To resolve cellular heterogeneity, we developed a combinatorial indexing strategy to profile the transcriptomes of single cells or nuclei, termed sci-RNA-seq (single-cell combinatorial indexing RNA sequencing). We applied sci-RNA-seq to profile nearly 50,000 cells from the nematode Caenorhabditis elegans at the L2 larval stage, which provided >50-fold “shotgun” cellular coverage of its somatic cell composition. From these data, we defined consensus expression profiles for 27 cell types and recovered rare neuronal cell types corresponding to as few as one or two cells in the L2 worm. We integrated these profiles with whole-animal chromatin immunoprecipitation sequencing data to deconvolve the cell type–specific effects of transcription factors. The data generated by sci-RNA-seq constitute a powerful resource for nematode biology and foreshadow similar atlases for other organisms.

/pdf/comprehensive-single-cell-transcriptional-profiling-of-a-4eahlwn5oc.pdf

Comprehensive single-cell transcriptional profiling of a multicellular organism

Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype–phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS. Despite the success of human genome-wide association studies (GWAS) in associating genetic variants and complex diseases or traits, criticisms of the usefulness of this study design remain. This Review assesses the pros and cons of GWAS, with a focus on the cardiometabolic field.

Benefits and limitations of genome-wide association studies.

The technology and biology of single-cell RNA sequencing.

Single-nucleus RNA sequencing (sNuc-seq) profiles RNA from tissues that are preserved or cannot be dissociated, but it does not provide high throughput. Here, we develop DroNc-seq: massively parallel sNuc-seq with droplet technology. We profile 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient, and unbiased classification of cell types, paving the way for systematic charting of cell atlases.

Massively-parallel single nucleus RNA-seq with DroNc-seq

The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.

https://science.sciencemag.org/content/sci/352/6293/1586.full.pdf

Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.

It has recently been established that synthesis of double-stranded cDNA can be done from a single cell for use in DNA sequencing. Global gene expression can be quantified from the number of reads mapping to each gene, and mutations and mRNA splicing variants determined from the sequence reads. Here we demonstrate that this method of transcriptomic analysis can be done using the extremely low levels of mRNA in a single nucleus, isolated from a mouse neural progenitor cell line and from dissected hippocampal tissue. This method is characterized by excellent coverage and technical reproducibility. On average, more than 16,000 of the 24,057 mouse protein-coding genes were detected from single nuclei, and the amount of gene-expression variation was similar when measured between single nuclei and single cells. Several major advantages of the method exist: first, nuclei, compared with whole cells, have the advantage of being easily isolated from complex tissues and organs, such as those in the CNS. Second, the method can be widely applied to eukaryotic species, including those of different kingdoms. The method also provides insight into regulatory mechanisms specific to the nucleus. Finally, the method enables dissection of regulatory events at the single-cell level; pooling of 10 nuclei or 10 cells obscures some of the variability measured in transcript levels, implying that single nuclei and cells will be extremely useful in revealing the physiological state and interconnectedness of gene regulation in a manner that avoids the masking inherent to conventional transcriptomics using bulk cells or tissues.

https://www.pnas.org/content/pnas/110/49/19802.full.pdf

RNA-sequencing from single nuclei

Guillaume Lettre, Alexander Reiner, George Diaz and colleagues use an exome array to identify rare and low-frequency coding variants influencing hematological traits. They find several missense variants in CXCR2 associated with reduced white blood cell counts, and, in a separate family-based study, they identify a homozygous CXCR2 frameshift mutation in two siblings with congenital neutropenia.

/pdf/rare-and-low-frequency-coding-variants-in-cxcr2-and-other-p7t76kk9vy.pdf

Andrew O'Shaughnessy

Papers

RNA-sequencing from single nuclei

Rare and low-frequency coding variants in CXCR2 and other genes are associated with hematological traits