Guidelines for establishing locus specific databases

Global Globin Network and adopting genomic variant database requirements for thalassemia

Thalassemia is one of the most prevalent monogenic disorders in low- and middle-income countries (LMICs). There are an estimated 270 million carriers of hemoglobinopathies (abnormal hemoglobins and/or thalassemia) worldwide, necessitating global methods and solutions for effective and optimal therapy. LMICs are disproportionately impacted by thalassemia, and due to disparities in genomics awareness and diagnostic resources, certain LMICs lag behind high-income countries (HICs). This spurred the establishment of the Global Globin Network (GGN) in 2015 at UNESCO, Paris, as a project-wide endeavor within the Human Variome Project (HVP). Primarily aimed at enhancing thalassemia clinical services, research, and genomic diagnostic capabilities with a focus on LMIC needs, GGN aims to foster data collection in a shared database by all affected nations, thus improving data sharing and thalassemia management. In this paper, we propose a minimum requirement for establishing a genomic database in thalassemia based on the HVP database guidelines. We suggest using an existing platform recommended by HVP, the Leiden Open Variation Database (LOVD) (https://www.lovd.nl/). Adoption of our proposed criteria will assist in improving or supplementing the existing databases, allowing for better-quality services for individuals with thalassemia. Database URL: https://www.lovd.nl/.

AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

Despite genomic sequencing rapidly transforming from being a bench-side tool to a routine procedure in a hospital, there is a noticeable lack of genomic analysis software that supports both clinical and research workflows as well as crowdsourcing. Furthermore, most existing software packages are not forward-compatible in regards to supporting ever-changing diagnostic rules adopted by the genetics community. Regular updates of genomics databases pose challenges for reproducible and traceable automated genetic diagnostics tools. Lastly, most of the software tools score low on explainability amongst clinicians. We have created a fully open-source variant curation tool, AnFiSA, with the intention to invite and accept contributions from clinicians, researchers, and professional software developers. The design of AnFiSA addresses the aforementioned issues via the following architectural principles: using a multidimensional database management system (DBMS) for genomic data to address reproducibility, curated decision trees adaptable to changing clinical rules, and a crowdsourcing-friendly interface to address difficult-to-diagnose cases. We discuss how we have chosen our technology stack and describe the design and implementation of the software. Finally, we show in detail how selected workflows can be implemented using the current version of AnFiSA by a medical geneticist.

NR2F1 database: 112 variants and 84 patients support refining the clinical synopsis of Bosch-Boonstra-Schaaf optic atrophy syndrome

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 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 additional signs of hypotonia and 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.

Edgetic Perturbations Contribute to Phenotypic Variability in PEX26 Deficiency

Peroxisomes share metabolic pathways with other organelles and peroxisomes are embedded into key cellular processes. However, the specific function of many peroxisomal proteins remains unclear and restricted knowledge of the peroxisomal protein interaction network limits a precise mapping of this network into the cellular metabolism. Inborn peroxisomal disorders are autosomal or X-linked recessive diseases that affect peroxisomal biogenesis (PBD) and/or peroxisomal metabolism. Pathogenic variants in the PEX26 gene lead to peroxisomal disorders of the full Zellweger spectrum continuum. To investigate the phenotypic complexity of PEX26 deficiency, we performed a combined organelle protein interaction screen and network medicine approach and 1) analyzed whether PEX26 establishes interactions with other peroxisomal proteins, 2) deciphered the PEX26 interaction network, 3) determined how PEX26 is involved in further processes of peroxisomal biogenesis and metabolism, and 4) showed how variant-specific disruption of protein-protein interactions (edgetic perturbations) may contribute to phenotypic variability in PEX26 deficient patients. The discovery of 14 novel protein-protein interactions for PEX26 revealed a hub position of PEX26 inside the peroxisomal interactome. Analysis of edgetic perturbations of PEX26 variants revealed a strong correlation between the number of affected protein-protein interactions and the molecular phenotype of matrix protein import. The role of PEX26 in peroxisomal biogenesis was expanded encompassing matrix protein import, division and proliferation, and membrane assembly. Moreover, the PEX26 interaction network intersects with cellular lipid metabolism at different steps. The results of this study expand the knowledge about the function of PEX26 and refine genotype-phenotype correlations, which may contribute to our understanding of the underlying disease mechanism of PEX26 deficiency.

ACO2 clinicobiological dataset with extensive phenotype ontology annotation

Pathogenic variants of the aconitase 2 gene (ACO2) are responsible for a broad clinical spectrum involving optic nerve degeneration, ranging from isolated optic neuropathy with recessive or dominant inheritance, to complex neurodegenerative syndromes with recessive transmission. We created the first public locus-specific database (LSDB) dedicated to ACO2 within the "Global Variome shared LOVD" using exclusively the Human Phenotype Ontology (HPO), a standard vocabulary for describing phenotypic abnormalities. All the variants and clinical cases listed in the literature were incorporated into the database, from which we produced a dataset. We followed a rational and comprehensive approach based on the HPO thesaurus, demonstrating that ACO2 patients should not be classified separately between isolated and syndromic cases. Our data highlight that certain syndromic patients do not have optic neuropathy and provide support for the classification of the recurrent pathogenic variants c.220C>G and c.336C>G as likely pathogenic. Overall, our data records demonstrate that the clinical spectrum of ACO2 should be considered as a continuum of symptoms and refines the classification of some common variants.

