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Single-cell omics approaches are providing unprecedented insights into cellular function and dysfunction. This Editorial highlights the remarkable potential of these technologies and their profound impact on our understanding of biology and disease.
A study in Nature integrates single-cell RNA-sequencing data from more than 1,000 tumour samples to report a pan-cancer atlas of intratumour transcriptional heterogeneity.
A study in Nature Biotechnology describes Scriabin, a highly scalable framework for inference of cell–cell communication from scRNA-seq data at the level of individual cells.
Tanja Woyke highlights a 2014 study by Kashtan et al., who applied single-cell genomics to populations of the marine cyanobacterium Prochlorococcus, revealing hundreds of subpopulations with distinct genomic backbones of this wild uncultured microorganism.
In this Journal Club, Celine Vallot discusses two 2015 papers that introduced the concept of high-throughput RNA barcoding, which paved the way for today’s plethora of single-cell omic approaches.
Roser Vento-Tormo highlights the synergy of single-cell omics and organoids by Camp et al., who used single-cell RNA sequencing to characterize the cell–cell communication events driving tissue formation in human liver organoids.
Marja Timmermans recalls a series of papers published back-to-back in Science in 2018 that reported the use of single-cell RNA sequencing to obtain a more complete picture of the expression landscapes describing early vertebrate development.
In this Review, the authors discuss the latest advances in profiling multiple molecular modalities from single cells, including genomic, transcriptomic, epigenomic and proteomic information. They describe the diverse strategies for separately analysing different modalities, how the data can be computationally integrated, and approaches for obtaining spatially resolved data.
In this Review, Gaulton et al. discuss how single-cell epigenomic methods generate cell type-, subtype- and state-resolved maps of candidate cis-regulatory elements in heterogeneous human tissues that can help to interpret the genetic basis of common traits and diseases.
In this Review, the authors describe the emerging field of single-cell genetics, which lies at the intersection of single-cell genomics and human genetics. They review the first single-cell expression quantitative trait loci studies, which combine single-cell information with genotype data at the population scale and thereby link genetic variation to the cellular processes underpinning key aspects of human biology and disease.
Practitioners in the field of single-cell omics are now faced with diverse options for analytical tools to process and integrate data from various molecular modalities. In an Expert Recommendation article, the authors provide guidance on robust single-cell data analysis, including choices of best-performing tools from benchmarking studies.
In this Perspective, Lim et al. discuss the potential benefits of, and the challenges associated with, translating single-cell genomic approaches from research to clinical settings.
