Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA.

High-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with great accuracy, they fall short of analyzing how these individual events are combined into complete RNA transcript isoforms. Because of this shortfall, long-distance information is required to complement short-read sequencing to analyze transcriptomes on the level of full-length RNA transcript isoforms. While long-read sequencing technology can provide this long-distance information, there are issues with both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) long-read sequencing technologies that prevent their widespread adoption. Briefly, PacBio sequencers produce low numbers of reads with high accuracy, while ONT sequencers produce higher numbers of reads with lower accuracy. Here, we introduce and validate a long-read ONT-based sequencing method. At the same cost, our Rolling Circle Amplification to Concatemeric Consensus (R2C2) method generates more accurate reads of full-length RNA transcript isoforms than any other available long-read sequencing method. These reads can then be used to generate isoform-level transcriptomes for both genome annotation and differential expression analysis in bulk or single-cell samples

Single-Cell Nanopore Sequencing

Most transcriptomic analyses are done using Illumina short-read sequencing. While these analyses can be used for highly accurate annotation of individual splice junctions, they are incapable of piecing together combinations of splice junctions to reveal complete RNA transcript isoforms. Exon connectivity information is required for accurate full-length RNA transcript isoform analyses. While long-read sequencing technologies like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) can provide exon connectivity information, neither provide a cost effective way to produce high accuracy full-length reads. I present the ONT-based Rolling Circle Amplification to Concatemeric Consensus (R2C2) and Concatemeric Consensus Caller with Partial Order alignments (C3POa) methods, which generate more accurate reads of full-length RNA transcript isoforms than other long-read sequencing methods. I apply these methods to full-length RNA isoform sequencing in single-cells for differential isoform expression across cell types

Single-Cell Nanopore Sequencing

Most transcriptomic analyses are done using Illumina short-read sequencing. While these analyses can be used for highly accurate annotation of individual splice junctions, they are incapable of piecing together combinations of splice junctions to reveal complete RNA transcript isoforms. Exon connectivity information is required for accurate full-length RNA transcript isoform analyses. While long-read sequencing technologies like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) can provide exon connectivity information, neither provide a cost effective way to produce high accuracy full-length reads. I present the ONT-based Rolling Circle Amplification to Concatemeric Consensus (R2C2) and Concatemeric Consensus Caller with Partial Order alignments (C3POa) methods, which generate more accurate reads of full-length RNA transcript isoforms than other long-read sequencing methods. I apply these methods to full-length RNA isoform sequencing in single-cells for differential isoform expression across cell types

Single-cell isoform analysis in human immune cells

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