A chromatin-based model for deciphering gene interactions
Research Highlight
Published: 14 February 2025
Transcriptomics
Rong Li1Â
Nature Biotechnology
volume 43, page 176 (2025)Cite this article
Foundation models have leveraged diverse gene expression profiles for tasks such as cell type annotation or prediction of perturbation response. However, no model yet exists to demonstrate how the chromatin landscape regulates transcription. Writing in Nature, Lu et al. introduce the general expression transformer (GET), a foundation model trained on chromatin accessibility data from diverse human cell types, and use it to predict gene activity within specific cells.
The GET model was pretrained using single-cell chromatin accessibility data from 213 human cell types and subsequently fine-tuned on paired chromatin and RNA sequencing data, allowing it to learn how regions and features interact with each other across diverse cell types. In fetal erythroblasts, GET identified long-range cis-regulatory elements and their associated transcription factors that were missed by previous models. The researchers also constructed the publicly available GET Catalog, which combines GET-predicted regulatory sequences and protein structure information from AlphaFold2 to predict direct or indirect transcription factor interactions. They use the catalog to identify how the lymphocyte-specific PAX5 and nuclear receptor interaction might be enhanced by a specific PAX5 germline mutation associated with increased risk of B cell acute lymphoblastic leukemia.
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Author informationAuthors and AffiliationsNature Biotechnology https://www.nature.com/nbt/
Rong Li
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Rong Li.
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Cite this articleLi, R. A chromatin-based model for deciphering gene interactions.
Nat Biotechnol 43, 176 (2025). https://doi.org/10.1038/s41587-025-02573-4
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Published: 14 February 2025
Issue Date: February 2025
DOI: https://doi.org/10.1038/s41587-025-02573-4
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