FHLdb: A Comprehensive Database on the Molecular Basis of Familial Hemophagocytic Lymphohistiocytosis

Background: Primary immunodeficiencies (PIDs) are a heterogeneous group of disorders. The lack of comprehensive disease-specific mutation databases may hinder or delay classification of the genetic variants found in samples from these patients. This is especially true for familial hemophagocytic lymphohistiocytosis (FHL), a life-threatening PID classically considered an autosomal recessive condition, but with increasingly demonstrated genetic heterogeneity.

Objective: The aim of this study was to build an open-access repository to collect detailed information on the known genetic variants reported in FHL.

Methods: We manually reviewed more than 120 articles to identify all reported variants related to FHL. We retrieved relevant information about the allelic status, the number of patients with the same variant, and whether functional assays were done. We stored all the data retrieved in a PostgreSQL database and then built a website on top of it, using the Django framework.

Results: The database designed (FHLdb) (https://www.biotoclin.org/FHLdb) contains comprehensive information on reported variants in the 4 genes related to FHL (PRF1, UNC13D, STXBP2, STX11). It comprises 240 missense, 69 frameshift, 51 nonsense, 51 splicing, 10 in-frame indel, 7 deep intronic, and 5 large rearrangement variants together with their allelic status, carrier(s) information, and functional evidence. All genetic variants have been classified as pathogenic, likely pathogenic, uncertain significance, likely benign or benign, according to the American College of Medical Genetics guidelines. Additionally, it integrates information from other relevant databases: clinical evidence from ClinVar and UniProt, population allele frequency from ExAC and gnomAD, and pathogenicity predictions from well-recognized tools (e.g., PolyPhen-2, SIFT). Finally, a diagram depicts the location of the variant relative to the gene exon and protein domain structures.

Conclusion: FHLdb includes a broad range of data on the reported genetic variants in familial HLH genes. It is a free-access and easy-to-use resource that will facilitate the interpretation of molecular results of FHL patients, and it illustrates the potential value of disease-specific databases for other PIDs.

OPA1: 516 unique variants and 831 patients registered in an updated centralized Variome database

BACKGROUND

The dysfunction of OPA1, a dynamin GTPase involved in mitochondrial fusion, is responsible for a large spectrum of neurological disorders, each of which includes optic neuropathy. The database dedicated to OPA1 ( https://www.lovd.nl/OPA1 ), created in 2005, has now evolved towards a centralized and more reliable database using the Global Variome shared Leiden Open-source Variation Database (LOVD) installation.

RESULTS

The updated OPA1 database, which registers all the patients from our center as well as those reported in the literature, now covers a total of 831 patients: 697 with isolated dominant optic atrophy (DOA), 47 with DOA "plus", and 83 with asymptomatic or unclassified DOA. It comprises 516 unique OPA1 variants, of which more than 80% (414) are considered pathogenic. Full clinical data for 118 patients are documented using the Human Phenotype Ontology, a standard vocabulary for referencing phenotypic abnormalities. Contributors may now make online submissions of phenotypes related to OPA1 mutations, giving clinical and molecular descriptions together with detailed ophthalmological and neurological data, according to an international thesaurus.

CONCLUSIONS

The evolution of the OPA1 database towards the LOVD, using unified nomenclature, should ensure its interoperability with other databases and prove useful for molecular diagnoses based on gene-panel sequencing, large-scale mutation statistics, and genotype-phenotype correlations.

Checklist for gene/disease-specific variation database curators to enable ethical data management

Databases with variant and phenotype information are essential for advancing research and improving the health and welfare of individuals. These resources require data to be collected, curated, and shared among relevant specialties to maximize impact. The increasing generation of data which must be shared both nationally and globally for maximal effect presents important ethical and privacy concerns. Database curators need to ensure that their work conform to acceptable ethical standards. A Working Group of the Human Variome Project had the task of updating and streamlining ethical guidelines for locus-specific/gene variant database curators. In this article, we present practical and achievable steps which should assist database curators in carrying out their responsibilities within acceptable ethical norms.

GAA variants and phenotypes among 1,079 patients with Pompe disease: Data from the Pompe Registry

Identification of variants in the acid α‐glucosidase (GAA) gene in Pompe disease provides valuable insights and systematic overviews are needed. We report on the number, nature, frequency, and geographic distribution of GAA sequence variants listed in the Pompe Registry, a long‐term, observational program and the largest global repository of Pompe disease data. Variant information was reviewed and compared with publicly available GAA databases/resources. Among 1,079 eligible patients, 2,075 GAA variants (80 unique novel) were reported. Variants were listed by groups representing Pompe disease phenotypes. Patients were classified as Group A: Symptom onset ≤ 12 months of age with cardiomyopathy; Group B: Symptom onset ≤ 12 years of age (includes patients with symptom onset ≤ 12 months of age without cardiomyopathy); or Group C: Symptom onset > 12 years of age. Likely impact of novel variants was predicted using bioinformatics algorithms. Variants were classified by pathogenicity using ACMG guidelines. Data reported from the Pompe Registry provide new information about the distribution of GAA variants globally and across the clinical spectrum, add to the number and diversity of GAA variants registered in public databases through published data sharing, provide a first indication of the severity of novel variants, and assist in diagnostic practice and outcome prediction.

