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.

The use of whole-genome sequencing (WGS) has accelerated the pace of gene discovery and highlighted the need for open and collaborative data sharing in the search for novel disease genes and variants. GeneMatcher (GM) is designed to facilitate connections between researchers, clinicians, health-care providers and others to help in the identification of additional patients with variants in the same candidate disease genes. The Illumina Clinical Services Laboratory offers a WGS test for patients with suspected rare and undiagnosed genetic disease and regularly submits potential candidate genes to GM to strengthen gene-disease relationships. We describe our experience with GM, including criteria for evaluation of candidate genes, and our workflow for the submission and review process. We have made 69 submissions, 36 of which are currently active. Ten per cent of submissions have resulted in publications, with an additional 14 submissions part of ongoing collaborations and expected to result in a publication.

The amount of data available from genomic medicine has revolutionized the approach to identify the determinants underlying many rare diseases. The task of confirming a genotype-phenotype causality for a patient affected with a rare genetic disease is often challenging. In this context, the establishment of the MatchMaker Exchange (MME) network has assumed a pivotal role in bridging heterogeneous patient information stored on different medical and research servers. MME has made it possible to solve rare disease cases by “matching” the genotypic and phenotypic characteristics of a patient of interest with patient data available at other clinical facilities participating in the network. Here, we present PatientMatcher (https://github.com/Clinical-Genomics/patientMatcher), an open-source Python and MongoDB-based software solution developed by Clinical Genomics facility at the Science for Life Laboratory in Stockholm. PatientMatcher is designed as a standalone MME server, but can easily communicate via REST API with external applications managing genetic analyses and patient data. The MME node is being implemented in clinical production in collaboration with the Genomic Medicine Center Karolinska at the Karolinska University Hospital. PatientMatcher is written to implement the MME API and provides several customizable settings, including a custom-fit similarity score algorithm and adjustable matching results notifications.

Over 7,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources.

Microdeletions and gross deletions are important causes (~20%) of human inherited disease. Their genomic locations are strongly influenced by the local DNA sequence environment. Yet no systematic study has examined the generative mechanisms. Here, we obtained 42,098 pathogenic microdeletions and gross deletions from the Human Gene Mutation Database (HGMD) that together form a continuum of germline deletions ranging in size from 1 bp to 28,394,429 bp. We analyzed the sequence within 1-kb of the breakpoint junctions and found the frequencies of non-B DNA-forming repeats, GC content, and the presence of seven of 78 specific sequence motifs in the vicinity of pathogenic deletions correlated with deletion length for deletions of length ≤30 bp. Furthermore, we found the repeats of DR, GQ, and STR appear to be important for the formation of longer deletions (>30 bp) but not for the formation of shorter deletions (≤30 bp) and significantly (Chi-square test P-value < 2E-16) more microhomologies were identified in flanking short deletions than long deletions (length >30 bp). We provide evidence to support a functional distinction between microdeletions and gross deletions. A deletion length cut-off of 25-30 bp may serve as an objective means to functionally distinguish microdeletions from gross deletions.

Runs of long homozygous stretches (ROH) are considered to be the result of consanguinity and usually contain recessive deleterious disease causing mutations (Szpiech et al., 2013). Several algorithms have been developed to detect ROHs. Here, we developed a simple, alternative strategy by examining X chromosome non-pseudoautosomal region to detect the ROHs from next generation sequencing data utilizing the genotype probabilities and the Hidden Markov Model algorithm as a tool, namely ROHMM. It is implemented purely in java and contains both command-line and a graphical user interface. We tested ROHMM on simulated data as well as real population data from 1000G Project and a clinical sample. Our results have shown that ROHMM can perform robustly producing highly accurate homozygosity estimations under all conditions thereby meeting and even exceeding the performance of its natural competitors.

