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.

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.

CRISPR-Cas9-generated PTCHD1 2489T>G stem cells recapitulate patient phenotype when undergoing neural induction.

An estimated 3.5%-5.9% of the global population live with rare diseases, and approximately 80% of these diseases have a genetic cause. Rare genetic diseases are difficult to diagnose, with some affected individuals experiencing diagnostic delays of 5-30 years. Next-generation sequencing has improved clinical diagnostic rates to 33%-48%. In a majority of cases, novel variants potentially causing the disease are discovered. These variants require functional validation in specialist laboratories, resulting in a diagnostic delay. In the interim, the finding is classified as a genetic variant of uncertain significance (VUS) and the affected individual remains undiagnosed. A VUS (PTCHD1 c. 2489T>G) was identified in a child with autistic behavior, global developmental delay, and hypotonia. Loss of function mutations in PTCHD1 are associated with autism spectrum disorder and intellectual disability; however, the molecular function of PTCHD1 and its role in neurodevelopmental disease is unknown. Here, we apply CRISPR gene editing and induced pluripotent stem cell (iPSC) neural disease modeling to assess the variant. During differentiation from iPSCs to neural progenitors, we detect subtle but significant gene signatures in synaptic transmission and muscle contraction pathways. Our work supports the causal link between the genetic variant and the child's phenotype, providing evidence for the variant to be considered a pathogenic variant according to the American College of Medical Genetics and Genomics guidelines. In addition, our study provides molecular data on the role of PTCHD1 in the context of other neurodevelopmental disorders.

Gene editing and cardiac disease modelling for the interpretation of genetic variants of uncertain significance in congenital heart disease.

BACKGROUND: Genomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays. We investigated stem cell cardiac disease modelling and transcriptomics for the purpose of genetic variant classification using a GATA4 (p.Arg283Cys) VUS in a patient with CHD. METHODS: We performed high efficiency CRISPR gene editing with homology directed repair in induced pluripotent stem cells (iPSCs), followed by rapid clonal selection with amplicon sequencing. Genetic variant and healthy matched control cells were compared using cardiomyocyte disease modelling and transcriptomics. RESULTS: Genetic variant and healthy cardiomyocytes similarly expressed Troponin T (cTNNT), and GATA4. Transcriptomics analysis of cardiomyocyte differentiation identified changes consistent with the patient's clinical human phenotype ontology terms. Further, transcriptomics revealed changes in calcium signalling, and cardiomyocyte adrenergic signalling in the variant cells. Functional testing demonstrated, altered action potentials in GATA4 genetic variant cardiomyocytes were consistent with patient cardiac abnormalities. CONCLUSIONS: This work provides in vivo functional studies supportive of a damaging effect on the gene or gene product. Furthermore, we demonstrate the utility of iPSCs, CRISPR gene editing and cardiac disease modelling for genetic variant interpretation. The method can readily be applied to other genetic variants in GATA4 or other genes in cardiac disease, providing a centralised assessment pathway for patient genetic variant interpretation.

SAMStat 2: quality control for next generation sequencing data.

MOTIVATION: SAMStat is an efficient program to extract quality control metrics from fastq and SAM/BAM files. A distinguishing feature is that it displays sequence composition, base quality composition and mapping error profiles split by mapping quality. This allows users to rapidly identify reasons for poor mapping including the presence of untrimmed adapters or poor sequencing quality at individual read positions. RESULTS: Here, we present a major update to SAMStat. The new version now supports paired-end and long-read data. Quality control plots are drawn using the ploty javascript library. AVAILABILITY AND IMPLEMENTATION: The source code of SAMStat and code to reproduce the results are found here: https://github.com/timolassmann/samstat.

CD4+ T cells drive an inflammatory, TNF-α/IFN-rich tumor microenvironment responsive to chemotherapy.

