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Whole-cortex in situ sequencing reveals peripheral input-dependent cell type-defined area identity

View ORCID ProfileXiaoyin Chen, View ORCID ProfileStephan Fischer, View ORCID ProfileMara CP Rue, View ORCID ProfileAixin Zhang, View ORCID ProfileDidhiti Mukherjee, View ORCID ProfilePatrick O Kanold, View ORCID ProfileJesse Gillis, View ORCID ProfileAnthony M Zador
doi: https://doi.org/10.1101/2022.11.06.515380
Xiaoyin Chen
1Allen Institute for Brain Science, Seattle, WA, USA
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  • For correspondence: [email protected] [email protected] [email protected]
Stephan Fischer
2Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, F-75015 Paris, France
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Mara CP Rue
1Allen Institute for Brain Science, Seattle, WA, USA
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Aixin Zhang
1Allen Institute for Brain Science, Seattle, WA, USA
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Didhiti Mukherjee
3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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Patrick O Kanold
3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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Jesse Gillis
4Department of Physiology, University of Toronto, Toronto, Ontario, Canada
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Anthony M Zador
5Cold Spring Harbor Laboratory, New York, NY, USA
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  • For correspondence: [email protected] [email protected] [email protected]
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Abstract

The cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture (Brodmann 1909; Vogt and Vogt 1919; Von Bonin 1947), connectivity (Zingg et al. 2014; Harris et al. 2019), and neuronal activity (Schwarz et al. 2008; Ferrarini et al. 2009; He et al. 2009; Meunier et al. 2010; Bertolero et al. 2015), are wired into modular networks (Zingg et al. 2014; Harris et al. 2019; Huang et al. 2020). However, it remains unclear whether cortical areas and their modular organization can be similarly defined by their transcriptomic signatures and how such signatures are established in development. Here we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell type marker genes in 10.3 million cells, including 4,194,658 cortical neurons over nine mouse forebrain hemispheres at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types that were consistent with previous single-cell RNAseq studies(Yao et al. 2021a; Yao et al. 2021b). Gene expression and the distribution of fine-grained cell types vary along the contours of cortical areas, and the composition of transcriptomic types are highly predictive of cortical area identity. Moreover, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with areas that are highly connected, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. To explore how the transcriptomic profiles of cortical neurons depend on development, we compared the cell type distributions after neonatal binocular enucleation. Strikingly, binocular enucleation caused the cell type compositional profiles of visual areas to shift towards neighboring areas within the same cortical module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules. Enabled by the high-throughput, low-cost, and reproducibility of BARseq, our study provides a proof-of-principle for using large-scale in situ sequencing to reveal brain-wide molecular architecture and to understand its development.

Competing Interest Statement

A.M.Z. is a founder and equity owner of Cajal Neuroscience and a member of its scientific advisory board. The remaining authors declare no competing interests.

Footnotes

  • In this revision, we added substantial in situ sequencing data from additional four pairs of littermates (total eight animals), each with a control animal and an animal after binocular enucleation during early post-natal development. This new dataset not only was a technological feat (total 10.3 million cells sequenced in situ from 9 mouse forebrain hemispheres), but also allowed us to examine how peripheral sensory inputs shape both the gene expression of individual cortical neurons and the cell type compositional profiles of cortical areas. The brain-wide scale of the dataset further enabled us to interpret the observed changes in the context of whole-cortex organization. Figure 6-8 are added/updated. Three new Results sections are added and substantial changes to the Discussion. Added authors and updated Supplemental files.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 04, 2023.
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Whole-cortex in situ sequencing reveals peripheral input-dependent cell type-defined area identity
Xiaoyin Chen, Stephan Fischer, Mara CP Rue, Aixin Zhang, Didhiti Mukherjee, Patrick O Kanold, Jesse Gillis, Anthony M Zador
bioRxiv 2022.11.06.515380; doi: https://doi.org/10.1101/2022.11.06.515380
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Whole-cortex in situ sequencing reveals peripheral input-dependent cell type-defined area identity
Xiaoyin Chen, Stephan Fischer, Mara CP Rue, Aixin Zhang, Didhiti Mukherjee, Patrick O Kanold, Jesse Gillis, Anthony M Zador
bioRxiv 2022.11.06.515380; doi: https://doi.org/10.1101/2022.11.06.515380

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