Targeted Sequencing of 242 Clinically Important Genes in the Russian Population From the Ivanovo Region

We performed a targeted sequencing of 242 clinically important genes mostly associated with cardiovascular diseases in a representative population sample of 1,658 individuals from the Ivanovo region northeast of Moscow. Approximately 11% of 11,876 detected variants were not found in the Single Nucleotide Polymorphism Database (dbSNP) or reported earlier in the Russian population. Most novel variants were singletons and doubletons in our sample, and virtually no novel alleles presumably specific for the Russian population were able to reach the frequencies above 0.1–0.2%. The overwhelming majority (99.3%) of variants detected in this study in three or more copies were shared with other populations. We found two dominant and seven recessive known pathogenic variants with allele frequencies significantly increased compared to those in the gnomAD non-Finnish Europeans. Of the 242 targeted genes, 28 were in the list of 59 genes for which the American College of Medical Genetics and Genomics (ACMG) recommended the reporting of incidental findings. Based on the number of variants detected in the sequenced subset of ACMG59 genes, we approximated the prevalence of known pathogenic and novel or rare protein-truncating variants in the complete set of ACMG59 genes in the Ivanovo population at 1.4 and 2.8%, respectively. We analyzed the available clinical data and observed the incomplete penetrance of known pathogenic variants in the 28 ACMG59 genes: only 1 individual out of 12 with such variants had the phenotype most likely related to the variant. When known pathogenic and novel or rare protein-truncating variants were considered together, the overall rate of confirmed phenotypes was about 19%, with maximum in the subset of novel protein-truncating variants. We report three novel protein truncating variants in APOB and one in MYH7 observed in individuals with hypobetalipoproteinemia and hypertrophic cardiomyopathy, respectively. Our results provide a valuable reference for the clinical interpretation of gene sequencing in Russian and other populations.

Analysis of BRCA1/2 variants of unknown significance in the prospective Korean Hereditary Breast Cancer study

Genetic testing for BRCA1 and BRCA2 is crucial in diagnosing hereditary breast and ovarian cancer syndromes and has increased with the development of multigene panel tests. However, results classified as variants of uncertain significance (VUS) present challenges to clinicians in attempting to choose an appropriate management plans. We reviewed a total of 676 breast cancer patients included in the Korean Hereditary Breast Cancer (KOHBRA) study with a VUS on BRCA mutation tests between November 2007 and April 2013. These results were compared to the ClinVar database. We calculated the incidence and odds ratios for these variants using the Korean Reference Genome Database. A total of 58 and 91 distinct VUS in BRCA1 and BRCA2 were identified in the KOHBRA study (comprising 278 and 453 patients, respectively). A total of 27 variants in the KOHBRA study were not registered in the Single Nucleotide Polymorphism database. Among BRCA1 VUSs, 20 were reclassified as benign or likely benign, four were reclassified as pathogenic or likely pathogenic, and eight remained as VUSs according to the ClinVar database. Of the BRCA2 VUSs, 25 were reclassified as benign or likely benign, two were reclassified as pathogenic or likely pathogenic, and 33 remained as VUS according to the ClinVar database. There were 12 variants with conflicting interpretations of pathogenicity for BRCA1 and 18 for BRCA2. Among them, p.Leu1780Pro showed a particularly high odds ratio. Six pathogenic variants and one conflicting variant identified using ClinVar could be reclassified as pathogenic variants in this study. Using updated ClinVar information and calculating odds ratios can be helpful when reclassifying VUSs in BRCA1/2.

A Novel Pathogenic HSPG2 Mutation in Schwartz–Jampel Syndrome

Schwartz–Jampel syndrome is a rare autosomal recessive disease caused by mutation in the heparan sulfate proteoglycan 2 (HSPG2) gene. Its cardinal symptoms are skeletal dysplasia and neuromuscular hyperactivity. Herein, we identified a new pathogenic mutation site (NM_005529.6:c.1125C>G; p.Cys375Trp) of HSPG2 leading to Schwartz–Jampel syndrome by whole-exome sequencing. This mutation carried by the asymptomatic parents was previously registered in a single-nucleotide polymorphism database of the National Institutes of Health as a coding sequence variant rs543805444. The pathogenic nature of this missense mutation was demonstrated by in silico pathogenicity assessment, clinical presentations, and cellular function of primary fibroblast derived from patients. Various in silico software applications predicted the mutation to be pathogenic [Sorting Intolerant From Tolerant (SIFT), 0; Polyphen-2, 1; CADD (Combined Annotation Dependent Depletion), 23.7; MutationTaster, 1; DANN (deleterious annotation of genetic variants using neural networks); 0.9]. Needle electromyography revealed extensive complex repetitive discharges and multiple polyphasic motor unit action potentials in axial and limb muscles at rest. Short exercise test for myotonia showed Fournier pattern I. At cellular levels, mutant primary fibroblasts had reduced levels of secreted perlecan and impaired migration ability but normal capability of proliferation. Patients with this mutation showed more neuromuscular instability and relatively mild skeletal abnormality comparing with previously reported cases.

ncVarDB: a manually curated database for pathogenic non-coding variants and benign controls

