MeHA: A Computational Framework in Revealing the Genetic Basis of Animal Mental Health Traits Under an Intensive Farming System—A Case Study in Pigs - Jinyun Jiang; Lingyao Xu; Yizheng Zhuang; Xingyu Wei; Zhenyang Zhang; Wei Zhao; Qingyu Wang; Xiaowei Ye; Jiamin Gu; Caiyun Cao; Jiabao Sun; Kan He; et al. (Biology)
Intensively farmed animals such as pigs inevitably experience a certain degree of psychological stress, which leads to a reduction in production performance. Mental health traits are currently difficult to measure, resulting in a gap in understanding their genetic basis. To address this challenge, we propose a computational framework called mental health of animals (MeHA), capable of revealing genes related to animal mental health traits. Using MeHA, we identified 109 candidate genes associated with pig mental health and discovered their intricate connections with critical functions, such as memory, cognition, and neural development, which are essential components of mental health and cognitive performance. Importantly, our findings provide evidence of the potential impact of these genes on economically important traits, including meat quality and piglet survival. This research underscores the importance of genetic studies in enhancing our understanding of animal behavior and cognition, as well as promoting agricultural practices. By applying our approach to study the genetic basis of mental health in pigs as a case, we confirmed that our framework is an effective way to reveal genetic factors affecting animal mental health traits, which contributes to animal welfare and has potential implications for understanding human mental disorders.