ModelMatcher: A scientist-centric online platform to facilitate collaborations between stakeholders of rare and undiagnosed disease research.

Next-generation sequencing is a prevalent diagnostic tool for undiagnosed diseases and has played a significant role in rare disease gene discovery. Although this technology resolves some cases, others are given a list of possibly damaging genetic variants necessitating functional studies. Productive collaborations between scientists, clinicians, and patients (affected individuals) can help resolve such medical mysteries and provide insights into in vivo function of human genes.

Multi-parametric analysis of 57 SYNGAP1 variants reveal impacts on GTPase signaling, localization, and protein stability.

SYNGAP1 is a neuronal Ras and Rap GTPase-activating protein with important roles in regulating excitatory synaptic plasticity. While many SYNGAP1 missense and nonsense mutations have been associated with intellectual disability, epilepsy, schizophrenia, and autism spectrum disorder (ASD), whether and how they contribute to individual disease phenotypes is often unknown. Here, we characterize 57 variants in seven assays that examine multiple aspects of SYNGAP1 function.

Multi-model functionalization of disease-associated PTEN missense mutations identifies multiple molecular mechanisms underlying protein dysfunction.

Functional variomics provides the foundation for personalized medicine by linking genetic variation to disease expression, outcome and treatment, yet its utility is dependent on appropriate assays to evaluate mutation impact on protein function. To fully assess the effects of 106 missense and nonsense variants of PTEN associated with autism spectrum disorder, somatic cancer and PTEN hamartoma syndrome (PHTS), we take a deep phenotypic profiling approach using 18 assays in 5 model systems spanning diverse cellular environments ranging from molecular function to neuronal morphogenesis and behavior. Variants inducing instability occur across the protein, resulting in partial-to-complete loss-of-function (LoF), which is well correlated across models.

The Canadian Rare Diseases Models and Mechanisms (RDMM) Network: Connecting Understudied Genes to Model Organisms.

Advances in genomics have transformed our ability to identify the genetic causes of rare diseases (RDs), yet we have a limited understanding of the mechanistic roles of most genes in health and disease. When a novel RD gene is first discovered, there is minimal insight into its biological function, the pathogenic mechanisms of disease-causing variants, and how therapy might be approached. To address this gap, the Canadian Rare Diseases Models and Mechanisms (RDMM) Network was established to connect clinicians discovering new disease genes with Canadian scientists able to study equivalent genes and pathways in model organisms (MOs).

VariCarta: A Comprehensive Database of Harmonized Genomic Variants Found in Autism Spectrum Disorder Sequencing Studies.

Recent years have seen a boom in the application of the next-generation sequencing technology to the study of human disorders, including Autism Spectrum Disorder (ASD), where the focus has been on identifying rare, possibly causative genomic variants in ASD individuals. Because of the high genetic heterogeneity of ASD, a large number of subjects is needed to establish evidence for a variant or gene ASD-association, thus aggregating data across cohorts and studies is necessary. However, methodological inconsistencies and subject overlap across studies complicate data aggregation.

Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb.

Identifying variants causal for complex genetic disorders is challenging. With the advent of whole-exome and whole-genome sequencing, computational tools are needed to explore and analyze the list of variants for further validation. Correlating genetic variants with subject phenotype is crucial for the interpretation of the disease-causing mutations.

Meta-Analysis of Gene Expression Patterns in Animal Models of Prenatal Alcohol Exposure Suggests Role for Protein Synthesis Inhibition and Chromatin Remodeling.

Background: Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioral, and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models; however, there is a limited apparent consensus among the reported findings.

Transcriptome sequencing of the anterior cingulate in bipolar disorder: dysregulation of G protein-coupled receptors.

Objective: Gene expression dysregulation in the brain has been associated with bipolar disorder through candidate gene and microarray expression studies, but questions remain about isoform-specific dysregulation and the role of noncoding RNAs whose importance in the brain has been suggested recently but not yet characterized for bipolar disorder.

Method: The authors used RNA sequencing, a powerful technique that captures the complexity of gene expression, in postmortem tissue from the anterior cingulate cortex from 13 bipolar disorder case subjects and 13 matched comparison subjects. Differential expression was computed, and a global pattern of downregulation was detected, with 10 transcripts significant at a false discovery rate ≤5%.

Meta-Analysis of Gene Expression in Autism Spectrum Disorder.

Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. In general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. A considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus.

An RCOR1 loss-associated gene expression signature identifies a prognostically significant DLBCL subgroup.

Effective treatment of diffuse large B-cell lymphoma (DLBCL) is plagued by heterogeneous responses to standard therapy, and molecular mechanisms underlying unfavorable outcomes in lymphoma patients remain elusive. Here, we profiled 148 genomes with 91 matching transcriptomes in a DLBCL cohort treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) to uncover molecular subgroups linked to treatment failure. Systematic integration of high-resolution genotyping arrays and RNA sequencing data revealed novel deletions in RCOR1 to be associated with unfavorable progression-free survival (P = .

Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma.

