Abstract
Single-cell RNA sequencing provides powerful insight into the factors that determine each cell's unique identity. Previous studies led to the surprising observation that alternative splicing among single cells is highly variable and follows a bimodal pattern: a given cell consistently produces either one or the other isoform for a particular splicing choice, with few cells producing both isoforms. Here, we show that this pattern arises almost entirely from technical limitations. We analyze alternative splicing in human and mouse single-cell RNA-seq datasets, and model them with a probabilistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms. This gives the appearance of binary splicing outcomes, even when the underlying reality is consistent with more than one isoform per cell. We show that accounting for the true amount of information recovered can produce biologically meaningful measurements of splicing in single cells.
Highlights
Single-cell RNA sequencing has provided impressive temporal resolution to our understanding of continuous biological processes such as cell differentiation [1, 2]
The exons we inspected had more binary outcomes in cells with fewer reads covering their splice junctions, while cells with more reads were more likely to show non-binary Ψvalues (Figure 1a).This effect of coverage may reflect a non-binary reality, since even if both isoforms are expressed in a certain cell, the likelihood of observing both isoforms is reduced as the number of captured mRNAs decreases
We have shown here that the bimodal patterns could have an entirely different explanation: profound technical limitations of single cell RNA sequencing
Summary
Single-cell RNA sequencing (scRNA-seq) has provided impressive temporal resolution to our understanding of continuous biological processes such as cell differentiation [1, 2]. Some cells always spliced in a particular cassette exon, and some cells never spliced in the exon, but few cells showed truly intermediate inclusion within one cell This unexpected result contrasted with previous single molecule imaging studies of several alternative exons that showed that cell-to-cell variability is minimized and tightly regulated by the splicing machinery in single cells [10]. This led to investigations of the mechanisms that might be responsible for stochastic splicing variability among apparently homogeneous cells, such as variation in DNA methylation [11]
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