Dissecting the impact of transcription factor dose on cell reprogramming heterogeneity using scTF-seq
Reprogramming often yields heterogeneous cell fates, yet the underlying mechanisms remain poorly understood. To address this, we developed single-cell transcription factor sequencing (scTF-seq), a single-cell technique that induces barcoded, doxycycline-inducible TF overexpression and quantifies TF dose-dependent transcriptomic changes. Applied to mouse embryonic multipotent stromal cells, scTF-seq generated a gain-of-function atlas for 384 mouse TFs, identifying key regulators of lineage specification, cell cycle control and their interplay. Leveraging single-cell resolution, we uncovered how TF dose shapes reprogramming heterogeneity, revealing both dose-dependent and stochastic cell state transitions. We classified TFs into low-capacity and high-capacity groups, with the latter further subdivided by dose sensitivity. Combinatorial scTF-seq demonstrated that TF interactions can shift from synergistic to antagonistic depending on the relative dose. Altogether, scTF-seq enables the dissection of TF function, dose and cell fate control, providing a high-resolution framework to understand and predict reprogramming outcomes, advancing gene regulation research and the design of cell engineering strategies.
Authors
- Antoni J. Gralak (ORCID: https://orcid.org/0009-0007-1086-6165)
- Tingdang Liu
- Wouter Saelens (ORCID: https://orcid.org/0000-0002-7114-6248)
- Wangjie Liu (ORCID: https://orcid.org/0000-0002-0801-1164)
- Pernille Yde Rainer (ORCID: https://orcid.org/0000-0002-3559-4414)
- Bart Deplancke (ORCID: https://orcid.org/0000-0001-9935-843X)
- Wanze Chen (ORCID: https://orcid.org/0000-0002-7946-3336)
- Vincent Gardeux (ORCID: https://orcid.org/0000-0001-8954-2161)
- Julie Russeil (ORCID: https://orcid.org/0000-0002-0880-9483)
- Marjan Biočanin (ORCID: https://orcid.org/0000-0001-6350-1943)
- Guido van Mierlo (ORCID: https://orcid.org/0000-0001-5883-0339)
- Angelika Gebhart
Institutions
- SIB Swiss Institute of Bioinformatics (CH)
- Ghent University (BE)
- VIB-UGent Center for Inflammation Research (BE)
- Shenzhen Institutes of Advanced Technology (CN)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Journal
- Nature Genetics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1038/s41588-025-02343-7
- Citations
- 5
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 4.03