Distinct subtypes of proprioceptive dorsal root ganglion neurons regulate adaptive proprioception in mice.

Proprioceptive neurons (PNs) are essential for the proper execution of all our movements by providing muscle sensory feedback to the central motor network. Here, using deep single cell RNAseq of adult PNs coupled with virus and genetic tracings, we molecularly identify three main types of PNs (Ia, Ib and II) and find that they segregate into eight distinct subgroups. Our data unveil a highly sophisticated organization of PNs into discrete sensory input channels with distinct spatial distribution, innervation patterns and molecular profiles. Altogether, these features contribute to finely regulate proprioception during complex motor behavior. Moreover, while Ib- and II-PN subtypes are specified around birth, Ia-PN subtypes diversify later in life along with increased motor activity. We also show Ia-PNs plasticity following exercise training, suggesting Ia-PNs are important players in adaptive proprioceptive function in adult mice.

Single cell RNA sequencing identifies early diversity of sensory neurons forming via bi-potential intermediates.

Somatic sensation is defined by the existence of a diversity of primary sensory neurons with unique biological features and response profiles to external and internal stimuli. However, there is no coherent picture about how this diversity of cell states is transcriptionally generated. Here, we use deep single cell analysis to resolve fate splits and molecular biasing processes during sensory neurogenesis in mice. Our results identify a complex series of successive and specific transcriptional changes in post-mitotic neurons that delineate hierarchical regulatory states leading to the generation of the main sensory neuron classes. In addition, our analysis identifies previously undetected early gene modules expressed long before fate determination although being clearly associated with defined sensory subtypes. Overall, the early diversity of sensory neurons is generated through successive bi-potential intermediates in which synchronization of relevant gene modules and concurrent repression of competing fate programs precede cell fate stabilization and final commitment.

Muscle-selective RUNX3 dependence of sensorimotor circuit development.

The control of all our motor outputs requires constant monitoring by proprioceptive sensory neurons (PSNs) that convey continuous muscle sensory inputs to the spinal motor network. Yet the molecular programs that control the establishment of this sensorimotor circuit remain largely unknown. The transcription factor RUNX3 is essential for the early steps of PSNs differentiation, making it difficult to study its role during later aspects of PSNs specification. Here, we conditionally inactivate Runx3 in PSNs after peripheral innervation and identify that RUNX3 is necessary for maintenance of cell identity of only a subgroup of PSNs, without discernable cell death. RUNX3 also controls the sensorimotor connection between PSNs and motor neurons at limb level, with muscle-by-muscle variable sensitivities to the loss of Runx3 that correlate with levels of RUNX3 in PSNs. Finally, we find that muscles and neurotrophin 3 signaling are necessary for maintenance of RUNX3 expression in PSNs. Hence, a transcriptional regulator that is crucial for specifying a generic PSN type identity after neurogenesis is later regulated by target muscle-derived signals to contribute to the specialized aspects of the sensorimotor connection selectivity.

A cell fitness selection model for neuronal survival during development.

Developmental cell death plays an important role in the construction of functional neural circuits. In vertebrates, the canonical view proposes a selection of the surviving neurons through stochastic competition for target-derived neurotrophic signals, implying an equal potential for neurons to compete. Here we show an alternative cell fitness selection of neurons that is defined by a specific neuronal heterogeneity code. Proprioceptive sensory neurons that will undergo cell death and those that will survive exhibit different molecular signatures that are regulated by retinoic acid and transcription factors, and are independent of the target and neurotrophins. These molecular features are genetically encoded, representing two distinct subgroups of neurons with contrasted functional maturation states and survival outcome. Thus, in this model, a heterogeneous code of intrinsic cell fitness in neighboring neurons provides differential competitive advantage resulting in the selection of cells with higher capacity to survive and functionally integrate into neural networks.