Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

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Single-cell transcriptomics of 20 mouse organs creates a "Tabula Muris"

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

The Human Cell Atlas

Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNA-Seq

Continuous and Discrete Neuron Types of the Adult Murine Striatum

The striatum is a large brain region containing two major cell types: D1 (dopamine receptor 1) and D2 (dopamine receptor 2) expressing spiny projection neurons (SPNs). We generated a cell type atlas of the adult murine striatum using single-cell RNA-seq of SPNs combined with quantitative RNA in situ hybridization (ISH). We developed a novel computational pipeline that distinguishes discrete versus continuous cell identities in scRNA-seq data, and used it to show that SPNs in the striatum can be classified into four discrete types that reside in discrete anatomical clusters or are spatially intermingled. Within each discrete type, we find multiple independent axes of continuous cell identity that map to spatial gradients and whose genes are conserved between discrete types. These gradients correlate well to previously-mapped gradients of connectivity. Using these insights, we discovered multiple novel spatially localized region of the striatum, one of which contains patch-D2 SPNs that express Tac1, Htr7, and Th. Intriguingly, we found one subtype that strongly co-expresses both D1 and D2 dopamine receptors, and uniquely expresses a rare D2 receptor splice variant. These results collectively suggest an organizational principal of neuron identity in which major neuron types can be separated into discrete classes with little overlap and no implied spatial relationship. However these discrete classes are then continuously subdivided by multiple spatial gradients of expression defining anatomical location via a combinatorial mechanism. Finally, they suggest that neuronal circuitry has a substructure at far higher resolution than is typically interrogated which is defined by the precise identity and location of a neuron.

https://www.biorxiv.org/content/biorxiv/early/2019/03/27/591396.full.pdf

Geoffrey Stanley

Papers

Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNA-Seq

Continuous and Discrete Neuron Types of the Adult Murine Striatum

Discrete and Continuous Cell Identities of the Adult Murine Striatum