Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses.
In this study, University of Cambridge researchers take a simulation based approach in which they explicitly account for dropouts and isoform quantification errors. They use their simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, they ask what limitations must be overcome to make splicing analysis feasible. The researchers find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing. In mice and other well-established model organisms, the relatively low rate of isoform quantification errors poses a lesser obstacle to splicing analysis. They find that different models of isoform choice meaningfully change our simulation results.
Schematic of the simulation approach
To accurately study alternative splicing with single-cell RNA-seq, a better understanding of isoform choice and the errors associated with scRNA-seq is required. An increase in the capture efficiency of scRNA-seq would also be beneficial. Until some or all of the above are achieved, the authors do not recommend attempting to resolve isoforms in individual cells using scRNA-seq.