Variants within the non-coding genome are frequently associated with phenotypes in genome-wide association studies. These non-coding regions may be involved in the regulation of gene expression, encode functional non-coding RNAs, or influence splicing and other cellular functions. We have curated a list of characterized non-coding human genome variants based on the published evidence that indicates phenotypic consequences of the variation. In order to minimize annotation errors, two curators have independently verified the supporting evidence for pathogenicity of each non-coding variant in the published literature. The database consists of 721 non-coding variants linked to the published literature describing the evidence of functional consequences. We have also sampled 7228 covariate-matched benign controls, that have a population frequency of over 5%, from the single nucleotide polymorphism database (dbSNP151) database. These were sampled controlling for potential confounding factors such as linkage with pathogenic variants, annotation type (untranslated region, intron, intergenic, etc.) and variant type (substitution or indel). The dataset presented here represents a curated repository, with a potential use for the training or evaluation of algorithms used in the prediction of non-coding variant functionality. Database URL: https://github.com/Gardner-BinfLab/ncVarDB.

Identification of novel key biomarkers in Simpson-Golabi-Behmel Syndrome: Evidence from bioinformatics analysis

BackgroundThe Simpson-Golabi-Behmel Syndrome (SGBS) or overgrowth Syndrome is a rare inherited X-linked condition characterized by pre- and postnatal overgrowth. The aim of the present study is to identify functional non-synonymous SNPs of GPC3 gene using various in silico approaches. These SNPs are supposed to have a direct effect on protein stability through conformation changes.Material and methodsThe SNPs were retrieved from the Single Nucleotide Polymorphism database (dbSNP) and further used to investigate a damaging effect using SIFT, PolyPhen, PROVEAN, SNAP2, SNPs&GO, PHD-SNP and P-mut, While we used I-mutant and MUPro to study the effect of SNPs on GPC3 protein structure. The 3D structure of human GPC3 protein is not available in the Protein Data Bank, so we used RaptorX to generate a 3D structural model for wild-type GPC3 to visualize the amino acids changes by UCSF Chimera. For biophysical validation we used project HOPE. Lastly we run conservational analysis by BioEdit and Consurf web server respectively.Resultsour results revealed three novel missense mutations (rs1460413167, rs1295603457 and rs757475450) that are found to be the most deleterious which effect on the GPC3 structure and function.ConclusionThis present study could provide a novel insight into the molecular basis of overgrowth Syndrome.

Pan-cancer repository of validated natural and cryptic mRNA splicing mutations

We present a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. Likely mutations present in all tumor types reported in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) were identified based on the comparative strengths of splice sites in tumor versus normal genomes, and then validated by respectively comparing counts of splice junction spanning and abundance of transcript reads in RNA-Seq data from matched tissues and tumors lacking these mutations. The comprehensive resource features 341,486 of these validated mutations, the majority of which (69.9%) are not present in the Single Nucleotide Polymorphism Database (dbSNP 150). There are 131,347 unique mutations which weaken or abolish natural splice sites, and 222,071 mutations which strengthen cryptic splice sites (11,932 affect both simultaneously). 28,812 novel or rare flagged variants (with <1% population frequency in dbSNP) were observed in multiple tumor tissue types. Single variants or chromosome ranges can be queried using a Global Alliance for Genomics and Health (GA4GH)-compliant, web-based Beacon “Validated Splicing Mutations” either separately or in aggregate alongside other Beacons through the public Beacon Network, as well as through our website.

An effective biomedical data migration tool from resource description framework to JSON

Resource Description Framework (RDF) is widely used for representing biomedical data in practical applications. With the increases of RDF-based applications, there is an emerging requirement of novel architectures to provide effective supports for the future RDF data explosion. Inspired by the success of the new designs in National Center for Biotechnology Information dbSNP (The Single Nucleotide Polymorphism Database) for managing the increasing data volumes using JSON (JavaScript Object Notation), in this paper we present an effective mapping tool that allows data migrations from RDF to JSON for supporting future massive data explosions and releases. We firstly introduce a set of mapping rules, which transform an RDF format into the JSON format, and then present the corresponding transformation algorithm. On this basis, we develop an effective and user-friendly tool called RDF2JSON, which enables automating the process of RDF data extractions and the corresponding JSON data generations.

Pan-cancer repository of validated natural and cryptic mRNA splicing mutations

We present a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. Likely mutations present in all tumor types reported in the Cancer Genome Atlas (TCGA) were identified based on the comparative strengths of splice sites in tumor versus normal genomes, and then validated by respectively comparing counts of splice junction spanning and abundance of transcript reads in RNA-Seq data from matched tissues and tumors lacking these mutations. The comprehensive resource features 351,423 of these validated mutations, the majority of which (69.1%) are not present in the Single Nucleotide Polymorphism Database (dbSNP 150). There are 117,951 unique mutations which weaken or abolish natural splice sites, and 244,415 mutations which strengthen cryptic splice sites (10,943 affect both simultaneously). 27,803 novel or rare flagged variants (with <1% population frequency in dbSNP) were observed in multiple tumor tissue types. Single variants or chromosome ranges can be queried using a Global Alliance for Genomics and Health (GA4GH)-compliant, web-based Beacon “Validated Splicing Mutations” either separately or in aggregate alongside other Beacons through the public Beacon Network (http://www.beacon-network.org/#/search?beacon=cytognomix), as well as through our website (https://validsplicemut.cytognomix.com/).