A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus) and Panthera species, using targeted bisulphite sequencing and machine learning models.

Individual age can be used to design more efficient and suitable management plans in both in situ and ex situ conservation programmes for targeted wildlife species. DNA methylation is a promising marker of epigenetic ageing that can accurately estimate age from small amounts of biological material, which can be collected in a minimally invasive manner. In this study, we sequenced five targeted genetic regions and used 8-23 selected CpG sites to build age estimation models using machine learning methods at only about $3-7 per sample. Blood samples of seven Felidae species were used, ranging from small to big, and domestic to endangered species: domestic cats (Felis catus, 139 samples), Tsushima leopard cats (Prionailurus bengalensis euptilurus, 84 samples) and five Panthera species (96 samples). The models achieved satisfactory accuracy, with the mean absolute error of the most accurate models recorded at 1.966, 1.348 and 1.552 years in domestic cats, Tsushima leopard cats and Panthera spp. respectively. We developed the models in domestic cats and Tsushima leopard cats, which were applicable to individuals regardless of health conditions; therefore, these models are applicable to samples collected from individuals with diverse characteristics, which is often the case in conservation. We also showed the possibility of developing universal age estimation models for the five Panthera spp. using only two of the five genetic regions. We do not recommend building a common age estimation model for all the target species using our markers, because of the degraded performance of models that included all species.

Metabarcoding analysis provides insight into the link between prey and plant intake in a large alpine cat carnivore, the snow leopard.

Species of the family Felidae are thought to be obligate carnivores. However, detection of plants in their faeces raises questions about the role of plants in their diet. This is particularly true for the snow leopard (Panthera uncia). Our study aimed to comprehensively identify the prey and plants consumed by snow leopards. We applied DNA metabarcoding methods on 90 faecal samples of snow leopards collected in Kyrgyzstan, employing one vertebrate and four plant markers. We found that argali (Ovis ammon) was detected only from male snow leopards. Myricaraia sp. was the most consumed among 77 plant operational taxonomic units found in snow leopard samples. It frequently appeared in samples lacking any prey animal DNA, indicating that snow leopards might have consumed this plant especially when their digestive tracts were empty. We also observed differences in the patterns of plant consumption between male and female snow leopards. Our comprehensive overview of prey and plants detected in the faeces of snow leopards and other sympatric mammals will help in formulating hypotheses and guiding future research to understand the adaptive significance of plant-eating behaviour in felids. This knowledge supports the enhancement of their captive environments and the conservation planning of their natural habitats.