While chemotherapy remains the first-line treatment for many cancers, it is still unclear what distinguishes responders from non-responders. Here, we characterize the chemotherapy-responsive tumor microenvironment in mice, using RNA sequencing on tumors before and after cyclophosphamide, and compare the gene expression profiles of responders with progressors. Responsive tumors have an inflammatory and highly immune infiltrated pre-treatment tumor microenvironment characterized by the enrichment of pathways associated with CD4+ T cells, interferons (IFNs), and tumor necrosis factor alpha (TNF-α). The same gene expression profile is associated with response to cyclophosphamide-based chemotherapy in patients with breast cancer. Finally, we demonstrate that tumors can be sensitized to cyclophosphamide and 5-FU chemotherapy by pre-treatment with recombinant TNF-α, IFNγ, and poly(I:C). Thus, a CD4+ T cell-inflamed pre-treatment tumor microenvironment is necessary for response to chemotherapy, and this state can be therapeutically attained by targeted immunotherapy.

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.

An expanded phenotype centric benchmark of variant prioritisation tools.

Identifying the causal variant for diagnosis of genetic diseases is challenging when using next-generation sequencing approaches and variant prioritization tools can assist in this task. These tools provide in silico predictions of variant pathogenicity, however they are agnostic to the disease under study. We previously performed a disease-specific benchmark of 24 such tools to assess how they perform in different disease contexts. We found that the tools themselves show large differences in performance, but more importantly that the best tools for variant prioritization are dependent on the disease phenotypes being considered. Here we expand the assessment to 37 tools and refine our assessment by separating performance for nonsynonymous single nucleotide variants (nsSNVs) and missense variants (i.e., excluding nonsense variants). We found differences in performance for missense variants compared to nsSNVs and recommend three tools that stand out in terms of their performance (BayesDel, CADD, and ClinPred).

Functional validation of variants of unknown significance using CRISPR gene editing and transcriptomics: A Kleefstra syndrome case study.

There are an estimated > 400 million people living with a rare disease globally, with genetic variants the cause of approximately 80% of cases. Next Generation Sequencing (NGS) rapidly identifies genetic variants however they are often of unknown significance. Low throughput functional validation in specialist laboratories is the current ad hoc approach for functional validation of genetic variants, which creating major bottlenecks in patient diagnosis. This study investigates the application of CRISPR gene editing followed by genome wide transcriptomic profiling to facilitate patient diagnosis. As proof-of-concept, we introduced a variant in the Euchromatin histone methyl transferase (EHMT1) gene into HEK293T cells. We identified changes in the regulation of the cell cycle, neural gene expression and suppression of gene expression changes on chromosome 19 and chromosome X, that are in keeping with Kleefstra syndrome clinical phenotype and/or provide insight into disease mechanism. This study demonstrates the utility of genome editing followed by functional readouts to rapidly and systematically validating the function of variants of unknown significance in patients suffering from rare diseases.

CRISPR single base editing, neuronal disease modelling and functional genomics for genetic variant analysis: pipeline validation using Kleefstra syndrome EHMT1 haploinsufficiency.

BACKGROUND: Over 400 million people worldwide are living with a rare disease. Next Generation Sequencing (NGS) identifies potential disease causative genetic variants. However, many are identified as variants of uncertain significance (VUS) and require functional laboratory validation to determine pathogenicity, and this creates major diagnostic delays. METHODS: In this study we test a rapid genetic variant assessment pipeline using CRISPR homology directed repair to introduce single nucleotide variants into inducible pluripotent stem cells (iPSCs), followed by neuronal disease modelling, and functional genomics on amplicon and RNA sequencing, to determine cellular changes to support patient diagnosis and identify disease mechanism. RESULTS: As proof-of-principle, we investigated an EHMT1 (Euchromatin histone methyltransferase 1; EHMT1 c.3430C > T; p.Gln1144*) genetic variant pathogenic for Kleefstra syndrome and determined changes in gene expression during neuronal progenitor cell differentiation. This pipeline rapidly identified Kleefstra syndrome in genetic variant cells compared to healthy cells, and revealed novel findings potentially implicating the key transcription factors REST and SP1 in disease pathogenesis. CONCLUSION: The study pipeline is a rapid, robust method for genetic variant assessment that will support rare diseases patient diagnosis. The results also provide valuable information on genome wide perturbations key to disease mechanism that can be targeted for drug treatments.

