Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures.

The lack of benchmark data sets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two human lung adenocarcinoma cell lines that were each profiled in triplicate together with synthetic, spliced, spike-in RNAs (sequins). Samples were deeply sequenced on both Illumina short-read and Oxford Nanopore Technologies long-read platforms. Alongside the ground-truth available via the sequins, we created in silico mixture samples to allow performance assessment in the absence of true positives or true negatives. Our results show that StringTie2 and bambu outperformed other tools from the six isoform detection tools tested, DESeq2, edgeR and limma-voom were best among the five differential transcript expression tools tested and there was no clear front-runner for performing differential transcript usage analysis between the five tools compared, which suggests further methods development is needed for this application.

Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data.

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce two new approaches that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold-standard methods that do not account for group heteroscedasticity, we show results from simulations and various experiments that demonstrate the superior performance of voomByGroup and voomQWB in terms of error control and power when group variances in pseudo-bulk single-cell RNA-seq data are unequal.

Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing.

A modified Chromium 10x droplet-based protocol that subsamples cells for both short-read and long-read (nanopore) sequencing together with a new computational pipeline (FLAMES) is developed to enable isoform discovery, splicing analysis, and mutation detection in single cells. We identify thousands of unannotated isoforms and find conserved functional modules that are enriched for alternative transcript usage in different cell types and species, including ribosome biogenesis and mRNA splicing. Analysis at the transcript level allows data integration with scATAC-seq on individual promoters, improved correlation with protein expression data, and linked mutations known to confer drug resistance to transcriptome heterogeneity.

Homeostatic apoptosis prevents competition-induced atrophy in follicular B cells.

While the intrinsic apoptosis pathway is thought to play a central role in shaping the B cell lineage, its precise role in mature B cell homeostasis remains elusive. Using mice in which mature B cells are unable to undergo apoptotic cell death, we show that apoptosis constrains follicular B (FoB) cell lifespan but plays no role in marginal zone B (MZB) cell homeostasis. In these mice, FoB cells accumulate abnormally. This intensifies intercellular competition for BAFF, resulting in a contraction of the MZB cell compartment, and reducing the growth, trafficking, and fitness of FoB cells. Diminished BAFF signaling dampens the non-canonical NF-κB pathway, undermining FoB cell growth despite the concurrent triggering of a protective p53 response. Thus, MZB and FoB cells exhibit a differential requirement for the intrinsic apoptosis pathway. Homeostatic apoptosis constrains the size of the FoB cell compartment, thereby preventing competition-induced FoB cell atrophy.

A functional genetic screen identifies aurora kinase b as an essential regulator of Sox9-positive mouse embryonic lung progenitor cells.

Development of a branching tree in the embryonic lung is crucial for the formation of a fully mature functional lung at birth. Sox9+ cells present at the tip of the primary embryonic lung endoderm are multipotent cells responsible for branch formation and elongation. We performed a genetic screen in murine primary cells and identified aurora kinase b (Aurkb) as an essential regulator of Sox9+ cells ex vivo. In vivo conditional knockout studies confirmed that Aurkb was required for lung development but was not necessary for postnatal growth and the repair of the adult lung after injury. Deletion of Aurkb in embryonic Sox9+ cells led to the formation of a stunted lung that retained the expression of Sox2 in the proximal airways, as well as Sox9 in the distal tips. Although we found no change in cell polarity, we showed that loss of Aurkb or chemical inhibition of Aurkb caused Sox9+ cells to arrest at G2/M, likely responsible for the lack of branch bifurcation. This work demonstrates the power of genetic screens in identifying novel regulators of Sox9+ progenitor cells and lung branching morphogenesis.

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools.

Application of Oxford Nanopore Technologies' long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ('sequins') as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

The impact of influenza pulmonary infection and inflammation on vagal bronchopulmonary sensory neurons.

Influenza A virus (IAV) is rapidly detected in the airways by the immune system, with resident parenchymal cells and leukocytes orchestrating viral sensing and the induction of antiviral inflammatory responses. The airways are innervated by heterogeneous populations of vagal sensory neurons which also play an important role in pulmonary defense. How these neurons respond to IAV respiratory infection remains unclear. Here, we use a murine model to provide the first evidence that vagal sensory neurons undergo significant transcriptional changes following a respiratory IAV infection. RNA sequencing on vagal sensory ganglia showed that IAV infection induced the expression of many genes associated with an antiviral and pro-inflammatory response and this was accompanied by a significant increase in inflammatory cell recruitment into the vagal ganglia. Assessment of gene expression in single-vagal sensory neurons confirmed that IAV infection induced a neuronal inflammatory phenotype, which was most prominent in bronchopulmonary neurons, and also evident in some neurons innervating other organs. The altered transcriptome could be mimicked by intranasal treatment with cytokines and the lung homogenates of infected mice, in the absence of infectious virus. These data argue that IAV pulmonary infection and subsequent inflammation induces vagal sensory ganglia neuroinflammation and this may have important implications for IAV-induced morbidity.

Dashboard-style interactive plots for RNA-seq analysis are R Markdown ready with Glimma 2.0.

Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Here, we present a major update to Glimma that brings improved interactivity and reproducibility using high-level visualization frameworks for R and JavaScript. Glimma 2.0 plots are now readily embeddable in R Markdown, thus allowing users to create reproducible reports containing interactive graphics. The revamped multidimensional scaling plot features dashboard-style controls allowing the user to dynamically change the colour, shape and size of sample points according to different experimental conditions. Interactivity was enhanced in the MA-style plot for comparing differences to average expression, which now supports selecting multiple genes, export options to PNG, SVG or CSV formats and includes a new volcano plot function. Feature-rich and user-friendly, Glimma makes exploring data for gene expression analysis more accessible and intuitive and is available on Bioconductor and GitHub.

Germline heterozygous mutations in Nxf1 perturb RNA metabolism and trigger thrombocytopenia and lymphopenia in mice.

In eukaryotic cells, messenger RNA (mRNA) molecules are exported from the nucleus to the cytoplasm, where they are translated. The highly conserved protein nuclear RNA export factor1 (Nxf1) is an important mediator of this process. Although studies in yeast and in human cell lines have shed light on the biochemical mechanisms of Nxf1 function, its contribution to mammalian physiology is less clear. Several groups have identified recurrent NXF1 mutations in chronic lymphocytic leukemia (CLL), placing it alongside several RNA-metabolism factors (including SF3B1, XPO, RPS15) whose dysregulation is thought to contribute to CLL pathogenesis. We report here an allelic series of germline point mutations in murine Nxf1. Mice heterozygous for these loss-of-function Nxf1 mutations exhibit thrombocytopenia and lymphopenia, together with milder hematological defects. This is primarily caused by cell-intrinsic defects in the survival of platelets and peripheral lymphocytes, which are sensitized to intrinsic apoptosis. In contrast, Nxf1 mutations have almost no effect on red blood cell homeostasis. Comparative transcriptome analysis of platelets, lymphocytes, and erythrocytes from Nxf1-mutant mice shows that, in response to impaired Nxf1 function, the cytoplasmic representation of transcripts encoding regulators of RNA metabolism is altered in a unique, lineage-specific way. Thus, blood cell lineages exhibit differential requirements for Nxf1-mediated global mRNA export.