Time-course RNAseq data of murine AB1 mesothelioma and Renca renal cancer following immune checkpoint therapy.

Time-critical transcriptional events in the immune microenvironment are important for response to immune checkpoint blockade (ICB), yet these events are difficult to characterise and remain incompletely understood. Here, we present whole tumor RNA sequencing data in the context of treatment with ICB in murine models of AB1 mesothelioma and Renca renal cell cancer. We sequenced 144 bulk RNAseq samples from these two cancer types across 4 time points prior and after treatment with ICB. We also performed single-cell sequencing on 12 samples of AB1 and Renca tumors an hour before ICB administration. Our samples were equally distributed between responders and non-responders to treatment. Additionally, we sequenced AB1-HA mesothelioma tumors treated with two sample dissociation protocols to assess the impact of these protocols on the quality transcriptional information in our samples. These datasets provide time-course information to transcriptionally characterize the ICB response and provide detailed information at the single-cell level of the early tumor microenvironment prior to ICB therapy.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Immune checkpoint therapy responders display early clonal expansion of tumor infiltrating lymphocytes.

Immune checkpoint therapy (ICT) causes durable tumour responses in a subgroup of patients, but it is not well known how T cell receptor beta (TCRß) repertoire dynamics contribute to the therapeutic response. Using murine models that exclude variation in host genetics, environmental factors and tumour mutation burden, limiting variation between animals to naturally diverse TCRß repertoires, we applied TCRseq, single cell RNAseq and flow cytometry to study TCRß repertoire dynamics in ICT responders and non-responders. Increased oligoclonal expansion of TCRß clonotypes was observed in responding tumours. Machine learning identified TCRß CDR3 signatures unique to each tumour model, and signatures associated with ICT response at various timepoints before or during ICT. Clonally expanded CD8+ T cells in responding tumours post ICT displayed effector T cell gene signatures and phenotype. An early burst of clonal expansion during ICT is associated with response, and we report unique dynamics in TCRß signatures associated with ICT response.

Therapeutic blockade of ER stress and inflammation prevents NASH and progression to HCC.

The incidence of hepatocellular carcinoma (HCC) is rapidly rising largely because of increased obesity leading to nonalcoholic steatohepatitis (NASH), a known HCC risk factor. There are no approved treatments to treat NASH. Here, we first used single-nucleus RNA sequencing to characterize a mouse model that mimics human NASH-driven HCC, the MUP-uPA mouse fed a high-fat diet. Activation of endoplasmic reticulum (ER) stress and inflammation was observed in a subset of hepatocytes that was enriched in mice that progress to HCC. We next treated MUP-uPA mice with the ER stress inhibitor BGP-15 and soluble gp130Fc, a drug that blocks inflammation by preventing interleukin-6 trans-signaling. Both drugs have progressed to phase 2/3 human clinical trials for other indications. We show that this combined therapy reversed NASH and reduced NASH-driven HCC. Our data suggest that these drugs could provide a potential therapy for NASH progression to HCC.

Single-nucleus RNA sequencing of pre-malignant liver reveals disease-associated hepatocyte state with HCC prognostic potential.

Current approaches to staging chronic liver diseases have limited utility for predicting liver cancer risk. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to characterize the cellular microenvironment of healthy and pre-malignant livers using two distinct mouse models. Downstream analyses unraveled a previously uncharacterized disease-associated hepatocyte (daHep) transcriptional state. These cells were absent in healthy livers but increasingly prevalent as chronic liver disease progressed. Copy number variation (CNV) analysis of microdissected tissue demonstrated that daHep-enriched regions are riddled with structural variants, suggesting these cells represent a pre-malignant intermediary. Integrated analysis of three recent human snRNA-seq datasets confirmed the presence of a similar phenotype in human chronic liver disease and further supported its enhanced mutational burden. Importantly, we show that high daHep levels precede carcinogenesis and predict a higher risk of hepatocellular carcinoma development. These findings may change the way chronic liver disease patients are staged, surveilled, and risk stratified.

