MutationTaster2021.

Here we present an update to MutationTaster, our DNA variant effect prediction tool. The new version uses a different prediction model and attains higher accuracy than its predecessor, especially for rare benign variants. In addition, we have integrated many sources of data that only became available after the last release (such as gnomAD and ExAC pLI scores) and changed the splice site prediction model. To more easily assess the relevance of detected known disease mutations to the clinical phenotype of the patient, MutationTaster now provides information on the diseases they cause. Further changes represent a major overhaul of the interfaces to increase user-friendliness whilst many changes under the hood have been designed to accelerate the processing of uploaded VCF files. We also offer an API for the rapid automated query of smaller numbers of variants from within other software. MutationTaster2021 integrates our disease mutation search engine, MutationDistiller, to prioritise variants from VCF files using the patient's clinical phenotype. The novel version is available at https://www.genecascade.org/MutationTaster2021/. This website is free and open to all users and there is no login requirement.

Public data sources for regulatory genomic features.

High-throughput technologies have led to a continuously growing amount of information about regulatory features in the genome. A wealth of data generated by large international research consortia is available from online databases. Disease-driven studies provide details on specific DNA elements or epigenetic modifications regulating gene expression in specific cellular and developmental contexts, but these results are usually only published in scientific articles. All this information can be helpful in interpreting variants in the regulatory genome. This review describes a selection of high-profile data sources providing information on the non-coding genome, as well as pitfalls and techniques to search and capture information from the literature.

Novel sequencing technologies and bioinformatic tools for deciphering the non-coding genome.

High-throughput sequencing techniques have significantly increased the molecular diagnosis rate for patients with monogenic disorders. This is primarily due to a substantially increased identification rate of disease mutations in the coding sequence, primarily SNVs and indels. Further progress is hampered by difficulties in the detection of structural variants and the interpretation of variants outside the coding sequence. In this review, we provide an overview about how novel sequencing techniques and state-of-the-art algorithms can be used to discover small and structural variants across the whole genome and introduce bioinformatic tools for the prediction of effects variants may have in the non-coding part of the genome.

A new homozygous HERC1 gain-of-function variant in MDFPMR syndrome leads to mTORC1 hyperactivation and reduced autophagy during cell catabolism.

The giant 532 kDa HERC1 protein is a ubiquitin ligase that interacts with tuberous sclerosis complex subunit 2 (TSC2), a negative upstream regulator of the mammalian target of rapamycin complex 1 (mTORC1). TSC2 regulates anabolic cell growth through its influence on protein synthesis, cell growth, proliferation, autophagy, and differentiation. TSC subunit 1 (TSC1) stabilizes TSC2 by inhibiting the interaction between TSC2 and HERC1, forming a TSC1-TSC2 complex that negatively regulates mTORC1. HERC1-TSC2 interaction destabilizes and degrades TSC2. Recessive mutations in HERC1 have been reported in patients with intellectual disability. Some patients exhibit epilepsy, macrocephaly, somatic overgrowth, and dysmorphic facial features as well. Here we describe two sisters from a consanguineous marriage with a novel homozygous missense variant in the C-terminal HECT domain of HERC1 [chr15:g63,907,989C>G GRCh37.p11 | c.14,072G>C NM_003922 | p.(Arg4,691Pro)]. Symptoms compris global developmental delay, macrocephaly, somatic overgrowth, intellectual disability, seizures, schizoaffective disorder, and pyramidal tract signs. We functionally assessed the HERC1 mutation by investigation of patient and control fibroblasts under normal and nutrient starving conditions. During catabolic state, mTORC1 activity remained high in patient fibroblasts, which stands in stark contrast to its downregulation in controls. This was corroborated by an abnormally high phosphorylation of S6K1-kinase, a direct downstream target of mTORC1, in patients. Moreover, autophagy, usually enhanced in catabolic states, was down-regulated in patient fibroblasts. These data confirm that the missense variant found in both patients results in a gain-of-function for the mutant HERC1 protein.

MutationDistiller: user-driven identification of pathogenic DNA variants.

