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Only two avian oncogenic viruses specifically cause acute leukaemias yet do not transform chicken fibroblasts in culture: E26, which causes erythroblastosis and a low level of concomitant myeloblastosis in chickens, and avian myeloblastosis virus (AMV), which causes myeloblastosis exclusively. Both viruses are replication-defective and share a sequence termed myb (also known as amv) which is unrelated to essential virion genes and is therefore thought to be part of the transforming onc genes of these viruses. However, the genetic structure of the two viruses differs. E26 has a genomic RNA of 5.7 kilobases (kb) and encodes a 135,000 molecular weight gag-related protein (p135) with probable transforming function. We show here by in vitro translation that the 5.7-kb E26 RNA directs the synthesis of p135. Oligonucleotide analysis indicates that E26 RNA contains an internal 0.8-kb subset of the 1.2-kb AMV-related sequence (mybA), termed mybE. A 2.46-kb molecular clone prepared from cDNA transcribed in vitro from E26 RNA contained an E26 transformation-specific (ets) sequence flanked by mybE and an env-related sequence. A complete DNA sequence of this clone indicates that the 1.5-kb ets sequence extends the open reading frame of mybE for 491 amino acids. Thus, the p135 gene of E26 is a genetic hybrid of three distinct elements, approximately 1.2 kb derived from the 5' region of the retroviral gag gene, mybE and the ets sequence, linked in the order 5'-delta gag-mybE-ets-3'. The myeloid leukaemogenicity shared by E26 and AMV correlates with the common myb sequence, while the distinct erythroid leukaemogenicity of E26 correlates with ets and the E26-specific linkage of myb to delta gag.

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.

Mammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer–gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.

The mammalian cerebrum performs high-level sensory perception, motor control and cognitive functions through highly specialized cortical and subcortical structures1. Recent surveys of mouse and human brains with single-cell transcriptomics2–6 and high-throughput imaging technologies7,8 have uncovered hundreds of neural cell types distributed in different brain regions, but the transcriptional regulatory programs that are responsible for the unique identity and function of each cell type remain unknown. Here we probe the accessible chromatin in more than 800,000 individual nuclei from 45 regions that span the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to map the state of 491,818 candidate cis-regulatory DNA elements in 160 distinct cell types. We find high specificity of spatial distribution for not only excitatory neurons, but also most classes of inhibitory neurons and a subset of glial cell types. We characterize the gene regulatory sequences associated with the regional specificity within these cell types. We further link a considerable fraction of the cis-regulatory elements to putative target genes expressed in diverse cerebral cell types and predict transcriptional regulators that are involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of noncoding risk variants associated with various neurological diseases and traits in humans.