A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain, bioRxiv, 2018-04-10

The mammalian brain is composed of diverse, specialized cell populations, few of which we fully understand. To more systematically ascertain and learn from cellular specializations in the brain, we used Drop-seq to perform single-cell RNA sequencing of 690,000 cells sampled from nine regions of the adult mouse brain frontal and posterior cortex (156,000 and 99,000 cells, respectively), hippocampus (113,000), thalamus (89,000), cerebellum (26,000), and all of the basal ganglia – the striatum (77,000), globus pallidus externusnucleus basalis (66,000), entopeduncularsubthalamic nuclei (19,000), and the substantia nigraventral tegmental area (44,000). We developed computational approaches to distinguish biological from technical signals in single-cell data, then identified 565 transcriptionally distinct groups of cells, which we annotate and present through interactive online software we developed for visualizing and re-analyzing these data (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpdropviz.org>DropViz<jatsext-link>). Comparison of cell classes and types across regions revealed features of brain organization. These included a neuronal gene-expression module for synthesizing axonal and presynaptic components; widely shared patterns in the combinatorial co-deployment of voltage-gated ion channels by diverse neuronal populations; functional distinctions among cells of the brain vasculature; and specialization of glutamatergic neurons across cortical regions to a degree not observed in other neuronal or non-neuronal populations. We describe systematic neuronal classifications for two complex, understudied regions of the basal ganglia, the globus pallidus externus and substantia nigra reticulata. In the striatum, where neuron types have been intensely researched, our data reveal a previously undescribed population of striatal spiny projection neurons (SPNs) comprising 4% of SPNs. The adult mouse brain cell atlas can serve as a reference for analyses of development, disease, and evolution.

biorxiv neuroscience 200-500-users 2018

Accurate functional classification of thousands of BRCA1 variants with saturation genome editing, bioRxiv, 2018-04-05

AbstractVariants of uncertain significance (VUS) fundamentally limit the utility of genetic information in a clinical setting. The challenge of VUS is epitomized by BRCA1, a tumor suppressor gene integral to DNA repair and genomic stability. Germline BRCA1 loss-of-function (LOF) variants predispose women to early-onset breast and ovarian cancers. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Data sharing attenuates this problem but it is unlikely to solve it, as most newly observed variants are exceedingly rare. In lieu of genetic evidence, experimental approaches can be used to functionally characterize VUS. However, to date, functional studies of BRCA1 VUS have been conducted in a post hoc, piecemeal fashion. Here we employ saturation genome editing to assay 96.5% of all possible single nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Our assay measures cellular fitness in a haploid human cell line whose survival is dependent on intact BRCA1 function. The resulting function scores for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Sequence-function maps enhanced by parallel measurements of variant effects on mRNA levels reveal mechanisms by which loss-of-function SNVs arise. Hundreds of missense SNVs critical for protein function are identified, as well as dozens of exonic and intronic SNVs that compromise BRCA1 function by disrupting splicing or transcript stability. We predict that these function scores will be directly useful for the clinical interpretation of cancer risk based on BRCA1 sequencing. Furthermore, we propose that this paradigm can be extended to overcome the challenge of VUS in other genes in which genetic variation is clinically actionable.

biorxiv genomics 200-500-users 2018

The organization of intracortical connections by layer and cell class in the mouse brain, bioRxiv, 2018-04-01

AbstractThe mammalian cortex is a laminar structure composed of many cell types densely interconnected in complex ways. Recent systematic efforts to map the mouse mesoscale connectome provide comprehensive projection data on interareal connections, but not at the level of specific cell classes or layers within cortical areas. We present here a significant expansion of the Allen Mouse Brain Connectivity Atlas, with ∼1,000 new axonal projection mapping experiments across nearly all isocortical areas in 49 Cre driver lines. Using 13 lines selective for cortical layer-specific projection neuron classes, we identify the differential contribution of each layerclass to the overall intracortical connectivity patterns. We find layer 5 (L5) projection neurons account for essentially all intracortical outputs. L23, L4, and L6 neurons contact a subset of the L5 cortical targets. We also describe the most common axon lamination patterns in cortical targets. Most patterns are consistent with previous anatomical rules used to determine hierarchical position between cortical areas (feedforward, feedback), with notable exceptions. While diverse target lamination patterns arise from every source layerclass, L23 and L4 neurons are primarily associated with feedforward type projection patterns and L6 with feedback. L5 has both feedforward and feedback projection patterns. Finally, network analyses revealed a modular organization of the intracortical connectome. By labeling interareal and intermodule connections as feedforward or feedback, we present an integrated view of the intracortical connectome as a hierarchical network.

biorxiv neuroscience 200-500-users 2018

 

Created with the audiences framework by Jedidiah Carlson

Powered by Hugo