Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Communications
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. nature communications
  3. articles
  4. article
An in vivo and in vitro spatiotemporal profile of human midbrain development
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 03 February 2026

An in vivo and in vitro spatiotemporal profile of human midbrain development

  • Dimitri Budinger  ORCID: orcid.org/0000-0001-7002-10911 na1,
  • Pau Puigdevall  ORCID: orcid.org/0000-0002-8687-49422,3 na1,
  • George T. Hall  ORCID: orcid.org/0000-0002-4828-06683 na1,
  • Charlotte Roth  ORCID: orcid.org/0000-0003-0227-33391,
  • Theodoros Xenakis  ORCID: orcid.org/0000-0003-3682-88733,
  • Elena Marrosu1,
  • Julie Jerber4,
  • Alessandro Di Domenico1,
  • Francesca Picco1,
  • Helena Kilpinen  ORCID: orcid.org/0000-0001-6692-61542,5,6,
  • Sergi Castellano3,
  • Manju A. Kurian  ORCID: orcid.org/0000-0003-3529-50751,7 na2 &
  • …
  • Serena Barral  ORCID: orcid.org/0000-0002-1430-36141 na2 

Nature Communications , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cell type diversity
  • Induced pluripotent stem cells
  • Neurodegeneration

Abstract

The dopaminergic system has key roles in human physiology and is implicated in a broad range of neurological and neuropsychiatric conditions that are increasingly investigated using induced pluripotent stem cell-derived midbrain models. To determine similarities of such models to human systems, here we undertake single-cell and spatial profiling of first and second trimester fetal midbrain and compare it to in vitro midbrain models. Histological examination reveals that, by the second trimester, fetal midbrain tissue exhibits structural complexity comparable to that of adults. At the molecular level, single-cell profiling uncovers differences in cellular composition across models, with brain organoids most closely resembling late first trimester tissue — an observation supported by meta-integration of existing midbrain datasets. By reconstructing developmental trajectories of neuronal and astrocytic lineages, we map gene expression dynamics associated with maturation. Importantly, integration of spatial transcriptomics provides critical context for aligning organoid models, revealing that their spatial organization and intercellular signaling resemble the architecture and microenvironment of the second trimester midbrain. Ultimately, we leverage our findings to study Dopamine Transporter Deficiency Syndrome progression in patient-derived midbrain organoids, validating their relevance. Understanding the extent of human tissue recapitulation in midbrain laboratory models is essential to justify their use as biological proxies.

Data availability

Raw FASTQ files for both single-cell and spatial transcriptomics generated in this study have been deposited in Gene Expression Omnibus (GEO) under accession code GSE277032, accessible at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE277032. The four supplemental data files generated in this study are available in a Zenodo repository (https://zenodo.org/records/13765496), detailed as follows: Files S1, S2: VCF files with donor genotypes to deconvolute pooled scRNA-seq data. File S3: Single-cell data generated in our study (RDS object: Seurat object with counts and metadata). File S4: Integrated datasets (RDS object: Seurat object with counts and metadata). Additionally, the images from the immunohistochemistry analysis on midbrain tissues are available in the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) Atlas (https://hdbratlas.org/gene-expression/midbrain.html). Source data for graphs and tables are included with the manuscript. Source data are provided with this paper.

Code availability

Two GitHub repositories are available for reproducing the analysis and figures of the manuscript: one for single-cell transcriptomics (https://github.com/paupuigdevall/MLOscRNAseq, archived at https://doi.org/10.5281/zenodo.17541380) and another for spatial transcriptomics (https://github.com/george-hall-ucl/mlo_spatial_transcriptomics, archived at https://doi.org/10.5281/zenodo.17550243). These repositories include scripts for processing steps, data analysis and figure generation. Additionally, the Docker images used for spatial transcriptomics are available on Dockerhub (main pipeline: georgehallucl/midbrain_tissues_organoids_docker; commot: georgehallucl/commot_docker; cell2location: georgehallucl/cell2location_docker). An archive to reproduce the spatial transcriptomics analysis is available at https://doi.org/10.5522/04/27044423.

