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

Depletion of Hemoglobin Transcripts and Long-Read Sequencing Improves the Transcriptome Annotation of the Polar Bear (Ursus maritimus)

Transcriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic, as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result, long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9-based depletion method (depletion of abundant sequences by hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears (Ursus maritimus). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion, we discovered ∼6,000 high-confidence isoforms and a number of novel genes. This indicates that there is a high diversity of gene isoforms within U. maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic

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

christopher-vollmers/Mandalorion: v4.5 - Somehow Isoform Returned

<ul> <li>sam to psl conversion now has more robust multiprocessing for tens of millions of reads</li> <li>new quantification for isoform features: TSSs, PolyA, and splice Junctions.</li> <li>Quant files renamed from tpm to rpm to correctly reflect normalization method</li> <li>added GenomeBrowserShot.py script to enable visualization of isoforms.</li> </ul&gt