Searching for a technology-driven acute rheumatic fever test: the START study protocol.

INTRODUCTION: The absence of a diagnostic test for acute rheumatic fever (ARF) is a major impediment in managing this serious childhood condition. ARF is an autoimmune condition triggered by infection with group A Streptococcus. It is the precursor to rheumatic heart disease (RHD), a leading cause of health inequity and premature mortality for Indigenous peoples of Australia, New Zealand and internationally. METHODS AND ANALYSIS: 'Searching for a Technology-Driven Acute Rheumatic Fever Test' (START) is a biomarker discovery study that aims to detect and test a biomarker signature that distinguishes ARF cases from non-ARF, and use systems biology and serology to better understand ARF pathogenesis. Eligible participants with ARF diagnosed by an expert clinical panel according to the 2015 Revised Jones Criteria, aged 5-30 years, will be recruited from three hospitals in Australia and New Zealand. Age, sex and ethnicity-matched individuals who are healthy or have non-ARF acute diagnoses or RHD, will be recruited as controls. In the discovery cohort, blood samples collected at baseline, and during convalescence in a subset, will be interrogated by comprehensive profiling to generate possible diagnostic biomarker signatures. A biomarker validation cohort will subsequently be used to test promising combinations of biomarkers. By defining the first biomarker signatures able to discriminate between ARF and other clinical conditions, the START study has the potential to transform the approach to ARF diagnosis and RHD prevention. ETHICS AND DISSEMINATION: The study has approval from the Northern Territory Department of Health and Menzies School of Health Research ethics committee and the New Zealand Health and Disability Ethics Committee. It will be conducted according to ethical standards for research involving Indigenous Australians and New Zealand Maori and Pacific Peoples. Indigenous investigators and governance groups will provide oversight of study processes and advise on cultural matters.

Common and Rare Genetic Variants That Could Contribute to Severe Otitis Media in an Australian Aboriginal Population.

BACKGROUND: Our goal was to identify genetic risk factors for severe otitis media (OM) in Aboriginal Australians. METHODS: Illumina® Omni2.5 BeadChip and imputed data were compared between 21 children with severe OM (multiple episodes chronic suppurative OM and/or perforations or tympanic sclerosis) and 370 individuals without this phenotype, followed by FUnctional Mapping and Annotation (FUMA). Exome data filtered for common (EXaC_all ≥ 0.1) putative deleterious variants influencing protein coding (CADD-scaled scores ≥15] were used to compare 15 severe OM cases with 9 mild cases (single episode of acute OM recorded over ≥3 consecutive years). Rare (ExAC_all ≤ 0.01) such variants were filtered for those present only in severe OM. Enrichr was used to determine enrichment of genes contributing to pathways/processes relevant to OM. RESULTS: FUMA analysis identified 2 plausible genetic risk loci for severe OM: NR3C1 (Pimputed_1000G = 3.62 × 10-6) encoding the glucocorticoid receptor, and NREP (Pimputed_1000G = 3.67 × 10-6) encoding neuronal regeneration-related protein. Exome analysis showed: (i) association of severe OM with variants influencing protein coding (CADD-scaled ≥ 15) in a gene-set (GRXCR1, CDH23, LRP2, FAT4, ARSA, EYA4) enriched for Mammalian Phenotype Level 4 abnormal hair cell stereociliary bundle morphology and related phenotypes; (ii) rare variants influencing protein coding only seen in severe OM provided gene-sets enriched for "abnormal ear" (LMNA, CDH23, LRP2, MYO7A, FGFR1), integrin interactions, transforming growth factor signaling, and cell projection phenotypes including hair cell stereociliary bundles and cilium assembly. CONCLUSIONS: This study highlights interacting genes and pathways related to cilium structure and function that may contribute to extreme susceptibility to OM in Aboriginal Australian children.