Inherited glycophosphatidylinositol deficiency variant database and analysis of pathogenic variants

Background

Glycophosphatidylinositol‐anchored proteins (GPI‐APs) mediate several physiological processes such as embryogenesis and neurogenesis. Germline variants in genes involved in their synthesis can disrupt normal development and result in a variety of clinical phenotypes. With the advent of new sequencing technologies, more cases are identified, leading to a rapidly growing number of reported genetic variants. With this number expected to rise with increased accessibility to molecular tests, an accurate and up‐to‐date database is needed to keep track of the information and help interpret results.

Methods

We therefore developed an online resource (www.gpibiosynthesis.org) which compiles all published pathogenic variants in GPI biosynthesis genes which are deposited in the LOVD database. It contains 276 individuals and 192 unique public variants; 92% of which are predicted as damaging by bioinformatics tools.

Results

A significant proportion of recorded variants was substitution variants (81%) and resulted mainly in missense and frameshift alterations. Interestingly, five patients (2%) had deleterious mutations in untranslated regions. CADD score analysis placed 97% of variants in the top 1% of deleterious variants in the human genome. In genome aggregation database, the gene with the highest frequency of reported pathogenic variants is PIGL, with a carrier rate of 1/937.

Conclusion

We thus present the GPI biosynthesis database and review the molecular genetics of published variants in GPI‐anchor biosynthesis genes.

Uncovering a multitude of human glucocorticoid receptor variants: an expansive survey of a single gene

Background

Glucocorticoids are commonly used in the clinical setting for their potent anti-inflammatory effects; however, significant variations in response to treatment have been demonstrated. Although the underlying mechanisms have yet to be fully understood, this variable response may be a result of alterations in human glucocorticoid receptor (hGR) expression and function. In addition to hGRα, the biologically active isoform, a screening of current databases and publications revealed five alternative splice isoforms and hundreds of variants that have been reported to date. Many of these changes in the hGR-coding gene, NR3C1, have been linked to pathophysiology. However, many studies focus on evaluating hGR expression in vitro or detecting previously reported variants.

Results

In this study, blood from healthy volunteers, burn and asthma patients, as well as from peripheral blood mononuclear cells isolated from leukoreduced donor whole blood, were screened for NR3C1 isoforms. We identified more than 1500 variants, including an additional 21 unique splice isoforms which contain 15 new cryptic exons. A dynamic database, named the Universal hGR (UhGR), was created to annotate and visualize the variants.

Conclusion

This identification of naturally occurring and stress-induced hGR isoforms, as well as the establishment of an hGR-specific database, may reveal new patterns or suggest areas of interest that will lead to the improved understanding of the human stress response system.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0718-z) contains supplementary material, which is available to authorized users.

UVEOGENE: An SNP database for investigations on genetic factors associated with uveitis and their relationship with other systemic autoimmune diseases

Uveitis is an intraocular inflammatory disease which can lead to serious visual impairment. Genetic factors have been shown to be involved in its development. However, few databases have focused on the information of associations between single nucleotide polymorphisms (SNPs) and uveitis. To discover the exact genetic background of uveitis, we developed an SNP database specific for uveitis, “UVEOGENE,” which includes 370 genes and 918 SNPs covering 14 uveitis entities and 40 populations from 286 PubMed English‐language papers. Stratification analyses by gender, HLA status, and different clinical features were also extracted from the publications. As a result, 371 associations were judged as “statistically significant.” These associations were also shared with Global Variome shared Leiden Open Variation Database (LOVD) (https://databases.lovd.nl/shared/genes). Based on these associations, we investigated the genetic relationship among three widely studied uveitis entities including Behcet's disease (BD), Vogt–Koyanagi–Harada (VKH) disease, and acute anterior uveitis (AAU). Furthermore, “UVEOGENE” can be used as a reliable and informative resource to identify similarities as well as differences in the genetic susceptibility among uveitis and other autoimmune diseases. UVEOGENE is freely accessible at http://www.uvogene.com.

NDDVD: an integrated and manually curated Neurodegenerative Diseases Variation Database

Neurodegenerative diseases (NDDs) are associated with genetic variations including point substitutions, copy number alterations, insertions and deletions. At present, a few genetic variation repositories for some individual NDDs have been created, however, these databases are needed to be integrated and expanded to all the NDDs for systems biological investigation. We here build a relational database termed as NDDVD to integrate all the variations of NDDs using Leiden Open Variation Database (LOVD) platform. The items in the NDDVD are collected manually from PubMed or extracted from the existed variation databases. The cross-disease database includes over 6374 genetic variations of 289 genes associated with 37 different NDDs. The patterns, conservations and biological functions for variations in different NDDs are statistically compared and a user-friendly interface is provided for NDDVD at: http://bioinf.suda.edu.cn/NDDvarbase/LOVDv.3.0.