Characterization of the humanized FRG mouse model and development of an AAV-LK03 variant with improved liver lobular biodistribution.

Recent clinical successes have intensified interest in using adeno-associated virus (AAV) vectors for therapeutic gene delivery. The liver is a key clinical target, given its critical physiological functions and involvement in a wide range of genetic diseases. In the present study, we first investigated the validity of a liver xenograft mouse model repopulated with primary hepatocytes using single-nucleus RNA sequencing (sn-RNA-seq) by studying the transcriptomic profile of human hepatocytes pre- and post-engraftment. Complementary immunofluorescence analyses performed in highly engrafted animals confirmed that the human hepatocytes organize and present appropriate patterns of zone-dependent enzyme expression in this model. Next, we tested a set of rationally designed HSPG de-targeted AAV-LK03 variants for relative transduction performance in human hepatocytes. We used immunofluorescence, next-generation sequencing, and single-nucleus transcriptomics data from highly engrafted FRG mice to demonstrate that the optimally HSPG de-targeted AAV-LK03 displayed a significantly improved lobular transduction profile in this model.

Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution.

Human brain development is underpinned by cellular and molecular reconfigurations continuing into the third decade of life. To reveal cell dynamics orchestrating neural maturation, we profiled human prefrontal cortex gene expression and chromatin accessibility at single-cell resolution from gestation to adulthood. Integrative analyses define the dynamic trajectories of each cell type, revealing major gene expression reconfiguration at the prenatal-to-postnatal transition in all cell types followed by continuous reconfiguration into adulthood and identifying regulatory networks guiding cellular developmental programs, states, and functions. We uncover links between expression dynamics and developmental milestones, characterize the diverse timing of when cells acquire adult-like states, and identify molecular convergence from distinct developmental origins. We further reveal cellular dynamics and their regulators implicated in neurological disorders. Finally, using this reference, we benchmark cell identities and maturation states in organoid models. Together, this captures the dynamic regulatory landscape of human cortical development.

Correction: MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments.

[This corrects the article DOI: 10.1371/journal.pcbi.1010241.].

Temporally restricted activation of IFNß signaling underlies response to immune checkpoint therapy in mice.

The biological determinants of the response to immune checkpoint blockade (ICB) in cancer remain incompletely understood. Little is known about dynamic biological events that underpin therapeutic efficacy due to the inability to frequently sample tumours in patients. Here, we map the transcriptional profiles of 144 responding and non-responding tumours within two mouse models at four time points during ICB. We find that responding tumours display on/fast-off kinetics of type-I-interferon (IFN) signaling. Phenocopying of this kinetics using time-dependent sequential dosing of recombinant IFNs and neutralizing antibodies markedly improves ICB efficacy, but only when IFNß is targeted, not IFNα. We identify Ly6C+/CD11b+ inflammatory monocytes as the primary source of IFNß and find that active type-I-IFN signaling in tumour-infiltrating inflammatory monocytes is associated with T cell expansion in patients treated with ICB. Together, our results suggest that on/fast-off modulation of IFNß signaling is critical to the therapeutic response to ICB, which can be exploited to drive clinical outcomes towards response.

Deep sequencing of short capped RNAs reveals novel families of noncoding RNAs.

In eukaryotes, capped RNAs include long transcripts such as messenger RNAs and long noncoding RNAs, as well as shorter transcripts such as spliceosomal RNAs, small nucleolar RNAs, and enhancer RNAs. Long capped transcripts can be profiled using cap analysis gene expression (CAGE) sequencing and other methods. Here, we describe a sequencing library preparation protocol for short capped RNAs, apply it to a differentiation time course of the human cell line THP-1, and systematically compare the landscape of short capped RNAs to that of long capped RNAs. Transcription initiation peaks associated with genes in the sense direction have a strong preference to produce either long or short capped RNAs, with one out of six peaks detected in the short capped RNA libraries only. Gene-associated short capped RNAs have highly specific 3' ends, typically overlapping splice sites. Enhancers also preferentially generate either short or long capped RNAs, with 10% of enhancers observed in the short capped RNA libraries only. Enhancers producing either short or long capped RNAs show enrichment for GWAS-associated disease SNPs. We conclude that deep sequencing of short capped RNAs reveals new families of noncoding RNAs and elucidates the diversity of transcripts generated at known and novel promoters and enhancers.