References

  1. Parraga, R. G. et al. Microsurgical anatomy and internal architecture of the brainstem in 3D images: surgical considerations. J. Neurosurg. 124, 1377–1395 (2016).

    Google Scholar 

  2. Faissner, A. Low-density lipoprotein receptor-related protein-1 (LRP1) in the glial lineage modulates neuronal excitability. Front. Netw. Physiol. 3, 1190240 (2023).

    Google Scholar 

  3. Garritsen, O., van Battum, E. Y., Grossouw, L. M. & Pasterkamp, R. J. Development, wiring and function of dopamine neuron subtypes. Nat. Rev. Neurosci. 24, 134–152 (2023).

    Google Scholar 

  4. Bissonette, G. B. & Roesch, M. R. Development and function of the midbrain dopamine system: what we know and what we need to. Genes Brain Behav. 15, 62–73 (2016).

    Google Scholar 

  5. Kurian, M. A., Gissen, P., Smith, M., Heales, S. Jr. & Clayton, P. T. The monoamine neurotransmitter disorders: an expanding range of neurological syndromes. Lancet Neurol. 10, 721–733 (2011).

    Google Scholar 

  6. La Manno, G. et al. Molecular diversity of midbrain development in mouse, human, and stem cells. Cell 167, 566–580 e519 (2016).

    Google Scholar 

  7. Birtele, M. et al. Single-cell transcriptional and functional analysis of dopaminergic neurons in organoid-like cultures derived from human fetal midbrain. Development 149, dev200504 (2022).

  8. Zagare, A. et al. Midbrain organoids mimic early embryonic neurodevelopment and recapitulate LRRK2-p.Gly2019Ser-associated gene expression. Am. J. Hum. Genet. 109, 311–327 (2022).

    Google Scholar 

  9. Nelander, J., Hebsgaard, J. B. & Parmar, M. Organization of the human embryonic ventral mesencephalon. Gene Expr. Patterns 9, 555–561 (2009).

    Google Scholar 

  10. Li, Y. et al. Spatiotemporal transcriptome atlas reveals the regional specification of the developing human brain. Cell 186, 5892–5909 e5822 (2023).

    Google Scholar 

  11. Braun, E. et al. Comprehensive cell atlas of the first-trimester developing human brain. Science 382, eadf1226 (2023).

    Google Scholar 

  12. Siletti, K. et al. Transcriptomic diversity of cell types across the adult human brain. Science 382, eadd7046 (2023).

    Google Scholar 

  13. Eze, U. C., Bhaduri, A., Haeussler, M., Nowakowski, T. J. & Kriegstein, A. R. Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia. Nat. Neurosci. 24, 584–594 (2021).

    Google Scholar 

  14. Yu, Y. et al. Interneuron origin and molecular diversity in the human fetal brain. Nat. Neurosci. 24, 1745–1756 (2021).

    Google Scholar 

  15. Barral, S. & Kurian, M. A. Utility of induced pluripotent stem cells for the study and treatment of genetic diseases: focus on childhood neurological disorders. Front. Mol. Neurosci. 9, 78 (2016).

    Google Scholar 

  16. Gantner, C. W., Cota-Coronado, A., Thompson, L. H. & Parish, C. L. An optimized protocol for the generation of midbrain dopamine neurons under defined conditions. STAR Protoc. 1, 100065 (2020).

    Google Scholar 

  17. Carola, G. et al. Parkinson’s disease patient-specific neuronal networks carrying the LRRK2 G2019S mutation unveil early functional alterations that predate neurodegeneration. NPJ Parkinsons Dis. 7, 55 (2021).

    Google Scholar 

  18. Fiorenzano, A. et al. Single-cell transcriptomics captures features of human midbrain development and dopamine neuron diversity in brain organoids. Nat. Commun. 12, 7302 (2021).

