Clinical Implementation of MetaFusion for Accurate Cancer-Driving Fusion Detection from RNA Sequencing.

Oncogenic fusion genes may be identified from next-generation sequencing data, typically RNA-sequencing. However, in a clinical setting, identifying these alterations is challenging against a background of nonrelevant fusion calls that reduce workflow precision and specificity. Furthermore, although numerous algorithms have been developed to detect fusions in RNA-sequencing, there are variations in their individual sensitivities.

Evaluation of single-cell RNAseq labelling algorithms using cancer datasets.

Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated labelling methods rely on either unsupervised, cluster-based approaches or supervised, cell-based approaches to identify cell types. The high complexity of cancer poses a unique challenge, as tumor microenvironments are often composed of diverse cell subpopulations with unique functional effects that may lead to disease progression, metastasis and treatment resistance.

Evaluation of single-cell RNA-seq clustering algorithms on cancer tumor datasets.

Tumors are complex biological entities that comprise cell types of different origins, with different mutational profiles and different patterns of transcriptional dysregulation. The exploration of data related to cancer biology requires careful analytical methods to reflect the heterogeneity of cell populations in cancer samples. Single-cell techniques are now able to capture the transcriptional profiles of individual cells.

Generation of DNA Methylation Signatures and Classification of Variants in Rare Neurodevelopmental Disorders Using EpigenCentral.

There are more than 700 genes that encode proteins that function in epigenetic regulation and chromatin modification. Germline variants in these genes (typically heterozygous) are associated with rare neurodevelopmental disorders (NDDs) characterized by growth abnormalities and intellectual and developmental delay. Advancements in next-generation sequencing have dramatically increased the detection of pathogenic sequence variants in genes encoding epigenetic machinery associated with NDDs and, concurrently, the number of clinically uninterpretable variants classified as variants of uncertain significance (VUS).

Genomics4RD: An integrated platform to share Canadian deep-phenotype and multiomic data for international rare disease gene discovery.

Despite recent progress in the understanding of the genetic etiologies of rare diseases (RDs), a significant number remain intractable to diagnostic and discovery efforts. Broad data collection and sharing of information among RD researchers is therefore critical. In 2018, the Care4Rare Canada Consortium launched the project C4R-SOLVE, a subaim of which was to collect, harmonize, and share both retrospective and prospective Canadian clinical and multiomic data.

Anatomy of DNA methylation signatures: Emerging insights and applications.

DNA methylation (DNAm) signatures are unique patterns of DNAm alterations defined for rare disorders caused by pathogenic variants in epigenetic regulatory genes. The potential of DNAm signatures (also known as "episignatures") is just beginning to emerge as there are >300 known epigenetic regulatory genes, ∼100 of which are linked to neurodevelopmental disorders. To date, approximately 50 signatures have been identified, which have proven unexpectedly successful as predictive tools for classifying variants of uncertain significance as pathogenic or benign.

MetaFusion: a high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates.

Motivation: Current fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function.

Results: MetaFusion is a flexible metacalling tool that amalgamates outputs from any number of fusion callers.

Navigating the Global Protein-Protein Interaction Landscape Using iRefWeb.

iRefWeb is a resource that provides web interface to a large collection of protein-protein interactions aggregated from major primary databases. The underlying data-consolidation process, called iRefIndex, implements a rigorous methodology of identifying redundant protein sequences and integrating disparate data records that reference the same peptide sequences, despite many potential differences in data identifiers across various source databases. iRefWeb offers a unified user interface to all interaction records and associated information collected by iRefIndex, in addition to a number of data filters and visual features that present the supporting evidence.

Obsessive-compulsive disorder and attention-deficit/hyperactivity disorder: distinct associations with DNA methylation and genetic variation.

Background: A growing body of research has demonstrated associations between specific neurodevelopmental disorders and variation in DNA methylation (DNAm), implicating this molecular mark as a possible contributor to the molecular etiology of these disorders and/or as a novel disease biomarker. Furthermore, genetic risk variants of neurodevelopmental disorders have been found to be enriched at loci associated with DNAm patterns, referred to as methylation quantitative trait loci (mQTLs).

Methods: We conducted two epigenome-wide association studies in individuals with attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD) (aged 4-18 years) using DNA extracted from saliva.

EpigenCentral: Portal for DNA methylation data analysis and classification in rare diseases.

Epigenetic processes play a key role in regulating gene expression. Genetic variants that disrupt chromatin-modifying proteins are associated with a broad range of diseases, some of which have specific epigenetic patterns, such as aberrant DNA methylation (DNAm), which may be used as disease biomarkers. While much of the epigenetic research has focused on cancer, there is a paucity of resources devoted to neurodevelopmental disorders (NDDs), which include autism spectrum disorder and many rare, clinically overlapping syndromes.

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes.

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism.

Correction to: DNA methylation signature is prognostic of choroid plexus tumor aggressiveness.

After publication of the original article [1], authors have requested to add a 'J' as middle name for Richard Gilbertson. Hence, full name should be Richard J Gilbertson.

DNA methylation signature is prognostic of choroid plexus tumor aggressiveness.

