Coverage-dependent bias creates the appearance of binary splicing in single cells

Abstract
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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.

The following previously published data sets were used

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Article and author information

Author details

Carlos F Buen Abad Najar

Center for Computational Biology, University of California, Berkeley, Berkeley, United States

Competing interests
The authors declare that no competing interests exist.
Nir Yosef

Department of Electrical Engineering and Computer Science and the Center for Computational Biology, University of California, Berkeley, Berkeley, United States

For correspondence
niryosef@berkeley.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-9004-1225
Liana F Lareau

Department of Bioengineering, University of California, Berkeley, Berkeley, United States

For correspondence
lareau@berkeley.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-3223-3426

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.

Copyright

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.