URL: http://bioinf.suda.edu.cn/NDDvarbase/LOVDv.3.0

LAMA2 gene mutation update: Toward a more comprehensive picture of the laminin-α2 variome and its related phenotypes

Congenital muscular dystrophy type 1A (MDC1A) is one of the main subtypes of early-onset muscle disease, caused by disease-associated variants in the laminin-α2 (LAMA2) gene. MDC1A usually presents as a severe neonatal hypotonia and failure to thrive. Muscle weakness compromises normal motor development, leading to the inability to sit unsupported or to walk independently. The phenotype associated with LAMA2 defects has been expanded to include milder and atypical cases, being now collectively known as LAMA2-related muscular dystrophies (LAMA2-MD). Through an international multicenter collaborative effort, 61 new LAMA2 disease-associated variants were identified in 86 patients, representing the largest number of patients and new disease-causing variants in a single report. The collaborative variant collection was supported by the LOVD-powered LAMA2 gene variant database (https://www.LOVD.nl/LAMA2), updated as part of this work. As of December 2017, the database contains 486 unique LAMA2 variants (309 disease-associated), obtained from direct submissions and literature reports. Database content was systematically reviewed and further insights concerning LAMA2-MD are presented. We focus on the impact of missense changes, especially the c.2461A > C (p.Thr821Pro) variant and its association with late-onset LAMA2-MD. Finally, we report diagnostically challenging cases, highlighting the relevance of modern genetic analysis in the characterization of clinically heterogeneous muscle diseases.

PON-tstab: Protein Variant Stability Predictor. Importance of Training Data Quality

Several methods have been developed to predict effects of amino acid substitutions on protein stability. Benchmark datasets are essential for method training and testing and have numerous requirements including that the data is representative for the investigated phenomenon. Available machine learning algorithms for variant stability have all been trained with ProTherm data. We noticed a number of issues with the contents, quality and relevance of the database. There were errors, but also features that had not been clearly communicated. Consequently, all machine learning variant stability predictors have been trained on biased and incorrect data. We obtained a corrected dataset and trained a random forests-based tool, PON-tstab, applicable to variants in any organism. Our results highlight the importance of the benchmark quality, suitability and appropriateness. Predictions are provided for three categories: stability decreasing, increasing and those not affecting stability.

CFTR-France, a national relational patient database for sharing genetic and phenotypic data associated with rare CFTR variants

Most of the 2,000 variants identified in the CFTR (cystic fibrosis transmembrane regulator) gene are rare or private. Their interpretation is hampered by the lack of available data and resources, making patient care and genetic counseling challenging. We developed a patient-based database dedicated to the annotations of rare CFTR variants in the context of their cis- and trans-allelic combinations. Based on almost 30 years of experience of CFTR testing, CFTR-France (https://cftr.iurc.montp.inserm.fr/cftr) currently compiles 16,819 variant records from 4,615 individuals with cystic fibrosis (CF) or CFTR-RD (related disorders), fetuses with ultrasound bowel anomalies, newborns awaiting clinical diagnosis, and asymptomatic compound heterozygotes. For each of the 736 different variants reported in the database, patient characteristics and genetic information (other variations in cis or in trans) have been thoroughly checked by a dedicated curator. Combining updated clinical, epidemiological, in silico, or in vitro functional data helps to the interpretation of unclassified and the reassessment of misclassified variants. This comprehensive CFTR database is now an invaluable tool for diagnostic laboratories gathering information on rare variants, especially in the context of genetic counseling, prenatal and preimplantation genetic diagnosis. CFTR-France is thus highly complementary to the international database CFTR2 focused so far on the most common CF-causing alleles.

Monogenic diabetes syndromes: Locus-specific databases for Alström, Wolfram, and Thiamine-responsive megaloblastic anemia

We developed a variant database for diabetes syndrome genes, using the Leiden Open Variation Database platform, containing observed phenotypes matched to the genetic variations. We populated it with 628 published disease-associated variants (December 2016) for: WFS1 (n = 309), CISD2 (n = 3), ALMS1 (n = 268), and SLC19A2 (n = 48) for Wolfram type 1, Wolfram type 2, Alström, and Thiamine-responsive megaloblastic anemia syndromes, respectively; and included 23 previously unpublished novel germline variants in WFS1 and 17 variants in ALMS1. We then investigated genotype-phenotype relations for the WFS1 gene. The presence of biallelic loss-of-function variants predicted Wolfram syndrome defined by insulin-dependent diabetes and optic atrophy, with a sensitivity of 79% (95% CI 75%-83%) and specificity of 92% (83%-97%). The presence of minor loss-of-function variants in WFS1 predicted isolated diabetes, isolated deafness, or isolated congenital cataracts without development of the full syndrome (sensitivity 100% [93%-100%]; specificity 78% [73%-82%]). The ability to provide a prognostic prediction based on genotype will lead to improvements in patient care and counseling. The development of the database as a repository for monogenic diabetes gene variants will allow prognostic predictions for other diabetes syndromes as next-generation sequencing expands the repertoire of genotypes and phenotypes. The database is publicly available online at https://lovd.euro-wabb.org.

PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned

Computational tools are widely used for ranking and prioritizing variants for characterizing their disease relevance. Since numerous tools have been developed, they have to be properly assessed before being applied. Critical Assessment of Genome Interpretation (CAGI) experiments have significantly contributed toward the assessment of prediction methods for various tasks. Within and outside the CAGI, we have addressed several questions that facilitate development and assessment of variation interpretation tools. These areas include collection and distribution of benchmark datasets, their use for systematic large-scale method assessment, and the development of guidelines for reporting methods and their performance. For us, CAGI has provided a chance to experiment with new ideas, test the application areas of our methods, and network with other prediction method developers. In this article, we discuss our experiences and lessons learned from the various CAGI challenges. We describe our approaches, their performance, and impact of CAGI on our research. Finally, we discuss some of the possibilities that CAGI experiments have opened up and make some suggestions for future experiments.

Establishment of an international database for genetic variants in esophageal cancer

The establishment of a database has been suggested in order to collect, organize, and distribute genetic information about esophageal cancer. The World Organization for Specialized Studies on Diseases of the Esophagus and the Human Variome Project will be in charge of a central database of information about esophageal cancer-related variations from publications, databases, and laboratories; in addition to genetic details, clinical parameters will also be included. The aim will be to get all the central players in research, clinical, and commercial laboratories to contribute. The database will follow established recommendations and guidelines. The database will require a team of dedicated curators with different backgrounds. Numerous layers of systematics will be applied to facilitate computational analyses. The data items will be extensively integrated with other information sources. The database will be distributed as open access to ensure exchange of the data with other databases. Variations will be reported in relation to reference sequences on three levels--DNA, RNA, and protein-whenever applicable. In the first phase, the database will concentrate on genetic variations including both somatic and germline variations for susceptibility genes. Additional types of information can be integrated at a later stage.

Clinical Interpretation of Genomic Variations

Novel high-throughput sequencing technologies generate large-scale genomic data and are used extensively for disease mapping of monogenic and/or complex disorders, personalized treatment, and pharmacogenomics. Next-generation sequencing is rapidly becoming routine tool for diagnosis and molecular monitoring of patients to evaluate therapeutic efficiency. The next-generation sequencing platforms generate huge amounts of genetic variation data and it remains a challenge to interpret the variations that are identified. Such data interpretation needs close collaboration among bioinformaticians, clinicians, and geneticists. There are several problems that must be addressed, such as the generation of new algorithms for mapping and annotation, harmonization of the terminology, correct use of nomenclature, reference genomes for different populations, rare disease variant databases, and clinical reports.

Deciphering Variability of PKD1 and PKD2 in an Italian Cohort of 643 Patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD)

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most common hereditary kidney disease. We analysed PKD1 and PKD2, in a large cohort of 440 unrelated Italian patients with ADPKD and 203 relatives by direct sequencing and MLPA. Molecular and detailed phenotypic data have been collected and submitted to the PKD1/PKD2 LOVD database. This is the first large retrospective study in Italian patients, describing 701 variants, 249 (35.5%) already associated with ADPKD and 452 (64.5%) novel. According to the criteria adopted, the overall detection rate was 80% (352/440). Novel variants with uncertain significance were found in 14% of patients. Among patients with pathogenic variants, in 301 (85.5%) the disease is associated with PKD1, 196 (55.7%) truncating, 81 (23%) non truncating, 24 (6.8%) IF indels, and in 51 (14.5%) with PKD2. Our results outline the high allelic heterogeneity of variants, complicated by the presence of variants of uncertain significance as well as of multiple variants in the same subject. Classification of novel variants may be particularly cumbersome having an important impact on the genetic counselling. Our study confirms the importance to improve the assessment of variant pathogenicity for ADPKD; to this point databasing of both clinical and molecular data is crucial.

Human Variome Project Quality Assessment Criteria for Variation Databases

Numerous databases containing information about DNA, RNA, and protein variations are available. Gene-specific variant databases (locus-specific variation databases, LSDBs) are typically curated and maintained for single genes or groups of genes for a certain disease(s). These databases are widely considered as the most reliable information source for a particular gene/protein/disease, but it should also be made clear they may have widely varying contents, infrastructure, and quality. Quality is very important to evaluate because these databases may affect health decision-making, research, and clinical practice. The Human Variome Project (HVP) established a Working Group for Variant Database Quality Assessment. The basic principle was to develop a simple system that nevertheless provides a good overview of the quality of a database. The HVP quality evaluation criteria that resulted are divided into four main components: data quality, technical quality, accessibility, and timeliness. This report elaborates on the developed quality criteria and how implementation of the quality scheme can be achieved. Examples are provided for the current status of the quality items in two different databases, BTKbase, an LSDB, and ClinVar, a central archive of submissions about variants and their clinical significance.

VariOtator, a Software Tool for Variation Annotation with the Variation Ontology

The Variation Ontology (VariO) is used for describing and annotating types, effects, consequences, and mechanisms of variations. To facilitate easy and consistent annotations, the online application VariOtator was developed. For variation type annotations, VariOtator is fully automated, accepting variant descriptions in Human Genome Variation Society (HGVS) format, and generating VariO terms, either with or without full lineage, that is, all parent terms. When a coding DNA variant description with a reference sequence is provided, VariOtator checks the description first with Mutalyzer and then generates the predicted RNA and protein descriptions with their respective VariO annotations. For the other sublevels, function, structure, and property, annotations cannot be automated, and VariOtator generates annotation based on provided details. For VariO terms relating to structure and property, one can use attribute terms as modifiers and evidence code terms for annotating experimental evidence. There is an online batch version, and stand-alone batch versions to be used with a Leiden Open Variation Database (LOVD) download file. A SOAP Web service allows client programs to access VariOtator programmatically. Thus, systematic variation effect and type annotations can be efficiently generated to allow easy use and integration of variations and their consequences.

