Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Cell Types and Their Activity During Behavior

To understand the cellular basis of behavior, it is necessary to know the types of cells that exist in the nervous system and their contributions to function. Spinal cord networks are essential for sensory processing and motor behavior; however, the cellular correlates of these functions are not well understood. Here, we developed a massively parallel single nucleus RNA sequencing technique to first create a cell type atlas of the adult mouse spinal cord and then to use the transcriptional signatures of neuronal activity to map the cell types associated with specific behaviors. This approach, which we term Activity-SEQ, provided a broad and unbiased definition of the set of neuronal populations that were active in response to a painful stimulus and during locomotion. In the future, Activity-SEQ could provide a powerful strategy to reveal the molecular and cellular basis for a wide range of behaviors. Single-cell RNA profiles for nuclei collected from 24 different mouse brains via Drop-Seq protocol. Included among the nuclei profiled were those from 9 control mice (f1, m1, M4, M5, F3, F4, facx, fbcx, Macx), 10 formalin-exposed mice, and 5 rotarod-challenged mice.