{ "abstract": "RNA velocity has emerged as a popular approach for modeling cellular change along the phenotypic landscape but routinely omits regulatory interactions between genes. Conversely, methods that infer gene regulatory networks (GRNs) do not consider the dynamically changing nature of biological systems. To integrate these two currently disconnected fields, we present RegVelo, an end-to-end dynamic, interpretable, and actionable deep learning model that learns a joint model of splicing kinetics and gene regulatory relationships and allows us to perform in silico perturbation predictions. When applied to datasets of the cell cycle, human hematopoiesis, and murine pancreatic endocrinogenesis, RegVelo demonstrates superior predictive power for interactions and perturbation simulations, for example, compared to methods that focus solely on dynamics or GRN inference. To leverage RegVelo’s full potential, we studied the dynamics of zebrafish neural crest development and underlying regulatory mechanisms using our Smart-seq3 dataset and shared gene expression and chromatin accessibility measurements. Using RegVelo’s in silico perturbation predictions, validated by CRISPR/Cas9-mediated knockout and single-cell Perturb-seq, we establish transcription factor tfec as an early driver and elf1 as a novel regulator of pigment cell fate and propose a gene-regulatory circuit involving tfec and elf1 interactions via the toggle-switch model.", "abstract_shown": true, "affiliations": [ "Institute of Computational Biology, Computational Health Center, Helmholtz Munich, Munich, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany", "Institute of Computational Biology, Computational Health Center, Helmholtz Munich, Munich, Germany", "TUM School of Life Sciences Weihenstephan, Technical University of Munich, Germany", "MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Reproductive Medicine Center, Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Zhongnan Hospital, Wuhan University, Wuhan, China", "MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford", "Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Wuhan University", "Oxford, United Kingdom", "Wuhan, China", "Institute of Computational Biology, Computational Health Center, Helmholtz Munich, Munich, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany", "School of Computation, Information and Technology, Technical University of Munich, Munich, Germany", "MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK", "Institute of Computational Biology, Computational Health Center, Helmholtz Munich, Munich, Germany; Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland", "Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland", "Department of Biology, New York University, New York, NY, USA", "Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA", "Stowers Institute for Medical Research, Kansas City, MO, USA", "Institute of Translational Genomics, Helmholtz Munich, Germany", "Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA; Department of Biology, New York University, New York, NY, USA", "MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom", "School of Computation, Information and Technology, Technical University of Munich, Munich, Germany; Institute of Translational Genomics, Helmholtz Munich, Munich, Germany", "MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Stowers Institute for Medical Research, Kansas City, MO, USA; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK. Electronic address: tsauka-spengler@stowers.org", "Institute of Computational Biology, Computational Health Center, Helmholtz Munich, Munich, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. Electronic address: fabian.theis@helmholtz-munich.de" ], "article_type": null, "arxiv": null, "author_total": 11, "authors": [ { "affs": [ 0, 1, 2 ], "name": "Weixu Wang" }, { "affs": [ 3, 4, 5, 6, 7 ], "name": "Zhiyuan Hu", "orcid": "0000-0002-1688-6032" }, { "affs": [ 8, 1, 9, 2 ], "name": "Philipp Weiler", "orcid": "0000-0002-0992-7043" }, { "affs": [ 10, 4, 6 ], "name": "Sarah Mayes", "orcid": "0000-0001-7630-9272" }, { "affs": [ 11, 12, 1 ], "name": "Marius Lange", "orcid": "0000-0002-4846-1266" }, { "affs": [ 10, 13, 14 ], "name": "Daniel Mark Fountain", "orcid": "0000-0001-6227-9930" }, { "affs": [ 15, 16, 9 ], "name": "Julianna O. Haug", "orcid": "0000-0001-8093-0221" }, { "affs": [ 17, 18, 4, 6, 15 ], "name": "Jingye Wang" }, { "affs": [ 19, 1, 9, 2 ], "name": "Zhengyuan Xue", "orcid": "0009-0004-4738-4395" }, { "affs": [ 20 ], "name": "Tatjana Sauka‐Spengler", "orcid": "0000-0001-9289-0263" }, { "affs": [ 21 ], "name": "Fabian Joachim Theis", "orcid": "0000-0002-2419-1943" } ], "bibtex": "https://research.draconitic.com/paper/9egeebpqkt7sp.bib", "cited_by": 26, "doi": "10.1016/j.cell.2026.04.022", "fulltext_url": null, "id": "9egeebpqkt7sp", "issns": [ "0092-8674", "1097-4172" ], "landing_url": "https://doi.org/10.1016/j.cell.2026.04.022", "language": "en", "licence": "CC-BY", "licence_label": "CC BY", "licence_source": "journal", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "1312|Gene Regulatory Network Analysis" ] ], "openalex": "W4405307613", "pdf_url": null, "pmcid": null, "pmid": "42119563", "published": "2026-05-12", "publisher": "Cell Press", "ris": "https://research.draconitic.com/paper/9egeebpqkt7sp.ris", "sources": [ { "first_seen": "2026-10-30T13:26:46Z", "native_id": "W4405307613", "source": "openalex", "url": "https://doi.org/10.1016/j.cell.2026.04.022" } ], "subjects": [ { "field": "biochemistry", "origin": "openalex:1312|Gene Regulatory Network Analysis", "subfield": "molecular-biology" } ], "title": "RegVelo: Gene-regulatory-informed dynamics of single cells", "title_text": "RegVelo: Gene-regulatory-informed dynamics of single cells", "type": "peer-reviewed", "updated_at": "2026-11-07T13:20:47Z", "url": "https://research.draconitic.com/paper/9egeebpqkt7sp", "venue": "Cell", "versions": [] }