    Google Scholar 

  19. Jo, J. et al. Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons. Cell Stem Cell 19, 248–257 (2016).

    Google Scholar 

  20. Nickels, S. L. et al. Reproducible generation of human midbrain organoids for in vitro modeling of Parkinson’s disease. Stem Cell Res. 46, 101870 (2020).

    Google Scholar 

  21. Marklund, U. et al. Detailed expression analysis of regulatory genes in the early developing human neural tube. Stem Cells Dev. 23, 5–15 (2014).

    Google Scholar 

  22. Tiklova, K. et al. Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development. Nat. Commun. 10, 581 (2019).

    Google Scholar 

  23. Almqvist, P. M. et al. First trimester development of the human nigrostriatal dopamine system. Exp. Neurol. 139, 227–237 (1996).

    Google Scholar 

  24. Ferri, A. L. et al. Foxa1 and Foxa2 regulate multiple phases of midbrain dopaminergic neuron development in a dosage-dependent manner. Development 134, 2761–2769 (2007).

    Google Scholar 

  25. Andersson, E. et al. Identification of intrinsic determinants of midbrain dopamine neurons. Cell 124, 393–405 (2006).

    Google Scholar 

  26. Asgrimsdottir, E. S. & Arenas, E. Midbrain dopaminergic neuron development at the single cell level: in vivo and in stem cells. Front. Cell Dev. Biol. 8, 463 (2020).

    Google Scholar 

  27. Waldvogel, H. J., Curtis, M. A., Baer, K., Rees, M. I. & Faull, R. L. Immunohistochemical staining of post-mortem adult human brain sections. Nat. Protoc. 1, 2719–2732 (2006).

    Google Scholar 

  28. Hegarty, S. V., Sullivan, A. M. & O’Keeffe, G. W. Midbrain dopaminergic neurons: a review of the molecular circuitry that regulates their development. Dev. Biol. 379, 123–138 (2013).

    Google Scholar 

  29. Reyes, S. et al. GIRK2 expression in dopamine neurons of the substantia nigra and ventral tegmental area. J. Comp. Neurol. 520, 2591–2607 (2012).

    Google Scholar 

  30. Di Salvio, M., Di Giovannantonio, L. G., Omodei, D., Acampora, D. & Simeone, A. Otx2 expression is restricted to dopaminergic neurons of the ventral tegmental area in the adult brain. Int J. Dev. Biol. 54, 939–945 (2010).

    Google Scholar 

  31. Arenas, E., Denham, M. & Villaescusa, J. C. How to make a midbrain dopaminergic neuron. Development 142, 1918–1936 (2015).

    Google Scholar 

  32. Hanaway, J., McConnell, J. A. & Netsky, M. G. Histogenesis of the substantia nigra, ventral tegmental area of Tsai and interpeduncular nucleus: an autoradiographic study of the mesencephalon in the rat. J. Comp. Neurol. 142, 59–73 (1971).

    Google Scholar 

  33. Kawano, H., Ohyama, K., Kawamura, K. & Nagatsu, I. Migration of dopaminergic neurons in the embryonic mesencephalon of mice. Brain Res. Dev. Brain Res. 86, 101–113 (1995).

    Google Scholar 

  34. Gupta, D. Neuroanatomy. in Essentials of Neuroanesthesia (ed. Prabhakar, H.) 3–40 (Academic Press, 2017).

  35. Johns, P. Functional neuroanatomy. in Clinical Neuroscience 27–47 (Churchill Livingstone/Elsevier, 2014).

  36. Ng, J. et al. Gene therapy restores dopamine transporter expression and ameliorates pathology in iPSC and mouse models of infantile Parkinsonism. Sci. Transl. Med. 13, eaaw1564 (2021).

  37. Kirkeby, A. et al. Generation of regionally specified neural progenitors and functional neurons from human embryonic stem cells under defined conditions. Cell Rep. 1, 703–714 (2012).

    Google Scholar 

  38. Abela, L. et al. Neurodevelopmental and synaptic defects in DNAJC6 parkinsonism, amenable to gene therapy. Brain 147, 2023–2037 (2024).

