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CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions

文献类型：期刊论文

作者Feng, Guihai6,7,8; Qin, Xin9,10; Zhang, Jiahao1,10; Huang, Wuliang9,10; Zhang, Yiyang1,5; Cui, Wentao2,10; Chen, Yao3; Li, Shirui1,10; Liu, Wenhao6,10; Tian, Yao6,10
刊名ADVANCED SCIENCE
出版日期2026-01-07
页码18
关键词cell fate gene regulatory network perturbation simulation transfer learning
DOI10.1002/advs.202508697
英文摘要Cell fate decisions are orchestrated by intricate gene regulatory networks (GRNs), which govern gene expression with precise spatiotemporal control. However, accurately capturing context-specific nature of gene regulation remains challenging, particularly when integrating multi-omics data at bulk and single-cell level across diverse cellular contexts.Here, we present CellPolaris, a unified computational framework designed to decode the roles of transcription factors (TFs) in developmental processes. CellPolaris performs TF-centered GRN construction, master TF identification, and TF perturbation simulation. By leveraging transfer learning, the framework generates tissue-specific or cell-type-specific GRNs using pre-constructed high-confidence GRNs of diverse contexts and requires only transcriptomic data as input. Using these learned GRNs, CellPolaris identifies underlying master TFs critical for cell fate transitions and simulates the effects of TF perturbations on developmental processes. Benchmarking tests demonstrate the robust performance of CellPolaris in GRN construction. The efficacy of CellPolaris is supported by the significant overlap between predicted top-ranked master regulators and known TF combinations experimentally validated in cell fate conversion experiments. Furthermore, CellPolaris accurately simulates the developmental consequences of Rfx2 knockout during round spermatid differentiation. In summary, we present CellPolaris, a comprehensive framework that enables GRN construction through transfer learning, identification of key TFs driving cell fate transitions, and simulation of TF perturbations. This tool allows us to further elucidate the regulatory mechanisms underlying developmental processes and cell state transitions.
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA0510400] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDC0200000] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB1350201] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB0990000] ; Science and Technology Commission of Shanghai Municipality[23ZR1469700] ; National Natural Science Foundation of China[61836013] ; National Natural Science Foundation of China[12025107] ; National Natural Science Foundation of China[32341013] ; National Natural Science Foundation of China[62402476] ; National Natural Science Foundation of China[82530052] ; National Natural Science Foundation of China[32170861] ; Informatization Plan of Chinese Academy of Sciences[CAS-WX2021SF-0101] ; China Postdoctoral Science Foundation[2024M753296] ; CAS Project for Young Scientists in Basic Research[YSBR-076] ; CAS Project for Young Scientists in Basic Research[YSBR-077] ; CAS Project for Young Scientists in Basic Research[YSBR-034] ; National Key Research and Development Program of China[2023YFA1802000] ; National Key Research and Development Program of China[2022YFA1104101] ; National Key Research and Development Program of China[2021YFC2700200] ; National Key Research and Development Program of China[2022YFA1004800] ; National Key Research and Development Program of China[2019YFA0110901] ; National Key Research and Development Program of China[2025YFF1207900] ; National Key Research and Development Program of China[2022YFC2702602] ; National Key Research and Development Program of China[2022YFC2702800]
WOS研究方向Chemistry ; Science & Technology - Other Topics ; Materials Science
语种英语
WOS记录号WOS:001655495400001
出版者WILEY
源URL[http://119.78.100.204/handle/2XEOYT63/42915]  
专题中国科学院计算技术研究所
通讯作者Feng, Guihai; Tong, Ming-Han; Zhou, Yuanchun; Zhang, Shihua; Chen, Yiqiang; Wang, Yong; Li, Xin
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, State Key Lab Math Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Shanghai Inst Biochem & Cell Biol, Chinese Acad Sci,Shanghai Key Lab Mol Androl, Ctr Excellence Mol Cell Sci,State Key Lab Mol Biol, Shanghai, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing, Peoples R China
5.Yunnan Univ, Sch Software, Kunming, Peoples R China
6.Chinese Acad Sci, Inst Zool, State Key Lab Organ Regenerat & Reconstruct, Beijing, Peoples R China
7.Chinese Acad Sci, Inst Stem Cell & Regenerat Med, Beijing, Peoples R China
8.Beijing Inst Stem Cell & Regenerat Med, Beijing, Peoples R China
9.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
10.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Feng, Guihai,Qin, Xin,Zhang, Jiahao,et al. CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions[J]. ADVANCED SCIENCE,2026:18.
APA Feng, Guihai.,Qin, Xin.,Zhang, Jiahao.,Huang, Wuliang.,Zhang, Yiyang.,...&Li, Xin.(2026).CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions.ADVANCED SCIENCE,18.
MLA Feng, Guihai,et al."CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions".ADVANCED SCIENCE (2026):18.

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