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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.

Long-read sequencing holds great potential for transcriptome analysis because it offers researchers an affordable method to annotate the transcriptomes of non-model organisms. This, in turn, will greatly benefit future work on less-researched organisms like unicellular eukaryotes that cannot rely on large consortia to generate these transcriptome annotations. However, to realize this potential, several remaining molecular and computational challenges will have to be overcome. In this review, we have outlined the limitations of short-read sequencing technology and how long-read sequencing technology overcomes these limitations. We have also highlighted the unique challenges still present for long-read sequencing technology and provided some suggestions on how to overcome these challenges going forward. This article is part of a discussion meeting issue ‘Single cell ecology’.

Understanding gene regulation and function requires a genome-wide method capable of capturing both gene expression levels and isoform diversity at the single-cell level. Short-read RNAseq is limited in its ability to resolve complex isoforms because it fails to sequence full-length cDNA copies of RNA molecules. Here, we investigate whether RNAseq using the long-read single-molecule Oxford Nanopore MinION sequencer is able to identify and quantify complex isoforms without sacrificing accurate gene expression quantification. After benchmarking our approach, we analyse individual murine B1a cells using a custom multiplexing strategy. We identify thousands of unannotated transcription start and end sites, as well as hundreds of alternative splicing events in these B1a cells. We also identify hundreds of genes expressed across B1a cells that display multiple complex isoforms, including several B cell-specific surface receptors. Our results show that we can identify and quantify complex isoforms at the single cell level. Short-read RNA-seq is limited in its ability to resolve complex transcript isoforms since it cannot sequence full-length cDNA. Here the authors use Oxford Nanopore MinION and their Mandalorion analysis pipeline to measure complex isoforms in B1a cells.

Antibodies are created and refined by somatic evolution in B cell populations, which endows the human immune system with the ability to recognize and eliminate diverse pathogens. However, the evolutionary processes that sculpt antibody repertoires remain poorly understood. Here, using an unbiased repertoire-scale approach, we show that the population genetic signatures of evolution are evident in human B cell lineages and reveal how antibodies evolve somatically. We measured the dynamics and genetic diversity of B cell responses in five adults longitudinally before and after influenza vaccination using high-throughput antibody repertoire sequencing. We identified vaccine-responsive B cell lineages that carry signatures of selective sweeps driven by positive selection, and discovered that they often display evidence for selective sweeps favoring multiple subclones. We also found persistent B cell lineages that exhibit stable population dynamics and carry signatures of neutral drift. By exploiting the relationship between B cell fitness and antibody binding affinity, we demonstrate the potential for using phylogenetic approaches to identify antibodies with high binding affinity. This quantitative characterization reveals that antibody repertoires are shaped by an unexpectedly broad spectrum of evolutionary processes and shows how signatures of evolutionary history can be harnessed for antibody discovery and engineering.

Recent studies have identified thousands of long noncoding RNAs (lncRNAs) in mammalian genomes that regulate gene expression in different biological processes. Although lncRNAs have been identified in a variety of immune cells and implicated in immune response, the biological function and mechanism of the majority remain unexplored, especially in sepsis. Here, we identify a role for a lncRNA—gastric adenocarcinoma predictive long intergenic noncoding RNA (GAPLINC)—previously characterized for its role in cancer, now in the context of innate immunity, macrophages, and LPS-induced endotoxic shock. Transcriptome analysis of macrophages from humans and mice reveals that GAPLINC is a conserved lncRNA that is highly expressed following macrophage differentiation. Upon inflammatory activation, GAPLINC is rapidly down-regulated. Macrophages depleted of GAPLINC display enhanced expression of inflammatory genes at baseline, while overexpression of GAPLINC suppresses this response. Consistent with GAPLINC-depleted cells, Gaplinc knockout mice display enhanced basal levels of inflammatory genes and show resistance to LPS-induced endotoxic shock. Mechanistically, survival is linked to increased levels of nuclear NF-κB in Gaplinc knockout mice that drives basal expression of target genes typically only activated following inflammatory stimulation. We show that this activation of immune response genes prior to LPS challenge leads to decreased blood clot formation, which protects Gaplinc knockout mice from multiorgan failure and death. Together, our results identify a previously unknown function for GAPLINC as a negative regulator of inflammation and uncover a key role for this lncRNA in modulating endotoxic shock.