Defects in DNA repair genes have been extensively associated to cancer susceptibility. Germline pathogenic variants (GPV) in genes involved in homologous recombination repair pathway predispose to cancers arising mainly in breast and ovary, but also other tissues. The RAD51 paralogs RAD51C and RAD51D were included in this group 10 years ago, when germline variants were associated to non-BRCA1/2 familial ovarian cancer. However, whether GPVs in these genes are associated with other cancers remains unknown. Here, we have reviewed the landscape of RAD51C and RAD51D germline variants in cancer reported in the literature during the last decade, curating a total of 341 variants and the phenotypes found in families with RAD51C/D variant carriers. A comprehensive catalogue has been generated pinpointing to the existence of recurrent variants in both genes. Investigation of pedigrees found fourteen other cancer types reported more than five times in families with carriers of RAD51C/D pathogenic variants. Among those, colorectal (3.72% and 4.43%) (RAD51C/D respectively), pancreatic (1.19% and 0.86%), lung (1.27% and 2.58%), prostate (1.56% and 1.48%), and leukemia (1.56% and 1.11%) cancer were the most prevalent types. This work highlights how both genes might confer susceptibility to a broader spectrum of cancer types than ovary and breast.

Genome sequencing(GS) has been applied in the diagnosis of global developmental delay(GDD)/intellectual disability(ID). However, the performance in those with inconclusive results from chromosomal microarray analysis(CMA) and exome sequencing(ES) is unknown. We recruited 100 pediatric GDD/ID patients from multiple sites in China from February 2018 to August 2020 for GS. Patients have received at least one genomic diagnostic test prior to enrollment. Reanalysis of CMA/ES data was performed. The yield of GS was calculated and explanations for missed diagnoses by CMA/ES were investigated. Clinical utility was assessed by interviewing the parents by phone. The overall diagnostic yield of GS was 23%. Seven families could have been solved with reanalysis of ES data. 13 families were missed by previous CMA/ES due to improper method. Three remained unsolved after ES reanalysis due to allele dropout, complex variants missed by ES, and a CNV in untranslated regions. Follow-up of the diagnosed families revealed that nine families experienced changes in clinical management, including identification of targeted treatments, cessation of unnecessary treatment, and considerations for family planning. GS demonstrated high diagnostic yield and clinical utility in this cohort of undiagnosed GDD/ID patients, detecting a wide range of variant types of different sizes in a single workflow.

Clinical genetic sequencing tests often identify variants of uncertain significance (VUS). One source of data that can help classify the pothogenicity of variants is familial cosegregation analysis. Identifying and genotyping relatives for cosegregation analysis can be time consuming and costly. We propose an algorithm that describes a single measure of expected variant information gain from genotyping a single additional relative in a family. Then we explore the performance of this algorithm by comparing actual recruitment strategies used in 35 families who had pursued cosegregation analysis with synthetic pedigrees of possible testing outcomes if the families had pursued an optimized testing strategy instead. For each actual and synthetic pedigree, we calculated the likelihood ratio of pathogenicity as each successive test was added to the pedigree. We analyzed the differences in cosegregation likelihood ratio over time resulting from actual versus optimized testing approaches. Employing the testing strategy indicated by the algorithm would have led to maximal information more rapidly in 30 of the 35 pedigrees (86%). Many clinical and research laboratories are involved in targeted cosegregation analysis. The algorithm we present can facilitate a data driven approach to optimal relative recruitment and genotyping for cosegregation analysis and more efficient variant classification.

The genes MECP2, CDKL5, FOXG1, UBE3A, SLC9A6, and TCF4 present unique challenges for current ACMG/AMP variant interpretation guidelines. To address those challenges, the Rett and Angelman-like Disorders Variant Curation Expert Panel (Rett/AS VCEP) drafted gene-specific modifications. A pilot study was conducted to test the clarity and accuracy of using the customized variant interpretation criteria. Multiple curators obtained the same interpretation for 78 out of the 87 variants (~90%), indicating appropriate usage of the modified guidelines the majority of times by all the curators. The classification of 13 variants changed using these criteria specifications compared to when the variants were originally curated and as present in ClinVar. Many of these changes were due to internal data shared from laboratory members however some changes were because of changes in strength of criteria. There were no two step classification changes and only 1 clinically relevant change (Likely pathogenic to VUS). The Rett/AS VCEP hopes that these gene-specific variant curation rules and the assertions provided help clinicians, clinical laboratories, and others interpret variants in these genes but also other fully penetrant, early-onset genes associated with rare disorders.

