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PreprintCited by 148Single-cell and spatial transcriptomicsGene Regulatory Network AnalysisGenomics and Chromatin Dynamics

The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.

GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with Knowledge-Informed Cross-Species Foundation Model

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Yang, Xiaodong, Liu, Guole, Feng, Guihai, Bu, Dechao, Wang, Pengfei, Jiang, Jie, Chen, Shubai, Yang, Qinmeng, Zhang, Yiyang, Man, Zhenpeng, Liang, Zhongming, Wang, Zichen, Li, Yaning, Li, Zheng, Liu, Yana, Tian, Yao, Li, Ao, Dong, Jingxi, Hu, Zhilong, Fang, Chen, Miao, Hefan, 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, 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·2023·Cell Research
DOI 10.1101/2023.09.26.559542PMC PMC11615217

Preprint — published as 10.1038/s41422-024-01034-y · Paper page

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Abstract

Deciphering the universal gene regulatory mechanisms in diverse organisms holds great potential to advance our knowledge of fundamental life process and facilitate research on clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms, resulting in limited collection and integration of complex features on various cell types across species. Recent breakthroughs in single-cell sequencing and advancements in deep learning techniques present an unprecedented opportunity to tackle this challenge. In this study, we developed GeneCompass, the first knowledge-informed, cross-species foundation model pre-trained on an extensive dataset of over 120 million single-cell transcriptomes from human and mouse. During pre-training, GeneCompass effectively integrates four types of biological prior knowledge to enhance the understanding of gene regulatory mechanisms in a self-supervised manner. Fine-tuning towards multiple downstream tasks, GeneCompass outperforms competing state-of-the-art models in multiple tasks on single species and unlocks new realms of cross-species biological investigation. Overall, GeneCompass marks a milestone in advancing knowledge of universal gene regulatory mechanisms and accelerating the discovery of key cell fate regulators and candidate targets for drug development.

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  1. 10.1126/SCIENCE.ABL4896/SUPPL_FILE/SCIENCE.ABL4896_MDAR_REPRODUCIBILITY_CHECKLIST.PDF · DOI
  2. Paszke, A. , et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library. in Neural Information Processing Systems. (2019).

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Metadata

Authors
Yang, X., Liu, G., Feng, G., Bu, D., Wang, P., Jiang, J., Chen, S., Yang, Q., Zhang, Y., Man, Z., Liang, Z., Wang, Z., Li, Y., Li, Z., Liu, Y., Tian, Y., Li, A., Dong, J., Hu, Z., Fang, C., Miao, H., Cui, L., Deng, Z., Jiang, H., Cui, W., Zhang, J., Yang, Z., Li, H., He, X., Zhong, L., Zhou, J., Wang, Z., Long, Q., Xu, P., The X-Compass Consortium, Wang, H., Meng, Z., Wang, X., Wang, Y., Wang, Y., Zhang, S., Guo, J., Zhao, Y., Zhou, Y., Li, F., Liu, J., Chen, Y., Yang, G., & Li, X.
Affiliations
Chinese Academy of Sciences (CN)
Corresponding author
Zhao, Yi
ORCID
Venue
Cell Research
Publisher
openRxiv
Published
2023-09-28
Volume
34
Issue
12
Pages
830-845
ISSN
1001-0602 (ISSN-L)
DOI
10.1101/2023.09.26.559542
PMC
PMC11615217
OpenAlex
W4403174218
Cited by
148
References
75
Citations by year
2026: 63 · 2025: 63 · 2024: 20 · 2023: 1
FWCI
19.82
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Cell Research (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Natural Science Foundation of China (62202455, No.91954201, No.32341013, 31971289, 91954201, No.62202455, No.31971289, 32341019, 32341013)
  • Chinese Academy of Sciences (YSBR‐076, CAS-WX2021SF-0101, YSBR-034)
  • Institute of Zoology, Chinese Academy of Sciences
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
gene regulatory mechanisms, single-cell transcriptomics, self-supervised learning, cell fate transitions, gonadal differentiation, human embryonic stem cells, drug target identification
MeSH terms
Animals, Cell Differentiation, Gene Expression Regulation, Humans, Species Specificity, Mice, Gene Regulatory Networks, Single-Cell Analysis, Transcriptome

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