Patch-seq analysis reveals transcriptomic correlates of neuronal firing rate adaptation across subtypes and species
Abstract
Can the transcriptomic profile of a neuron predict its physiological properties? Using a Patch-seq dataset of the primary visual cortex, we addressed this question by focusing on spike rate adaptation (SRA), a well-known phenomenon that depends on small conductance calcium (Ca)-dependent potassium (SK) channels. We first show that in parvalbumin-expressing (PV) and somatostatin-expressing (SST) interneurons, expression levels of genes encoding the ion channels underlying action potential generation are correlated with the half-width (HW) of spikes. Surprisingly, the SK encoding genes are not correlated with the degree of SRA (dAdap). Instead, genes that encode proteins upstream from the SK current, as well as the low-voltage-activated calcium channel, are correlated with dAdap. This general principle is supported by datasets from the mouse primary motor cortex and multiple macaque brain regions. Finally, we generate testable predictions by constructing a minimal computational model.
Related
- Comparative Genomic, Metabolic and Transcriptomic Profiling of Bacterial Isolates Reveals Strain-Specific Adaptation and Safety Traits
- Time-resolved transcriptomic analysis reveals envelope stress–mediated adaptation of Escherichia coli to the LPS transport inhibitor thanatin
- Transcriptomic Study of Diffuse Large B-Cell Lymphoma Associated with HIV Infection: Identification of Novel Molecular Subtypes
- DNA methylation reveals molecular heterogeneity and urate excretion-associated subtypes of gout
- Type I interferon signature strength correlates with alloimmunization-associated transcriptomic programs in systemic lupus erythematosus: A multi-cohort analysis
BibTeX
@article{meng2026patchseq,
title = {{Patch-seq analysis reveals transcriptomic correlates of neuronal firing rate adaptation across subtypes and species}},
author = {John Hongyu Meng and Yijie Kang and Alan Lai and Michael Feyerabend and Wataru Inoue and Julio Martinez-Trujillo and Bernardo Rudy and Xiao-Jing Wang},
journal = {iScience},
year = {2026},
month = oct,
doi = {10.1016/j.isci.2026.117712},
url = {https://www.cell.com/iscience/fulltext/S2589-0042(26)03093-2},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Patch-seq analysis reveals transcriptomic correlates of neuronal firing rate adaptation across subtypes and species
AU - John Hongyu Meng
AU - Yijie Kang
AU - Alan Lai
AU - Michael Feyerabend
AU - Wataru Inoue
AU - Julio Martinez-Trujillo
AU - Bernardo Rudy
AU - Xiao-Jing Wang
PY - 2026
DA - 2026/10/08
JO - iScience
DO - 10.1016/j.isci.2026.117712
UR - https://www.cell.com/iscience/fulltext/S2589-0042(26)03093-2
AB - Can the transcriptomic profile of a neuron predict its physiological properties? Using a Patch-seq dataset of the primary visual cortex, we addressed this question by focusing on spike rate adaptation (SRA), a well-known phenomenon that depends on small conductance calcium (Ca)-dependent potassium (SK) channels. We first show that in parvalbumin-expressing (PV) and somatostatin-expressing (SST) interneurons, expression levels of genes encoding the ion channels underlying action potential generation are correlated with the half-width (HW) of spikes. Surprisingly, the SK encoding genes are not correlated with the degree of SRA (dAdap). Instead, genes that encode proteins upstream from the SK current, as well as the low-voltage-activated calcium channel, are correlated with dAdap. This general principle is supported by datasets from the mouse primary motor cortex and multiple macaque brain regions. Finally, we generate testable predictions by constructing a minimal computational model.
SN - 2589-0042
ER -