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A critical step in the assembly of the neural circuits that control tetrapod locomotion is the specification of the lateral motor column (LMC), a diverse motor neuron population targeting limb musculature. Hox6 paralog group genes have been implicated as key determinants of LMC fate at forelimb levels of the spinal cord, through their ability to promote expression of the LMC-restricted genes Foxp1 and Raldh2 and to suppress thoracic fates through exclusion of Hoxc9. The specific roles and mechanisms of Hox6 gene function in LMC neurons, however, are not known. We show that Hox6 genes are critical for diverse facets of LMC identity and define motifs required for their in vivo specificities. Although Hox6 genes are necessary for generating the appropriate number of LMC neurons, they are not absolutely required for the induction of forelimb LMC molecular determinants. In the absence of Hox6 activity, LMC identity appears to be preserved through a diverse array of Hox5-Hox8 paralogs, which are sufficient to reprogram thoracic motor neurons to an LMC fate. In contrast to the apparently permissive Hox inputs to early LMC gene programs, individual Hox genes, such as Hoxc6, have specific roles in promoting motor neuron pool diversity within the LMC. Dissection of motifs required for Hox in vivo specificities reveals that either cross-repressive interactions or cooperativity with Pbx cofactors are sufficient to induce LMC identity, with the N-terminus capable of promoting columnar, but not pool, identity when transferred to a heterologous homeodomain. These results indicate that Hox proteins orchestrate diverse aspects of cell fate specification through both the convergent regulation of gene programs regulated by many paralogs and also more restricted actions encoded through specificity determinants in the N-terminus.

Complementary actions of the neocortex and the hippocampus enable encoding and long-term storage of experience dependent memories. Standard models for memory storage assume that sensory signals reach the hippocampus from superficial layers of the entorhinal cortex (EC). Deep layers of the EC on the other hand relay hippocampal outputs to the telencephalic structures including many parts of the neocortex. Here, we show that cells in layer 5a of the medial EC send a copy of their telencephalic outputs back to the CA1 region of the hippocampus. Combining cell-type-specific anatomical tracing with high-throughput RNA-sequencing based projection mapping and optogenetics aided circuit mapping, we show that in the mouse brain these projections have a unique topography and target hippocampal pyramidal cells and interneurons. Our results suggest that projections of deep medial EC neurons are anatomically configured to influence the hippocampus and neocortex simultaneously and therefore lead to novel hypotheses on the functional role of the deep EC.

Distinctions between cell types underpin organizational principles for nervous system function. Functional variation also exists between neurons of the same type. This is exemplified by correspondence between grid cell spatial scales and the synaptic integrative properties of stellate cells (SCs) in the medial entorhinal cortex. However, we know little about how functional variability is structured either within or between individuals. Using ex-vivo patch-clamp recordings from up to 55 SCs per mouse, we found that integrative properties vary between mice and, in contrast to the modularity of grid cell spatial scales, have a continuous dorsoventral organization. Our results constrain mechanisms for modular grid firing and provide evidence for inter-animal phenotypic variability among neurons of the same type. We suggest that neuron type properties are tuned to circuit-level set points that vary within and between animals.

Neural circuits in the medial entorhinal cortex (MEC) encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.