Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. Here, we construct a cellular taxonomy of one cortical region, primary visual cortex, in adult mice based on single cell RNA-sequencing. We identify 49 transcriptomic cell types including 23 GABAergic, 19 glutamatergic and seven non-neuronal types. We also analyze cell-type specific mRNA processing and characterize genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we show that some of our transcriptomic cell types display specific and differential electrophysiological and axon projection properties, thereby confirming that the single cell transcriptomic signatures can be associated with specific cellular properties.

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation Graphical abstract Highlights d Single-cell transcriptomics from >1.3 million cells in the mouse cortex and hippocampus d Many neuron types specific to associational cortex and hippocampal regions are identified d Parallel cell-type and laminar organization between isocortex and hippocampal formation d Large-scale continuous neuron-type variation in isocortex and hippocampus/subiculum

Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

In humans and other mammalian species, lesions in the preoptic area (POA) of the hypothalamus cause profound sleep impairment1–5, indicating a crucial role of the POA in sleep generation. However, the underlying circuit mechanism remains poorly understood. Electrophysiological recordings and c-Fos immunohistochemistry showed the existence of sleep-active neurons in the POA, especially in the ventrolateral preoptic area (VLPO) and median preoptic nucleus (MnPO)6–9. Pharmacogenetic activation of c-Fos-labeled sleep-active neurons has been shown to induce sleep10. However, the sleep-active neurons are spatially intermingled with wake-active neurons6,7, making it difficult to target the sleep neurons specifically for circuit analysis. Here, we have identified a population of POA sleep neurons based on their projection target and discovered their molecular markers. Using a lentivirus expressing channelrhodopsin-2 (ChR2) or a light-activated chloride channel (iC++) for retrograde labeling, bidirectional optogenetic manipulation, and optrode recording, we showed that the POA GABAergic neurons projecting to the tuberomammillary nucleus (TMN) are both sleep active and sleep promoting. Furthermore, translating ribosome affinity purification (TRAP) and single-cell RNA-seq identified candidate markers for these neurons, and optogenetic and pharmacogenetic manipulations demonstrated that several peptide markers (cholecystokinin, corticotropin releasing hormone, and tachykinin 1) label sleep-promoting neurons. Together, these findings provide easy genetic access to sleep-promoting POA neurons and a valuable entry point for dissecting the sleep control circuit.

SUMMARY To provide a temporal framework for the genoarchitecture of brain development, in situ hybridization data were generated for embryonic and postnatal mouse brain at 7 developmental stages for ~2100 genes, processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, 7 reference atlases, an ontogenetic ontology, and tools to explore co-expression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (developingmouse.brain-map.org).

Activity in motor cortex predicts specific movements, seconds before they are initiated. This preparatory activity has been observed in L5 descending 'pyramidal tract' (PT) neurons. A key question is how preparatory activity can be maintained without causing movement, and how preparatory activity is eventually converted to a motor command to trigger appropriate movements. We used single cell transcriptional profiling and axonal reconstructions to identify two types of PT neuron. Both types share projections to multiple targets in the basal ganglia and brainstem. One type projects to thalamic regions that connect back to motor cortex. In a delayed-response task, these neurons produced early preparatory activity that persisted until the movement. The second type projects to motor centers in the medulla and produced late preparatory activity and motor commands. These results indicate that two motor cortex output neurons are specialized for distinct roles in motor control.