Identifying transposable element expression dynamics and heterogeneity during development at the single-cell level with a processing pipeline scTE

Abstract

Transposable elements (TEs) make up a majority of a typical eukaryote’s genome, and contribute to cell heterogeneity in unclear ways. Single-cell sequencing technologies are powerful tools to explore cells, however analysis is typically gene-centric and TE expression has not been addressed. Here, we develop a single-cell TE processing pipeline, scTE, and report the expression of TEs in single cells in a range of biological contexts. Specific TE types are expressed in subpopulations of embryonic stem cells and are dynamically regulated during pluripotency reprogramming, differentiation, and embryogenesis. Unexpectedly, TEs are expressed in somatic cells, including human disease-specific TEs that are undetectable in bulk analyses. Finally, we apply scTE to single-cell ATAC-seq data, and demonstrate that scTE can discriminate cell type using chromatin accessibly of TEs alone. Overall, our results classify the dynamic patterns of TEs in single cells and their contributions to cell heterogeneity.

Transposable element sequence fragments incorporated into coding and noncoding transcripts modulate the transcriptome of human pluripotent stem cells

“…In addition to gene expression heterogeneity in single cells, there is evidence that TEs are heterogeneously expressed and mark subpopulations of cells ( 58 ). However, the TE complement in sc-RNA-seq has only been analyzed by merging all genomic TE copies to produce a single expression score for each TE ( 58 ), or by using short reads to guide transcript assembly to then measure TE enrichment in specific RNAs ( 97 ).…”

“…In addition to gene expression heterogeneity in single cells, there is evidence that TEs are heterogeneously expressed and mark subpopulations of cells ( 58 ). However, the TE complement in sc-RNA-seq has only been analyzed by merging all genomic TE copies to produce a single expression score for each TE ( 58 ), or by using short reads to guide transcript assembly to then measure TE enrichment in specific RNAs ( 97 ). As we use unique 3′ ends we can associate the 3′ end with the corresponding full-length transcript from our hPSC-specific assembly, and so measure the TE content of the expressed transcripts in each cell.…”

“…This reduced the number of transcripts to 88520 (87%) out of the total set of 101479 transcripts. The sc-RNA-seq reads were aligned to the hg38 genome with STARsolo ( 43 ), using the appropriate whitelist barcode file, and processed using scTE ( 58 ). The matrices were filtered and analyzed using SCANPY ( 59 ).…”

Transposable elements and their KZFP controllers are drivers of transcriptional innovation in the developing human brain

“…We propose that increased postnatal TE expression may possibly be reflective of the development of cell types not present in early prenatal stages, such as astrocytes, microglia, and oligodendrocytes, the developmental and transcriptional trajectories of which were identified by scRNA-seq analyses (Li et al 2018). To determine the transposcriptome in scRNA-seq data remains technically challenging because many TE-derived transcripts are lowly abundant, a limitation that will hopefully be alleviated by progress in sequencing techniques and computational approaches (Linker et al 2020;He et al 2021). Of note, TEs heavily contribute to long noncoding RNAs (lncRNAs), which are abundant in the human brain (Derrien et al 2012;Kelley and Rinn 2012;Zimmer-Bensch 2019).…”

Transcriptome analysis reveals high tumor heterogeneity with respect to re-activation of stemness and proliferation programs

“…Therefore, another source of stemness heterogeneity may come from the epigenetic component or from other factors such as variability in pre-mRNA splicing [89] and expression of non-coding genes, e.g. transposons [90]. A combined analysis of single-cell transcriptomes, pre-mRNA splicing by bulk RNA-seq, epigenetic assays based on ChIP-seq, and non-coding RNA quantification is needed for the detailed August 29, 2021 9/19 characterization of the stemness heterogeneity landscape.…”