D-SPIN constructs regulatory network models from scRNA-seq that reveal organizing principles of perturbation response
Year: 2026
Type: article
Abstract: Gene regulatory networks within cells modulate the expression of the genome in response to signals and changing environmental conditions. Reconstructions of gene regulatory networks can reveal the information processing and control principles used by cells to maintain homeostasis and execute cell-state transitions. Here, we introduce a computational framework, D-SPIN, that generates quantitative models of gene regulatory networks from single-cell mRNA-seq datasets collected across thousands of distinct perturbation conditions. D-SPIN constructs probabilistic models of regulatory interactions between genes or gene-expression programs to fit the cell state distributions under different perturbations. Using large Perturb-seq and drug-response datasets, we demonstrate that D-SPIN models reveal key regulators of cell fate decisions and the coordination of distant cellular pathways in response to gene knockdown perturbations. D-SPIN also dissects gene-level drug response mechanisms in heterogeneous cell populations, elucidating how combinations of immunomodulatory drugs acting on distinct regulators induce novel cell states through additive recruitment of gene expression programs. D-SPIN provides a computational framework for constructing interpretable models of gene regulatory networks to reveal principles of cellular information processing and physiological control.
Source: Cell
Institutions: California Institute of Technology, Rockefeller University, University of California, San Francisco, Parker Institute for Cancer Immunotherapy, Stanford University, Brigham and Women's Hospital, Harvard University, Simon Fraser University, Chan Zuckerberg Biohub San Francisco, UCSF Helen Diller Family Comprehensive Cancer Center
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $11,400
Funders: Amgen, Shurl and Kay Curci Foundation, Heritage Medical Research Institute, Chan Zuckerberg Initiative, National Institutes of Health, University of California, San Francisco, Beckman Institute, California Institute of Technology, Natural Sciences and Engineering Research Council of Canada, National Cancer Institute, National Institute of General Medical Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Merkin Institute for Translational Research, California Institute of Technology
Awards: Universal Sample Multiplexing for Single Cell Analysis, Role of very long chain fatty acids in protein quality control and membrane homeostasis, Quantitative models for controlling collective cell fate selection in stem cells, Illumina NovaSeq 6000 Sequencing System, Increasing organoid reproducibility and complexity for drug testing and disease modeling, Structural and Functional Analysis of Proteasome Core Particle Biogenesis, A Global Map of Interactions Among Human Cell Surface Proteins and Secreted Ligands, Molecular basis for contrasting programs of fetal and adult T cell development, Understanding breast cancer progression as a defect in the mechanics of tissue self-organization
OpenAlex ID: W7160895022