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

eLife

Jingsi Ming¹  Stephen R Quake²  SoRi Jang³  Mark A Krasnow³  Peter L Wang³  Roozbeh Dehghannasiri⁴  Julia Salzman⁴  Angela Ruohao Wu⁵  Antoine de Morree⁶  Serena Y Tan⁷  Julia Eve Olivieri⁸ 

[1] Academy for Statistics and Interdisciplinary Sciences, Faculty of Economics and Management,East China Normal University, Shanghai, China;Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China;Chan Zuckerberg Biohub, San Francisco, United States;Department of Bioengineering, Stanford University, Stanford, United States;Department of Biochemistry, Stanford University, Stanford, United States;Department of Biomedical Data Science, Stanford University, Stanford, United States;Department of Biochemistry, Stanford University, Stanford, United States;Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China;Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, United States;Department of Pathology, Stanford University Medical Center, Stanford, United States;Institute for Computational and Mathematical Engineering, Stanford University, Stanford, United States;Department of Biomedical Data Science, Stanford University, Stanford, United States;Department of Biochemistry, Stanford University, Stanford, United States;

关键词: scRNA-seq;    splicing;    statistics;    computational biology;    RNA;    Human;    Mouse;    Mouse lemur;   

DOI  :  10.7554/eLife.70692

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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 Chromium 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.

【 授权许可】

CC BY