Classical Hodgkin lymphoma and primary mediastinal B cell lymphoma (PMBCL) are related lymphomas sharing pathological, molecular and clinical characteristics. Here we discovered by whole-genome and whole-transcriptome sequencing recurrent somatic coding-sequence mutations in the PTPN1 gene. Mutations were found in 6 of 30 (20%) Hodgkin lymphoma cases, in 6 of 9 (67%) Hodgkin lymphoma-derived cell lines, in 17 of 77 (22%) PMBCL cases and in 1 of 3 (33%) PMBCL-derived cell lines, consisting of nonsense, missense and frameshift mutations.

Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing.

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer composed of at least 2 molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease. Here we provide a whole-genome-sequencing-based perspective of DLBCL mutational complexity by characterizing 40 de novo DLBCL cases and 13 DLBCL cell lines and combining these data with DNA copy number analysis and RNA-seq from an extended cohort of 96 cases.

The E3 ubiquitin ligase UBR5 is recurrently mutated in mantle cell lymphoma.

We have recently reported the application of RNAseq to mantle cell lymphoma (MCL) transcriptomes revealing recurrent mutations in NOTCH1. Here we describe the targeted resequencing of 18 genes mutated in this discovery cohort using a larger cohort of MCL tumors. In addition to frequent mutations in ATM, CCND1, TP53, and NOTCH1, mutations were also observed recurrently in MEF2B, TRAF2, and TET2.

Gene expression-based model using formalin-fixed paraffin-embedded biopsies predicts overall survival in advanced-stage classical Hodgkin lymphoma.

Purpose: Our aim was to reliably identify patients with advanced-stage classical Hodgkin lymphoma (cHL) at increased risk of death by developing a robust predictor of overall survival (OS) using gene expression measured in routinely available formalin-fixed paraffin-embedded tissue (FFPET).

Methods: Expression levels of 259 genes, including those previously reported to be associated with outcome in cHL, were determined by digital expression profiling of pretreatment FFPET biopsies from 290 patients enrolled onto the E2496 Intergroup trial comparing doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) and Stanford V regimens in locally extensive and advanced-stage cHL. A model for OS separating patients into low- and high-risk groups was produced using penalized Cox regression.

Concurrent expression of MYC and BCL2 in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone.

Purpose: Diffuse large B-cell lymphoma (DLBCL) is curable in 60% of patients treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). MYC translocations, with or without BCL2 translocations, have been associated with inferior survival in DLBCL. We investigated whether expression of MYC protein, with or without BCL2 protein expression, could risk-stratify patients at diagnosis.

TBL1XR1/TP63: a novel recurrent gene fusion in B-cell non-Hodgkin lymphoma.

Recently, the landscape of single base mutations in diffuse large B-cell lymphoma (DLBCL) was described. Here we report the discovery of a gene fusion between TBL1XR1 and TP63, the only recurrent somatic novel gene fusion identified in our analysis of transcriptome data from 96 DLBCL cases. Based on this cohort and a further 157 DLBCL cases analyzed by FISH, the incidence in de novo germinal center B cell-like (GCB) DLBCL is 5% (6 of 115).

Whole transcriptome sequencing reveals recurrent NOTCH1 mutations in mantle cell lymphoma.

Mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma, is characterized by the hallmark translocation t(11;14)(q13;q32) and the resulting overexpression of cyclin D1 (CCND1). Our current knowledge of this disease encompasses frequent secondary cytogenetic aberrations and the recurrent mutation of a handful of genes, such as TP53, ATM, and CCND1. However, these findings insufficiently explain the biologic underpinnings of MCL.

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma.

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations.

Meta-analysis of kindling-induced gene expression changes in the rat hippocampus.

Numerous studies have been performed to examine gene expression patterns in the rodent hippocampus in the kindling model of epilepsy. However, recent reviews of this literature have revealed limited agreement among studies. Because this conclusion was based on retrospective comparison of reported "hit lists" from individual studies, we hypothesized that re-analysis of the original expression data would help address this concern.

Correlation between the secondary structure of pre-mRNA introns and the efficiency of splicing in Saccharomyces cerevisiae.

Background: Secondary structure interactions within introns have been shown to be essential for efficient splicing of several yeast genes. The nature of these base-pairing interactions and their effect on splicing efficiency were most extensively studied in ribosomal protein gene RPS17B (previously known as RP51B). It was determined that complementary pairing between two sequence segments located downstream of the 5' splice site and upstream of the branchpoint sequence promotes efficient splicing of the RPS17B pre-mRNA, presumably by shortening the branchpoint distance.

GeneComber: combining outputs of gene prediction programs for improved results.

Unlabelled: We recently demonstrated that combining the output from Genscan and HMMgene can provide increased accuracy of gene predictions. We have created a robust software system that runs algorithms previously described on DNA sequences and provides a public web interface to the system for use by the biological community worldwide. The GeneComber system performs ab initio gene prediction by first taking a user inputted DNA sequence and running Genscan and HMMgene.

Improving gene recognition accuracy by combining predictions from two gene-finding programs.

Motivation: Despite constant improvements in prediction accuracy, gene-finding programs are still unable to provide automatic gene discovery with desired correctness. The current programs can identify up to 75% of exons correctly and less than 50% of predicted gene structures correspond to actual genes. New approaches to computational gene-finding are clearly needed.