{"title":"MeHA:揭示集约化养殖系统下动物心理健康特征遗传基础的计算框架--猪的案例研究。","authors":"Jinyun Jiang, Lingyao Xu, Yizheng Zhuang, Xingyu Wei, Zhenyang Zhang, Wei Zhao, Qingyu Wang, Xiaowei Ye, Jiamin Gu, Caiyun Cao, Jiabao Sun, Kan He, Zhe Zhang, Qishan Wang, Yuchun Pan, Zhen Wang","doi":"10.3390/biology13100843","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":48624,"journal":{"name":"Biology-Basel","volume":"13 10","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11504952/pdf/","citationCount":"0","resultStr":"{\"title\":\"MeHA: A Computational Framework in Revealing the Genetic Basis of Animal Mental Health Traits Under an Intensive Farming System-A Case Study in Pigs.\",\"authors\":\"Jinyun Jiang, Lingyao Xu, Yizheng Zhuang, Xingyu Wei, Zhenyang Zhang, Wei Zhao, Qingyu Wang, Xiaowei Ye, Jiamin Gu, Caiyun Cao, Jiabao Sun, Kan He, Zhe Zhang, Qishan Wang, Yuchun Pan, Zhen Wang\",\"doi\":\"10.3390/biology13100843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":48624,\"journal\":{\"name\":\"Biology-Basel\",\"volume\":\"13 10\",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11504952/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biology-Basel\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3390/biology13100843\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biology-Basel","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/biology13100843","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
MeHA: A Computational Framework in Revealing the Genetic Basis of Animal Mental Health Traits Under an Intensive Farming System-A Case Study in Pigs.
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.
期刊介绍:
Biology (ISSN 2079-7737) is an international, peer-reviewed, quick-refereeing open access journal of Biological Science published by MDPI online. It publishes reviews, research papers and communications in all areas of biology and at the interface of related disciplines. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files regarding the full details of the experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.