The Human Variome Project: ensuring the quality of DNA variant databases in inherited renal disease

A recent review identified 60 common inherited renal diseases caused by DNA variants in 132 different genes. These diseases can be diagnosed with DNA sequencing, but each gene probably also has a thousand normal variants. Many more normal variants have been characterised by individual laboratories than are reported in the literature or found in publicly accessible collections. At present, testing laboratories must assess each novel change they identify for pathogenicity, even when this has been done elsewhere previously, and the distinction between normal and disease-associated variants is particularly an issue with the recent surge in exomic sequencing and gene discovery projects. The Human Variome Project recommends the establishment of gene-specific DNA variant databases to facilitate the sharing of DNA variants and decisions about likely disease causation. Databases improve diagnostic accuracy and testing efficiency, and reduce costs. They also help with genotype-phenotype correlations and predictive algorithms. The Human Variome Project advocates databases that use standardised descriptions, are up-to-date, include clinical information and are freely available. Currently, the genes affected in the most common inherited renal diseases correspond to 350 different variant databases, many of which are incomplete or have insufficient clinical details for genotype-phenotype correlations. Assistance is needed from nephrologists to maximise the usefulness of these databases for the diagnosis and management of inherited renal disease.

Quality standards for DNA sequence variation databases to improve clinical management under development in Australia

Despite the routine nature of comparing sequence variations identified during clinical testing to database records, few databases meet quality requirements for clinical diagnostics. To address this issue, The Royal College of Pathologists of Australasia (RCPA) in collaboration with the Human Genetics Society of Australasia (HGSA), and the Human Variome Project (HVP) is developing standards for DNA sequence variation databases intended for use in the Australian clinical environment. The outputs of this project will be promoted to other health systems and accreditation bodies by the Human Variome Project to support the development of similar frameworks in other jurisdictions.

Mutation databases for inherited renal disease: are they complete, accurate, clinically relevant, and freely available?

This study examined whether gene-specific DNA variant databases for inherited diseases of the kidney fulfilled the Human Variome Project recommendations of being complete, accurate, clinically relevant and freely available. A recent review identified 60 inherited renal diseases caused by mutations in 132 genes. The disease name, MIM number, gene name, together with "mutation" or "database," were used to identify web-based databases. Fifty-nine diseases (98%) due to mutations in 128 genes had a variant database. Altogether there were 349 databases (a median of 3 per gene, range 0-6), but no gene had two databases with the same number of variants, and 165 (50%) databases included fewer than 10 variants. About half the databases (180, 54%) had been updated in the previous year. Few (77, 23%) were curated by "experts" but these included nine of the 11 with the most variants. Even fewer databases (41, 12%) included clinical features apart from the name of the associated disease. Most (223, 67%) could be accessed without charge, including those for 50 genes (40%) with the maximum number of variants. Future efforts should focus on encouraging experts to collaborate on a single database for each gene affected in inherited renal disease, including both unpublished variants, and clinical phenotypes.

Variation ontology: annotator guide

Background

Systematic representation of information related to genetic and non-genetic variations is required to allow large scale studies, data mining and data integration, and to make it possible to reveal novel relationships between genotype and phenotype. Although lots of variation data is available it is often difficult to use due to lack of systematics.

Results

A novel ontology, Variation Ontology (VariO http://variationontology.org), was developed for annotation of effects, consequences and mechanisms of variations. In this article instructions are provided on how VariO annotations are made. The major levels for description are the three molecules, namely DNA, RNA and protein. They are further divided to four major sublevels: variation type, function, structure, and property, and further up to eight sublevels. VariO annotation summarizes existing knowledge about a variation and its effects and formalizes it so that computational analyses are efficient. The annotations should be made on as many levels as possible. VariO annotations are made in reference to normal states, which vary for each data item including e.g. reference sequences, wild type properties, and activities.

Conclusions

Detailed instructions together with examples are provided to indicate how VariO can be used for annotation of variations and their effects. A dedicated tool has been developed for annotation and will be further developed to cover also evidence for the annotations. VariO is suitable for annotation of data in many types of databases. As several different kinds of databases are in a process of adapting VariO annotations it is important to have guidelines to guarantee consistent annotation.

Annotating DNA variants is the next major goal for human genetics

Clinical genetic testing has undergone a dramatic transformation in the past two decades. Diagnostic laboratories that previously tested for well-established disease-causing DNA variants in a handful of genes have evolved into sequencing factories identifying thousands of variants of known and unknown medical consequence. Sorting out what does and does not cause disease in our genomes is the next great challenge in making genetics a central feature of healthcare. I propose that closing the gap in our ability to interpret variation responsible for Mendelian disorders provides a grand and unprecedented opportunity for geneticists. Human geneticists are well placed to coordinate a systematic evaluation of variants in collaboration with basic scientists and clinicians. Sharing of knowledge, data, methods, and tools will aid both researchers and healthcare workers in achieving their common goal of defining the pathogenic potential of variants. Generation of variant annotations will inform genetic testing and will deepen our understanding of gene and protein function, thereby aiding the search for molecular targeted therapies.

