Background: 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. Results: In this study, we take a simulation based approach in which we explicitly account for dropouts and isoform quantification errors. We use our simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, we ask what limitations must be overcome to make splicing analysis feasible. We 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. We find that different models of isoform choice meaningfully change our simulation results. Conclusions: 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, we do not recommend attempting to resolve isoforms in individual cells using scRNA-seq.

Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. We carried out a benchmark for five popular isoform quantification tools. Performance was generally good when run on simulated data based on SMARTer and SMART-seq2 data, but was poor for simulated Drop-seq data.Importantly, the reduction in performance for single-cell RNA-seq compared with bulk RNA-seq was small. An important biological insight comes from our analysis of real data which showed that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells.

Levels of parental care critically influence the development environment with the capacity to impact the growth, survival, physiology, and behaviour of offspring. Plastic changes in DNA methylation have been hypothesised to modulate gene expression responses to parental environments. Moreover, these effects can be inherited and so may affect the process of adaptive evolution. In this study, using experimental evolution, we investigated how plastic changes in DNA methylation induced by the loss of parental care have evolved in a biparental insect (Nicrophorus vespilloides) using experimental evolution. We show that removal of care in a single generation is associated with changes in gene expression in stress-related pathways in 1st instar larvae. However, in larvae that have adapted to the loss of parental care after being deprived of care for 30 generations, gene expression is shifted from stress-related gene expression towards growth and brain development pathways. We found that changes in gene body methylation arose both as a direct response to the loss of parental care and stochastically as populations diverged. Overall, our results suggest that a complex interplay between transcription and DNA methylation shapes the molecular adaptation to environmental change.

Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. However, best practice for using existing quantification methods has not been established. We carry out a benchmark for five popular isoform quantification tools. Performance is generally good for simulated data based on SMARTer and SMART-seq2 data. The reduction in performance compared with bulk RNA-seq is small. An important biological insight comes from our analysis of real data which shows that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1571-5) contains supplementary material, which is available to authorized users.