    Google Scholar 

  39. Monzel, A. S. et al. Derivation of Human Midbrain-Specific Organoids from Neuroepithelial Stem Cells. Stem Cell Rep. 8, 1144–1154 (2017).

    Google Scholar 

  40. Lancaster, M. A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013).

    Google Scholar 

  41. Kang, H. M. et al. Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nat. Biotechnol. 36, 89–94 (2018).

    Google Scholar 

  42. Hao, Y. et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat. Biotechnol. 42, 293–304 (2024).

    Google Scholar 

  43. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

    Google Scholar 

  44. Funk, M. C. et al. Cyclin O (Ccno) functions during deuterosome-mediated centriole amplification of multiciliated cells. EMBO J. 34, 1078–1089 (2015).

    Google Scholar 

  45. Ricard-Blum, S. The collagen family. Cold Spring Harb. Perspect. Biol. 3, a004978 (2011).

    Google Scholar 

  46. Dann, E., Henderson, N. C., Teichmann, S. A., Morgan, M. D. & Marioni, J. C. Differential abundance testing on single-cell data using k-nearest neighbor graphs. Nat. Biotechnol. 40, 245–253 (2022).

    Google Scholar 

  47. Caporale, N. et al. Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single-cell resolution. Nat. Methods 22, 358–370 (2025).

    Google Scholar 

  48. Van den Berge, K. et al. Trajectory-based differential expression analysis for single-cell sequencing data. Nat. Commun. 11, 1201 (2020).

    Google Scholar 

  49. Agarwal, D. et al. A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated with neurological disorders. Nat. Commun. 11, 4183 (2020).

    Google Scholar 

  50. Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477 (2018).

    Google Scholar 

  51. Angerer, P. et al. destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics 32, 1241–1243 (2016).

    Google Scholar 

  52. Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).

    Google Scholar 

  53. Kolberg, L. et al. g:Profiler-interoperable web service for functional enrichment analysis and gene identifier mapping (2023 update). Nucleic Acids Res. 51, W207–W212 (2023).

    Google Scholar 

  54. Cable, D. M. et al. Cell type-specific inference of differential expression in spatial transcriptomics. Nat. Methods 19, 1076–1087 (2022).

    Google Scholar 

  55. Roll, S., Seul, J., Paulsson, M. & Hartmann, U. Testican-1 is dispensable for mouse development. Matrix Biol. 25, 373–381 (2006).

    Google Scholar 

  56. Vadasz, C. et al. Mesencephalic dopamine neuron number and tyrosine hydroxylase content: genetic control and candidate genes. Neuroscience 149, 561–572 (2007).

    Google Scholar 

  57. Novak, G. et al. Single-cell transcriptomics of human iPSC differentiation dynamics reveal a core molecular network of Parkinson’s disease. Commun. Biol. 5, 49 (2022).

    Google Scholar 

  58. Maffezzini, C., Calvo-Garrido, J., Wredenberg, A. & Freyer, C. Metabolic regulation of neurodifferentiation in the adult brain. Cell Mol. Life Sci. 77, 2483–2496 (2020).

    Google Scholar 

  59. Traxler, L. et al. Metabolism navigates neural cell fate in development, aging and neurodegeneration. Dis. Model. Mech. 14, dmm048993 (2021).

  60. Elkjaer, M. L. et al. Molecular signature of different lesion types in the brain white matter of patients with progressive multiple sclerosis. Acta Neuropathol. Commun. 7, 205 (2019).

    Google Scholar 

  61. Dou, D. & Joseph, R. Structure and organization of the human neuronatin gene. Genomics 33, 292–297 (1996).

    Google Scholar 

  62. Ren, S. et al. Lissencephaly caused by a de novo mutation in tubulin TUBA1A: a case report and literature review. Front. Pediatr. 12, 1367305 (2024).