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments.

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.

Bi-allelic loss-of-function OBSCN variants predispose individuals to severe recurrent rhabdomyolysis.

Rhabdomyolysis is the acute breakdown of skeletal myofibres in response to an initiating factor, most commonly toxins and over exertion. A variety of genetic disorders predispose to rhabdomyolysis through different pathogenic mechanisms, particularly in patients with recurrent episodes. However, most cases remain without a genetic diagnosis. Here we present six patients who presented with severe and recurrent rhabdomyolysis, usually with onset in the teenage years; other features included a history of myalgia and muscle cramps. We identified 10 bi-allelic loss-of-function variants in the gene encoding obscurin (OBSCN) predisposing individuals to recurrent rhabdomyolysis. We show reduced expression of OBSCN and loss of obscurin protein in patient muscle. Obscurin is proposed to be involved in sarcoplasmic reticulum function and Ca2+ handling. Patient cultured myoblasts appear more susceptible to starvation as evidenced by a greater decreased in sarcoplasmic reticulum Ca2+ content compared to control myoblasts. This likely reflects a lower efficiency when pumping Ca2+ back into the sarcoplasmic reticulum and/or a decrease in Ca2+ sarcoplasmic reticulum storage ability when metabolism is diminished. OSBCN variants have previously been associated with cardiomyopathies. None of the patients presented with a cardiomyopathy and cardiac examinations were normal in all cases in which cardiac function was assessed. There was also no history of cardiomyopathy in first degree relatives, in particular in any of the carrier parents. This cohort is relatively young, thus follow-up studies and the identification of additional cases with bi-allelic null OBSCN variants will further delineate OBSCN-related disease and the clinical course of disease.

Intra- and intertumoral heterogeneity of liver metastases in a patient with uveal melanoma revealed by single-cell RNA sequencing.

Tumor heterogeneity is a major obstacle to the success of cancer treatment. An accurate understanding and recognition of tumor heterogeneity is critical in the clinical management of cancer patients. Here, we utilized single-cell RNA sequencing (scRNA-seq) to uncover the intra- and intertumoral heterogeneity of liver metastases from a patient with metastatic uveal melanoma. The two metastases analyzed were largely infiltrated by noncancerous cells with significant variability in the proportion of different cell types. Analysis of copy-number variations (CNVs) showed gain of 8q and loss of 6q in both tumors, but loss of Chromosome 3 was only detected in one of the tumors. Single-nucleotide polymorphism (SNP) array revealed a uniparental isodisomy 3 in the tumor with two copies of Chromosome 3, indicating a regain of Chromosome 3 during the development of the metastatic disease. In addition, both tumors harbored subclones with additional CNVs. Pathway enrichment analysis of differentially expressed genes revealed that cancer cells in the metastasis with isodisomy 3 showed up-regulation in epithelial-mesenchymal transition and myogenesis related genes. In contrast, up-regulation in interferon signaling was observed in the metastasis with monosomy 3 and increased T-cell infiltrate. This study highlights the complexity and heterogeneity of different metastases within an individual case of uveal melanoma.

Improved CRISPR/Cas9 gene editing in primary human myoblasts using low confluency cultures on Matrigel.

