The Ensembl Variant Effect Predictor (VEP) is a freely available, open source tool for the annotation and filtering of genomic variants. It predicts variant molecular consequence using the Ensembl/GENCODE or RefSeq gene sets. It also reports phenotype associations from databases such as ClinVar, allele frequencies from studies including gnomAD, and predictions of deleteriousness from tools such as SIFT and CADD. Ensembl VEP includes filtering options to customise variant prioritisation. It is well supported and updated roughly quarterly to incorporate the latest gene, variant and phenotype association information. Ensembl VEP analysis can be performed using a highly configurable, extensible command-line tool, a Representational State Transfer (REST) application programming interface (API) and a user-friendly web interface. These access methods are designed to suit different levels of bioinformatics experience and meet different needs in terms of data size, visualisation and flexibility. In this tutorial, we will describe performing variant annotation using the Ensembl VEP web tool, which enables sophisticated analysis through a simple interface.

Juvenile open angle glaucoma (JOAG) is a severe type of glaucoma with childhood onset and dominant inheritance. Using exome sequencing we identified 3 independent families from the Philippines with rare EFEMP1 variants (c.238A>T, p.Asn80Tyr; c.1480T>C p.Ter494Glnext*29; and c.1429C>T, p.Arg477Cysteine ) co-segregating with disease. Affected variant carriers (N= 34) exhibited severe disease with average age of onset of 16 years and with 76% developing blindness. To investigate functional effects, we transfected COS7 cells with vectors expressing the three novel EFEMP1 variants and showed that all three variants found in JOAG patients caused significant intracellular protein aggregation and retention compared to wild type and also compared to EFEMP1 variants associated with other ocular phenotypes including an early-onset form of macular degeneration, Malattia Leventinese/Doyne’s Honeycomb retinal dystrophy. These results suggest that rare EFEMP1 coding variants can cause JOAG through a mechanism involving protein aggregation and retention, and that the extent of intracellular retention correlates with disease phenotype. This is the first report of EFEMP1 variants causing JOAG, expanding the EFEMP1 disease spectrum. Our results suggest that EFEMP1 mutations appear to be a relatively common cause of JOAG in Filipino families, an ethnically diverse population.

Mitogen-Activated Protein 3 Kinase 7 (MAP3K7, MIM 602614) encodes the ubiquitously expressed transforming growth factor β (TGF-β)–activated kinase 1 (TAK1), which plays a crucial role in many cellular processes. Variants in the MAP3K7 gene have been linked to 2 distinct disorders: frontometaphyseal dysplasia type 2 (FMD2, MIM #617137) and cardiospondylocarpofacial syndrome (CSCF, MIM #157800). The fact that different variants can induce 2 distinct phenotypes suggests a phenotype/genotype correlation, but no side-by-side comparison has been done thus far to confirm this. Here we significantly expand the cohort and the description of clinical phenotypes for individuals with CSCF and FMD2 who carry variants in MAP3K7. We show that in contrast to FMD2-causing variants, CSCF-causing variants in MAP3K7 have a loss-of-function effect. Additionally, patients with pathogenic variants in MAP3K7 are at risk for cardiac disease, have symptoms associated with connective tissue disease and we show overlap in clinical phenotypes of CSCF with Noonan syndrome. Together, we provide evidence for a molecular fingerprint of FMD2- versus CSCF-causing MAP3K7 variants and conclude that variants in MAP3K7 should be considered in the differential diagnosis of patients with syndromic congenital cardiac defects and/or cardiomyopathy, syndromic connective tissue disorders and in the differential diagnosis of Noonan syndrome.

Routine exome sequencing (ES) in individuals with neurodevelopmental disorders (NDD) remains inconclusive in >50%. Research analysis of unsolved cases can identify novel candidate genes but is time consuming, subjective, and hard to compare between labs. The field therefore needs automated and standardized assessment methods to prioritize candidates for matchmaking. We developed AutoCaSc (https://autocasc.uni-leipzig.de) based on our candidate scoring scheme (CaSc). We validated our approach using synthetic trios and real in-house trio ES data. AutoCaSc consistently (94.5%) scored variants in valid novel NDD genes in the top three ranks. In 93 real trio exomes, AutoCaSc identified most (97.5%) previously manually scored variants while evaluating additional highly scoring variants missed in manual evaluation. It identified candidate variants in previously undescribed NDD candidate genes ( CNTN2, DLGAP1, SMURF1, NRXN3, PRICKLE1). AutoCaSc enables anybody to quickly screen a variant for its plausibility in NDD. After contributing >40 descriptions of NDD associated genes, we provide usage recommendations based on our extensive experience. Our implementation is capable of pipeline integration and therefore allows screening of large cohorts for candidate genes. AutoCaSc empowers even small labs to a standardized matchmaking collaboration and to contribute to the ongoing identification of novel NDD entities.

