RNA splicing programs define tissue compartments and cell types at single cell resolution
- Stanford University, United States
- Stanford University School of Medicine, United States
- The Hong Kong University of Science and Technology, Hong Kong
- The Hong Kong University of Science and Technology, China
- Chan Zuckerberg Biohub, United States
Abstract
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, to detect cell-type-specific splicing in >110K cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type-specifically spliced, including ubiquitously expressed genes MYL6 and RPS24. These results are validated with RNA FISH, single-cell PCR, and Smart-seq2. SpliZ analysis reveals 170 genes with regulated splicing during human spermatogenesis, including examples conserved in mouse and mouse lemur. The SpliZ allows model-based identification of subpopulations indistinguishable based on gene expression, illustrated by subpopulation-specific splicing of classical monocytes involving an ultraconserved exon in SAT1. Together, this analysis of differential splicing across multiple organs establishes that splicing is regulated cell-type-specifically.
Data availability
The fastq files for the Tabula Sapiens data (Consortium et al., 2021) (both 10x and Smart-seq2) were downloaded from https://tabula-sapiens-portal.ds.czbiohub.org/. The pilot 2 individual is referred to as individual 1, and the pilot 1 individual is referred to as individual 2 in this manuscript. Pancreas data was removed from individual 2. Cell type annotations were downloaded on March 19th, 2021, and the "ground truth" column was used as the within-tissue-compartment cell type. The Tabula Muris data was downloaded from a public AWS S3 bucket according to https://registry.opendata.aws/tabula-muris-senis/. The P1 (30-M-2) mouse is referred to as individual 1 and P2 (30-M-4) is referred to as individual 2 in this manuscript. Compartment annotations were assigned based on knowledge of cell type. The fastq files for the Tabula Microcebus mouse lemur data were downloaded from https://tabula-microcebus.ds.czbiohub.org. Lemurs 4 and 2 are referred to as individuals 1 and and 2, respectively, in this manuscript. The propagated_cell_ontology_class column was used as the within-tissue-compartment cell type. Because tissue compartments in the mouse lemur were annotated more finely, we collapsed the lymphoid, myeloid, and megakaryocyte-erythroid compartments into the immune compartment.Human and mouse unselected spermatogenesis data was downloaded from the SRA databases with accession IDs SRR6459190 (AdultHuman_17-3), SRR6459191 (AdultHuman_17-4), and SRR6459192 (AdultHuman_17-5) for human, and accession IDs SRR6459155 (AdultMouse-Rep1), SRR6459156 (AdultMouse-Rep2), and SRR6459157 (AdultMouse-Rep3) for mouse. The files containing SpliZ values can be accessed at the following FigShare repository: DOI: 10.6084/m9.figshare.14531721.
Article and author information
Author details
Julia Eve Olivieri
Roozbeh Dehghannasiri
Funding
National Science Foundation (DGE-1656518)
- Julia Eve Olivieri
National Institute of General Medical Sciences (R01 GM116847)
- Julia Salzman
National Science Foundation (MCB1552196)
- Julia Salzman
National Institutes of Health (T15 LM7033-36)
- Roozbeh Dehghannasiri
National Cancer Institute (R25 CA180993)
- Roozbeh Dehghannasiri
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Olivieri 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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RNA splicing programs define tissue compartments and cell types at single cell resolution
eLife 10:e70692.
https://doi.org/10.7554/eLife.70692
