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High-resolution spatial transcriptomics and cell lineage analysis reveal spatiotemporal cell fate determination during craniofacial development

Author

Listed:
  • Jifan Feng

    (Los Angeles)

  • Eva Janečková

    (Los Angeles)

  • Tingwei Guo

    (Los Angeles)

  • Heliya Ziaei

    (Los Angeles)

  • Mingyi Zhang

    (Los Angeles)

  • Jessica Junyan Geng

    (Los Angeles)

  • Sa Cha

    (Los Angeles)

  • Angelita Araujo-Villalba

    (Los Angeles)

  • Mengmeng Liu

    (Los Angeles)

  • Thach-Vu Ho

    (Los Angeles)

  • Yang Chai

    (Los Angeles)

Abstract

The differentiation of post-migratory cranial neural crest cells (CNCCs) into distinct mesenchymal lineages is crucial for craniofacial development. Here we report a high-resolution spatiotemporal transcriptomic and cell-type atlas of CNCC-derived mesenchymal lineage diversification during mouse palatogenesis. We systematically defined each mesenchymal cell type by mapping their transcriptomic profiles to spatial identities. Integrative analysis of spatial transcriptomic data from E12.5 to E15.5 further revealed mesenchymal lineage establishment at or prior to initiation of palatogenesis. We also identified a heterogeneous Sox9+ mesenchymal progenitor population at the onset of palatal development, with subpopulations already activating early lineage-specific markers. In vivo lineage tracing using these early lineage-specific markers demonstrated that distinct mesenchymal populations are established as early as E10.5 to E11.5, preceding palatal development, and contribute to their respective lineages. Together, our findings reveal the comprehensive, dynamic molecular and cellular landscape of palate development and shed light on cell fate regulation during embryogenesis.

Suggested Citation

  • Jifan Feng & Eva Janečková & Tingwei Guo & Heliya Ziaei & Mingyi Zhang & Jessica Junyan Geng & Sa Cha & Angelita Araujo-Villalba & Mengmeng Liu & Thach-Vu Ho & Yang Chai, 2025. "High-resolution spatial transcriptomics and cell lineage analysis reveal spatiotemporal cell fate determination during craniofacial development," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59206-2
    DOI: 10.1038/s41467-025-59206-2
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    References listed on IDEAS

    as
    1. Junjun Jing & Jifan Feng & Yuan Yuan & Tingwei Guo & Jie Lei & Fei Pei & Thach-Vu Ho & Yang Chai, 2022. "Spatiotemporal single-cell regulatory atlas reveals neural crest lineage diversification and cellular function during tooth morphogenesis," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    2. C. Biben & T. S. Weber & K. S. Potts & J. Choi & D. C. Miles & A. Carmagnac & T. Sargeant & C. A. Graaf & K. A. Fennell & A. Farley & O. J. Stonehouse & M. A. Dawson & D. J. Hilton & S. H. Naik & S. T, 2023. "In vivo clonal tracking reveals evidence of haemangioblast and haematomesoblast contribution to yolk sac haematopoiesis," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. D’Juan T. Farmer & Hana Mlcochova & Yan Zhou & Nils Koelling & Guanlin Wang & Neil Ashley & Helena Bugacov & Hung-Jhen Chen & Riana Parvez & Kuo-Chang Tseng & Amy E. Merrill & Robert E. Maxson & Andre, 2021. "The developing mouse coronal suture at single-cell resolution," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    4. Fangfang Yan & Akiko Suzuki & Chihiro Iwaya & Guangsheng Pei & Xian Chen & Hiroki Yoshioka & Meifang Yu & Lukas M. Simon & Junichi Iwata & Zhongming Zhao, 2024. "Single-cell multiomics decodes regulatory programs for mouse secondary palate development," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    5. Chee-Huat Linus Eng & Michael Lawson & Qian Zhu & Ruben Dries & Noushin Koulena & Yodai Takei & Jina Yun & Christopher Cronin & Christoph Karp & Guo-Cheng Yuan & Long Cai, 2019. "Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+," Nature, Nature, vol. 568(7751), pages 235-239, April.
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