1 | Introduction
Life history is a crucial factor that determines the ecology of animal species, and each species exhibits a specific life history strategy. Growth stages can be roughly classified based on life history traits such as the timing of weaning, maturation, and lifespan. However, the allocation of resources towards growth, survival, and future reproduction varies among species (Williams, 1966), and each species has a different duration for each life stage (e.g. in female Indo-Pacific bottlenose dolphins (Tursiops aduncus ): calf (pre-weaning): 0–3.5 years, subadult (immature): 3.5–10.3 years, adult (after first parturition): 10.3–50 years, Kogi et al ., 2004; Kogi, 2013; Wang, 2018). There have been reports on age-related cessation of reproductive ability (e.g. post reproductive lifespan in humans (Homo sapiens ): Levitis & Bingham, 2011; killer whales (Orcinus orca ): Croft et al ., 2015; Franks et al ., 2016, belugas (Delphinapterus leucas ): Ellis et al ., 2018), and age-related changes in sociality (red deers (Cervus elaphus ): Albery et al ., 2020). These reports provide evidence of the changes in resource allocation occurring after maturity, indicating that information on age is necessary to clarify the life history of a species, rather than growth stage.
However, longitudinal observation is expensive and time-consuming, especially for long-lived animals like the Indo-Pacific bottlenose dolphins which can live about 50 years (Wang, 2018). Therefore, age estimation methods are essential to efficiently investigate the age structure of a specific population.
A commonly used method for age estimation in toothed whales (odontocetes) is counting dental growth layer groups (GLGs) (see Perrin and Myrick, 1980). This method requires capturing of individuals to collect dental samples. The invasive nature of measuring dental GLGs, makes it unsuitable for small or threatened populations. It is also difficult to estimate age using dental GLGs for populations living in offshore areas where capture can be difficult and for populations that are targeted for tourism. Thus, methods of non-invasive age estimation for toothed whales has developed recently. One is the method using age-related external appearance changes on the body, including scars and body cololations (e.g. risso’s dolphins (Grampus griseus ): Hartman et al., 2015; Indo-Pacific humpback dolphins (Sousa chinensis ): Guo et al ., 2020). Krzyszczyk & Mann (2012) and Yagi et al . (2022) described the age-related changes to the speckle appearance patterns on the Indo-Pacific bottlenose dolphins in Shark Bay, Australia, and Mikura Island, Japan respectively. Yagiet al. (2023) developed a speckle-based age estimation model that showed high accuracy (R2 = 0.77, standard deviation (SD) = 2.58). However, the model is only limited to estimating the ages between 7.68–21 years due to the spots appearing age and the upper limit of the age-known individuals.
Aging occurs in many organisms and it leads to various changes at the tissue and cellular levels (Petralia et al ., 2014). Although aging is thought to be caused by the combined effects of various factors (López-Otin et al. , 2013), one of the factors that regulates aging are epigenetic changes which are dysfunctional systems that accompany aging at the gene level (Booth & Brunet, 2016). DNA methylation is an example of an epigenetic changes, in which DNA methylation rates at CpG sites (cytosine-phosphate-guanine) in specific gene regions changes with age. Recently, the correlation between DNA methylation rate and aging has been used to develop an age estimation method, known as the epigenetic clock. This method was initially developed for humans (Horvath, 2013) and has since been applied to several species (e.g. Bechstein’s bats (Myotis bechsteinii ): Wright et al., 2018; domestic cats (Felis catus ) & snow leopards (Panthera uncia ): Qi et al ., 2021; brown bears (Ursus arctos ): Nakamura et al ., 2023). In cetaceans, Polanowski et al . (2014) was the first to report the application of DNA extracted from skin samples in humpback whales (Megaptera novaeangliae ). Following this pioneering study, similar approaches have been successfully applied to other cetacean species (belugas: Borset al. , 2020; Antarctic minke whales (Balaenoptera bonaerensis ): Tanabe et al ., 2020; common bottlenose dolphins (T. truncatus ): Beal et al ., 2019; Indo-Pacific bottlenose dolphins: Peters et al ., 2022). Capture methods from research whaling, commercial whaling and hunting are extremely invasive. These previous studies on cetaceans using epigenetic clock analyses relied on the samples obtained from invasive methods including commercial whaling (fin whales (B. physalus ): García‐Vernet et al ., 2021), whale research program (Antarctic minke whales: Tanabe et al ., 2020), capture and release of wild individuals (common bottlenose dolphins: Beal et al., 2019), stranded carcasses (belugas: Borset al ., 2021), and the use of rifles and crossbows for biopsy (humpback whales: Polanowski et al ., 2014; belugas: Bors et al ., 2021; Indo-Pacific bottlenose dolphins: Peters et al ., 2022). Although biopsy procedures are less invasive compared to capture methods including whaling and hunting, it remains at a certain level of invasiveness, particularly for small cetacean species where instances of mortality have been reported (Weller et al ., 1997; Bearzi, 2000; Noren & Mocklin, 2012). By using fecal samples, DNA can be collected non-invasively without the need to touch individuals. However, there is a limited number of studies based on fecal-sampled epigenetic clocks. To our knowledge, the only studies to have developed epigenetic clocks using fecal samples are from Nakano et al . (2019, 2020) which reported a significant correlation between the methylation rate ofELOVL2 (Elongation of very long chain fatty acids protein 2) and age in chimpanzees (Pan troglodytes ) and Japanese macaques (Macaca fuscata ).
To examine the correlation between methylation rate and age, fecal samples from age-known individuals are required. At our research field, coastal water off Mikura Island located approximately 200 km south of Tokyo, Japan, around 160 Indo-Pacific bottlenose dolphins were living year-round (Kakuda et al ., 2002; Kogi et al ., 2004). Since 1994, longitudinal individual identification surveys using underwater video data have been conducted around this island (Kogi et al ., 2004). These underwater surveys allow tracking the actual ages of individuals born after 1994 and collection of fecal samples from individuals, making the population well-suited for fecal sample-based age estimation studies.
Here, we investigated the correlation between DNA methylation rate and age in fecal samples using a low-cost and convenient method called methylation-sensitive high-resolution melting (MS-HRM) analysis (Wojdacz & Dobrovic, 2007; Wojdacz et al ., 2008; Tse et al ., 2011). We focused on the genes TET2 (ten eleven translocation 2),GRIA2 (glutamate receptor Ia2/AMPA2), and CDKN2A (cyclin dependent kinase inhibitor 2A), which reported a correlation between age and methylation rate in skin samples of a closely related species, the common bottlenose dolphins (Beal et al., 2019). Furthermore, we developed an age estimation model using the methylation rates of these genes. We also assessed the effects of biological factors (sex differences and female nursing states) on methylation rate because in humans, various stressors are known to affect the epigenetic clock (e.g. Lawn et al ., 2018, Marini et al ., 2020) such as increased frequency of pregnancy causes acceleration in epigenetic age (Ryanet al., 2018). This study aimed to develop a non-invasive age estimation model using DNA extracted from fecal samples ahead of other mammals and to contribute to ecological and conservation studies.