Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 32 min ago
Peer-reviewedCC BY-NC-NDCell

D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response

  • Jialong Jiang1
  • Sisi Chen2
  • Tiffany Tsou2
  • Christopher S. McGinnis3
  • Tahmineh Khazaei4
  • Qin Zhu5
  • Jong Hyeok Park2
  • Inna-Marie Strazhnik4
  • Jost Vielmetter4
  • Yingying Gong4
  • John Hanna6
  • Eric D. Chow7
3 more authors
  • David A. Sivak8
  • Zev J. Gartner9
  • Matt W. Thomson10
10 affiliations
  1. 1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Center for Studies in Physics and Biology, The Rockefeller University, New York, NY, USA. Electronic address: [email protected]
  2. 2Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Beckman Single-Cell Profiling and Engineering Center, California Institute of Technology, Pasadena, CA, USA
  3. 3Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA; Department of Pathology, School of Medicine, Stanford University, Palo Alto, CA, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
  4. 4Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
  5. 5Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
  6. 6Department of Pathology, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
  7. 7Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA; Center for Advanced Technology, University of California, San Francisco, San Francisco, CA, USA
  8. 8Department of Physics, Simon Fraser University, Burnaby, BC, Canada
  9. 9Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA; Center for Cellular Construction, University of California, San Francisco, San Francisco, CA, USA
  10. 10Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA; Beckman Single-Cell Profiling and Engineering Center, California Institute of Technology, Pasadena, CA, USA. Electronic address: [email protected]
Open at sourceDOICite

Abstract

Gene regulatory networks modulate the expression of the genome in response to signals and environmental conditions. Reconstructions of such networks can reveal the control principles cells use to maintain homeostasis and execute cell-state transitions. Here, we introduce a computational framework, dimension-scalable single-cell perturbation integration network (D-SPIN), that infers mechanistically interpretable and generative models of gene regulatory networks from single-cell mRNA-seq datasets collected across thousands of perturbation conditions. The models explain how perturbations modulate cell-state proportions by reconfiguring underlying regulatory interactions. Using large Perturb-seq and drug response datasets, D-SPIN models reveal key regulators of cell fate decisions and the coordination of distant cellular pathways in response to gene knockdowns and drug treatments, elucidate how combinations of immunomodulatory drugs induce combinatorial cell states through additive recruitment of gene expression programs, and simulate shifts in immune cell population structures across unobserved drug dosage combinations. D-SPIN provides a computational framework for revealing principles of cellular information processing and physiological control.

Related

  1. Dynamic three-dimensional chromatin remodeling in lung disease: mechanistic principles, pathogenic regulatory networks, and translational challenges
    Tiantian Liu, Songshan Jiang, Jing Wang +1
    Frontiers in cell and developmental biologyPeer-reviewedCC BYFull textGeneral biochemistryEurope PMC
  2. An integrative multi-omics modeling framework for chemotherapy response prediction through microRNA–target regulatory signatures
    Briefings in bioinformaticsPeer-reviewedCC BYFull textMolecular biology & gene regulationEurope PMC
  3. A systematic comparison of single-cell perturbation response prediction models
    Lanxiang Li, Yue You, Yunlin Fu +11
    Science AdvancesPeer-reviewedCC BY30 citedMolecular biology & gene regulationOpenAlex
  4. Dynamic graph prior-guided latent adaptation for generalizable single-cell perturbation response prediction.
    Yunlong Bie, Peishan Fan, Qijin Yin +1
    Bioinformatics (Oxford, England)Peer-reviewedCC BYFull textMolecular biology & gene regulationEurope PMCCrossref
  5. Protein Lysine Lactylation in DNA Damage Response: Regulatory Mechanisms and Emerging Functions
    Xinke Pei, Jinhui Zhang, Yue Gao +8
    BiomoleculesPeer-reviewedCC BY 4.0Full textMolecular biology & gene regulationCrossrefEurope PMC

Cite

BibTeXRIS
BibTeX
@article{jiang2026dspin,
  title = {{D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response}},
  author = {Jialong Jiang and Sisi Chen and Tiffany Tsou and Christopher S. McGinnis and Tahmineh Khazaei and Qin Zhu and Jong Hyeok Park and Inna-Marie Strazhnik and Jost Vielmetter and Yingying Gong and John Hanna and Eric D. Chow and David A. Sivak and Zev J. Gartner and Matt W. Thomson},
  journal = {Cell},
  year = {2026},
  month = may,
  doi = {10.1016/j.cell.2026.04.028},
  url = {https://doi.org/10.1016/j.cell.2026.04.028},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response
AU  - Jialong Jiang
AU  - Sisi Chen
AU  - Tiffany Tsou
AU  - Christopher S. McGinnis
AU  - Tahmineh Khazaei
AU  - Qin Zhu
AU  - Jong Hyeok Park
AU  - Inna-Marie Strazhnik
AU  - Jost Vielmetter
AU  - Yingying Gong
AU  - John Hanna
AU  - Eric D. Chow
AU  - David A. Sivak
AU  - Zev J. Gartner
AU  - Matt W. Thomson
PY  - 2026
DA  - 2026/05/12
JO  - Cell
DO  - 10.1016/j.cell.2026.04.028
UR  - https://doi.org/10.1016/j.cell.2026.04.028
AB  - Gene regulatory networks modulate the expression of the genome in response to signals and environmental conditions. Reconstructions of such networks can reveal the control principles cells use to maintain homeostasis and execute cell-state transitions. Here, we introduce a computational framework, dimension-scalable single-cell perturbation integration network (D-SPIN), that infers mechanistically interpretable and generative models of gene regulatory networks from single-cell mRNA-seq datasets collected across thousands of perturbation conditions. The models explain how perturbations modulate cell-state proportions by reconfiguring underlying regulatory interactions. Using large Perturb-seq and drug response datasets, D-SPIN models reveal key regulators of cell fate decisions and the coordination of distant cellular pathways in response to gene knockdowns and drug treatments, elucidate how combinations of immunomodulatory drugs induce combinatorial cell states through additive recruitment of gene expression programs, and simulate shifts in immune cell population structures across unobserved drug dosage combinations. D-SPIN provides a computational framework for revealing principles of cellular information processing and physiological control.
SN  - 0092-8674
SN  - 1097-4172
ER  -