Mapping transcriptomic vector fields of single cells

Abstract

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

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     Zhou JX, and Huang S (2011 ). Understanding gene circuits at cell-fate branch points for rational cell reprogramming. Trends Genet. 27, 55–62.

     Not in our library10.1016/j.tig.2010.11.002

Cited by papers we hold 10

• Invasion and metastasis in cancer: molecular insights and therapeutic targets · 2025
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• CellRank 2: unified fate mapping in multiview single-cell data · 2024
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• Deciphering cell states and genealogies of human haematopoiesis · 2024
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• Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST · 2023
  Corrected
• Tumor heterogeneity: preclinical models, emerging technologies, and future applications · 2023
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• Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response · 2023
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• CellRank for directed single-cell fate mapping · 2022
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• RNA velocity unraveled · 2022
  No notice
• Computational Approaches and Challenges in Spatial Transcriptomics · 2022
  No notice
• Dexamethasone modulates immature neutrophils and interferon programming in severe COVID-19 · 2021
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