Connectomics of predicted Sst transcriptomic types in mouse visual cortex

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between them<sup>1</sup>. Neural cell types have previously been defined by morphology<sup>2,3</sup>, electrophysiology<sup>4</sup>, transcriptomic expression<sup>5,6</sup>, connectivity<sup>7-9</sup> or a combination of such modalities<sup>10-12</sup>. The Patch-seq technique enables the characterization of morphology, electrophysiology and transcriptomic properties from individual cells<sup>13-15</sup>. These properties were integrated to define 28 inhibitory, morpho-electric-transcriptomic (MET) cell types in mouse visual cortex<sup>16</sup>, which do not include synaptic connectivity. Conversely, large-scale electron microscopy (EM) enables morphological reconstruction and a near-complete description of a neuron's local synaptic connectivity, but does not include transcriptomic or electrophysiological information. Here, we leveraged morphological information from Patch-seq to predict the transcriptomically defined cell subclass and/or MET-type of inhibitory neurons within a large-scale EM dataset. We further analysed Martinotti cells-a somatostatin (Sst)-positive<sup>17</sup> morphological cell type<sup>18,19</sup>-which were classified successfully into Sst MET-types with distinct axon myelination and synaptic output connectivity patterns. We demonstrate that morphological features can be used to link cell types across experimental modalities, enabling further comparison of connectivity to gene expression and electrophysiology. We observe unique connectivity rules for predicted Sst cell types.

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Journal
Nature
Published
2025-04-09
DOI
https://doi.org/10.1038/s41586-025-08805-6
Citations
18
Primary Topic
Neural dynamics and brain function
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article
Field-Weighted Citation Impact
24.33
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article

Connectomics of predicted Sst transcriptomic types in mouse visual cortex

Ágnes L. Bodor, R. Clay Reid, Hongkui Zeng, Philip R. Nicovich et al.
18 citations
Nature
Neural dynamics and brain function
24.33
article

Connectomics of predicted Sst transcriptomic types in mouse visual cortex

Ágnes L. Bodor, R. Clay Reid, Hongkui Zeng, Philip R. Nicovich, Sergiy Popovych, JoAnn Buchanan, Szi-chieh Yu, Clare Gamlin, Nuno Maçarico da Costa, Thomas Macrina, William S. Wong, Zhen Jia, Matthew Mallory, Tim Jarsky, Nathan W. Gouwens, Russel Torres, Sven Dorkenwald, Shanka Subhra Mondal, Manuel Castro, Leila Elabbady, Emily Joyce, Jim Berg, Nicholas L. Turner, H. Sebastian Seung, William Silversmith, Nico Kemnitz, Jingpeng Wu, Sam Kinn, Staci A. Sorensen, Marc Takeno, Daniel J. Bumbarger, Shang Mu, Akhilesh Halageri, Casey M Schneider-Mizell, Alice Mukora, Grace Williams, Eric Mitchell, Gayathri Mahalingam, Sharmishtaa Seshamani, Forrest Collman, Barak Nehoran, Rachel Dalley, Derrick Brittain, Daniel Kapner, Brian Lee, Kai Li, J. Alexander Bae, Wenjing Yin, Kisuk Lee, Ran Lu, Chris Jordan
article en
18 citations

Abstract

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between them<sup>1</sup>. Neural cell types have previously been defined by morphology<sup>2,3</sup>, electrophysiology<sup>4</sup>, transcriptomic expression<sup>5,6</sup>, connectivity<sup>7-9</sup> or a combination of such modalities<sup>10-12</sup>. The Patch-seq technique enables the characterization of morphology, electrophysiology and transcriptomic properties from individual cells<sup>13-15</sup>. These properties were integrated to define 28 inhibitory, morpho-electric-transcriptomic (MET) cell types in mouse visual cortex<sup>16</sup>, which do not include synaptic connectivity. Conversely, large-scale electron microscopy (EM) enables morphological reconstruction and a near-complete description of a neuron's local synaptic connectivity, but does not include transcriptomic or electrophysiological information. Here, we leveraged morphological information from Patch-seq to predict the transcriptomically defined cell subclass and/or MET-type of inhibitory neurons within a large-scale EM dataset. We further analysed Martinotti cells-a somatostatin (Sst)-positive<sup>17</sup> morphological cell type<sup>18,19</sup>-which were classified successfully into Sst MET-types with distinct axon myelination and synaptic output connectivity patterns. We demonstrate that morphological features can be used to link cell types across experimental modalities, enabling further comparison of connectivity to gene expression and electrophysiology. We observe unique connectivity rules for predicted Sst cell types.

NatureVol. 640(8058)
Allen Institute for Brain Science (US), Princeton University (US), University of Washington (US), Allen Institute (US), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 0%
Neural dynamics and brain function
24.33
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