GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model
Authors: Yang Xiaodong , Liu Guole , Feng Guihai , Bu Dechao , Wang Pengfei , Jiang Jie , Chen Shubai , Yang Qinmeng , Miao Hefan , Zhang Yiyang , Man Zhenpeng , Liang Zhongming , Wang Zichen , Li Yaning , Li Zheng , Liu Yana , Tian Yao , Liu Wenhao , Li Cong , Li Ao , Dong Jingxi , Hu Zhilong , Fang Chen , Cui Lina , Deng Zixu , Jiang Haiping , Cui Wentao , Zhang Jiahao , Yang Zhaohui , Li Handong , He Xingjian , Zhong Liqun , Zhou Jiaheng , Wang Zijian , Long Qingqing , Xu Ping ,   The X-Compass Consortium, Li Xin , Wang Hongmei , Hu Baoyang , Li Wei , Gao Fei , Guo Jingtao , Yu Leqian , Gu Qi , Zhai Weiwei , Zou Zhengting , Feng Guihai , Liu Wenhao , Tian Yao , Fang Chen , Dong Jingxi , Liu Yana , Yu Jingqi , Wu Wenhui , Lin Xinxin , Li Cong , Zou Yu , Ren Yongshun , Li Fan , Zhao Yixiao , Xin Yike , Han Longfei , Jiang Shuyang , Ma Kai , Chen Qicheng , Wang Haoyuan , Wu Huanhuan , He Chaofan , Hu Yilong , Guo Shuyu , Li Yiyun , Zhou Yuanchun , Wang Yangang , Wang Xuezhi , Wang Pengfei , Li Fei , Meng Zhen , Wang Zaitian , Xu Ping , Cui Wentao , Hu Zhilong , He Huimin , Zong Shan , Wang Jiajia , Chen Yan , Zhang Chunyang , Wang Chengrui , Zhang Ran , Xiao Meng , Wang Yining , Chen Yiqiang , Zhao Yi , Yang Xiaodong , Bu Dechao , Qin Xin , Qin Jiaxin , Yang Zhaohui , Li Chenhao , Xu Zhufeng , Zhang Zeyuan , Qi Xiaoning , Chen Shubai , Huang Wuliang , Li Yaning , Yang Ge , Liu Jing , Liu Guole , Zhong Liqun , Luo Yaoru , Zhou Jiaheng , Wang Zichen , Luo Qinxuan , Liu Ziwen , Li Ao , Wang Teng , Huang Yiming , Li Handong , Wang Yong , Zhang Shihua , Zhang Jiahao , Zhang Yiyang , Li Shirui , Liang Zhongming , Man Zhenpeng , Dong Kangning , Shen Qunlun , Wang Hongmei , Meng Zhen , Wang Xuezhi , Wang Yangang , Wang Yong , Zhang Shihua , Guo Jingtao , Zhao Yi , Zhou Yuanchun , Li Fei , Liu Jing , Chen Yiqiang , Yang Ge , Li Xin 
Published: October 2024

Deciphering universal gene regulatory mechanisms in diverse organisms holds great potential for advancing our knowledge of fundamental life processes and facilitating clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms and does not integrate various cell types across species. Recent breakthroughs in single-cell sequencing and deep learning techniques present an unprecedented opportunity to address this challenge. In this study, we built an extensive dataset of over 120 million human and mouse single-cell transcriptomes. After data preprocessing, we obtained 101,768,420 single-cell transcriptomes and developed a knowledge-informed cross-species foundation model, named GeneCompass. During pre-training, GeneCompass effectively integrated four types of prior biological knowledge to enhance our understanding of gene regulatory mechanisms in a self-supervised manner. By fine-tuning for multiple downstream tasks, GeneCompass outperformed state-of-the-art models in diverse applications for a single species and unlocked new realms of cross-species biological investigations. We also employed GeneCompass to search for key factors associated with cell fate transition and showed that the predicted candidate genes could successfully induce the differentiation of human embryonic stem cells into the gonadal fate. Overall, GeneCompass demonstrates the advantages of using artificial intelligence technology to decipher universal gene regulatory mechanisms and shows tremendous potential for accelerating the discovery of critical cell fate regulators and candidate drug targets.