ArticlePLoS computational biology2019
Transcriptomic correlates of electrophysiological and morphological diversity within and across excitatory and inhibitory neuron classes.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- A transcriptional program associated with neurotransmission in the living human brain.Molecular psychiatry · 2026Article
- A multimodal approach for visualizing and identifying electrophysiological cell types in vivo.Nature communications · 2026Article
- Autism spectrum disorder trios from consanguineous populations are enriched for rare homozygous variants, identifying 32 new candidate genes.Scientific reports · 2026Article
- Molecular and biophysical characterization of cultured DRG neurons in response to focused ultrasound.Scientific reports · 2026Article
- Higher-order interactions in neuronal function: From genes to ionic currents in biophysical models.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- In Search of Transcriptomic Correlates of Neuronal Firing-Rate Adaptation across Subtypes, Regions and Species: A Patch-seq Analysis.bioRxiv : the preprint server for biology · 2025Article
- A multimodal approach for visualization and identification of electrophysiological cell typesbioRxiv : the preprint server for biology · 2025Article
- In vivo cell-type and brain region classification via multimodal contrastive learning.bioRxiv : the preprint server for biology · 2025Article
- Transcriptomic Correlates of State Modulation in GABAergic Interneurons: A Cross-Species Analysis.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Loss of postnatal Arx transcriptional activity in parvalbumin interneurons reveals non-cell autonomous disturbances in CA1 pyramidal cells.Neuroscience · 2024Article
- Neurophysiological signatures of cortical micro-architecture.Nature communications · 2023Article
- Intrinsic neural diversity quenches the dynamic volatility of neural networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging.Neuroscience and biobehavioral reviews · 2023Review
- Neurophysiological signatures of cortical micro-architecture.bioRxiv : the preprint server for biology · 2023Article
- RNA Sequencing and Spatial Transcriptomics in Traumatic Spinal Cord Injury (Review).Sovremennye tekhnologii v meditsine · 2023Review
- Transient and Steady-State Properties ofFrontiers in cellular neuroscience · 2022Article
- Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics.Communications biology · 2021Article
- Sleep loss drives acetylcholine- and somatostatin interneuron-mediated gating of hippocampal activity to inhibit memory consolidation.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Cellular-resolution gene expression profiling in the neonatal marmoset brain reveals dynamic species- and region-specific differences.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Patch-seq: Past, Present, and Future.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
In order to further our understanding of how gene expression contributes to key functional properties of neurons, we combined publicly accessible gene expression, electrophysiology, and morphology measurements to identify cross-cell type correlations between these data modalities. Building on our previous work using a similar approach, we distinguished between correlations which were "class-driven," meaning those that could be explained by differences between excitatory and inhibitory cell classes, and those that reflected graded phenotypic differences within classes. Taking cell class identity into account increased the degree to which our results replicated in an independent dataset as well as their correspondence with known modes of ion channel function based on the literature. We also found a smaller set of genes whose relationships to electrophysiological or morphological properties appear to be specific to either excitatory or inhibitory cell types. Next, using data from PatchSeq experiments, allowing simultaneous single-cell characterization of gene expression and electrophysiology, we found that some of the gene-property correlations observed across cell types were further predictive of within-cell type heterogeneity. In summary, we have identified a number of relationships between gene expression, electrophysiology, and morphology that provide testable hypotheses for future studies.
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Registered trials
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