Single-Cell Analysis of Experience-Dependent Transcriptomic States in Mouse Visual Cortex

By Siniša Hrvatin, Daniel R. Hochbaum, M. Nagy, Marcelo Cicconet, Keiramarie Robertson, Lucas Cheadle, R. Zilionis, Alex Ratner, Rebeca Borges-Monroy, Allon M. Klein and 2 more. 2017

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Activity-dependent transcriptional responses shape cortical function. However, a comprehensive understanding of the diversity of these responses across the full range of cortical cell types, and how these changes contribute to neuronal plasticity and disease, is lacking. To investigate the breadth of transcriptional changes that occur across cell types in the mouse visual cortex after exposure to light, we applied high-throughput single-cell RNA sequencing. We identified significant and divergent transcriptional responses to stimulation in each of the 30 cell types characterized, thus revealing 611 stimulus-responsive genes. Excitatory pyramidal neurons exhibited inter- and intralaminar heterogeneity in the induction of stimulus-responsive genes. Non-neuronal cells showed clear transcriptional responses that may regulate experience-dependent changes in neurovascular coupling and myelination. Together, these results reveal the dynamic landscape of the stimulus-dependent transcriptional changes occurring across cell types in the visual cortex; these changes are probably critical for cortical function and may be sites of deregulation in developmental brain disorders. Using single-cell RNA-sequencing, the authors record snapshots of the dynamic sensory-experience-dependent transcriptome across all cell types of the visual cortex in mice exposed to a light stimulus. The authors note diverse cell-type-specific programs in pyramidal neuron subtypes and robust non-neuronal responses that may regulate experience-dependent neurovascular coupling and myelination.

Subfields: Cognitive Neuroscience, Molecular Biology, Neurology

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Citations in the corpus

The blood–brain barrier in health and disease: Important unanswered questions (2020, background): “Leakage is evident within hours of the primary insult, is subsequently reduced, and then reappears the day after (Huang et al., 1999; Kuroiwa et al., 1985; Fig.”
Three-dimensional intact-tissue sequencing of single-cell transcriptional states (2018, unknown): “In one arm of the experiment, visually evoked neural activity was provided to a cohort of mice via 1 hour of light exposure after 4 days of housing in the dark; other mice were kept continuously in the dark (27, 28).”
Deciphering cell–cell interactions and communication from gene expression (2020, methodology): “To date, this approach has been applied to brain 31,32 , heart 33,34 , kidney 35–37 , liver 38,39 , lungs 40–43 , placenta 29,30,44 , retina 45 and visual cortex 46 .”
A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain (2018, background): “In neurons, the most well-studied cell state, involving the expression of the immediate early genes (IEGs), is activated by Ca 2+ influx after neuronal action potential firing (Bading, 2013; Hrvatin et al., 2017).”
Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain (2018, background): “IEG expression is largely uniform across neuronal types (Hrvatin et al., 2017) and brain regions and exhibits little background expression, making it straightforward to detect in the Drop-seq data.”
DrImpute: imputing dropout events in single cell RNA sequencing data (2017, methodology): “The “ silver standard ” datasets included: Usoskin [34] and Hrvatin [35] datasets, where the cell labels were computationally derived and assigned based on the authors ’ knowledge of the underlying biology.”
SAVER: Gene expression recovery for single-cell RNA sequencing (2018, methodology): “Finally, we demonstrated SAVER in the analysis of a mouse visual cortex dataset where 47,209 cells were classified into main cell types and subtypes through extensive analysis 20 .”