Locus Reference Genomic: reference sequences for the reporting of clinically relevant sequence variants

Locus Reference Genomic (LRG; http://www.lrg-sequence.org/) records contain internationally recognized stable reference sequences designed specifically for reporting clinically relevant sequence variants. Each LRG is contained within a single file consisting of a stable ‘fixed’ section and a regularly updated ‘updatable’ section. The fixed section contains stable genomic DNA sequence for a genomic region, essential transcripts and proteins for variant reporting and an exon numbering system. The updatable section contains mapping information, annotation of all transcripts and overlapping genes in the region and legacy exon and amino acid numbering systems. LRGs provide a stable framework that is vital for reporting variants, according to Human Genome Variation Society (HGVS) conventions, in genomic DNA, transcript or protein coordinates. To enable translation of information between LRG and genomic coordinates, LRGs include mapping to the human genome assembly. LRGs are compiled and maintained by the National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EBI). LRG reference sequences are selected in collaboration with the diagnostic and research communities, locus-specific database curators and mutation consortia. Currently >700 LRGs have been created, of which >400 are publicly available. The aim is to create an LRG for every locus with clinical implications.

Variation Ontology for annotation of variation effects and mechanisms

Ontology organizes and formally conceptualizes information in a knowledge domain with a controlled vocabulary having defined terms and relationships between them. Several ontologies have been used to annotate numerous databases in biology and medicine. Due to their unambiguous nature, ontological annotations facilitate systematic description and data organization, data integration and mining, and pattern recognition and statistics, as well as development of analysis and prediction tools. The Variation Ontology (VariO) was developed to allow the annotation of effects, consequences, and mechanisms of DNA, RNA, and protein variations. Variation types are systematically organized, and a detailed description of effects and mechanisms is possible. VariO is for annotating the variant, not the normal-state features or properties, and requires a reference (e.g., reference sequence, reference-state property, activity, etc.) compared to which the changes are indicated. VariO is versatile and can be used for variations ranging from genomic multiplications to single nucleotide or amino acid changes, whether of genetic or nongenetic origin. VariO annotations are position-specific and can be used for variations in any organism.

The Finnish disease heritage database (FinDis) update-a database for the genes mutated in the Finnish disease heritage brought to the next-generation sequencing era

The Finnish Disease Heritage Database (FinDis) (http://findis.org) was originally published in 2004 as a centralized information resource for rare monogenic diseases enriched in the Finnish population. The FinDis database originally contained 405 causative variants for 30 diseases. At the time, the FinDis database was a comprehensive collection of data, but since 1994, a large amount of new information has emerged, making the necessity to update the database evident. We collected information and updated the database to contain genes and causative variants for 35 diseases, including six more genes and more than 1,400 additional disease-causing variants. Information for causative variants for each gene is collected under the LOVD 3.0 platform, enabling easy updating. The FinDis portal provides a centralized resource and user interface to link information on each disease and gene with variant data in the LOVD 3.0 platform. The software written to achieve this has been open-sourced and made available on GitHub (http://github.com/findis-db), allowing biomedical institutions in other countries to present their national data in a similar way, and to both contribute to, and benefit from, standardized variation data. The updated FinDis portal provides a unique resource to assist patient diagnosis, research, and the development of new cures.

Large numbers of genetic variants considered to be pathogenic are common in asymptomatic individuals

It is now affordable to order clinically interpreted whole-genome sequence reports from clinical laboratories. One major component of these reports is derived from the knowledge base of previously identified pathogenic variants, including research articles, locus-specific, and other databases. While over 150,000 such pathogenic variants have been identified, many of these were originally discovered in small cohort studies of affected individuals, so their applicability to asymptomatic populations is unclear. We analyzed the prevalence of a large set of pathogenic variants from the medical and scientific literature in a large set of asymptomatic individuals (N = 1,092) and found 8.5% of these pathogenic variants in at least one individual. In the average individual in the 1000 Genomes Project, previously identified pathogenic variants occur on average 294 times (σ = 25.5) in homozygous form and 942 times (σ = 68.2) in heterozygous form. We also find that many of these pathogenic variants are frequently occurring: there are 3,744 variants with minor allele frequency (MAF) ≥ 0.01 (4.6%) and 2,837 variants with MAF ≥ 0.05 (3.5%). This indicates that many of these variants may be erroneous findings or have lower penetrance than previously expected.

Defining the disease liability of variants in the cystic fibrosis transmembrane conductance regulator gene

Allelic heterogeneity in disease-causing genes presents a substantial challenge to the translation of genomic variation to clinical practice. Few of the almost 2,000 variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene have empirical evidence that they cause cystic fibrosis. To address this gap, we collected both genotype and phenotype data for 39,696 cystic fibrosis patients in registries and clinics in North America and Europe. Among these patients, 159 CFTR variants had an allele frequency of ≥0.01%. These variants were evaluated for both clinical severity and functional consequence with 127 (80%) meeting both clinical and functional criteria consistent with disease. Assessment of disease penetrance in 2,188 fathers of cystic fibrosis patients enabled assignment of 12 of the remaining 32 variants as neutral while the other 20 variants remained indeterminate. This study illustrates that sourcing data directly from well-phenotyped subjects can address the gap in our ability to interpret clinically-relevant genomic variation.