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5’/3’ splice sites, branch sites or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on machine learning approach, comprehensive assessment of variant effect on different splicing motifs. We gathered a curated set of 4,616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. Bayesian analysis provided us the number of control variants, i.e. variants without impact on splicing, to mimic the deluge of variants from high throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, significantly better than 0.965 spliceAI for the same dataset. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: [https://sourceforge.net/projects/splicing-prediction-pipeline/](https://sourceforge.net/projects/splicing-prediction-pipeline/)

Bi-allelic loss-of-function variants of OTOA are a well-known cause of moderate-to-severe hearing loss. Whereas non-allelic homologous recombination-mediated deletions of the gene are well known, gene conversions to pseudogene OTOAP1 have been reported in the literature but never fully described nor their pathogenicity assessed. Here, we report two unrelated patients with moderate hearing-loss, who were compound heterozygotes for a converted allele and a deletion of OTOA. The conversions were initially detected through sequencing depths anomalies at the OTOA locus after exome sequencing, then confirmed with long range polymerase chain reactions. Both conversions lead to loss-of-function by introducing a premature stop codon in exon 22 (p.Glu787*). Using genomic alignments and long read nanopore sequencing, we found that the two probands carry stretches of converted DNA of widely different lengths (at least 9 kbp and around 900 bp, respectively).

National genetic variation registries vastly increase the level of detail for the relevant population, while directly affecting patient management. Herein, we report CanVaS, a Cancer Variation reSource aiming to document the genetic variation of cancer patients in Greece. CanVaS comprises germline genetic data from 7,363 Greek individuals with a personal and/or family history of malignancy. The dataset incorporates ~24,000 functionally annotated rare variants in 97 established or suspected cancer susceptibility genes. For each variant, allele frequency for the Greek population, interpretation for clinical significance, anonymized family and segregation information, as well as phenotypic traits of the carriers, are included. Moreover, information on the geographic distribution of the variants across the country are provided, enabling the study of Greek population isolates. Direct comparisons between Greek (sub)populations with relevant genetic resources is supported, allowing fine-grain localized adjustment of guidelines and clinical decision-making. Most importantly, anonymized data are available for download, while the Leiden Open Variation Database schema is adopted, enabling integration/interconnection with central resources. CanVaS could become a stepping-stone for a countrywide effort to characterize the cancer genetic variation landscape, concurrently supporting national and international cancer research. The database can be accessed at: http://ithaka.rrp.demokritos.gr/CanVaS

Hereditary disorders are frequently caused by genetic variants that affect pre-mRNA splicing. Whilst genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the non-canonical splice sites (NCSS) and deep intronic (DI) regions are difficult to predict. Multiple splice prediction tools have been developed for this purpose, with the latest tools employing deep learning algorithms. We benchmarked established and deep learning splice prediction tools on gold standard sets of variants in the ABCA4 and MYBPC3 genes associated with Stargardt disease (STGD1) and cardiomyopathy, respectively, with functional assessment in midigene and minigene splice assays. The best performing splice prediction tool for both NCSS and DI variants in ABCA4 was SpliceAI, whilst SpliceSiteFinder-like performed best for NCSS variants in MYBPC3. Overall, the performance in a real time clinical setting is much more modest than reported by the developers of the tools.

The ATP-binding cassette (ABC) transporter superfamily comprises membrane proteins that efflux various substrates across extra- and intra-cellular membranes. Mutations in ABC genes cause 21 human disorders or phenotypes with Mendelian inheritance, including cystic fibrosis, adrenoleukodystrophy, retinal degeneration, cholesterol, and bile transport defects. Common polymorphisms and rare variants in ABC genes are associated with several complex phenotypes such as gout, gallstones, and cholesterol levels. Overexpression or amplification of specific drug efflux genes contributes to chemotherapy multidrug resistance. Conservation of the ATP-binding domains of ABC transporters defines the superfamily members, and phylogenetic analysis groups the 48 human ABC transporters into seven distinct subfamilies. While the conservation of ABC genes across most vertebrate species is high, there is also considerable gene duplication, deletion, and evolutionary diversification.

