Klein, D. ; Palla, G. ; Lange, M. ; Klein, M.* ; Piran, Z.* ; Gander, M. ; Meng-Papaxanthos, L.* ; Sterr, M. ; Saber, L. ; Jing, C. ; Bastidas-Ponce, A. ; Cota, P. ; Tarquis Medina, M. ; Parikh, S. ; Gold, I. ; Lickert, H. ; Bakhti, M. ; Nitzan, M.* ; Cuturi, M.C.* ; Theis, F.J.
Mapping cells through time and space with moscot.
Nature 638, 1065–1075 (2025)
Single-cell genomic technologies enable the multimodal profiling of millions of cells across temporal and spatial dimensions. However, experimental limitations hinder the comprehensive measurement of cells under native temporal dynamics and in their native spatial tissue niche. Optimal transport has emerged as a powerful tool to address these constraints and has facilitated the recovery of the original cellular context1-4. Yet, most optimal transport applications are unable to incorporate multimodal information or scale to single-cell atlases. Here we introduce multi-omics single-cell optimal transport (moscot), a scalable framework for optimal transport in single-cell genomics that supports multimodality across all applications. We demonstrate the capability of moscot to efficiently reconstruct developmental trajectories of 1.7 million cells from mouse embryos across 20 time points. To illustrate the capability of moscot in space, we enrich spatial transcriptomic datasets by mapping multimodal information from single-cell profiles in a mouse liver sample and align multiple coronal sections of the mouse brain. We present moscot.spatiotemporal, an approach that leverages gene-expression data across both spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. We also resolve endocrine-lineage relationships of delta and epsilon cells in a previously unpublished mouse, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility. Our findings are confirmed through experimental validation of NEUROD2 as a regulator of epsilon progenitor cells in a model of human induced pluripotent stem cell islet cell differentiation. Moscot is available as open-source software, accompanied by extensive documentation.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Scopus
Cited By
Altmetric
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Genome-wide Expression; Rna-seq; Mouse Embryos; Differentiation; Apoptosis; Reconstruction; Identification; Organogenesis; Heterogeneity; Trajectories
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2025
Prepublished im Jahr
0
HGF-Berichtsjahr
2025
ISSN (print) / ISBN
0028-0836
e-ISSN
1476-4687
ISBN
Bandtitel
Konferenztitel
Konferzenzdatum
Konferenzort
Konferenzband
Quellenangaben
Band: 638,
Heft: ,
Seiten: 1065–1075
Artikelnummer: ,
Supplement: ,
Reihe
Verlag
Nature Publishing Group
Verlagsort
London
Tag d. mündl. Prüfung
0000-00-00
Betreuer
Gutachter
Prüfer
Topic
Hochschule
Hochschulort
Fakultät
Veröffentlichungsdatum
0000-00-00
Anmeldedatum
0000-00-00
Anmelder/Inhaber
weitere Inhaber
Anmeldeland
Priorität
Begutachtungsstatus
Peer reviewed
POF Topic(s)
30205 - Bioengineering and Digital Health
30201 - Metabolic Health
90000 - German Center for Diabetes Research
Forschungsfeld(er)
Enabling and Novel Technologies
Helmholtz Diabetes Center
PSP-Element(e)
G-503800-001
G-502300-001
G-501900-231
Förderungen
Joachim Herz Foundation
EMBO Postdoctoral Fellowship
Israeli Council for Higher Education
Azrieli Foundation Early Career Faculty Fellowship
Center for Interdisciplinary Data Science Research at the Hebrew University of Jerusalem
Israel Science Foundation
European Union (ERC)
Wellcome Leap
Helmholtz Association under the joint research school Munich School for Data Science
BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI)
EU
Copyright
Erfassungsdatum
2025-03-25