Background: Histological grading of choroid plexus tumors (CPTs) remains the best prognostic tool to distinguish between aggressive choroid plexus carcinoma (CPC) and the more benign choroid plexus papilloma (CPP) or atypical choroid plexus papilloma (aCPP); however, these distinctions can be challenging. Standard treatment of CPC is very aggressive and often leads to severe damage to the young child's brain. Therefore, it is crucial to distinguish between CPC and less aggressive entities (CPP or aCPP) to avoid unnecessary exposure of the young patient to neurotoxic therapy.

New insights into DNA methylation signatures: SMARCA2 variants in Nicolaides-Baraitser syndrome.

Background: Nicolaides-Baraitser syndrome (NCBRS) is a neurodevelopmental disorder caused by pathogenic sequence variants in SMARCA2 which encodes the catalytic component of the chromatin remodeling BAF complex. Pathogenic variants in genes that encode epigenetic regulators have been associated with genome-wide changes in DNA methylation (DNAm) in affected individuals termed DNAm signatures.

Methods: Genome-wide DNAm was assessed in whole-blood samples from the individuals with pathogenic SMARCA2 variants and NCBRS diagnosis (n = 8) compared to neurotypical controls (n = 23) using the Illumina MethylationEPIC array.

Don't brush off buccal data heterogeneity.

Buccal epithelial cells are among the most clinically accessible tissues and are increasingly being used to identify epigenetic disease patterns. However, substantial variation in buccal DNA methylation patterns indicates heterogeneity of cell types within and between samples, raising questions of data quality. We systematically estimated cell-type composition for a large collection of buccal and saliva samples from 11 published studies of DNA methylation.

CHARGE and Kabuki Syndromes: Gene-Specific DNA Methylation Signatures Identify Epigenetic Mechanisms Linking These Clinically Overlapping Conditions.

Epigenetic dysregulation has emerged as a recurring mechanism in the etiology of neurodevelopmental disorders. Two such disorders, CHARGE and Kabuki syndromes, result from loss of function mutations in chromodomain helicase DNA-binding protein 7 (CHD7) and lysine (K) methyltransferase 2D (KMT2D), respectively. Although these two syndromes are clinically distinct, there is significant phenotypic overlap.

Genome-wide placental DNA methylation analysis of severely growth-discordant monochorionic twins reveals novel epigenetic targets for intrauterine growth restriction.

Background: Intrauterine growth restriction (IUGR), which refers to reduced fetal growth in the context of placental insufficiency, is etiologically heterogeneous. IUGR is associated not only with perinatal morbidity and mortality but also with adult-onset disorders, such as cardiovascular disease and diabetes, posing a major health burden. Placental epigenetic dysregulation has been proposed as one mechanism that causes IUGR; however, the spectrum of epigenetic pathophysiological mechanisms leading to IUGR remains to be elucidated.

The missing indels: an estimate of indel variation in a human genome and analysis of factors that impede detection.

With the development of High-Throughput Sequencing (HTS) thousands of human genomes have now been sequenced. Whenever different studies analyze the same genome they usually agree on the amount of single-nucleotide polymorphisms, but differ dramatically on the number of insertion and deletion variants (indels). Furthermore, there is evidence that indels are often severely under-reported.

Extracting high confidence protein interactions from affinity purification data: at the crossroads.

Unlabelled: Deriving protein-protein interactions from data generated by affinity-purification and mass spectrometry (AP-MS) techniques requires application of scoring methods to measure the reliability of detected putative interactions. Choosing the appropriate scoring method has become a major challenge. Here we apply six popular scoring methods to the same AP-MS dataset and compare their performance.

Role of STAT5 and epigenetics in lactation-associated upregulation of multidrug transporter ABCG2 in the mammary gland.

The multidrug resistance efflux transporter ATP-binding cassette subfamily G member 2 (ABCG2) is not only overexpressed in certain drug-resistant cancers but is also highly expressed in the mammary gland during lactation, carrying xenobiotics and nutrients into milk. We sought to investigate the molecular mechanisms involved in the upregulation of ABCG2 during lactation. Expression profiling of different mouse Abcg2 mRNA isoforms (E1a, E1b, and E1c) revealed that E1b is predominantly expressed and induced in the lactating mouse mammary gland.

Intercellular network structure and regulatory motifs in the human hematopoietic system.

The hematopoietic system is a distributed tissue that consists of functionally distinct cell types continuously produced through hematopoietic stem cell (HSC) differentiation. Combining genomic and phenotypic data with high-content experiments, we have built a directional cell-cell communication network between 12 cell types isolated from human umbilical cord blood. Network structure analysis revealed that ligand production is cell type dependent, whereas ligand binding is promiscuous.

Human-chromatin-related protein interactions identify a demethylase complex required for chromosome segregation.

Chromatin regulation is driven by multicomponent protein complexes, which form functional modules. Deciphering the components of these modules and their interactions is central to understanding the molecular pathways these proteins are regulating, their functions, and their relation to both normal development and disease. We describe the use of affinity purifications of tagged human proteins coupled with mass spectrometry to generate a protein-protein interaction map encompassing known and predicted chromatin-related proteins.