Prediction and analysis of functional RNA structures within the integrative genomics viewer

ABSTRACT In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results—in conjunction with probing data and other annotations—in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast ‘omics’ resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

Integrative Prioritization of Causal Genes for Coronary Artery Disease

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association studies data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

qtlXplorer: an online systems genetics browser in the Eucalyptus Genome Integrative Explorer (EucGenIE)

Background Affordable high-throughput DNA and RNA sequencing technologies are allowing genomic analysis of plant and animal populations and as a result empowering new systems genetics approaches to study complex traits. The availability of intuitive tools to browse and analyze the resulting large-scale genetic and genomic datasets remain a significant challenge. Furthermore, these integrative genomics approaches require innovative methods to dissect the flow and interconnectedness of biological information underlying complex trait variation. The Plant Genome Integrative Explorer (PlantGenIE.org) is a multi-species database and domain that houses online tools for model and woody plant species including Eucalyptus. Since the Eucalyptus Genome Integrative Explorer (EucGenIE) is integrated within PlantGenIE, it shares genome and expression analysis tools previously implemented within the various subdomains (ConGenIE, PopGenIE and AtGenIE). Despite the success in setting up integrative genomics databases, online tools for systems genetics modelling and high-resolution dissection of complex trait variation in plant populations have been lacking. Results We have developed qtlXplorer (https://eucgenie.org/QTLXplorer) for visualizing and exploring systems genetics data from genome-wide association studies including quantitative trait loci (QTLs) and expression-based QTL (eQTL) associations. This module allows users to, for example, find co-located QTLs and eQTLs using an interactive version of Circos, or explore underlying genes using JBrowse. It provides users with a means to build systems genetics models and generate hypotheses from large-scale population genomics data. We also substantially upgraded the EucGenIE resource and show how it enables users to combine genomics and systems genetics approaches to discover candidate genes involved in biotic stress responses and wood formation by focusing on two multigene families, laccases and peroxidases. Conclusions qtlXplorer adds a new dimension, population genomics, to the EucGenIE and PlantGenIE environment. The resource will be of interest to researchers and molecular breeders working in Eucalyptus and other woody plant species. It provides an example of how systems genetics data can be integrated with functional genetics data to provide biological insight and formulate hypotheses. Importantly, integration within PlantGenIE enables novel comparative genomics analyses to be performed from population-scale data.

Identification of downstream effectors of retinoic acid specifying the zebrafish pancreas by integrative genomics

Retinoic acid (RA) is a key signal for the specification of the pancreas. Still, the gene regulatory cascade triggered by RA in the endoderm remains poorly characterized. In this study, we investigated this regulatory network in zebrafish by combining RNA-seq, RAR ChIP-seq and ATAC-seq assays. By analysing the effect of RA and of the RA receptor (RAR) inverse-agonist BMS493 on the transcriptome and on the chromatin accessibility of endodermal cells, we identified a large set of genes and regulatory regions regulated by RA signalling. RAR ChIP-seq further defined the direct RAR target genes in zebrafish, including hox genes as well as several pancreatic regulators like mnx1, insm1b, hnf1ba and gata6. Comparison of zebrafish and murine RAR ChIP-seq data highlighted the conserved direct target genes and revealed that some RAR sites are under strong evolutionary constraints. Among them, a novel highly conserved RAR-induced enhancer was identified downstream of the HoxB locus and driving expression in the nervous system and in the gut in a RA-dependent manner. Finally, ATAC-seq data unveiled the role of the RAR-direct targets Hnf1ba and Gata6 in opening chromatin at many regulatory loci upon RA treatment.

TAMI-75. LIPID METABOLISM AS A THERAPEUTIC VULNERABILITY IN BET INHIBITOR-RESISTANT MEDULLOBLASTOMA

MYC-driven medulloblastomas are a particularly devastating group of pediatric brain tumors that exhibit resistance and continued progression despite standard of care treatments. Our preclinical work identified BET-bromodomain inhibitors as a potentially promising new class of drugs for children with medulloblastoma and other MYC-driven cancers, providing rationale to evaluate these agents in clinical trials. However, treatment with BET inhibitor (BETi) alone is unlikely to be sufficient for a cure, with most tumors evolving to acquire resistance to single-agent targeted therapies. We applied an integrative genomics approach to identify genes and pathways mediating BETi response in medulloblastoma. These studies revealed that MYC-driven medulloblastoma cells with acquired resistance to BETi reinstate transcription of essential genes suppressed by drug, and exhibit changes in cell state and new vulnerabilities not present in drug-sensitive cells. We now have a growing body of evidence showing that BET inhibition downregulates the expression of key lipid metabolism genes and metabolism-related signaling pathways, and that medulloblastoma cells with adaptive resistance to drug differentially express and exhibit preferential dependency on specific lipid metabolic genes and transcriptional regulators. Our studies explore the possibility of exploiting these novel metabolic vulnerabilities in order to overcome BETi resistance and provide a more efficacious upfront therapy.

