Integrating single-cell transcriptomics and microcircuit computer modeling

Biophysically realistic computer modeling of neuronal microcircuitry has served as a testing ground for hypotheses related to the structure and function of different brain microcircuits. Recent advances in single-cell transcriptomics provide snapshots of a neuron's molecular state and have demonstrated that cell-specific genetic markers engineer the electrophysiological properties of a neuron. Integrating these molecular details with biophysical modeling can allow unprecedented mechanistic insights. In this opinion review, we consider systems biology-based strategies involving statistical deconvolution and gene ontology to integrate the two approaches. We foresee that this integration will infer the nonlinear interactions between the transcriptomically detailed neurons in different brain states. For an initial assessment of these integrative strategies, we recommend testing them on a penetrant phenotype such as epilepsy or a basic organism model such as Caenorhabditis elegans.