High-throughput RNA sequencing of paraformaldehyde-fixed single cells

Current high-throughput single-cell transcriptomic methods are incompatible with paraformaldehyde, a common cell fixation technique. Here the authors present FD-seq, a method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single cells. Single-cell transcriptomic studies that require intracellular protein staining, rare cell sorting, or inactivation of infectious pathogens are severely limited. This is because current high-throughput single-cell RNA sequencing methods are either incompatible with or necessitate laborious sample preprocessing for paraformaldehyde treatment, a common tissue and cell fixation and preservation technique. Here we present FD-seq (Fixed Droplet RNA sequencing), a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, permeabilized and sorted single cells. We show that FD-seq preserves the RNA integrity and relative gene expression levels after fixation and permeabilization. Furthermore, FD-seq can detect a higher number of genes and transcripts than methanol fixation. We first apply FD-seq to analyze a rare subpopulation of cells supporting lytic reactivation of the human tumor virus KSHV, and identify TMEM119 as a potential host factor that mediates viral reactivation. Second, we find that infection with the human betacoronavirus OC43 leads to upregulation of pro-inflammatory pathways in cells that are exposed to the virus but fail to express high levels of viral genes. FD-seq thus enables integrating phenotypic with transcriptomic information in rare cell subpopulations, and preserving and inactivating pathogenic samples.

Automated summary

FD-seq is a high-throughput method for RNA sequencing of single cells fixed, stained, and sorted with paraformaldehyde, preserving RNA integrity and relative gene expression levels. This method can detect a higher number of genes and transcripts compared to methanol fixation, allowing for integration of phenotypic and transcriptomic information in rare cell subpopulations.