BACKGROUND: CRISPR/Cas9 is an invaluable tool for studying cell biology and the development of molecular therapies. However, delivery of CRISPR/Cas9 components into some cell types remains a major hurdle. Primary human myoblasts are a valuable cell model for muscle studies, but are notoriously difficult to transfect. There are currently no commercial lipofection protocols tailored for primary myoblasts, and most generic guidelines simply recommend transfecting healthy cells at high confluency. This study aimed to maximize CRISPR/Cas9 transfection and editing in primary human myoblasts. METHODS: Since increased cell proliferation is associated with increased transfection efficiency, we investigated two factors known to influence myoblast proliferation: cell confluency, and a basement membrane matrix, Matrigel. CRISPR/Cas9 editing was performed by delivering Cas9 ribonucleoprotein complexes via lipofection into primary human myoblasts, cultured in wells with or without a Matrigel coating, at low (~ 40%) or high (~ 80%) confluency. RESULTS: Cells transfected at low confluency on Matrigel-coated wells had the highest levels of transfection, and were most effectively edited across three different target loci, achieving a maximum editing efficiency of 93.8%. On average, editing under these conditions was >4-fold higher compared to commercial recommendations (high confluency, uncoated wells). CONCLUSION: This study presents a simple, effective and economical method of maximizing CRISPR/Cas9-mediated gene editing in primary human myoblasts. This protocol could be a valuable tool for improving the genetic manipulation of cultured human skeletal muscle cells, and potentially be adapted for use in other cell types.

Brain-Enriched Coding and Long Non-coding RNA Genes Are Overrepresented in Recurrent Neurodevelopmental Disorder CNVs.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with substantial phenotypic and etiological heterogeneity. Although 10%-20% of ASD cases are attributable to copy number variation (CNV), causative genomic loci and constituent genes remain unclarified. We have developed SNATCNV, a tool that outperforms existing tools, to identify 47 recurrent ASD CNV regions from 19,663 cases and 6,479 controls documented in the AutDB database. Analysis of ASD CNV gene content using FANTOM5 shows that constituent coding genes and long non-coding RNAs have brain-enriched patterns of expression. Notably, such enrichment is not observed for regions identified by using other tools. We also find evidence of sexual dimorphism, one locus uniquely comprising a single lncRNA gene, and correlation of CNVs to distinct clinical and behavioral traits. Finally, we analyze a large dataset for schizophrenia to further demonstrate that SNATCNV is an effective, publicly available tool to define genomic loci and causative genes for multiple CNV-associated conditions.

Predicting cell-to-cell communication networks using NATMI.

Development of high throughput single-cell sequencing technologies has made it cost-effective to profile thousands of cells from diverse samples containing multiple cell types. To study how these different cell types work together, here we develop NATMI (Network Analysis Toolkit for Multicellular Interactions). NATMI uses connectomeDB2020 (a database of 2293 manually curated ligand-receptor pairs with literature support) to predict and visualise cell-to-cell communication networks from single-cell (or bulk) expression data. Using multiple published single-cell datasets we demonstrate how NATMI can be used to identify (i) the cell-type pairs that are communicating the most (or most specifically) within a network, (ii) the most active (or specific) ligand-receptor pairs active within a network, (iii) putative highly-communicating cellular communities and (iv) differences in intercellular communication when profiling given cell types under different conditions. Furthermore, analysis of the Tabula Muris (organism-wide) atlas confirms our previous prediction that autocrine signalling is a major feature of cell-to-cell communication networks, while also revealing that hundreds of ligands and their cognate receptors are co-expressed in individual cells suggesting a substantial potential for self-signalling.

Human genetics and genomics meetings going virtual: practical lessons learned from two international meetings in early 2020.

The recent coronavirus disease 2019 (COVID-19) pandemic has caused worldwide disruption which also extends to the arena of scientific meetings around the world. Here, we explore the lessons learned from moving two human genetics and genomics meetings quickly to an online format in early 2020. The tips presented herein may be useful not only for future virtual meetings but may also enrich future physical if not hybrid meetings once they resume.

Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows.

