Coverage-dependent bias creates the appearance of binary splicing in single cells
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.
Data availability
All sequencing data reanalyzed in this study were acquired from GEO.
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Defining the early steps of cardiovascularlineage segregation by single cell RNA-seqNCBI Gene Expression Omnibus, GSE100471.
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Pseudo-temporal ordering of individual cells reveals regulators of differentiationNCBI Gene Expression Omnibus, GSE52529.
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Olfactory stem cell differentiation: horizontal basal cell (HBC) lineageNCBI Gene Expression Omnibus, GSE95601.
Article and author information
Author details
Funding
UC MEXUS-Conacyt (Doctoral Fellowship)
- Carlos F Buen Abad Najar
Chan Zuckerberg Biohub
- Nir Yosef
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- L Stirling Churchman, Harvard Medical School, United States
Version history
- Received: December 19, 2019
- Accepted: June 28, 2020
- Accepted Manuscript published: June 29, 2020 (version 1)
- Version of Record published: September 17, 2020 (version 2)
Copyright
© 2020, Buen Abad Najar et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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