Coverage-dependent bias creates the appearance of binary splicing in single cells
| Autor: | Carlos F. Buen Abad Najar, Liana F. Lareau, Nir Yosef |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Gene isoform Cell type Mouse QH301-705.5 Science Systems biology Cell Binary number Datasets as Topic Computational biology Biology General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Mice alternative splicing 0302 clinical medicine Bias Transcription (biology) Gene expression scRNA-seq medicine Animals Humans RNA Messenger Biology (General) Physics General Immunology and Microbiology Sequence Analysis RNA General Neuroscience Alternative splicing RNA Cell Differentiation General Medicine Chromosomes and Gene Expression single cell 030104 developmental biology medicine.anatomical_structure RNA splicing Medicine Single-Cell Analysis 030217 neurology & neurosurgery Research Article Computational and Systems Biology Human |
| Zdroj: | eLife eLife, Vol 9 (2020) |
| ISSN: | 2050-084X |
| Popis: | Single cell RNA sequencing provides powerful insight into the factors that determine each cell’s unique identity, including variation in transcription and RNA splicing among diverse cell types. Previous studies led to the surprising observation that alternative splicing outcomes among single cells are highly variable and follow 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 analyzed single cell alternative splicing in human and mouse single cell RNA-seq datasets, and modeled them with a probablistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms in single cells. This gives the appearance of a binary isoform distribution, 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. |
| Databáze: | OpenAIRE |
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