Nuclear oligo hashing improves differential analysis of single-cell RNA-seq

Single-cell RNA sequencing (scRNA-seq) offers a high-resolution molecular view into complex tissues, but suffers from high levels of technical noise which frustrates efforts to compare the gene expression programs of different cell types. “Spike-in” RNA standards help control for technical variation in scRNA-seq, but using them with recently developed, ultra-scalable scRNA-seq methods based on combinatorial indexing is not feasible. Here, we describe a simple and cost-effective method for normalizing transcript counts and subtracting technical variability that improves differential expression analysis in scRNA-seq. The method affixes a ladder of synthetic single-stranded DNA oligos to each cell that appears in its RNA-seq library. With improved normalization we explore chemical perturbations with broad or highly specific effects on gene regulation, including RNA pol II elongation, histone deacetylation, and activation of the glucocorticoid receptor. Our methods reveal that inhibiting histone deacetylation prevents cells from executing their canonical program of changes following glucocorticoid stimulation. Overall design: Single-cell RNA-seq libraries of untreated and drug treated HEK293T and A549 cells were generated using single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) and the nuclear oligo hashing method (sci-plex). Along with hash labels unique to each experimental conditions, hash ladders were spiked into each sci-RNA-seq libraries for normalization. Hash ladders were designed by mixing various hash species at different concentration.