The single-cell eQTLGen consortium aims to pinpoint the cellular contexts in which disease-causing genetic variants affect gene expression and its regulation.

Single-cell analyses of cells infected by Herpes Simplex Virus 1 revealed extreme heterogeneity among infected cells, including the robust activation of developmental gene programs in highly infected cells.

A new high-throughput method for single-cell RNA-seq in yeast cells shows how stochastic expression of glucose-repressed genes contributes to cell-to-cell differences during adaptation to an environmental change.

A single-cell atlas of the adult fly VNC charts the types and properties of cells for future studies of brain development and function.

Single-cell amplified genome sequencing uncovers virus-host interactions in uncultivated sulfur-oxidizing bacteria with relevance to coupled biogeochemical cycling in marine oxygen minimum zones.

By properly accounting for gene copy number and cell-cycle effects, single cell snapshots of nascent and mature mRNA can be used to unveil the stochastic kinetics of gene activity.

Single cell expression data can be used to determine how regulatory transcription factors and target genes are connected, and is especially useful when studying transcription factors controlling heterogeneous cell states.

A statistical method for summarizing single-cell gene expression data identifies normal and disease-specific transcriptional programs from an atlas of 57,600 cells.

The combination of single-cell transcriptomics and whole-brain mapping of bulk and single-cell projections reveals the relationship between the molecular architecture, cell body distribution, and axonal arborization of serotonin neurons.

Single-cell RNA-sequencing and germline substitutions provide novel insights into how testis is a hotspot for evolutionary innovation of genes, expression, and mutation at the single-cell level.