Zika Virus Changes Methylation of Genes Involved in Immune Response and Neural Development in Brazilian Babies Born With Congenital Microcephaly.

The recent increase in babies born with brain and eye malformations in Brazil is associated with Zika virus (ZIKV) infection in utero. ZIKV alters host DNA methylation in vitro. Using genome-wide DNA methylation profiling we compared 18 babies born with congenital ZIKV microcephaly with 20 controls. We found ZIKV-associated alteration of host methylation patterns, notably at RABGAP1L which is important in brain development, at viral host immunity genes MX1 and ISG15, and in an epigenetic module containing the causal microcephaly gene MCPH1. Our data support the hypothesis that clinical signs of congenital ZIKV are associated with changes in DNA methylation.

A flexible computational pipeline for research analyses of unsolved clinical exome cases.

Exome sequencing has enabled molecular diagnoses for rare disease patients but often with initial diagnostic rates of ~25-30%. Here we develop a robust computational pipeline to rank variants for reassessment of unsolved rare disease patients. A comprehensive web-based patient report is generated in which all deleterious variants can be filtered by gene, variant characteristics, OMIM disease and Phenolyzer scores, and all are annotated with an ACMG classification and links to ClinVar. The pipeline ranked 21/34 previously diagnosed variants as top, with 26 in total ranked ≤7th, 3 ranked ≥13th; 5 failed the pipeline filters. Pathogenic/likely pathogenic variants by ACMG criteria were identified for 22/145 unsolved cases, and a previously undefined candidate disease variant for 27/145. This open access pipeline supports the partnership between clinical and research laboratories to improve the diagnosis of unsolved exomes. It provides a flexible framework for iterative developments to further improve diagnosis.

Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses.

Immunotherapies have revolutionized cancer treatment. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. However, the majority of treated patients do not respond. Understanding immune mechanisms that underlie responsiveness to ICT will help identify predictive biomarkers of response and develop treatments to convert non-responding patients to responding ones. ICT primarily acts at the level of adaptive immunity. The specificity of adaptive immune cells, such as T and B cells, is determined by antigen-specific receptors. T cell repertoires can be comprehensively profiled by high-throughput sequencing at the bulk and single-cell level. T cell receptor (TCR) sequencing allows for sensitive tracking of dynamic changes in antigen-specific T cells at the clonal level, giving unprecedented insight into the mechanisms by which ICT alters T cell responses. Here, we review how the repertoire influences response to ICT and conversely how ICT affects repertoire diversity. We will also explore how changes to the repertoire in different anatomical locations can better correlate and perhaps predict treatment outcome. We discuss the advantages and limitations of current metrics used to characterize and represent TCR repertoire diversity. Discovery of predictive biomarkers could lie in novel analysis approaches, such as network analysis of amino acids similarities between TCR sequences. Single-cell sequencing is a breakthrough technology that can link phenotype with specificity, identifying T cell clones that are crucial for successful ICT. The field of immuno-sequencing is rapidly developing and cross-disciplinary efforts are required to maximize the analysis, application, and validation of sequencing data. Unravelling the dynamic behavior of the TCR repertoire during ICT will be highly valuable for tracking and understanding anti-tumor immunity, biomarker discovery, and ultimately for the development of novel strategies to improve patient outcomes.

The bone marrow microenvironment of pre-B acute lymphoblastic leukemia at single-cell resolution.

