RNA-sequencing of single-cells enables characterization of transcriptional heterogeneity in seemingly homogenous cell populations. In this study, reseachers from the Karolinska Institute propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of pairs of isoforms from the same gene in single-cell isoform-level expression data. They define six principal patterns of isoform expression relationships and introduce the concept of differential pattern analysis. They applied ISOP for analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in two independent datasets. In the primary dataset they detected and assigned pattern type of 16562 isoform-pairs from 4929 genes.
Their results showed that 78% of the isoform pairs displayed a mutually exclusive expression pattern, 14% of the isoform pairs displayed bimodal isoform preference and 8% isoform pairs displayed isoform preference. 26% of the isoform-pair patterns were significant, while remaining isoform-pair patterns can be understood as effects of transcriptional bursting, drop-out and biological heterogeneity. 32% of genes discovered through differential pattern analysis were novel and not detected by differential expression analysis.
Overview of the six principal isoform expression pattern types.
Each panel consists of two plots: a component plot (left) displaying the typical mixture model of Δa,b for the pattern, corresponding to isoform a and isoform b in the isoform pair, and a pair-line plot (right) of the two isoforms. (a) The Ipattern (isoform preference of cells) and its extension, the II-pattern (isoform preference in a subset of cells). (b) The V-pattern (bimodal isoform preference of cells) and its extension, the VI-pattern (bimodal isoform preference in a subset of cells). (c) The X-pattern (mutually exclusive expression commitment of cells) and its extension, the VI-pattern (mutually exclusive expression commitment in a subset of cells).
ISOP provides a novel approach for characterization of isoform-level expression in single-cell populations. These results reveal a common occurrence of isoform-level preference, commitment and heterogeneity in single-cell populations.