    Google Scholar 

  63. Granger, A. J., Wallace, M. L. & Sabatini, B. L. Multi-transmitter neurons in the mammalian central nervous system. Curr. Opin. Neurobiol. 45, 85–91 (2017).

    Google Scholar 

  64. Yao, J. J., Zhao, Q. R., Lu, J. M. & Mei, Y. A. Functions and the related signaling pathways of the neurotrophic factor neuritin. Acta Pharm. Sin. 39, 1414–1420 (2018).

    Google Scholar 

  65. Chen, J., Ding, Q., An, L. & Wang, H. Ca(2 + )-stimulated adenylyl cyclases as therapeutic targets for psychiatric and neurodevelopmental disorders. Front. Pharm. 13, 949384 (2022).

    Google Scholar 

  66. Cang, Z. et al. Screening cell-cell communication in spatial transcriptomics via collective optimal transport. Nat. Methods 20, 218–228 (2023).

    Google Scholar 

  67. Jung, C. G. et al. Pleiotrophin mRNA is highly expressed in neural stem (progenitor) cells of mouse ventral mesencephalon and the product promotes production of dopaminergic neurons from embryonic stem cell-derived nestin-positive cells. FASEB J. 18, 1237–1239 (2004).

    Google Scholar 

  68. Mourlevat, S. et al. Pleiotrophin mediates the neurotrophic effect of cyclic AMP on dopaminergic neurons: analysis of suppression-subtracted cDNA libraries and confirmation in vitro. Exp. Neurol. 194, 243–254 (2005).

    Google Scholar 

  69. Bloch, B., Normand, E., Kovesdi, I. & Bohlen, P. Expression of the HBNF (heparin-binding neurite-promoting factor) gene in the brain of fetal, neonatal and adult rat: an in situ hybridization study. Brain Res. Dev. Brain Res. 70, 267–278 (1992).

    Google Scholar 

  70. Winkler, C. & Yao, S. The midkine family of growth factors: diverse roles in nervous system formation and maintenance. Br. J. Pharm. 171, 905–912 (2014).

    Google Scholar 

  71. Fujikawa, A. et al. Mice deficient in protein tyrosine phosphatase receptor type Z (PTPRZ) show reduced responsivity to methamphetamine despite an enhanced response to novelty. PLoS One 14, e0221205 (2019).

    Google Scholar 

  72. Lodato, S. & Arlotta, P. Generating neuronal diversity in the mammalian cerebral cortex. Annu. Rev. Cell Dev. Biol. 31, 699–720 (2015).

    Google Scholar 

  73. Kurian, M. A. et al. Clinical and molecular characterisation of hereditary dopamine transporter deficiency syndrome: an observational cohort and experimental study. Lancet Neurol. 10, 54–62 (2011).

    Google Scholar 

  74. Caminero, F. & Cascella, M. Neuroanatomy, mesencephalon midbrain. in StatPearls [Internet] (StatPearls Publishing, 2022).

  75. Bodea, G. O. et al. Reelin and CXCL12 regulate distinct migratory behaviors during the development of the dopaminergic system. Development 141, 661–673 (2014).

    Google Scholar 

  76. Vaswani, A. R. et al. Correct setup of the substantia nigra requires Reelin-mediated fast, laterally-directed migration of dopaminergic neurons. Elife 8, e41623 (2019).

  77. Williams, C. G., Lee, H. J., Asatsuma, T., Vento-Tormo, R. & Haque, A. An introduction to spatial transcriptomics for biomedical research. Genome Med. 14, 68 (2022).

    Google Scholar 

  78. Zampese, E. et al. Ca(2 + ) channels couple spiking to mitochondrial metabolism in substantia nigra dopaminergic neurons. Sci. Adv. 8, eabp8701 (2022).

    Google Scholar 

  79. Ni, A. & Ernst, C. Evidence that substantia nigra pars compacta dopaminergic neurons are selectively vulnerable to oxidative stress because they are highly metabolically active. Front. Cell Neurosci. 16, 826193 (2022).

