From words to complete phrases: insight into single-cell isoforms using short and long reads

Abstract

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

“…Furthermore, 51% of the UMIs were composed of intra-priming and non-canonical artifacts before filtering, and their detection was only possible through isoform classification. Overall, our findings highlight the need for an isoform-specific quantification to accurately assess protein-coding gene expression 82 and narrow the RNA-protein gap 83–86 . Additionally, a better isoform characterization is needed to understand their biological implications, as we partly demonstrated with IGF1 Class I/II , cGSN, TPM2.3, RTN1-C, and OAS1 p42 .…”

“…Furthermore, 51% of the UMIs were composed of intra-priming and noncanonical artifacts before filtering, and their detection was only possible through isoform classification. Overall, our findings highlight the need for an isoform-specific quantification to accurately assess protein-coding gene expression 82 and narrow the RNA-protein gap [83][84][85][86] .…”

Single-cell Rapid Capture Hybridization sequencing (scRaCH-seq) to reliably detect isoform usage and coding mutations in targeted genes at a single-cell level

“…Cell identity and function could be influenced by the alternative splicing of transcripts which will result in a substantial number of transcript isoforms. However, a significant portion of alternative transcripts will not be detected through second-generation sequencing-based single-cell RNA-seq methods due to the short read length and the inherent bias toward 3′ or 5′ ends of the transcripts (11). To address this limitation, we developed scRaCH-seq, demonstrating high specificity and efficiency in capturing targeted long-read transcripts.…”

“…In recent years, several high-throughput methods have been developed to enable single-cell long-read sequencing. These approaches typically involve barcoding of cDNA using existing methods such as 10x Genomics or Drop-seq and sequencing the indexed full-length cDNA on platforms such as Pacific Biosciences (PacBio) or Oxford Nanopore Technologies (ONT)(11,12). While these unbiased single-cell long-read sequencing methods can detect a larger number of isoforms at a single-cell level, the lower overall sequencing level per cell reduces the ability to accurately quantify isoform usage and mutation calling.…”

De novo detection of somatic variants in long-read single-cell RNA sequencing data

“…Despite rapid progress in the LR scRNA-seq field (Al’Khafaji et al 2023; Dondi et al 2023; Joglekar et al 2023; Marx 2023), multiple technical limitations remain unsolved, limiting the potential of downstream analysis. First, variant detection remains challenging due to the sparsity and low coverage of scRNA-seq assays.…”