Pioneering work has revealed the broad patterns of gene expression across the mammalian brain (Lein et al., 2007). More recently, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful method for unbiased discovery of cell types and states based on gene activity (Islam et al., 2011, Jaitin et al., 2014, Macosko et al., 2015, Ramsköld et al., 2012, Shekhar et al., 2016, Tang et al., 2009, Tasic et al., 2016, Usoskin et al., 2015, Zeisel et al., 2015), and initiatives are underway to create atlases of both human and model organisms (Regev et al., 2017). Here, we used systematic scRNA-seq to survey cells across the central nervous system (CNS) and peripheral nervous system (PNS). We use the inferred molecular relationships between all cell types to propose a data-driven taxonomy of cell types, and we discuss the overall architecture of the mammalian nervous system in light of this taxonomy.