    Google Scholar 

  80. Norat, P. et al. Mitochondrial dysfunction in neurological disorders: exploring mitochondrial transplantation. NPJ Regen. Med. 5, 22 (2020).

    Google Scholar 

  81. Prasuhn, J., Davis, R. L. & Kumar, K. R. Targeting mitochondrial impairment in Parkinson’s disease: challenges and opportunities. Front. Cell Dev. Biol. 8, 615461 (2020).

    Google Scholar 

  82. Tekin, H. et al. Effects of 3D culturing conditions on the transcriptomic profile of stem-cell-derived neurons. Nat. Biomed. Eng. 2, 540–554 (2018).

    Google Scholar 

  83. Quadrato, G. et al. Cell diversity and network dynamics in photosensitive human brain organoids. Nature 545, 48–53 (2017).

    Google Scholar 

  84. Gillen, A. E. et al. Alternative polyadenylation of PRELID1 regulates mitochondrial ROS signaling and cancer outcomes. Mol. Cancer Res. 15, 1741–1751 (2017).

    Google Scholar 

  85. Green, D. R. Apoptotic pathways: ten minutes to dead. Cell 121, 671–674 (2005).

    Google Scholar 

  86. Ng, M. Y. W., Wai, T. & Simonsen, A. Quality control of the mitochondrion. Dev. Cell 56, 881–905 (2021).

    Google Scholar 

  87. Rossignoli, G. et al. Aromatic l-amino acid decarboxylase deficiency: a patient-derived neuronal model for precision therapies. Brain 144, 2443–2456 (2021).

    Google Scholar 

  88. Gene Ontology, C. et al. The Gene Ontology knowledgebase in 2023. Genetics 224, iyad031 (2023).

  89. Falcon, S. & Gentleman, R. Using GOstats to test gene lists for GO term association. Bioinformatics 23, 257–258 (2007).

    Google Scholar 

  90. Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).

    Google Scholar 

  91. Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).

    Google Scholar 

  92. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 e3529 (2021).

    Google Scholar 

  93. Kleshchevnikov, V. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat. Biotechnol. 40, 661–671 (2022).

    Google Scholar 

  94. Jin, S. et al. Inference and analysis of cell-cell communication using CellChat. Nat. Commun. 12, 1088 (2021).

    Google Scholar 

  95. Moran, P. A. Notes on continuous stochastic phenomena. Biometrika 37, 17–23 (1950).

    Google Scholar 

Download references

Acknowledgements

We sincerely thank our patients and their families for participating in this study. D.B. was supported by the Sir Jules Thorn Trust. P.P.C. and H.K. are currently funded by the Sigrid Jusélius Foundation and previously by the NIHR Great Ormond Street Hospital Biomedical Research Centre. G.T.H. is funded by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.J. was supported by a postdoctoral fellowship from OpenTargets. F.P. is supported by the UK Medical Research Council (MRC) [UKRI222 – PI S.B.]. M.A.K. is supported by the NIHR Professorship, the Sir Jules Thorn Award for Biomedical Research and the Rosetrees Trust. S.B. was supported by the Great Ormond Street Hospital Children’s Charity. We thank UCL Genomics (UCL GOS Institute of Child Health) and the Wellcome Sanger Institute for undertaking scRNA and spatial sequencing. We thank the Human Developmental Biology Resource (HDBR) for providing human midbrain fetal tissue. We thank the UCL Imaging Facility and the facility manager, Dr Dale Moulding, for the support with immunofluorescence analysis. This research was supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Graphical schemes have been created in BioRender. https://BioRender.com/.

Author information

Author notes
  1. These authors contributed equally: Dimitri Budinger, Pau Puigdevall, George T. Hall.