Massive parallel sequencing technology has become the predominant technique for genetic diagnostics and research. Many genetic laboratories have wrestled with the challenges of setting up genetic testing workflows based on a completely new technology. The learning curve we went through as a laboratory was accompanied by growing pains while we gained new knowledge and expertise. Here we discuss some important mistakes that have been made in our laboratory through ten years of clinical exome sequencing but that have given us important new insights on how to adapt our working methods. By providing these examples and the lessons that we learned from them, we hope that other laboratories do not need to make the same mistakes.

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.

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.

We have created a panel of twenty-nine NF1 variant cDNAs representing benign missense (MS) variants, pathogenic MS variants, many with clinically relevant phenotypes, in-frame deletions, splice variants, and nonsense (NS) variants. We have determined the functional consequences of the variants, assessing their ability to produce mature neurofibromin and restore Ras signaling activity in NF1 null (-/-) cells. cDNAs demonstrate variant-specific differences in neurofibromin protein levels, suggesting that some variants lead to protein instability or enhanced degradation. When expressed at high levels, some variant proteins are still able to repress Ras activity, indicating that the NF1 phenotype may be due to protein instability. In contrast, other variant proteins are incapable of repressing Ras activity, indicating that some do not functionally engage Ras and stimulate GTP-ase activity. We observed that stability and Ras activity can be mutually exclusive. These assays allow us to categorize variants by functional effects, may help to classify variants of unknown significance, and may have future implications for more directed therapeutics.

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.

Pathogenic variants of the nuclear receptor subfamily 2 group F member 1 gene (NR2F1) are responsible for Bosch-Boonstra-Schaaf optic atrophy syndrome (BBSOAS), an autosomal dominant disorder characterized by optic atrophy associated with developmental delay and intellectual disability, but with a clinical presentation which appears to be multifaceted. We created the first public locus-specific database (LSDB) dedicated to NR2F1. All variants and clinical cases reported in the literature, as well as new unpublished cases, were integrated into the database using standard nomenclature to describe both molecular and phenotypic anomalies. We subsequently pursued a comprehensive approach based on computed representation and analysis suggesting a refinement of the BBSOAS clinical description with respect to neurological features and the inclusion of musculoskeletal hypotonia and intestinal signs with feeding difficulties. This database is fully accessible for both clinician and molecular biologists and should prove useful in further refining the clinical synopsis of NR2F1 as new data is recorded.

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.

Hereditary papillary renal cell carcinoma (HPRCC) is a rare inherited renal cancer syndrome characterized by bilateral and multifocal papillary type 1 renal tumors (PRCC1). Activating germline pathogenic variants of MET gene were identified in HPRCC families. We reviewed the medical and molecular records of a large French series of 158 patients screened for MET oncogenic variants (153 index-cases and five relatives). MET pathogenic variant rate was 10.4% (16/153) with 37.5% among patients with familial PRCC1 and 3.3% among patients with sporadic PRCC1 presentation. The phenotype in MET mutated cases was characteristic as PRCC1 tumors were mainly bilateral (82.3%) and multifocal (85.8%). Histologically, six out of seven patients with MET germline pathogenic variant harboured biphasic squamoid alveolar PRCC. Genetic screening identified in four index-cases a novel missense pathogenic variant within the tyrosine kinase domain: MET c.3389T>C, p.(Leu1130Ser). Functional assay confirmed its oncogenic effect with a constitutive phosphorylation of ERK protein and an abnormal focus formation induced. The genotype-phenotype correlation between MET pathogenic variants and PRCC1 presentation should encourage to widen the screening, especially toward non-familial PRCC1. This precise phenotype also constitutes a strong argument for the classification of novel missense variants within the tyrosine kinase domain when functional assays aren’t accessible.