Cited by 1,784Single-cell and spatial transcriptomicsDevelopmental Biology and Gene RegulationGenomics and Chromatin Dynamics

The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index; none of the 50 sources its claims cite is checked for support yet.

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays

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Published version of a preprint

Abstract

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

Overview

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Written from the paper’s full text.

TL;DR

Stereo-seq combines DNA nanoball-patterned arrays with in situ RNA capture to achieve large field-of-view spatial transcriptomics at cellular resolution. The authors use it to build MOSTA, a mouse organogenesis atlas spanning E9.5–E16.5, and demonstrate analyses of tissue patterning, cell heterogeneity, and developmental disease gene expression.

Key findings

  • Stereo-seq captured 69 UMI on average per 2 µm bin, 1,450 per 10 µm bin, and 133,776 per 100 µm bin in mouse olfactory bulb, outperforming Seq-Scope’s 848 UMI per 10 µm bin; adjacent sections were highly consistent (R² = 0.963).
  • MOSTA profiled 53 sagittal sections from C57BL/6 mouse embryos at E9.5–E16.5, yielding 3,511,403 bins; average captured genes per bin ranged from 1,770 at E15.5 to 3,900 at E10.5, and UMI from 4,357 at E15.5 to 13,789 at E9.5.
  • In an E16.5 embryo section, image-based segmentation yielded 281,377 cells with an average of 1,107 UMI and 529 genes per cell, resolving 25 major cell types; adult mouse hemibrain segmentation yielded 50,140 cells with an average of 1,910 UMI and 792 genes per cell.
  • Dorsal midbrain analysis showed spatially heterogeneous progenitor organization: radial glia were most abundant at E12.5, declined rostrally by E14.5, and concentrated caudally by E16.5; HES1 regulon was active in glioblasts and HES6 in neuroblasts. Over 10% of captured transcripts contained intronic reads, enabling spatial RNA velocity of interneuron migration.

Methods

  • Stereo-seq uses DNB-patterned arrays with random barcodes, in situ sequencing to assign coordinate identities, and UMI-polyT capture probes; 10 µm frozen tissue sections are fixed, permeabilized, reverse transcribed, amplified, and sequenced.
  • Samples included adult mouse olfactory bulb, adult coronal hemibrain, and C57BL/6J embryos from E9.5 to E16.5; 53 sagittal embryo sections were profiled, including 18 E16.5 sections (13 from one embryo and 5 from another).
  • Analyses used the SAW pipeline with STAR alignment to mm10 and UMI collapsing, spatially constrained clustering (SCC), image-based cell segmentation, SCENIC, Hotspot, Tangram, dynamo, and monocle 3.

Limitations

  • The paper states that cell segmentation may be imperfect when multiple cell types are close, especially smaller cell types like immune cells, and that low-expression genes may be missed due to capture limitations.
  • The paper states that 53 sections covering 23.4 cm² may not fully cover all regional tissue types; incomplete sampling could affect inference of anatomic relationships and developmental trajectories, and 3D transcriptomic rendering is not possible with the current dataset.
  • The paper states that functional validations are needed and that additional algorithms may be required for broader applications; evident from the text, the atlas is mouse-only and disease-gene projections are correlative rather than experimentally validated in this study.

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Integrity signals

Registry

Crossref · 10.1016/j.cell.2022.04.003

Cites

56 of 56 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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  • It may state two separate claims as one. 51
  • The quote only partly states this claim. 2
  • Probably not a substantial claim. 33
76 of 76
  • The paper relies on this without support.

    The lack of topographical information greatly complicates interpretations of the hierarchical mechanisms underlying the emergence of cell positioning and identities.

    “However, the lack of topographical information greatly complicates the interpretations of the hierarchical mechanisms underlying the emergence of cell positioning and identities.”
  • The paper relies on this without support.

    The laboratory mouse is an excellent model animal to study development and establish parallels with larger mammalian species.

    “The laboratory mouse is an excellent model animal to study development and establish parallels with larger mammalian species.”
  • The paper relies on this without support.

    The lack of spatial information in scRNA-seq data is likely to confound important associations in gene regulatory network analysis.

    “but the lack of spatial information is likely to confound important associations.”
  • The paper relies on this without support.

    Amalgamation of different signals in complex tissues can complicate interpretations.

    “This is important because amalgamation ofdifferent signals in complex tissues can complicate the interpretations.”
  • The paper relies on this without support.

    The precise regulation of cell identity in the developing brain is critical for the establishment of brain architecture but is yet poorly understood.

    “The precise regulation of cell identity in the developing brain is critical for the establishment of brain architecture but is yet poorly understood.”
  • The paper relies on this without support.

