The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Mammalian hearing requires the development of the organ of Corti, a sensory epithelium comprising unique cell types. The limited number of each of these cell types, combined with their close proximity, has prevented characterization of individual cell types and/or their developmental progression. To examine cochlear development more closely, we transcriptionally profile approximately 30,000 isolated mouse cochlear cells collected at four developmental time points. Here we report on the analysis of those cells including the identification of both known and unknown cell types. Trajectory analysis for OHCs indicates four phases of gene expression while fate mapping of progenitor cells suggests that OHCs and their surrounding supporting cells arise from a distinct (lateral) progenitor pool. Tgfβr1 is identified as being expressed in lateral progenitor cells and a Tgfβr1 antagonist inhibits OHC development. These results provide insights regarding cochlear development and demonstrate the potential value and application of this data set.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

Normal vision in Drosophila requires NINAC, a class III myosin. Class III myosins are hybrid motor-signaling molecules, with an Nterminal kinase domain, highly conserved head and neck domains, and a class III-specific tail domain. In Drosophila rhabdomeres, NINAC interacts with actin filaments and with a PDZ scaffolding protein to organize the phototransduction machinery into a signaling complex. Recessive null mutations in Drosophila NINAC delay termination of the photoreceptor response and lead to progressive retinal degeneration. Here, we show that normal hearing in humans requires myosin IIIA, the human homolog of NINAC. In an extended Israeli family, nonsyndromic progressive hearing loss is caused by three different recessive, loss-of-function mutations in myosin IIIA. Of 18 affected relatives in Family N, 7 are homozygous and 11 are compound heterozygous for pairs of mutant alleles. Expression of mammalian myosin IIIA is highly restricted, with the strongest expression in retina and cochlea. The involvement of homologous class III myosins in both Drosophila vision and human hearing is an evolutionary link between these sensory systems.

Pou4f3 (Brn3.1, Brn3c) is a class IV POU domain transcription factor that has a central function in the development of all hair cells in the human and mouse inner ear sensory epithelia. A mutation of POU4F3 underlies human autosomal dominant non-syndromic progressive hearing loss DFNA15. Through a comparison of inner ear gene expression profiles of E16.5 wild-type and Pou4f3 mutant deaf mice using a high density oligonucleotide microarray, we identified the gene encoding growth factor independence 1 (Gfi1) as a likely in vivo target gene regulated by Pou4f3. To validate this result, we performed semi-quantitative RT-PCR and in situ hybridizations for Gfi1 on wild-type and Pou4f3 mutant mice. Our results demonstrate that a deficiency of Pou4f3 leads to a statistically significant reduction in Gfi1 expression levels and that the dynamics of Gfi1 mRNA abundance closely follow the pattern of expression for Pou4f3. To examine the role of Gfi1 in the pathogenesis of Pou4f3-related deafness, we performed comparative analyses of the embryonic inner ears of Pou4f3 and Gfi1 mouse mutants using immunohistochemistry and scanning electron microscopy. The loss of Gfi1 results in outer hair cell degeneration, which appears comparable to that observed in Pou4f3 mutants. These results identify Gfi1 as the first downstream target of a hair cell specific transcription factor and suggest that outer hair cell degeneration in Pou4f3 mutants is largely or entirely a result of the loss of expression of Gfi1.

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp.Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis. IntroductionNeural circuits are characterized by extraordinary diversity of their cellular components 1,2 . Single-cell molecular assays, especially transcriptomic measurements by RNA-Seq, have accelerated the discovery and characterization of cell types across brain regions and in diverse species. Recent advances include single-cell transcriptome datasets with >10 5 individual cells, identifying hundreds of neuronal and non-neuronal cell types across the mouse nervous system 3-5 . As the number of profiled cells grows into the millions, a key question is whether these data will converge toward a comprehensive and coherent taxonomy of cell types with broad utility for organizing knowledge of brain cells and their function. Data from different modalities, including transcriptomic and epigenomic data, must be cross-referenced and integrated to establish robust and consistent cell type classifications.Although a comprehensive atlas should incorporate anatomical and physiological information, the high throughput of single cell sequencing assays makes integration of molecular data a particularly urgent challenge. A rigorous and reproducible consensus molecular atlas of brain cell types would drive progress across modalities, including obtaining functional information.Single cell sequencing technologies can measure multiple molecular signatures of cell identity. The core molecular identity of a cell is largely established during development and maintained by a combination of gene regulatory proteins...

4 Laryngoscope, 128:S1-S13, 2018.