Series |

Single-cell omics

Recent technological advances are providing unprecedented opportunities to analyse the complexities of biological systems at the single-cell level. Various crucial biological phenomena are either invisible or only partially characterized when interrogated using standard analyses that average data across a bulk population of cells. However, high-throughput analyses of the genomes, transcriptomes and proteomes of single cells are providing novel and important insights into diverse processes such as development, gene-expression dynamics, tissue heterogeneity and disease pathogenesis.

Content

  • Nature Reviews Genetics | Review Article

    The functional interpretation of single-cell RNA sequencing (scRNA-seq) data can be enhanced by integrating additional data types beyond RNA-based gene expression. In this Review, Stuart and Satija discuss diverse approaches for integrative single-cell analysis, including experimental methods for profiling multiple omics types from the same cells, analytical approaches for extracting additional layers of information directly from scRNA-seq data and computational integration of omics data collected across different cell samples.

    • Tim Stuart
    •  &  Rahul Satija
  • Nature Reviews Genetics | Review Article

    Single-cell RNA sequencing (scRNA-seq) enables transcriptome-based characterization of the constituent cell types within a heterogeneous sample. However, reliable analysis and biological interpretation typically require optimal use of clustering algorithms. This Review discusses the multiple algorithmic options for clustering scRNA-seq data, including various technical, biological and computational considerations.

    • Vladimir Yu Kiselev
    • , Tallulah S. Andrews
    •  &  Martin Hemberg
  • Nature Reviews Genetics | Review Article

    As the genetic and phenotypic heterogeneities among cells become more appreciated, there is increasing demand for technologies that facilitate high-throughput and high-efficiency single-cell 'omic' analyses in miniaturized and automated formats. This Review discusses the diverse microfluidic methodologies — with a primary focus on valve-, droplet- and nanowell-based platforms — for characterization of the genomes, epigenomes, transcriptomes and proteomes of single cells, and addresses technical considerations and future opportunities.

    • Sanjay M. Prakadan
    • , Alex K. Shalek
    •  &  David A. Weitz
  • Nature Reviews Genetics | Review Article

    Lineage analyses of multicellular organisms provide key insights into developmental mechanisms and how these developmental trajectories go awry in diverse diseases. This Review discusses the features, technical challenges and latest opportunities of an evolving range of sophisticated genetic techniques for tracking cell lineages in organisms. These strategies include methods for prospective tracking using engineered genetic constructs, as well as retrospective tracking based on naturally occurring somatic mutations.

    • Mollie B. Woodworth
    • , Kelly M. Girskis
    •  &  Christopher A. Walsh
  • Nature Reviews Genetics | Review Article

    Single-cell genome sequencing can provide detailed insights into the composition of single genomes that are not readily apparent when studying bulk cell populations. This Review discusses the considerable technical challenges of amplifying and interrogating genomes from single cells, emerging innovative solutions and various applications in microbiology and human disease, in particular in cancer.

    • Charles Gawad
    • , Winston Koh
    •  &  Stephen R. Quake
  • Nature Reviews Genetics | Review Article

    Various methodologies have been developed to characterize diverse features of chromatin, but understanding how epigenomic states contribute to cellular heterogeneity requires adoption of these techniques at the single-cell level. This article discusses the technological developments driving single-cell epigenomics, including the practical and bioinformatic challenges and emerging biological insights.

    • Omer Schwartzman
    •  &  Amos Tanay