Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns.

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

Deconvolving the contributions of cell-type heterogeneity on cortical gene expression.

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer's disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).

Next-generation sequencing identifies rare variants associated with Noonan syndrome.

Noonan syndrome (NS) is a relatively common genetic disorder, characterized by typical facies, short stature, developmental delay, and cardiac abnormalities. Known causative genes account for 70-80% of clinically diagnosed NS patients, but the genetic basis for the remaining 20-30% of cases is unknown. We performed next-generation sequencing on germ-line DNA from 27 NS patients lacking a mutation in the known NS genes. We identified gain-of-function alleles in Ras-like without CAAX 1 (RIT1) and mitogen-activated protein kinase kinase 1 (MAP2K1) and previously unseen loss-of-function variants in RAS p21 protein activator 2 (RASA2) that are likely to cause NS in these patients. Expression of the mutant RASA2, MAP2K1, or RIT1 alleles in heterologous cells increased RAS-ERK pathway activation, supporting a causative role in NS pathogenesis. Two patients had more than one disease-associated variant. Moreover, the diagnosis of an individual initially thought to have NS was revised to neurofibromatosis type 1 based on an NF1 nonsense mutation detected in this patient. Another patient harbored a missense mutation in NF1 that resulted in decreased protein stability and impaired ability to suppress RAS-ERK activation; however, this patient continues to exhibit a NS-like phenotype. In addition, a nonsense mutation in RPS6KA3 was found in one patient initially diagnosed with NS whose diagnosis was later revised to Coffin-Lowry syndrome. Finally, we identified other potential candidates for new NS genes, as well as potential carrier alleles for unrelated syndromes. Taken together, our data suggest that next-generation sequencing can provide a useful adjunct to RASopathy diagnosis and emphasize that the standard clinical categories for RASopathies might not be adequate to describe all patients.

Copy number variation analysis implicates the cell polarity gene glypican 5 as a human spina bifida candidate gene.

Neural tube defects (NTDs) are common birth defects of complex etiology. Family and population-based studies have confirmed a genetic component to NTDs. However, despite more than three decades of research, the genes involved in human NTDs remain largely unknown. We tested the hypothesis that rare copy number variants (CNVs), especially de novo germline CNVs, are a significant risk factor for NTDs. We used array-based comparative genomic hybridization (aCGH) to identify rare CNVs in 128 Caucasian and 61 Hispanic patients with non-syndromic lumbar-sacral myelomeningocele. We also performed aCGH analysis on the parents of affected individuals with rare CNVs where parental DNA was available (42 sets). Among the eight de novo CNVs that we identified, three generated copy number changes of entire genes. One large heterozygous deletion removed 27 genes, including PAX3, a known spina bifida-associated gene. A second CNV altered genes (PGPD8, ZC3H6) for which little is known regarding function or expression. A third heterozygous deletion removed GPC5 and part of GPC6, genes encoding glypicans. Glypicans are proteoglycans that modulate the activity of morphogens such as Sonic Hedgehog (SHH) and bone morphogenetic proteins (BMPs), both of which have been implicated in NTDs. Additionally, glypicans function in the planar cell polarity (PCP) pathway, and several PCP genes have been associated with NTDs. Here, we show that GPC5 orthologs are expressed in the neural tube, and that inhibiting their expression in frog and fish embryos results in NTDs. These results implicate GPC5 as a gene required for normal neural tube development.

The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology.

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This Portal has been coupled with other resources like Viral AI and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this Portal, including its contextual data not available elsewhere, and the 'Duotang', a web platform that presents key genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Reactome: a database of reactions, pathways and biological processes.

Reactome (http://www.reactome.org) is a collaboration among groups at the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute, to develop an open source curated bioinformatics database of human pathways and reactions. Recently, we developed a new web site with improved tools for pathway browsing and data analysis. The Pathway Browser is an Systems Biology Graphical Notation (SBGN)-based visualization system that supports zooming, scrolling and event highlighting. It exploits PSIQUIC web services to overlay our curated pathways with molecular interaction data from the Reactome Functional Interaction Network and external interaction databases such as IntAct, BioGRID, ChEMBL, iRefIndex, MINT and STRING. Our Pathway and Expression Analysis tools enable ID mapping, pathway assignment and overrepresentation analysis of user-supplied data sets. To support pathway annotation and analysis in other species, we continue to make orthology-based inferences of pathways in non-human species, applying Ensembl Compara to identify orthologs of curated human proteins in each of 20 other species. The resulting inferred pathway sets can be browsed and analyzed with our Species Comparison tool. Collaborations are also underway to create manually curated data sets on the Reactome framework for chicken, Drosophila and rice.

Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome.

Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4+ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.

BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology.

BACKGROUND: Identified as an Alzheimer's disease (AD) susceptibility gene by genome wide-association studies, BIN1 has 10 isoforms that are expressed in the Central Nervous System (CNS). The distribution of these isoforms in different cell types, as well as their role in AD pathology still remains unclear. METHODS: Utilizing antibodies targeting specific BIN1 epitopes in human post-mortem tissue and analyzing mRNA expression data from purified microglia, we identified three isoforms expressed in neurons and astrocytes (isoforms 1, 2 and 3) and four isoforms expressed in microglia (isoforms 6, 9, 10 and 12). The abundance of selected peptides, which correspond to groups of BIN1 protein isoforms, was measured in dorsolateral prefrontal cortex, and their relation to neuropathological features of AD was assessed. RESULTS: Peptides contained in exon 7 of BIN1's N-BAR domain were found to be significantly associated with AD-related traits and, particularly, tau tangles. Decreased expression of BIN1 isoforms containing exon 7 is associated with greater accumulation of tangles and subsequent cognitive decline, with astrocytic rather than neuronal BIN1 being the more likely culprit. These effects are independent of the BIN1 AD risk variant. CONCLUSIONS: Exploring the molecular mechanisms of specific BIN1 isoforms expressed by astrocytes may open new avenues for modulating the accumulation of Tau pathology in AD.

Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer's disease.

The extent of microglial heterogeneity in humans remains a central yet poorly explored question in light of the development of therapies targeting this cell type. Here, we investigate the population structure of live microglia purified from human cerebral cortex samples obtained at autopsy and during neurosurgical procedures. Using single cell RNA sequencing, we find that some subsets are enriched for disease-related genes and RNA signatures. We confirm the presence of four of these microglial subpopulations histologically and illustrate the utility of our data by characterizing further microglial cluster 7, enriched for genes depleted in the cortex of individuals with Alzheimer's disease (AD). Histologically, these cluster 7 microglia are reduced in frequency in AD tissue, and we validate this observation in an independent set of single nucleus data. Thus, our live human microglia identify a range of subtypes, and we prioritize one of these as being altered in AD.

Foxo1 Promotes Th9 Cell Differentiation and Airway Allergy.

T helper 9 (Th9) cells are effector CD4+ T cells that are characterized by the production of interleukin-9 (IL-9) and have been associated with allergic responses. Here, we found that the expression of the transcription factor forkhead box O1 (Foxo1) was induced in Th9 and Foxo1 plays a crucial role in the differentiation of Th9 cells. Pharmacological inhibition of Foxo1 or genetic disruption of Foxo1 in CD4+ T cells caused a reduction in IL-9 expression while upregulating IL-17A and IFNγ production. Furthermore, chromatin immunoprecipitation (ChIP) followed by luciferase assays revealed direct binding of Foxo1 to both the Il9 and Irf4 promoters and induces their transactivation. Lastly, adoptive transfer of Th9 cells into lungs induced asthma-like symptoms that were ameliorated by Foxo1 inhibitor, AS1842856. Together, our findings demonstrate a novel regulator of Th9 cells with a direct implication in allergic inflammation.

A transcriptomic atlas of aged human microglia.

With a rapidly aging global human population, finding a cure for late onset neurodegenerative diseases has become an urgent enterprise. However, these efforts are hindered by the lack of understanding of what constitutes the phenotype of aged human microglia-the cell type that has been strongly implicated by genetic studies in the pathogenesis of age-related neurodegenerative disease. Here, we establish the set of genes that is preferentially expressed by microglia in the aged human brain. This HuMi_Aged gene set captures a unique phenotype, which we confirm at the protein level. Furthermore, we find this gene set to be enriched in susceptibility genes for Alzheimer's disease and multiple sclerosis, to be increased with advancing age, and to be reduced by the protective APOEε2 haplotype. APOEε4 has no effect. These findings confirm the existence of an aging-related microglial phenotype in the aged human brain and its involvement in the pathological processes associated with brain aging.

