Li Jinghui, Zhao Tianjing, Guan Dailu, Pan Zhangyuan, Bai Zhonghao, Teng Jinyan, Zhang Zhe, Zheng Zhili, Zeng Jian, Zhou Huaijun, Fang Lingzhao, Cheng Hao
Department of Animal Science, University of California, Davis, Davis, CA 95616, USA.
Center for Quantitative Genetics and Genomics (QGG), Aarhus University, 8000 Aarhus, Denmark.
Cell Genom. 2023 Aug 24;3(10):100390. doi: 10.1016/j.xgen.2023.100390. eCollection 2023 Oct 11.
Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.
在功能水平上评估人类和猪之间的基因组保守性可以提高猪作为人类生物医学模型的潜力。为了解决这个问题,我们开发了一种基于深度学习的方法,通过分别整合来自人类和猪的386个和374个功能图谱,来学习物种间功能水平上的基因组保守性(DeepGCF)。与之前的方法相比,DeepGCF表现出了更好的预测性能。此外,通过检查染色质状态、序列本体和调控变异,得到的DeepGCF分数捕捉了人类和猪之间的功能保守性。我们确定了一组核心基因组区域在功能上是保守的,这些区域在基因调控中起关键作用,并且在人类复杂性状和疾病的遗传力中富集。我们的结果强调了跨物种功能比较在阐明复杂表型的遗传和进化基础方面的重要性。