Search

Abstract Background Dystroglycanopathies, which are caused by reduced glycosylation of alpha-dystroglycan, are a heterogeneous group of neurodegenerative disorders characterized by variable brain and skeletal muscle involvement. Muscle-eye-brain disease (or muscular dystrophy-dystroglycanopathy type 3 A) is an autosomal recessive disorder characterized by congenital muscular dystrophy, ocular abnormalities, and lissencephaly. Case presentation We report clinical and genetic characteristics of a 6-year-old boy affected by muscular dystrophy-dystroglycanopathy. He has severe a delay in psychomotor and speech development, muscle hypotony, congenital myopia, partial atrophy of the optic nerve disc, increased level of creatine kinase, primary-muscle lesion, polymicrogyria, ventriculomegaly, hypoplasia of the corpus callosum, cysts of the cerebellum. Exome sequencing revealed compound heterozygous mutations in POMGNT1 gene (transcript NM_001243766.1): c.1539 + 1G > A and c.385C > T. Conclusions The present case report shows diagnostic algorithm step by step and helps better understand the clinical and genetic features of congenital muscular dystrophy.

Summary: Semantic ontology mapping of clinical descriptors with disease outcome is essential. ClinVar is a key resource for human variation with known clinical significance. We present CMAT, a software toolkit and curation protocol for accurately enriching ClinVar releases with disease ontology associations and complex functional consequences., Availability and Implementation: The software and ontology mappings can be obtained from: https://github.com/EBIvariation/CMAT., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

The Open Targets Platform (https://platform.opentargets.org/) is an open source resource to systematically assist drug target identification and prioritisation using publicly available data. Since our last update, we have reimagined, redesigned, and rebuilt the Platform in order to streamline data integration and harmonisation, expand the ways in which users can explore the data, and improve the user experience. The gene-disease causal evidence has been enhanced and expanded to better capture disease causality across rare, common, and somatic diseases. For target and drug annotations, we have incorporated new features that help assess target safety and tractability, including genetic constraint, PROTACtability assessments, and AlphaFold structure predictions. We have also introduced new machine learning applications for knowledge extraction from the published literature, clinical trial information, and drug labels. The new technologies and frameworks introduced since the last update will ease the introduction of new features and the creation of separate instances of the Platform adapted to user requirements. Our new Community forum, expanded training materials, and outreach programme support our users in a range of use cases., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The European Variation Archive (EVA; https://www.ebi.ac.uk/eva/) is a resource for sharing all types of genetic variation data (SNPs, indels, and structural variants) for all species. The EVA was created in 2014 to provide FAIR access to genetic variation data and has since grown to be a primary resource for genomic variants hosting >3 billion records. The EVA and dbSNP have established a compatible global system to assign unique identifiers to all submitted genetic variants. The EVA is active within the Global Alliance of Genomics and Health (GA4GH), maintaining, contributing and implementing standards such as VCF, Refget and Variant Representation Specification (VRS). In this article, we describe the submission and permanent accessioning services along with the different ways the data can be retrieved by the scientific community., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced "verse"), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH)., Competing Interests: DECLARATION OF INTERESTS H.L.R. is a member of the advisory board for Cell Genomics.

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established h uman CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Salgado D et al.)

Non-invasive prenatal testing (NIPT) for aneuploidy on Chromosomes 21 (T21), 18 (T18) and 13 (T13) is actively used in clinical practice around the world. One of the limitations of the wider implementation of this test is the high cost of the analysis itself, as high-throughput sequencing is still relatively expensive. At the same time, there is an increasing trend in the length of reads yielded by sequencers. Since extracellular DNA is short, in the order of 140-160 bp, it is not possible to effectively use long reads. The authors used high-performance sequencing of cell-free DNA (cfDNA) libraries that went through additional stages of enzymatic fragmentation and random ligation of the resulting products to create long chimeric reads. The authors used a controlled set of samples to analyze a set of cfDNA samples from pregnant women with a high risk of fetus aneuploidy according to the results of the first trimester screening and confirmed by invasive karyotyping of the fetus using laboratory and analytical approaches developed by the authors. They evaluated the sensitivity, specificity, PPV (positive predictive value), and NPV (negative predictive value) of the results. The authors developed a technique for constructing long chimeric reads from short cfDNA fragments and validated the test using a control set of extracellular DNA samples obtained from pregnant women. The obtained sensitivity and specificity parameters of the NIPT developed by the authors corresponded to the approaches proposed earlier (99.93% and 99.14% for T21; 100% and 98.34% for T18; 100% and 99.17% for T13, respectively)., Competing Interests: The authors declare no conflict of interest.

We aimed to develop a pipeline for the bioinformatic analysis and interpretation of NGS data and detection of a wide range of single-nucleotide somatic mutations within tumor DNA. Initially, the NGS reads were submitted to a quality control check by the Cutadapt program. Low-quality 3¢-nucleotides were removed. After that the reads were mapped to the reference genome hg19 (GRCh37.p13) by BWA. The SAMtools program was used for exclusion of duplicates. MuTect was used for SNV calling. The functional effect of SNVs was evaluated using the algorithm, including annotation and evaluation of SNV pathogenicity by SnpEff and analysis of such databases as COSMIC, dbNSFP, Clinvar, and OMIM. The effect of SNV on the protein function was estimated by SIFT and PolyPhen2. Mutation frequencies were obtained from 1000 Genomes and ExAC projects, as well as from our own databases with frequency data. In order to evaluate the pipeline we used 18 breast cancer tumor biopsies. The MYbaits Onconome KL v1.5 Panel ("MYcroarray") was used for targeted enrichment. NGS was performed on the Illumina HiSeq 2500 platform. As a result, we identified alterations in BRCA1, BRCA2, ATM, CDH1, CHEK2, TP53 genes that affected the sequence of encoded proteins. Our pipeline can be used for effective search and annotation of tumor SNVs. In this study, for the first time, we have tested this pipeline for NGS data analysis of samples from patients of the Russian population. However, further confirmation of efficiency and accuracy of the pipeline is required on NGS data from larger datasets as well as data from several types of solid tumors.