A Metastatic Mouse Model Identifies Genes That Regulate Neuroblastoma Metastasis.

Metastatic relapse is the major cause of death in pediatric neuroblastoma, where there remains a lack of therapies to target this stage of disease. To understand the molecular mechanisms mediating neuroblastoma metastasis, we developed a mouse model using intracardiac injection and in vivo selection to isolate malignant cell subpopulations with a higher propensity for metastasis to bone and the central nervous system. Gene expression profiling revealed primary and metastatic cells as two distinct cell populations defined by differential expression of 412 genes and of multiple pathways, including CADM1, SPHK1, and YAP/TAZ, whose expression independently predicted survival. In the metastatic subpopulations, a gene signature was defined (MET-75) that predicted survival of neuroblastoma patients with metastatic disease. Mechanistic investigations demonstrated causal roles for CADM1, SPHK1, and YAP/TAZ in mediating metastatic phenotypes in vitro and in vivo Notably, pharmacologic targeting of SPHK1 or YAP/TAZ was sufficient to inhibit neuroblastoma metastasis in vivo Overall, we identify gene expression signatures and candidate therapeutics that could improve the treatment of metastatic neuroblastoma. Cancer Res; 77(3); 696-706. ©2017 AACR.

PhyloWGS: reconstructing subclonal composition and evolution from whole-genome sequencing of tumors.

Tumors often contain multiple subpopulations of cancerous cells defined by distinct somatic mutations. We describe a new method, PhyloWGS, which can be applied to whole-genome sequencing data from one or more tumor samples to reconstruct complete genotypes of these subpopulations based on variant allele frequencies (VAFs) of point mutations and population frequencies of structural variations. We introduce a principled phylogenic correction for VAFs in loci affected by copy number alterations and we show that this correction greatly improves subclonal reconstruction compared to existing methods. PhyloWGS is free, open-source software, available at https://github.com/morrislab/phylowgs.

A cancer cell-line titration series for evaluating somatic classification.

BACKGROUND: Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. RESULTS: Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. CONCLUSIONS: Our cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium's Data Access Compliance Office (ICGC DACO).

The Reactome BioMart.

Reactome is an open source, expert-authored, manually curated and peer-reviewed database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Reactome BioMart provides biologists and bioinformaticians with a single web interface for performing simple or elaborate queries of the Reactome database, aggregating data from different sources and providing an opportunity to integrate experimental and computational results with information relating to biological pathways. Database URL: http://www.reactome.org.

Optimization of paper bridge loading for 2-DE analysis in the basic pH region: application to the mitochondrial subproteome.

Separation of basic proteins with 2-DE presents technical challenges involving protein precipitation, load limitations, and streaking. Cardiac mitochondria are enriched in basic proteins and difficult to resolve by 2-DE. We investigated two methods, cup and paper bridge, for sample loading of this subproteome into the basic range (pH 6-11) gels. Paper bridge loading consistently produced improved resolution of both analytical and preparative protein loads. A unique benefit of this technique is that proteins retained in the paper bridge after loading basic gels can be reloaded onto lower pH gradients (pH 4-7), allowing valued samples to be analyzed on multiple pH ranges.

Gene expression profiles in end-stage human idiopathic dilated cardiomyopathy: altered expression of apoptotic and cytoskeletal genes.

Dilated cardiomyopathy is now the leading cause of cardiovascular morbidity and mortality. While the molecular basis of this disease remains uncertain, evidence is emerging that gene expression profiles of left ventricular myocardium isolated from failing versus nonfailing patients differ dramatically. In this study, we use high-density oligonucleotide microarrays with approximately 22000 probes to characterize differences in the expression profiles further. To facilitate interpretation of experimental data, we evaluate algorithms for normalization of hybridization data and for computation of gene expression indices using a control spike-in data set. We then use these methods to identify statistically significant changes in the expression levels of genes not previously implicated in the molecular phenotype of heart failure. These regulated genes take part in diverse cellular processes, including transcription, apoptosis, sarcomeric and cytoskeletal function, remodeling of the extracellular matrix, membrane transport, and metabolism.