Transcriptomic correlates of neuron electrophysiological diversity.

ABSTRACT: How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date. We identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 physiological parameters. We next trained statistical models to infer cellular features from multivariate gene expression patterns. Such models were predictive of gene-ele

SUBMITTER: Tripathy SJ 

PROVIDER: S-EPMC5673240 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature