilkinson, 2013), whileCDKN2A encodes for several tumor suppressor proteins (Foulkeset al ., 1997; Zhao et al ., 2016). From a functional perspective, it is difficult to consider the exact factors that could lead to the decrease in methylation rates during the calving period. However, a decrease in methylation could be associated with specific physiological changes that occur during suckling and other parenting- or calf-nursing-related activities. Although age-related changes in methylation rate decreased in females specifically, no significant sex differences were found overall. Therefore, it is possible that female methylation rates are adjusted after calving by unknown factors, and further studies examining the longitudinal variation in methylation rates of individuals are needed in the future. The female nursing states did not contribute to the precision and accuracy of the age estimation model. This may be due to the different regression methods employed. The ANCOVA was used to examine the sex differences in methylation rate changes with age for each gene based on the least squares method. This calculates the regression line by minimizing the distance from all data plots on the scatterplot. On the other hand, the SVR used in building the age estimation model in this study, is based on the maximum-margin principle, where the regression line is determined by maximizing the distance from the outer plots on the scatterplot. These conceptual differences between the regression methods suggest that an effect observed in one method may not be detectable in the other. It is recommended that future analyses of similar studies should take this effect into account.
Conventional age estimation has been based on counting the growth layers formed on the tooth cross section in odontocetes (see Perrin & Myrick, 1980). This method requires capturing of individuals to collect their teeth. In recent years, there have been attempts to develop an age estimation method using epigenetic clock analysis in various taxa (e.g. humans: Horvath, 2013; Bechstein’s bats: Wright et al ., 2018; Asian elephants (Elephas maximus ) & African elephants (Loxodonta africana ): Prado et al., 2020). All previous studies of epigenetic clock analysis on cetaceans have used skin samples, which require biopsy surveys or capture procedures to be conducted in the wild (Polanowski et al ., 2014; Beal et al ., 2019; Tanabe et al ., 2020; Bors et al ., 2021; Peterset al ., 2023). Biopsy surveys are generally considered less invasive compared to capture methods; however, it is worth noting that there have been instances of mortality, especially in small cetaceans (Bearzi, 2000; Noren & Mocklin, 2012). Our method allows for non-invasive age estimation as fecal samples were collected underwater, without touching and disrupting the dolphins. As stated by Qi et al., (2021), pyrosequencing is the gold standard method for quantifying DNA methylation rate. However, each analysis requires 3–4 hours for completion and costs $14, while MS-HRM offers a more cost-effective alternative, with each analysis requiring only two hours and costing $7. This cost-effectiveness, combined with the shorter turnaround time, makes the MS-HRM method highly suitable for implementation in various research sites.
The framework of this study can be extended to other cetacean species and populations where fecal samples can be collected. For instance, the Atlantic spotted dolphins (Stenella frontalis ) around the Bahamas and the dwarf minke whales (Balaenoptera acutorostratasubsp.) in Australia have conducted underwater identification surveys (see Herzing, 1997; Birtles et al., 2002). These populations have favorable conditions for collecting fecal samples. In addition, fecal samples of large cetaceans can be collected whilst being on board (see Smith & Whitehead, 2000; Reidy et al., 2022). Identification surveys on gray whales (Eschrichius robustus ), North Atlantic right whales (Eubalaena glacialis ), Southern right whales (E. australis ), sperm whales (Physeter macrocephalus ), blue whales (B. musculus ), and humpback whales have been conducted using natural marks such as color patterns and the shape of flukes (Hammond et al., 1990). Thus, it may be possible to introduce age estimation using fecal samples as well. Even in areas where long-term individual identification surveys have not been conducted by researchers, activities such as swim-with-dolphin programs, scuba diving, and wading in close proximity to observation targets have been developed in more than 11 genera of cetaceans, over 54 areas in 32 counties (Carzon et al., 2023). Therefore, there is potential for collaboration with the tourism industry in these areas, where fecal samples could be collected in conjunction with tourism activities. This synergy between research and tourism allows for the collection of fecal samples while visitors engage in educational and conservation efforts. Terrestrial mammals may get better results because hydrolysis is less likely to occur on land. If the fecal samples-based age estimation can be applicated to terrestrial animals, it may lead to benefits for both study species and researchers because fecal samples may be collected non-invasively even in species that are difficult and/or dangerous to encounter.
The successful quantification of methylation rates using fecal samples of Indo-Pacific bottlenose dolphins in this study, suggests the potential applications of age estimation using the same genes in other cetacean species. This study serves as a steppingstone towards the widespread application of non-invasive age estimation methods in various mammal species, offering valuable contributions towards the understanding of their ecology through age-related information.