Robust and annotation-free analysis of alternative splicing across diverse cell types in mice

  1. Gonzalo Benegas
  2. Jonathan Fischer
  3. Yun S Song  Is a corresponding author
  1. University of California, Berkeley, United States
  2. University of Florida, United States

Abstract

Although alternative splicing is a fundamental and pervasive aspect of gene expression in higher eukaryotes, it is often omitted from single-cell studies due to quantification challenges inherent to commonly used short-read sequencing technologies. Here, we undertake the analysis of alternative splicing across numerous diverse murine cell types from two large-scale single-cell datasets-the Tabula Muris and BRAIN Initiative Cell Census Network-while accounting for understudied technical artifacts and unannotated events. We find strong and general cell-type-specific alternative splicing, complementary to total gene expression but of similar discriminatory value, and identify a large volume of novel splicing events. We specifically highlight splicing variation across different cell types in primary motor cortex neurons, bone marrow B cells, and various epithelial cells, and we show that the implicated transcripts include many genes which do not display total expression differences. To elucidate the regulation of alternative splicing, we build a custom predictive model based on splicing factor activity, recovering several known interactions while generating new hypotheses, including potential regulatory roles for novel alternative splicing events in critical genes like Khdrbs3 and Rbfox1. We make our results available using public interactive browsers to spur further exploration by the community.

Data availability

All data analyzed in this study are publicly available and URL links are provided in the Materials and Methods section of our manuscript.Our source code as well as all results represented in figures and tables are publicly available on our lab's GitHub repositories:https://github.com/songlab-cal/scquint andhttps://github.com/songlab-cal/scquint-analysis

The following previously published data sets were used

Article and author information

Author details

  1. Gonzalo Benegas

    Graduate Group in Computational Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jonathan Fischer

    Department of Biostatistics, University of Florida, Gainesville, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Yun S Song

    Computer Science Division, University of California, Berkeley, Berkeley, United States
    For correspondence
    yss@berkeley.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0734-9868

Funding

National Institutes of Health (R35-GM134922)

  • Gonzalo Benegas
  • Yun S Song

Chan Zuckerberg Initiative (CZF2019-002449)

  • Gonzalo Benegas
  • Yun S Song

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Eduardo Eyras, Australian National University, Australia

Version history

  1. Preprint posted: April 27, 2021 (view preprint)
  2. Received: September 1, 2021
  3. Accepted: February 27, 2022
  4. Accepted Manuscript published: March 1, 2022 (version 1)
  5. Version of Record published: April 1, 2022 (version 2)

Copyright

© 2022, Benegas 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

  • 5,076
    views
  • 479
    downloads
  • 8
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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)

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

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

  1. Gonzalo Benegas
  2. Jonathan Fischer
  3. Yun S Song
(2022)
Robust and annotation-free analysis of alternative splicing across diverse cell types in mice
eLife 11:e73520.
https://doi.org/10.7554/eLife.73520

Share this article

https://doi.org/10.7554/eLife.73520

Further reading

    1. Biochemistry and Chemical Biology
    2. Chromosomes and Gene Expression
    Ramona Weber, Chung-Te Chang
    Research Article

    Recent findings indicate that the translation elongation rate influences mRNA stability. One of the factors that has been implicated in this link between mRNA decay and translation speed is the yeast DEAD-box helicase Dhh1p. Here, we demonstrated that the human ortholog of Dhh1p, DDX6, triggers the deadenylation-dependent decay of inefficiently translated mRNAs in human cells. DDX6 interacts with the ribosome through the Phe-Asp-Phe (FDF) motif in its RecA2 domain. Furthermore, RecA2-mediated interactions and ATPase activity are both required for DDX6 to destabilize inefficiently translated mRNAs. Using ribosome profiling and RNA sequencing, we identified two classes of endogenous mRNAs that are regulated in a DDX6-dependent manner. The identified targets are either translationally regulated or regulated at the steady-state-level and either exhibit signatures of poor overall translation or of locally reduced ribosome translocation rates. Transferring the identified sequence stretches into a reporter mRNA caused translation- and DDX6-dependent degradation of the reporter mRNA. In summary, these results identify DDX6 as a crucial regulator of mRNA translation and decay triggered by slow ribosome movement and provide insights into the mechanism by which DDX6 destabilizes inefficiently translated mRNAs.

    1. Chromosomes and Gene Expression
    Marwan Anoud, Emmanuelle Delagoutte ... Jean-Paul Concordet
    Research Article

    Tardigrades are microscopic animals renowned for their ability to withstand extreme conditions, including high doses of ionizing radiation (IR). To better understand their radio-resistance, we first characterized induction and repair of DNA double- and single-strand breaks after exposure to IR in the model species Hypsibius exemplaris. Importantly, we found that the rate of single-strand breaks induced was roughly equivalent to that in human cells, suggesting that DNA repair plays a predominant role in tardigrades’ radio-resistance. To identify novel tardigrade-specific genes involved, we next conducted a comparative transcriptomics analysis across three different species. In all three species, many DNA repair genes were among the most strongly overexpressed genes alongside a novel tardigrade-specific gene, which we named Tardigrade DNA damage Response 1 (TDR1). We found that TDR1 protein interacts with DNA and forms aggregates at high concentration suggesting it may condensate DNA and preserve chromosome organization until DNA repair is accomplished. Remarkably, when expressed in human cells, TDR1 improved resistance to Bleomycin, a radiomimetic drug. Based on these findings, we propose that TDR1 is a novel tardigrade-specific gene conferring resistance to IR. Our study sheds light on mechanisms of DNA repair helping cope with high levels of DNA damage inflicted by IR.