  2. These authors jointly supervised this work: Manju A. Kurian, Serena Barral

Authors and Affiliations

  1. Developmental Neurosciences, Zayed Centre for Research, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

    Dimitri Budinger, Charlotte Roth, Elena Marrosu, Alessandro Di Domenico, Francesca Picco, Manju A. Kurian & Serena Barral

  2. Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland

    Pau Puigdevall & Helena Kilpinen

  3. Genetics and Genomics Medicine, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

    Pau Puigdevall, George T. Hall, Theodoros Xenakis & Sergi Castellano

  4. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom

    Julie Jerber

  5. Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland

    Helena Kilpinen

  6. Faculty of Medicine, University of Helsinki, Helsinki, Finland

    Helena Kilpinen

  7. Department of Neurology, Great Ormond Street Hospital, London, United Kingdom

    Manju A. Kurian

Authors
  1. Dimitri Budinger
    View author publications

    Search author on:PubMed Google Scholar

  2. Pau Puigdevall
    View author publications

    Search author on:PubMed Google Scholar

  3. George T. Hall
    View author publications

    Search author on:PubMed Google Scholar

  4. Charlotte Roth
    View author publications

    Search author on:PubMed Google Scholar

  5. Theodoros Xenakis
    View author publications

    Search author on:PubMed Google Scholar

  6. Elena Marrosu
    View author publications

    Search author on:PubMed Google Scholar

  7. Julie Jerber
    View author publications

    Search author on:PubMed Google Scholar

  8. Alessandro Di Domenico
    View author publications

    Search author on:PubMed Google Scholar

  9. Francesca Picco
    View author publications

    Search author on:PubMed Google Scholar

  10. Helena Kilpinen
    View author publications

    Search author on:PubMed Google Scholar

  11. Sergi Castellano
    View author publications

    Search author on:PubMed Google Scholar

  12. Manju A. Kurian
    View author publications

    Search author on:PubMed Google Scholar

  13. Serena Barral
    View author publications

    Search author on:PubMed Google Scholar

Contributions

D.B., S.B., and M.A.K. conceived and designed the study. S.B. designed and performed experiments and data analysis for the in vitro and in vivo study. D.B. designed and performed experiments and data analysis for the in vitro and in vivo study. P.P.C. designed and performed data analysis for the scRNA-seq study. G.T.H. designed and performed data analysis for the spatial transcriptomic study. C.R. performed experiments for the in vitro study. T.X. designed and performed experiments for the scRNA-seq and spatial transcriptomic studies. E.M. performed experiments for the spatial transcriptomics study. J.J. performed experiments for the scRNA-seq study. A.D.D. performed experiments for the in vitro study. F.P. performed experiments for the in vivo study. H.K. supervised the scRNA-seq study. S.C. supervised scRNA-seq and spatial transcriptomic studies. D.B., P.P.C., G.T.H., S.C., S.B., and M.A.K. drafted the manuscript. C.R. and T.X. contributed to the written sections of the manuscript. All authors reviewed the manuscript prior to submission.

Corresponding authors

Correspondence to Manju A. Kurian or Serena Barral.

Ethics declarations

Competing interests

M.A.K. is a founder of and consultant to Bloomsbury Genetic Therapies. She has received honoraria from PTC for sponsored symposia and provided consultancy. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Figs.

Description of Additional Supplementary Files

Supplementary Data 1–16

Reporting Summary

Transparent Peer Review file

Source data

Source Data

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Budinger, D., Puigdevall, P., Hall, G.T. et al. An in vivo and in vitro spatiotemporal profile of human midbrain development. Nat Commun (2026). https://doi.org/10.1038/s41467-025-67779-1

Download citation

  • Received: 08 November 2024

  • Accepted: 05 December 2025

  • Published: 03 February 2026

  • DOI: https://doi.org/10.1038/s41467-025-67779-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Associated content

Collection

In vitro models of human development

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Videos
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on Twitter
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Editors
  • Journal Information
  • Open Access Fees and Funding
  • Calls for Papers
  • Editorial Values Statement
  • Journal Metrics
  • Editors' Highlights
  • Contact
  • Editorial policies
  • Top Articles

Publish with us

  • For authors
  • For Reviewers
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Communications (Nat Commun)

ISSN 2041-1723 (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing