Modeling and designing enhancers by introducing and harnessing transcription factor binding units
Abstract Enhancers serve as pivotal regulators of gene expression throughout various biological processes by interacting with transcription factors (TFs). While transcription factor binding sites (TFBSs) are widely acknowledged as key determinants of TF binding and enhancer activity, the significant...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-56749-2 |
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| author | Jiaqi Li Pengcheng Zhang Xi Xi Liyang Liu Lei Wei Xiaowo Wang |
| author_facet | Jiaqi Li Pengcheng Zhang Xi Xi Liyang Liu Lei Wei Xiaowo Wang |
| author_sort | Jiaqi Li |
| collection | DOAJ |
| description | Abstract Enhancers serve as pivotal regulators of gene expression throughout various biological processes by interacting with transcription factors (TFs). While transcription factor binding sites (TFBSs) are widely acknowledged as key determinants of TF binding and enhancer activity, the significant role of their surrounding context sequences remains to be quantitatively characterized. Here we propose the concept of transcription factor binding unit (TFBU) to modularly model enhancers by quantifying the impact of context sequences surrounding TFBSs using deep learning models. Based on this concept, we develop DeepTFBU, a comprehensive toolkit for enhancer design. We demonstrate that designing TFBS context sequences can significantly modulate enhancer activities and produce cell type-specific responses. DeepTFBU is also highly efficient in the de novo design of enhancers containing multiple TFBSs. Furthermore, DeepTFBU enables flexible decoupling and optimization of generalized enhancers. We prove that TFBU is a crucial concept, and DeepTFBU is highly effective for rational enhancer design. |
| format | Article |
| id | doaj-art-1e5967ad002a4b3fb22cb5c06d2f52b7 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-1e5967ad002a4b3fb22cb5c06d2f52b72025-02-09T12:45:53ZengNature PortfolioNature Communications2041-17232025-02-0116111610.1038/s41467-025-56749-2Modeling and designing enhancers by introducing and harnessing transcription factor binding unitsJiaqi Li0Pengcheng Zhang1Xi Xi2Liyang Liu3Lei Wei4Xiaowo Wang5Ministry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua UniversityAbstract Enhancers serve as pivotal regulators of gene expression throughout various biological processes by interacting with transcription factors (TFs). While transcription factor binding sites (TFBSs) are widely acknowledged as key determinants of TF binding and enhancer activity, the significant role of their surrounding context sequences remains to be quantitatively characterized. Here we propose the concept of transcription factor binding unit (TFBU) to modularly model enhancers by quantifying the impact of context sequences surrounding TFBSs using deep learning models. Based on this concept, we develop DeepTFBU, a comprehensive toolkit for enhancer design. We demonstrate that designing TFBS context sequences can significantly modulate enhancer activities and produce cell type-specific responses. DeepTFBU is also highly efficient in the de novo design of enhancers containing multiple TFBSs. Furthermore, DeepTFBU enables flexible decoupling and optimization of generalized enhancers. We prove that TFBU is a crucial concept, and DeepTFBU is highly effective for rational enhancer design.https://doi.org/10.1038/s41467-025-56749-2 |
| spellingShingle | Jiaqi Li Pengcheng Zhang Xi Xi Liyang Liu Lei Wei Xiaowo Wang Modeling and designing enhancers by introducing and harnessing transcription factor binding units Nature Communications |
| title | Modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| title_full | Modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| title_fullStr | Modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| title_full_unstemmed | Modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| title_short | Modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| title_sort | modeling and designing enhancers by introducing and harnessing transcription factor binding units |
| url | https://doi.org/10.1038/s41467-025-56749-2 |
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