Application of a custom NGS Gene Panel revealed a high diagnostic utility for molecular testing of hereditary ataxias.

Background Hereditary ataxias (HA) are a rare group of heterogeneous disorders. Here, we present results of molecular testing a group of ataxia patients using custom-designed Next Generation Sequencing (NGS) panel. Due to genetic and clinical overlapping of hereditary ataxias and spastic paraplegias (HSP), designed panel encompassing together HA and HSP genes. Methods The NGS libraries comprising coding sequence for 152 genes were performed using KAPA HyperPlus and HyperCap Target Enrichment Kit and sequenced on the MiSeq instrument. Obtained results were analyzed using BaseSpace Variant Interpreter and Integrative Genomics Viewer. All pathogenic and likely pathogenic variants were confirmed using the Sanger sequencing. Results A total of 29 patients with hereditary ataxias were enrolled to the NGS testing, and 16 patients had a confirmed molecular diagnosis with diagnostic efficiency of 55.2%. Pathogenic or likely pathogenic mutations were identified in 10 different genes: POLG (PEOA1, n=3; SCAE, n=2), CACNA1A (EA2, n=2), SACS (ARSACS, n=2), SLC33A1 (SPG42, n=2), STUB1 (SCA48, n=1), SPTBN2 (SCA5, n=1), TGM6 (SCA35, n=1), SETX (AOA2, n=1), ANO10 (SCAR10, n=1), SPAST (SPG4, n=1). Conclusions We demonstrated that approach based on targeted NGS panel can be highly effective and useful tool in the molecular diagnosis of ataxia patients. Furthermore, we highlight that sequencing panel targeted to ataxias together with HSP genes increase the diagnostic success.

Integrative genomics uncover mechanisms of renal medullary carcinoma transformation, microenvironment landscape and therapeutic vulnerabilities.

Renal medullary carcinoma (RMC) is an aggressive desmoplastic tumour driven by bi-allelic loss of SMARCB1, however the cell-of-origin, the oncogenic mechanism and the features of its microenvironment remain poorly understood. Using single-cell and multi-region sequencing of human RMC, we defined transformation of thick ascending limb (TAL) cells into at least three RMC cell states along an epithelial-mesenchymal gradient through a transcriptional switch involving loss of renal transcription factor TFCP2L1 and gain of a NFE2L2-associated ferroptosis resistance program. SMARCB1 re-expression in cultured RMC cells reactivates TFCP2L1 that relocates SWI/SNF from the promoters of the MYC-driven oncogenic program to the enhancers of TAL identity genes followed by ferroptotic cell death. We further show that RMC is associated with abundant M2-type macrophages and cancer-associated fibroblasts (CAFs) and we identify key regulatory cross-talks that shape this immunosuppressive microenvironment. Together our data describe the molecular events of RMC transformation and identify novel therapeutically targetable vulnerabilities.

Integrative genomics analysis of nasal intestinal-type adenocarcinomas demonstrates the major role of CACNA1C and paves the way for a simple diagnostic tool in male woodworkers

Background Nasal intestinal-type adenocarcinomas (ITAC) are strongly related to chronic wood dust exposure: The intestinal phenotype relies on CDX2 overexpression but underlying molecular mechanisms remain unknown. Our objectives were to investigate transcriptomic and methylation differences between healthy non-exposed and tumor olfactory cleft mucosae and to compare transcriptomic profiles between non-exposed, wood dust-exposed and ITAC mucosa cells. Methods We conducted a prospective monocentric study (NCT0281823) including 16 woodworkers with ITAC, 16 healthy exposed woodworkers and 13 healthy, non-exposed, controls. We compared tumor samples with healthy non-exposed samples, both in transcriptome and in methylome analyses. We also investigated wood dust-induced transcriptome modifications of exposed (without tumor) male woodworkers’ samples and of contralateral sides of woodworkers with tumors. We conducted in parallel transcriptome and methylome analysis, and then, the transcriptome analysis was focused on the genes highlighted in methylome analysis. We replicated our results on dataset GSE17433. Results Several clusters of genes enabled the distinction between healthy and ITAC samples. Transcriptomic and IHC analysis confirmed a constant overexpression of CDX2 in ITAC samples, without any specific DNA methylation profile regarding the CDX2 locus. ITAC woodworkers also exhibited a specific transcriptomic profile in their contralateral (non-tumor) olfactory cleft, different from that of other exposed woodworkers, suggesting that they had a different exposure or a different susceptibility. Two top-loci (CACNA1C/CACNA1C-AS1 and SLC26A10) were identified with a hemimethylated profile, but only CACNA1C appeared to be overexpressed both in transcriptomic analysis and in immunohistochemistry. Conclusions Several clusters of genes enable the distinction between healthy mucosa and ITAC samples even in contralateral nasal fossa thus paving the way for a simple diagnostic tool for ITAC in male woodworkers. CACNA1C might be considered as a master gene of ITAC and should be further investigated. Trial registration: NIH ClinicalTrials, NCT0281823, registered May 23d 2016, https://www.clinicaltrials.gov/NCT0281823.