Bayesian Sparse Regression Analysis Documents the Diversity of Spinal Inhibitory Interneurons

Abstract

SUMMARY Documenting the extent of cellular diversity is a critical step in defining the functional organization of tissues and organs. To infer cell type diversity from partial or incomplete transcription factor expression data we devised a sparse Bayesian framework that is able to handle estimation uncertainty, and can incorporate diverse cellular characteristics to optimize experimental design. Focusing on spinal V1 inhibitory interneurons, for which the spatial expression of 19 transcription factors has been mapped, we infer the existence of approximately 50 candidate V1 neuronal types, many of which localize in compact spatial domains in the ventral spinal cord. We have validated the existence of inferred cell types by direct experimental measurement, establishing this Bayesian framework as an effective platform for cell type characterization in the nervous system and elsewhere.

Spinal Inhibitory Interneuron Diversity Delineates Variant Motor Microcircuits

“…We estimated the number of neuronal types within the parental V1 population through application of a Bayesian sparse linear regression algorithm that assigns V1 interneuron cell types on the basis of TF expression and settling position (Gabitto et al, 2016). The extent of co-expression was determined for binary TF combinations, with each pairing gated to LacZ + neurons in p0 En1.LacZ mice (Figure 2D).…”

“…The extent of co-expression was determined for binary TF combinations, with each pairing gated to LacZ + neurons in p0 En1.LacZ mice (Figure 2D). This analysis assigns 50 ± 2 V1 interneuron cell types, some defined by as many as 9 TFs (Gabitto et al, 2016). Four TFs - FoxP2, MafA, Pou6f2, and Sp8 - delineate non-overlapping clades that comprise 64% of the parental V1 population at p0, with each clade containing multiple cell types (Figures 2C,E and S2D).…”

“…Since individual V1 cell types are defined by as many as 9 TFs (Gabitto et al, 2016), it is not practical to delineate them on the basis of their complete transcriptional profile. We therefore assessed the spatial distributions defined by each of the 19 V1 TFs individually (Figure S3A) or in a few cases by the superimposition of two TFs (Figure S3B).…”

“…In this study we use molecular genetic approaches, and in an accompanying paper statistical analysis (Gabitto et al, 2016), to delineate the extent and consequences of diversity within the V1 interneuron population. This combined analysis reveals that V1 interneurons can be fragmented into fifty transcriptionally defined subtypes.…”

Making sense out of spinal cord somatosensory development

“…While progress has been made on all these fronts, we are just at the tip of the iceberg. Indeed, extensive molecular analysis of the V1 population in the ventral spinal cord has identified up to 50 transcriptionally defined subsets that distinguish neuronal populations with unique physiological properties and connectivity Gabitto et al, 2016). Similarly, identification of molecularly and developmentally defined populations in the dorsal horn is beginning to distinguish microcircuits that mediate particular somatosensory behaviors, such as mechanical allodynia and proprioception (Duan et al, 2014;Peirs et al, 2015;Yuengert et al, 2015).…”