BACKGROUND: Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample dissociation and storage of single cells have been proposed as have single-nuclei profiling methods. What has been lacking is a systematic comparison of their relative biases and benefits. RESULTS: Here, we compare gene expression and cellular composition of single-cell suspensions prepared from adult mouse kidney using two tissue dissociation protocols. For each sample, we also compare fresh cells to cryopreserved and methanol-fixed cells. Lastly, we compare this single-cell data to that generated using three single-nucleus RNA sequencing workflows. Our data confirms prior reports that digestion on ice avoids the stress response observed with 37 °C dissociation. It also reveals cell types more abundant either in the cold or warm dissociations that may represent populations that require gentler or harsher conditions to be released intact. For cell storage, cryopreservation of dissociated cells results in a major loss of epithelial cell types; in contrast, methanol fixation maintains the cellular composition but suffers from ambient RNA leakage. Finally, cell type composition differences are observed between single-cell and single-nucleus RNA sequencing libraries. In particular, we note an underrepresentation of T, B, and NK lymphocytes in the single-nucleus libraries. CONCLUSIONS: Systematic comparison of recovered cell types and their transcriptional profiles across the workflows has highlighted protocol-specific biases and thus enables researchers starting single-cell experiments to make an informed choice.

Comprehensive Characterization of Transcriptional Activity during Influenza A Virus Infection Reveals Biases in Cap-Snatching of Host RNA Sequences.

Macrophages in the lung detect and respond to influenza A virus (IAV), determining the nature of the immune response. Using terminal-depth cap analysis of gene expression (CAGE), we quantified transcriptional activity of both host and pathogen over a 24-h time course of IAV infection in primary human monocyte-derived macrophages (MDMs). This method allowed us to observe heterogenous host sequences incorporated into IAV mRNA, "snatched" 5' RNA caps, and corresponding RNA sequences from host RNAs. In order to determine whether cap-snatching is random or exhibits a bias, we systematically compared host sequences incorporated into viral mRNA ("snatched") against a complete survey of all background host RNA in the same cells, at the same time. Using a computational strategy designed to eliminate sources of bias due to read length, sequencing depth, and multimapping, we were able to quantify overrepresentation of host RNA features among the sequences that were snatched by IAV. We demonstrate biased snatching of numerous host RNAs, particularly small nuclear RNAs (snRNAs), and avoidance of host transcripts encoding host ribosomal proteins, which are required by IAV for replication. We then used a systems approach to describe the transcriptional landscape of the host response to IAV, observing many new features, including a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation, seen in response to other treatments.IMPORTANCE Infection with influenza A virus (IAV) infection is responsible for an estimated 500,000 deaths and up to 5 million cases of severe respiratory illness each year. In this study, we looked at human primary immune cells (macrophages) infected with IAV. Our method allows us to look at both the host and the virus in parallel. We used these data to explore a process known as "cap-snatching," where IAV snatches a short nucleotide sequence from capped host RNA. This process was believed to be random. We demonstrate biased snatching of numerous host RNAs, including those associated with snRNA transcription, and avoidance of host transcripts encoding host ribosomal proteins, which are required by IAV for replication. We then describe the transcriptional landscape of the host response to IAV, observing new features, including a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation, seen in response to other treatments.

CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes.

Analysis of cancer mutational signatures have been instrumental in identification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly interface for analysis of cancer mutational signatures is necessary. In this manuscript we introduce CANCERSIGN, which enables users to identify 3-mer and 5-mer mutational signatures within whole genome, whole exome or pooled samples. Additionally, this tool enables users to perform clustering on tumor samples based on the proportion of mutational signatures in each sample. Using CANCERSIGN, we analysed all the whole genome somatic mutation datasets profiled by the International Cancer Genome Consortium (ICGC) and identified a number of novel signatures. By examining signatures found in exonic and non-exonic regions of the genome using WGS and comparing this to signatures found in WES data we observe that WGS can identify additional non-exonic signatures that are enriched in the non-coding regions of the genome while the deeper sequencing of WES may help identify weak signatures that are otherwise missed in shallower WGS data.