1. Chromosomes and Gene Expression
  2. Computational and Systems Biology
Download icon

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

  1. Carlos F Buen Abad Najar
  2. Nir Yosef  Is a corresponding author
  3. Liana F Lareau  Is a corresponding author
  1. University of California, Berkeley, United States
Research Article
  • Cited 0
  • Views 1,961
  • Annotations
Cite this article as: eLife 2020;9:e54603 doi: 10.7554/eLife.54603

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.

Article and author information

Author details

  1. 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.
  2. 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.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9004-1225
  3. 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.
    ORCID icon "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.

Reviewing Editor

  1. L Stirling Churchman, Harvard Medical School, United States

Publication history

  1. Received: December 19, 2019
  2. Accepted: June 28, 2020
  3. Accepted Manuscript published: June 29, 2020 (version 1)

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.

Metrics

  • 1,961
    Page views
  • 198
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Cell Biology
    2. Chromosomes and Gene Expression
    Stefan Golfier et al.
    Research Article Updated
    1. Chromosomes and Gene Expression
    2. Developmental Biology
    Michael Zavortink et al.
    Research Article