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In vivo Application of the REMOTE-control System for the Manipulation of Endogenous Gene Expression
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GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation
Xiaodong Yang1,2,3, Guole Liu4,5, Guihai Feng1,6,7
1State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Cell Research
|October 7, 2024
Summary
We developed GeneCompass, an AI model analyzing millions of single-cell transcriptomes to uncover universal gene regulatory mechanisms across species. This approach accelerates the discovery of cell fate regulators and potential drug targets.
Area of Science:
- Genomics
- Computational Biology
- Developmental Biology
Background:
- Understanding universal gene regulatory mechanisms is key for biology and medicine.
- Current research often overlooks cross-species and multi-cell type integration.
- Single-cell sequencing and deep learning offer new avenues for integrated analysis.
Purpose of the Study:
- To develop a cross-species foundation model for deciphering gene regulatory mechanisms.
- To integrate large-scale single-cell transcriptomic data from humans and mice.
- To identify key factors in cell fate transitions and potential therapeutic targets.
Main Methods:
- Constructed a dataset of over 101 million human and mouse single-cell transcriptomes.
- Developed GeneCompass, a knowledge-informed, cross-species foundation model.
- Utilized self-supervised learning and fine-tuning for downstream biological tasks.
Main Results:
- GeneCompass effectively integrated biological knowledge for enhanced gene regulation understanding.
- The model outperformed existing methods in single-species and cross-species analyses.
- Identified candidate genes that successfully induced human embryonic stem cell differentiation into gonadal fate.
Conclusions:
- GeneCompass leverages AI to reveal universal gene regulatory mechanisms.
- The model shows significant potential for discovering cell fate regulators.
- Accelerates identification of novel drug targets for clinical applications.
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