In mammals, the circadian oscillator generates approximately 24-h rhythms in feeding behavior, even under constant environmental conditions. Livers of mice held under constant darkness exhibit circadian rhythm in abundance in up to 15% of expressed transcripts. Therefore, oscillations in hepatic transcripts could be driven by rhythmic food intake or sustained by the hepatic circadian oscillator, or a combination of both. To address this question, we used distinct feeding and fasting paradigms on wild-type (WT) and circadian clock-deficient mice. We monitored temporal patterns of feeding and hepatic transcription. Both food availability and the temporal pattern of feeding determined the repertoire, phase, and amplitude of the circadian transcriptome in WT liver. In the absence of feeding, only a small subset of transcripts continued to express circadian patterns. Conversely, temporally restricted feeding restored rhythmic transcription of hundreds of genes in oscillator-deficient mouse liver. Our findings show that both temporal pattern of food intake and the circadian clock drive rhythmic transcription, thereby highlighting temporal regulation of hepatic transcription as an emergent property of the circadian system.

Annual influenza vaccinations aim to protect against seasonal infections, and vaccine strain compositions are updated every year. This protection is based on antibodies that are produced by either newly activated or memory B cells recalled from previous encounters with influenza vaccination or infection. The extent to which the B-cell repertoire responds to vaccination and recalls antibodies has so far not been analyzed at a genetic level—which is to say, at the level of antibody sequences. Here, we developed a consensus read sequencing approach that incorporates unique barcode labels on each starting RNA molecule. These labels allow one to combine multiple sequencing reads covering the same RNA molecule to reduce the error rate to a desired level, and they also enable accurate quantification of RNA and isotype levels. We validated this approach and analyzed the differential response of the antibody repertoire to live-attenuated or trivalent-inactivated influenza vaccination. Additionally, we analyzed the antibody repertoire in response to repeated yearly vaccinations with trivalent-inactivated influenza vaccination. We found antibody sequences that were present in both years, providing a direct genetic measurement of B-cell recall.

Background RNA-seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants (SNVs) in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme that mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung adenocarcinoma cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, the use of short-read RNA-seq has limited the community’s ability to interrogate both forms of RNA variation simultaneously. Results We employ long-read sequencing technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We develop a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generate nanopore data with high sequence accuracy from H1975 lung adenocarcinoma cells with and without knockdown of ADAR . We apply our workflow to identify key inosine isoform associations to help clarify the prominence of ADAR in tumorigenesis. Conclusions Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

In this manuscript, we introduce and benchmark Mandalorion v4.1 for the identification and quantification of full-length transcriptome sequencing reads. It further improves upon the already strong performance of Mandalorion v3.6 used in the LRGASP consortium challenge. By processing real and simulated data, we show three main features of Mandalorion: first, Mandalorion-based isoform identification has very high precision and maintains high recall even in the absence of any genome annotation. Second, isoform read counts as quantified by Mandalorion show a high correlation with simulated read counts. Third, isoforms identified by Mandalorion closely reflect the full-length transcriptome sequencing data sets they are based on.

The diversity of antibody variable regions makes cDNA sequencing challenging, and conventional monoclonal antibody cDNA amplification requires the use of degenerate primers. Here, we describe a simplified workflow for amplification of IgG antibody variable regions from hybridoma RNA by a specialized RT-PCR followed by Sanger sequencing. We perform three separate reactions for each hybridoma: one each for kappa, lambda, and heavy chain transcripts. We prime reverse transcription with a primer specific to the respective constant region and use a template-switch oligonucleotide, which creates a custom sequence at the 5' end of the antibody cDNA. This template-switching circumvents the issue of low sequence homology and the need for degenerate primers. Instead, subsequent PCR amplification of the antibody cDNA molecules requires only two primers: one primer specific for the template-switch oligonucleotide sequence and a nested primer to the respective constant region. We successfully sequenced the variable regions of five mouse monoclonal IgG antibodies using this method, which enabled us to design chimeric mouse/human antibody expression plasmids for recombinant antibody production in mammalian cell culture expression systems. All five recombinant antibodies bind their respective antigens with high affinity, confirming that the amino acid sequences determined by our method are correct and demonstrating the high success rate of our method. Furthermore, we also designed RT-PCR primers and amplified the variable regions from RNA of cells transfected with chimeric mouse/human antibody expression plasmids, showing that our approach is also applicable to IgG antibodies of human origin. Our monoclonal antibody sequencing method is highly accurate, user-friendly, and very cost-effective.