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 (INs), 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 gene is not correlated with the degree of SRA (dAdap). Instead, genes that encode proteins upstream from the SK current are correlated with dAdap, a finding validated by a different dataset from the mouse's primary motor cortex that includes pyramidal cells and interneurons, as well as physiological datasets from multiple regions of macaque monkeys. Finally, we construct a minimal model to reproduce observed heterogeneity across cells, with testable predictions.