MORC2 gene encodes a ubiquitously expressed nuclear protein involved in chromatin remodeling, DNA repair, and transcriptional regulation. Heterozygous mutations in MORC2 gene have been associated with a spectrum of disorders affecting the peripheral nervous system such as Charcot-Marie-Tooth (CMT2Z), spinal muscular atrophy-like (SMA-like) with or without cerebellar involvement, and a developmental syndrome associated with impaired growth, craniofacial dysmorphism and axonal neuropathy (DIGFAN syndrome). Such variability in clinical manifestations associated with the increasing number of variants of unknown significance detected by next-generation sequencing constitutes a serious diagnostic challenge. Here we report the characterization of an in vitro model to evaluate the pathogenicity of variants of unknown significance based on MORC2 overexpression in a neuroblastoma cell line SH-EP or in cortical neurons. Likewise, we show that MORC2 mutants affect survival and trigger apoptosis over time in SH-EP cell line. Furthermore, overexpression in primary cortical neurons increases apoptotic cell death and decreases neurite outgrowth. Altogether, these approaches establish the pathogenicity of two new variants p.G444R and p.H446Q in three patients from two families. These new mutations in MORC2 gene are associated with autosomal dominant CMT and with adult late onset SMA-like phenotype, further increasing the spectrum of clinical manifestations associated with MORC2 mutations.

Brittle cornea syndrome (BCS) is a rare autosomal recessive disorder characterized by corneal thinning and fragility, leading to corneal rupture, the main hallmark of this disorder. Non-ocular symptoms include hearing loss, but also signs of connective tissue fragility, placing it in the Ehlers-Danlos syndrome (EDS) spectrum. It is caused by biallelic pathogenic variants in ZNF469 or PRDM5, which presumably encode transcription factors for extracellular matrix components. We report the clinical and molecular features of nine novel BCS families, four of which harbor variants in ZNF469 and five in PRDM5. We also performed a genotype and phenotype-oriented literature overview of all (N=85) reported patients with ZNF469 (N=53) and PRDM5 (N=32) variants. Musculoskeletal findings may be the mean reason for referral, and often raise suspicion of another heritable connective tissue disorder such as kyphoscoliotic EDS, osteogenesis imperfecta or Marfan syndrome, especially when corneal rupture has not yet occurred. Our findings highlight the multisystemic nature of BCS and validate its inclusion in the EDS classification. Importantly, gene panels for heritable connective tissue disorders should include ZNF469 and PRDM5 to allow for timely diagnosis and appropriate preventive measures for this rare condition.

Background: CHEK2 variants are associated with intermediate breast cancer risk among other cancers. We aimed to comprehensively describe CHEK2 variants in a Spanish hereditary cancer (HC) cohort and adjust American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP) guidelines for their classification. Methods: First, three CHEK2 frequent variants were screened in a retrospective Hereditary Breast and Ovarian Cancer cohort of 516 patients. After, the whole CHEK2 coding region was analyzed by next-generation sequencing in 1,848 prospective patients with HC suspicion. We refined ACMGAMP criteria and applied different combinatorial rules to classify CHEK2 variants and define risk alleles. Results: We identified 10 CHEK2 null variants, 6 missense variants with discordant interpretation in ClinVar database, and 35 additional variants of unknown significance. Twelve variants were classified as (likely)-pathogenic; 2 can also be considered “established risk-alleles” and one as “likely risk-allele”. The prevalence of (likely)-pathogenic variants in the HC cohort was 0.8% (1.3% in breast cancer patients and 1.0% in hereditary non-polyposis colorectal cancer patients). Conclusions: Here we provide ACMG adjustment guidelines to classify CHEK2 variants. We hope that this work would be useful for variant classification of other genes with low effect variants

The congenital sideroblastic anemias (CSAs) are a heterogeneous group of inherited disorders of erythropoiesis characterized by pathologic deposits of iron in the mitochondria of developing erythroblasts. Mutations in the mitochondrial glycine carrier SLC25A38 cause the most common recessive form of CSA. Nonetheless, the disease is still rare, there being fewer than 70 reported families. Here we describe the clinical phenotype and genotypes of 31 individuals from 24 families, including 11 novel mutations. We also review the spectrum of reported mutations and genotypes associated with the disease, describe the unique localization of missense mutations in transmembrane domains and account for the reoccurrence of several alleles in different populations.

Purpose:There have been concerted efforts towards cataloging rare and deleterious variants in different world population using high throughput genotyping and sequencing based methods. The Indian populations are underrepresented or its information w.r.t. clinically relevant variants are sparse in public datasets. The aim of this study was to estimate the burden of monogenic disease causing variants in Indian populations. Towards this, we have assessed the frequency profile of monogenic phenotype associated ClinVar variants. Methods: The study utilized genotype dataset (global-screening-array, Illumina) from 2795 individuals (multiple in-house genomics cohorts) representing diverse ethnic and geographically distinct Indian populations. Results: Of the analyzed variants from GSA, ~12% were found to be informative and were either not known earlier or underrepresented in public databases in terms of their frequencies. These variants were linked to disorders, viz. Inborn-errors of Metabolism, Monogenic-diabetes, hereditary cancers and various other hereditary conditions. We have also shown that our study cohort is genetically better representatives of Indian populations than its representation in1000 genome project (South-Asians). Conclusion: We have created a database, ClinIndb [(http://clinindb.igib.res.in) and (https://databases.lovd.nl/shared/variants?search_owned_by_=%3D%22Mohamed%20Faruq%22)], to help clinicians and researchers in diagnosis, counseling and development of appropriate genetic screening tools relevant to the Indian populations and Indians living abroad.

DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymised phenotype-linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualise genomic and phenotypic data to enable more informed variant interpretation, incorporating international standards for variant classification. DECIPHER supports almost all types of germline and mosaic variation in the nuclear and mitochondrial genome: sequence variants, short tandem repeats, copy-number variants and large structural variants. Patient phenotypes are deposited using Human Phenotype Ontology (HPO) terms, supplemented by quantitative data, which is aggregated to derive gene-specific phenotypic summaries. It hosts data from >250 projects from ~40 countries, openly sharing ~40,000 patient records containing >51,000 variants and >172,000 phenotype terms. The rich phenotype-linked variant data in DECIPHER drives rare disease research and diagnosis by enabling patient matching within DECIPHER and with other resources, and has been cited in >2,600 publications. In this paper, we describe the types of data deposited to DECIPHER, the variant interpretation tools, and patient matching interfaces which make DECIPHER an invaluable rare disease resource.

In Cystic Fibrosis (CF), correction of splicing defects represents an interesting therapeutic approach to restore normal CFTR function. In this study, we focused on ten common mutations/variants, 711+3A>G/C, 711+5G>A, 1863C>T, 1898+3A>G, 2789+5G>A, TG13T3, TG13T5, TG12T5 and 3120G>A that induce skipping of the corresponding CFTR exons 5, 9, 13, 16 and 18. To rescue the splicing defects we tested, in a minigene assay, a panel of modified U1 snRNAs, named Exon Specific U1s (ExSpeU1) that were engineered to bind to intronic sequences downstream of each defective exon. Using this approach, we show that all ten splicing mutations analysed are efficiently corrected by specific ExSpeU1s. Using cDNA-splicing competent minigenes, we also show that the ExspeU1-mediated splicing correction at the RNA level recovered the full-length CFTR protein for 1863C>T, 1898+3A>G, 2789+5G>A variants. In addition, detailed mutagenesis experiments performed on exon 13 led us to identify a novel intronic regulatory element involved in the ExSpeU1-mediated splicing rescue. These results provide a common strategy based on modified U1 snRNAs to correct exon skipping in a group of disease-causing CFTR mutations.

Mucopolysaccharidoses (MPSs) are rare, heterogeneous inborn errors of metabolism (IEM) diagnosed through a combination of clinical, biochemical, and genetic investigations. The aim of this study was molecular characterization of the largest cohort of Iranian MPS patients (302 patients from 289 unrelated families), along with tracking their ethnicity and geographical origins. 185/289 patients were studied using an IEM-targeted NGS panel followed by complementary Sanger sequencing, which led to the diagnosis of 154 MPS patients and 5 non-MPS IEMs (diagnostic yield: 85.9%). Furthermore, 106/289 patients who were referred with positive findings went through re-analysis and confirmatory tests which confirmed MPS diagnosis in 104. Among the total of 258 MPS patients, 225 were homozygous, and 9 had copy number variations, and 90 had novel variants. MPS IV was the most common type (34.8%) followed by MPS I (22.7%) and MPS VI (22.5%). Geographical origin analysis unveiled a pattern of distribution for frequent variants in ARSB (c.430G>A, c.962C>T, c.281C>A), GALNS (c.319G>A, c.860C>T, c.1042A>G), and IDUA (c.1A>C, c.1598C>G). Our extensive patient cohort reveals the genetic and geographic landscape of MPS in Iran, which provides insight into the genetic epidemiology of MPS and can facilitate a more cost-effective, time-efficient diagnostic approach based on the region-specific variants.

The UCSC Genome Browser has been an important tool for genomics and clinical genetics since the sequence of the human genome was first released in 2000. As it has grown in scope to display more types of data it has also grown more complicated. The data, which are dispersed at many locations worldwide, are collected into one view on the Browser, where the graphical interface presents the data in one location. This supports the expertise of the researcher to interpret variants in the genome. Because the analysis of Single Nucleotide Variants (SNVs) and Copy Number Variants (CNVs) require interpretation of data at very different genomic scales, different data resources are required. We present here several Recommended Track Sets designed to facilitate the interpretation of variants in the clinic, offering quick access to datasets relevant to the appropriate scale.