Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

RNA splicing programs define tissue compartments and cell types at single cell resolution

Julia Eve Olivieri, Roozbeh Dehghannasiri, Peter Wang, SoRi Jang, Antoine de Morree, Serena Y. Tan, Jingsi Ming, View ORCID ProfileAngela Ruohao Wu, Tabula Sapiens Consortium, Stephen R. Quake, Mark A. Krasnow, Julia Salzman
doi: https://doi.org/10.1101/2021.05.01.442281
Julia Eve Olivieri
1Department of Biochemistry, Stanford University, Stanford, CA 94305
2Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Roozbeh Dehghannasiri
1Department of Biochemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter Wang
1Department of Biochemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SoRi Jang
1Department of Biochemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Antoine de Morree
3Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Serena Y. Tan
4Department of Pathology, Stanford University Medical Center, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jingsi Ming
5Academy for Statistics and Interdisciplinary Sciences, Faculty of Economics and Management, East China Normal University, Shanghai, China
6Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong SAR, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Angela Ruohao Wu
7Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Angela Ruohao Wu
Tabula Sapiens Consortium
11Members listed at the end
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephen R. Quake
8Department of Bioengineering, Stanford University, Stanford, CA 94305
8Department of Bioengineering, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mark A. Krasnow
1Department of Biochemistry, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Julia Salzman
1Department of Biochemistry, Stanford University, Stanford, CA 94305
10Department of Biomedical Data Science, Stanford University, Stanford, CA 94305
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: julia.salzman@stanford.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

More than 95% of human genes are alternatively spliced. Yet, the extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach that is agnostic to transcript annotation, to detect cell-type-specific regulated splicing in > 110K carefully annotated single cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type specifically spliced. These results are validated with RNA FISH, single cell PCR, and in high throughput with Smart-seq2. Regulated splicing is found in ubiquitously expressed genes such as actin light chain subunit MYL6 and ribosomal protein RPS24, which has an epithelial-specific microexon. 13% of the statistically most variable splice sites in cell-type specifically regulated genes are also most variable in mouse lemur or mouse. SpliZ analysis further reveals 170 genes with regulated splicing during sperm development using, 10 of which are conserved in mouse and mouse lemur. The statistical properties of the SpliZ allow model-based identification of subpopulations within otherwise indistinguishable cells based on gene expression, illustrated by subpopulations of classical monocytes with stereotyped splicing, including an un-annotated exon, in SAT1, a Diamine acetyltransferase. Together, this unsupervised and annotation-free analysis of differential splicing in ultra high throughput droplet-based sequencing of human cells across multiple organs establishes splicing is regulated cell-type-specifically independent of gene expression.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/juliaolivieri/DiffSplice

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted May 02, 2021.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
RNA splicing programs define tissue compartments and cell types at single cell resolution
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
RNA splicing programs define tissue compartments and cell types at single cell resolution
Julia Eve Olivieri, Roozbeh Dehghannasiri, Peter Wang, SoRi Jang, Antoine de Morree, Serena Y. Tan, Jingsi Ming, Angela Ruohao Wu, Tabula Sapiens Consortium, Stephen R. Quake, Mark A. Krasnow, Julia Salzman
bioRxiv 2021.05.01.442281; doi: https://doi.org/10.1101/2021.05.01.442281
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
RNA splicing programs define tissue compartments and cell types at single cell resolution
Julia Eve Olivieri, Roozbeh Dehghannasiri, Peter Wang, SoRi Jang, Antoine de Morree, Serena Y. Tan, Jingsi Ming, Angela Ruohao Wu, Tabula Sapiens Consortium, Stephen R. Quake, Mark A. Krasnow, Julia Salzman
bioRxiv 2021.05.01.442281; doi: https://doi.org/10.1101/2021.05.01.442281

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4672)
  • Biochemistry (10340)
  • Bioengineering (7658)
  • Bioinformatics (26300)
  • Biophysics (13501)
  • Cancer Biology (10672)
  • Cell Biology (15412)
  • Clinical Trials (138)
  • Developmental Biology (8487)
  • Ecology (12806)
  • Epidemiology (2067)
  • Evolutionary Biology (16831)
  • Genetics (11382)
  • Genomics (15469)
  • Immunology (10601)
  • Microbiology (25181)
  • Molecular Biology (10209)
  • Neuroscience (54383)
  • Paleontology (399)
  • Pathology (1667)
  • Pharmacology and Toxicology (2889)
  • Physiology (4334)
  • Plant Biology (9235)
  • Scientific Communication and Education (1586)
  • Synthetic Biology (2555)
  • Systems Biology (6773)
  • Zoology (1461)