Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes 1-11 , but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far 12,13. Although single splicing events have been described for ≤200 single cells with statistical confidence 14,15 , full-length mRNA analyses for hundreds of cells have not been reported. Singlecell short-read 3′ sequencing enables the identification of cellular subtypes 16-21 , but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-typespecific combination patterns of distant splice sites 6-9,22,23. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms. Unlike sorting-based methods (Supplementary Fig. 1a), ScISOr-Seq identifies isoforms in >1,000 single cells from bulk tissue without cell sorting by combining two technologies (Fig. 1a). We used microfluidics to amplify full-length cDNA from single cells in a sample. cDNA produced from each single cell was barcoded to enable cell-of-origin identification and then split into two pools, with one pool being used for short-read Illumina 3′ sequencing to measure gene expression and the other pool being used for long-read sequencing and isoform identification. Short-read 3′ sequencing provided molecular counts for each gene and cell, which enabled clustering of cells and cell type assignment using cell-type-specific markers. Long-read sequencing with Pacific Biosciences (PacBio) 1,2,4,5 or Oxford Nanopore 3 was used to identify full-length RNA isoforms. Single-cell barcodes were also present in long reads and could be used to determine the individual
The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19.
Full-length isoform sequencing has advanced our knowledge of isoform biology 1-11 . However, apart from applying full-length isoform sequencing to very few single cells 12,13 , isoform sequencing has been limited to bulk tissue, cell lines, or sorted cells. Single splicing events have been described for <=200 single cells with great statistical success 14,15 , but these methods do not describe full-length mRNAs.Single cell short-read 3' sequencing has allowed identification of many cell subtypes 16-23 , but full-length isoforms for these cell types have not been profiled. UsingAll rights reserved. No reuse allowed without permission.was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
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