General olfactory sensitivity database (GOSdb): candidate genes and their genomic variations

Genetic variations in olfactory receptors likely contribute to the diversity of odorant-specific sensitivity phenotypes. Our working hypothesis is that genetic variations in auxiliary olfactory genes, including those mediating transduction and sensory neuronal development, may constitute the genetic basis for general olfactory sensitivity (GOS) and congenital general anosmia (CGA). We thus performed a systematic exploration for auxiliary olfactory genes and their documented variation. This included a literature survey, seeking relevant functional in vitro studies, mouse gene knockouts and human disorders with olfactory phenotypes, as well as data mining in published transcriptome and proteome data for genes expressed in olfactory tissues. In addition, we performed next-generation transcriptome sequencing (RNA-seq) of human olfactory epithelium and mouse olfactory epithelium and bulb, so as to identify sensory-enriched transcripts. Employing a global score system based on attributes of the 11 data sources utilized, we identified a list of 1,680 candidate auxiliary olfactory genes, of which 450 are shortlisted as having higher probability of a functional role. For the top-scoring 136 genes, we identified genomic variants (probably damaging single nucleotide polymorphisms, indels, and copy number deletions) gleaned from public variation repositories. This database of genes and their variants should assist in rationalizing the great interindividual variation in human overall olfactory sensitivity (http://genome.weizmann.ac.il/GOSdb).

The curation of genetic variants: difficulties and possible solutions

The curation of genetic variants from biomedical articles is required for various clinical and research purposes. Nowadays, establishment of variant databases that include overall information about variants is becoming quite popular. These databases have immense utility, serving as a user-friendly information storehouse of variants for information seekers. While manual curation is the gold standard method for curation of variants, it can turn out to be time-consuming on a large scale thus necessitating the need for automation. Curation of variants described in biomedical literature may not be straightforward mainly due to various nomenclature and expression issues. Though current trends in paper writing on variants is inclined to the standard nomenclature such that variants can easily be retrieved, we have a massive store of variants in the literature that are present as non-standard names and the online search engines that are predominantly used may not be capable of finding them. For effective curation of variants, knowledge about the overall process of curation, nature and types of difficulties in curation, and ways to tackle the difficulties during the task are crucial. Only by effective curation, can variants be correctly interpreted. This paper presents the process and difficulties of curation of genetic variants with possible solutions and suggestions from our work experience in the field including literature support. The paper also highlights aspects of interpretation of genetic variants and the importance of writing papers on variants following standard and retrievable methods.

VarioML framework for comprehensive variation data representation and exchange

BACKGROUND

Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement.

RESULTS

The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components.

CONCLUSIONS

VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

Expanding the MTM1 mutational spectrum: novel variants including the first multi-exonic duplication and development of a locus-specific database

Myotubular myopathy (MIM#310400), the X-linked form of Centronuclear myopathy (CNM) is mainly characterized by neonatal hypotonia and inability to maintain unassisted respiration. The MTM1 gene, responsible for this disease, encodes myotubularin - a lipidic phosphatase involved in vesicle trafficking regulation and maturation. Recently, it was shown that myotubularin interacts with desmin, being a major regulator of intermediate filaments. We report the development of a locus-specific database for MTM1 using the Leiden Open Variation database software (http://www.lovd.nl/MTM1), with data collated for 474 mutations identified in 472 patients (by June 2012). Among the entries are a total of 25 new mutations, including a large deletion encompassing introns 2-15. During database implementation it was noticed that no large duplications had been reported. We tested a group of eight uncharacterized CNM patients for this specific type of mutation, by multiple ligation-dependent probe amplification (MLPA) analysis. A large duplication spanning exons 1-5 was identified in a boy with a mild phenotype, with results pointing toward possible somatic mosaicism. Further characterization revealed that this duplication causes an in-frame deletion at the mRNA level (r.343_444del). Results obtained with a next generation sequencing approach suggested that the duplication extends into the neighboring MAMLD1 gene and subsequent cDNA analysis detected the presence of a MTM1/MAMLD1 fusion transcript. A complex rearrangement involving the duplication of exon 10 has since been reported, with detection also enabled by MLPA analysis. It is thus conceivable that large duplications in MTM1 may account for a number of CNM cases that have remained genetically unresolved.

Human Variome Project country nodes: documenting genetic information within a country

The Human Variome Project (http://www.humanvariomeproject.org) is an international effort aiming to systematically collect and share information on all human genetic variation. The two main pillars of this effort are gene/disease-specific databases and a network of Human Variome Project Country Nodes. The latter are nationwide efforts to document the genomic variation reported within a specific population. The development and successful operation of the Human Variome Project Country Nodes are of utmost importance to the success of Human Variome Project's aims and goals because they not only allow the genetic burden of disease to be quantified in different countries, but also provide diagnosticians and researchers access to an up-to-date resource that will assist them in their daily clinical practice and biomedical research, respectively. Here, we report the discussions and recommendations that resulted from the inaugural meeting of the International Confederation of Countries Advisory Council, held on 12th December 2011, during the 2011 Human Variome Project Beijing Meeting. We discuss the steps necessary to maximize the impact of the Country Node effort for developing regional and country-specific clinical genetics resources and summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects.