Volume 34, No 12, Dec 2024

ISSN: 1001-0602 
EISSN: 1748-7838 2018 
impact factor 17.848* 
(Clarivate Analytics, 2019)

Volume 34 Issue 12, December 2024: 830-845   |  Open Access

ORIGINAL ARTICLES

GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model

Xiaodong Yang^1,2,3,† , Guole Liu^4,5,† , Guihai Feng^1,6,7,† , Dechao Bu^2,3,8,† , Pengfei Wang^3,9,† , Jie Jiang^10,† , Shubai Chen^2,3,† , Qinmeng Yang^9,† , Hefan Miao^1,3 , Yiyang Zhang^3,11 , Zhenpeng Man^3,11 , Zhongming Liang^3,11 , Zichen Wang^4,5 , Yaning Li^2,3 , Zheng Li⁹ , Yana Liu¹ , Yao Tian^1,3 , Wenhao Liu¹ , Cong Li^1,3 , Ao Li^4,5 , Jingxi Dong¹ , Zhilong Hu^3,9 , Chen Fang^1,3 , Lina Cui^1,3 , Zixu Deng^2,3 , Haiping Jiang^1,3 , Wentao Cui^3,9 , Jiahao Zhang^3,11 , Zhaohui Yang^2,3,8 , Handong Li^5,10 , Xingjian He¹⁰ , Liqun Zhong^4,5 , Jiaheng Zhou^4,5 , Zijian Wang⁹ , Qingqing Long⁹ , Ping Xu^3,9 , The X-Compass Consortium¹³ , Hongmei Wang^1,6,7 , Zhen Meng^3,9 , Xuezhi Wang^3,9 , Yangang Wang^3,9 , Yong Wang^3,11 , Shihua Zhang^3,11 , Jingtao Guo^1,3,6,7 , Yi Zhao^2,3,8,* , Yuanchun Zhou^3,9,* , Fei Li^3,9,* , Jing Liu^5,10,* , Yiqiang Chen^2,3 , Ge Yang^4,5 , Xin Li^1,3,6,7,*

¹State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
²Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
³University of Chinese Academy of Sciences, Beijing, China
⁴State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
⁵School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
⁶Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, China
⁷Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
⁸Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
⁹Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
¹⁰Institute of Automation, Chinese Academy of Sciences, Beijing, China
¹¹CEMS, NCMIS, HCMS, MDIS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
^†These authors contributed equally: Xiaodong Yang, Guole Liu, Guihai Feng, Dechao Bu, Pengfei Wang, Jie Jiang, Shubai Chen, Qinmeng Yang
¹³A list of authors and their affiliations appears at the end of the paper
Correspondence: Yi Zhao(biozy@ict.ac.cn)Yuanchun Zhou(zyc@cnic.cn)Fei Li(lifei@cnic.cn)Jing Liu(jliu@nlpr.ia.ac.cn)Xin Li(xinli@ioz.ac.cn)

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.

https://doi.org/10.1038/s41422-024-01034-y

FULL TEXT | PDF

Browse 365