The bone marrow microenvironment (BMM) plays a key role in leukemia progression, but its molecular complexity in pre-B cell acute lymphoblastic leukemia (B-ALL), the most common cancer in children, remains poorly understood. To gain further insight, we used single-cell RNA sequencing to characterize the kinetics of the murine BMM during B-ALL progression. Normal pro- and pre-B cells were found to be the most affected at the earliest stages of disease and this was associated with changes in expression of genes regulated by the AP1-transcription factor complex and regulatory factors NELFE, MYC and BCL11A. Granulocyte-macrophage progenitors show reduced expression of the tumor suppressor long non-coding RNA Neat1 and disruptions in the rate of transcription. Intercellular communication networks revealed monocyte-dendritic precursors to be consistently active during B-ALL progression, with enriched processes including cytokine-mediated signaling pathway, neutrophil-mediated immunity and regulation of cell migration and proliferation. In addition, we confirmed that the hematopoietic stem and progenitor cell compartment was perturbed during leukemogenesis. These findings extend our understanding of the complexity of changes and molecular interactions among the normal cells of the BMM during B-ALL progression.

Reference exome data for a Northern Brazilian population.

Exome sequencing is widely used in the diagnosis of rare genetic diseases and provides useful variant data for analysis of complex diseases. There is not always adequate population-specific reference data to assist in assigning a diagnostic variant to a specific clinical condition. Here we provide a catalogue of variants called after sequencing the exomes of 45 babies from Rio Grande do Nord in Brazil. Sequence data were processed using an 'intersect-then-combine' (ITC) approach, using GATK and SAMtools to call variants. A total of 612,761 variants were identified in at least one individual in this Brazilian Cohort, including 559,448 single nucleotide variants (SNVs) and 53,313 insertion/deletions. Of these, 58,111 overlapped with nonsynonymous (nsSNVs) or splice site (ssSNVs) SNVs in dbNSFP. As an aid to clinical diagnosis of rare diseases, we used the American College of Medicine Genetics and Genomics (ACMG) guidelines to assign pathogenic/likely pathogenic status to 185 (0.32%) of the 58,111 nsSNVs and ssSNVs. Our data set provides a useful reference point for diagnosis of rare diseases in Brazil. (169 words).

Rhinovirus Infection Drives Complex Host Airway Molecular Responses in Children With Cystic Fibrosis.

Early-life viral infections are responsible for pulmonary exacerbations that can contribute to disease progression in young children with cystic fibrosis (CF). The most common respiratory viruses detected in the CF airway are human rhinoviruses (RV), and augmented airway inflammation in CF has been attributed to dysregulated airway epithelial responses although evidence has been conflicting. Here, we exposed airway epithelial cells from children with and without CF to RV in vitro. Using RNA-Seq, we profiled the transcriptomic differences of CF and non-CF airway epithelial cells at baseline and in response to RV. There were only modest differences between CF and non-CF cells at baseline. In response to RV, there were 1,442 and 896 differentially expressed genes in CF and non-CF airway epithelial cells, respectively. The core antiviral responses in CF and non-CF airway epithelial cells were mediated through interferon signaling although type 1 and 3 interferon signaling, when measured, were reduced in CF airway epithelial cells following viral challenge consistent with previous reports. The transcriptional responses in CF airway epithelial cells were more complex than in non-CF airway epithelial cells with diverse over-represented biological pathways, such as cytokine signaling and metabolic and biosynthetic pathways. Network analysis highlighted that the differentially expressed genes of CF airway epithelial cells' transcriptional responses were highly interconnected and formed a more complex network than observed in non-CF airway epithelial cells. We corroborate observations in fully differentiated air-liquid interface (ALI) cultures, identifying genes involved in IL-1 signaling and mucin glycosylation that are only dysregulated in the CF airway epithelial response to RV infection. These data provide novel insights into the CF airway epithelial cells' responses to RV infection and highlight potential pathways that could be targeted to improve antiviral and anti-inflammatory responses in CF.

Comparative transcriptomics of primary cells in vertebrates.

Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.

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.