    The cell capture bias and lack of contextual microenvironment limits the power of scRNA-seq for predicting the origin and mechanisms of genetic diseases.

    “However, the cell capture bias and lack of contextual microenvironment limits the power of this approach.”
  • The paper relies on this without support.

    Dorsal cortical ventricular zones give rise to glutamatergic neurons that populate the cerebral cortex and hippocampus, and ventral ventricular zones of the lateral, medial, and caudal ganglionic eminence give rise to GABAergic interneurons that populate the striatum and globus pallidus and migrate into the cerebral cortex.

    “Dorsal cortical ventricular zones give rise to glutamatergic neurons that populate the cerebral cortex and hippocampus. The ventral ventricular zones of the lateral, medial, and caudal ganglionic eminence give rise to GABAergic interneurons that populate the striatum and globus pallidus and migrate into the cerebral cortex.”
  • The paper relies on this without support.

    The development of the dorsal midbrain has been less well characterized in terms of cellular taxonomy and organization compared with other brain regions.

    “However, its development has been less well characterized in terms of cellular taxonomy and organization compared with other brain regions.”
  • The paper relies on this without support.

    Topographic transcriptomic information is fundamental for dissection of the molecular events driving tissue patterning during development.

    “Topographic transcriptomic information is fundamental for dissection of the molecular events driving tissue patterning during development.”
  • The paper relies on this without support.

    Mice and humans differ in multiple aspects of normal physiology and disease.

    “Mice and humans differ in multiple aspects of normal physiology and disease; hence, there are caveats”
10 of 10

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  • Disease-gene count differs between Results and Methods

    Minor

    The Results and Figure 6A state that 1,959 disease-associated genes were analyzed, while the Methods state that filtering left 1,919 genes for further analysis.

  • Figure legend labels an E15.1 section despite E15.5 sampling

    Minor

    The Figure 3A legend identifies an E15.1 section, but the paper describes one-day sampling intervals and lists E15.5, not E15.1, among the collected embryonic stages.

2 of 2

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Metadata

Authors
Chen, A., Liao, S., Cheng, M., Ma, K., Wu, L., Lai, Y., Qiu, X., Yang, J., Xu, J., Hao, S., Wang, X., Lu, H., Chen, X., Liu, X., Huang, X., Li, Z., Hong, Y., Jiang, Y., Peng, J., Liu, S., Shen, M., Liu, C., Li, Q., Yuan, Y., Wei, X., Zheng, H., Feng, W., Wang, Z., Liu, Y., Wang, Z., Yang, Y., Xiang, H., Han, L., Qin, B., Guo, P., Lai, G., Muñoz-Cánoves, P., Maxwell, P. H., Thiery, J. P., Wu, Q.-F., Zhao, F., Chen, B., Li, M., Dai, X., Wang, S., Kuang, H., Hui, J., Wang, L., Fei, J.-F., Wang, O., Wei, X., Lu, H., Wang, B., Liu, S., Gu, Y., Ni, M., Zhang, W., Mu, F., Yin, Y., Yang, H., Lisby, M., Cornall, R. J., Mulder, J., Uhlén, M., Esteban, M. A., Li, Y., Liu, L., Xu, X., & Wang, J.
Affiliations
  • BGI Group (China) (CN)
  • Howard Hughes Medical Institute (US)
  • MGI (CN)
  • Chinese Academy of Sciences (CN)
  • University of Cambridge (GB)
  • Guangzhou Laboratory (CN)
  • Guangdong Academy of Medical Sciences (CN)
  • China National GeneBank (CN)
  • University of Copenhagen (DK)
  • University of Oxford (GB)
  • Science for Life Laboratory (SE)
Corresponding author
  • Esteban, Miguel A.
  • Li, Yuxiang
  • Liu, Longqi
  • Xu, Xun
  • Wang, Jian
Venue
Cell
Publisher
Elsevier BV
Published
2022-05
Volume
185
Issue
10
Pages
1777-1792.e21
ISSN
0092-8674 (ISSN-L)
OpenAlex
W4229033508
Cited by
1,784
References
54
Citations by year
2026: 526 · 2025: 509 · 2024: 427 · 2023: 227 · 2022: 94
FWCI
104.42
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
Funders
Medical Research Council (MC_UU_00008/6)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
spatiotemporal transcriptomics, Stereo-seq, spatial transcriptomics, embryonic development, dorsal midbrain, cell fate specification, transcriptional dynamics
MeSH terms
Animals, DNA, Embryo, Mammalian, Female, Mammals, Pregnancy, Sequence Analysis, RNA, Gene Expression Profiling, Organogenesis, Mice, Single-Cell Analysis, Transcriptome

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