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Transcript assembly improves expression quantification of transposable elements in single cell RNA-seq data

By Wanqing Shao, Ting Wang

Posted 31 Jul 2020
bioRxiv DOI: 10.1101/2020.07.31.231027

Transposable elements (TEs) are an integral part of the host transcriptome. TE-containing noncoding RNAs (ncRNAs) exhibit considerable tissue specificity and play crucial roles during development, including stem cell maintenance and cell differentiation. Recent advances in single cell RNA-seq (scRNA-seq) revolutionized cell-type specific gene expression analysis. However, scRNA-seq quantification tools tailored for TEs are lacking, limiting our ability to dissect TE expression dynamics at single cell resolution. To address this issue, we established a TE expression quantification pipeline that is compatible with scRNA-seq data generated across multiple technology platforms. We constructed TE containing ncRNA references using bulk RNA-seq data and demonstrated that quantifying TE expression at the transcript level effectively reduces noise. As proof of principle, we applied this strategy to mouse embryonic stem cells and successfully captured the expression profile of endogenous retroviruses in single cells. We further expanded our analysis to scRNA-seq data from early stages of mouse embryogenesis. Our results illustrated the dynamic TE expression at pre-implantation stages and revealed 137 TE-containing ncRNA transcripts with substantial tissue specificity during gastrulation and early organogenesis. ### Competing Interest Statement The authors have declared no competing interest.

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