Single-cell isoform analysis in human immune cells

Abstract

High-throughput single-cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5′ or 3′ end. Here, we used R2C2 to sequence and demultiplex 12 million full-length cDNA molecules generated by the 10X Genomics platform from ~3000 peripheral blood mononuclear cells. We use these reads, independent from Illumina data, to identify B cell, T cell, and monocyte clusters and generate isoform-level transcriptomes for cells and cell types. Finally, we extract paired adaptive immune receptor sequences unique to each T and B cell.

NAb-seq: an accurate, rapid and cost-effective method for antibody long-read sequencing in hybridoma cell lines and single B cells

“…This simple and universal protocol is a major advantage over all targeted sequencing techniques (Sanger, Illumina, PacBio/ONT; 9, 10, 17, 20 ). It is also much simpler, cheaper and less prone to chimerism than whole-transcriptome concatemer nanopore sequencing 22 .…”

“…Lowden and Henry 20 found that, without error correction steps, 75-80% of antibody fragment reads were unable to have their CDR3 identified. Error correction methods that rely on the sequencing of concatemers from rolling circle amplification can successfully reconstruct BCR sequences from single B cells 22 , however they require more time and computational power than NAb-seq. Similarly, the assembly-based approach employed to characterize cancerous B cells 21 , though effective, is slower and more computationally intensive than the simple consensus strategy implemented by NAb-seq.…”

“…The remaining errors in ONT, notably systematic homopolymer errors (insertions/deletions in tracts of >5 identical bases) can lead to frameshifts, complicating translation of nanopore-derived sequences into accurate antibody protein sequences 18 . Notably, improvements in sequencing accuracy and correction techniques 19 have enabled the study of antibody fragments 20 and B cells [21][22][23] , although these studies employ complex and costly error correction methods 22 , are specific to cancerous cells 21 or are too high throughput to be realistically used for hybridoma sequencing 24 .…”

ScisorWiz: visualizing differential isoform expression in single-cell long-read data

“…Differential isoform expression between cell types and across conditions plays a major role in the diversification of the proteome ( Nilsen and Graveley, 2010 ) and functionality of transcripts in the cell ( Yang et al , 2016 ). Long-read sequencing has become widely used to address this problem ( Au et al , 2013 ; Bolisetty et al , 2015 ; Koren et al , 2012 ; Leung et al , 2021 ; Oikonomopoulos et al , 2016 ; Ruiz-Reche et al , 2019 ; Schulz et al , 2021 ; Sharon et al , 2013 ; Tilgner et al , 2015 ), and with applications to single-cell isoform sequencing studies ( Arzalluz-Luque et al , 2022 ; Gupta et al , 2018 ; Hardwick et al , 2022 ; Joglekar et al , 2021 ; Volden and Vollmers, 2022 ). These approaches have been reviewed in Hardwick et al (2019) .…”

ScisorWiz: Visualizing Differential Isoform Expression in Single-Cell Long-Read Data

“…Differential isoform expression between cell types and across conditions plays a major role in the diversification of the proteome (1) and functionality of transcripts in the cell (2). Long-read sequencing has become widely used to address this problem (3)(4)(5)(6)(7)(8)(9)(10)(11), and with applications to single-cell isoform sequencing studies (12)(13)(14)(15)(16). These approaches have been reviewed in Hardwick et al, 2019 (17).…”