MutationDistiller is a freely available online tool for user-driven analyses of Whole Exome Sequencing data. It offers a user-friendly interface aimed at clinicians and researchers, who are not necessarily bioinformaticians. MutationDistiller combines MutationTaster's pathogenicity predictions with a phenotype-based approach. Phenotypic information is not limited to symptoms included in the Human Phenotype Ontology (HPO), but may also comprise clinical diagnoses and the suspected mode of inheritance. The search can be restricted to lists of candidate genes (e.g. virtual gene panels) and by tissue-specific gene expression. The inclusion of GeneOntology (GO) and metabolic pathways facilitates the discovery of hitherto unknown disease genes. In a novel approach, we trained MutationDistiller's HPO-based prioritization on authentic genotype-phenotype sets obtained from ClinVar and found it to match or outcompete current prioritization tools in terms of accuracy. In the output, the program provides a list of potential disease mutations ordered by the likelihood of the affected genes to cause the phenotype. MutationDistiller provides links to gene-related information from various resources. It has been extensively tested by clinicians and their suggestions have been valued in many iterative cycles of revisions. The tool, a comprehensive documentation and examples are freely available at https://www.mutationdistiller.org/.

RegulationSpotter: annotation and interpretation of extratranscriptic DNA variants.

RegulationSpotter is a web-based tool for the user-friendly annotation and interpretation of DNA variants located outside of protein-coding transcripts (extratranscriptic variants). It is designed for clinicians and researchers who wish to assess the potential impact of the considerable number of non-coding variants found in Whole Genome Sequencing runs. It annotates individual variants with underlying regulatory features in an intuitive way by assessing over 100 genome-wide annotations. Additionally, it calculates a score, which reflects the regulatory potential of the variant region. Its dichotomous classifications, 'functional' or 'non-functional', and a human-readable presentation of the underlying evidence allow a biologically meaningful interpretation of the score. The output shows key aspects of every variant and allows rapid access to more detailed information about its possible role in gene regulation. RegulationSpotter can either analyse single variants or complete VCF files. Variants located within protein-coding transcripts are automatically assessed by MutationTaster as well as by RegulationSpotter to account for possible intragenic regulatory effects. RegulationSpotter offers the possibility of using phenotypic data to focus on known disease genes or genomic elements interacting with them. RegulationSpotter is freely available at https://www.regulationspotter.org.

Recessive mutation in EXOSC3 associates with mitochondrial dysfunction and pontocerebellar hypoplasia.

Recessive mutations in EXOSC3, encoding a subunit of the human RNA exosome complex, cause pontocerebellar hypoplasia type 1b (PCH1B). We report a boy with severe muscular hypotonia, psychomotor retardation, progressive microcephaly, and cerebellar atrophy. Biochemical abnormalities comprised mitochondrial complex I and pyruvate dehydrogenase complex (PDHc) deficiency. Whole exome sequencing uncovered a known EXOSC3 mutation p.(D132A) as the underlying cause. In patient fibroblasts, a large portion of the EXOSC3 protein was trapped in the cytosol. MtDNA copy numbers in muscle were reduced to 35%, but mutations in the mtDNA and in nuclear mitochondrial genes were ruled out. RNA-Seq of patient muscle showed highly increased mRNA copy numbers, especially for genes encoding structural subunits of OXPHOS complexes I, III, and IV, possibly due to reduced degradation by a dysfunctional exosome complex. This is the first case of mitochondrial dysfunction associated with an EXOSC3 mutation, which expands the phenotypic spectrum of PCH1B. We discuss the links between exosome and mitochondrial dysfunction.

A systematic, large-scale comparison of transcription factor binding site models.

BACKGROUND: The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified "real" in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. RESULTS: While the area-under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. CONCLUSIONS: Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM ( http:/mutationtaster.charite.de/ePOSSUM/ ) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites.

CNVinspector: a web-based tool for the interactive evaluation of copy number variations in single patients and in cohorts.

OBJECTIVES: Many genetic disorders are caused by copy number variations (CNVs) in the human genome. However, the large number of benign CNV polymorphisms makes it difficult to delineate causative variants for a certain disease phenotype. Hence, we set out to create software that accumulates and visualises locus-specific knowledge and enables clinicians to study their own CNVs in the context of known polymorphisms and disease variants. METHODS: CNV data from healthy cohorts (Database of Genomic Variants) and from disease-related databases (DECIPHER) were integrated into a joint resource. Data are presented in an interactive web-based application that allows inspection, evaluation and filtering of CNVs in single individuals or in entire cohorts. RESULTS: CNVinspector provides simple interfaces to upload CNV data, compare them with own or published control data and visualise the results in graphical interfaces. Beyond choosing control data from different public studies, platforms and methods, dedicated filter options allow the detection of CNVs that are either enriched in patients or depleted in controls. Alternatively, a search can be restricted to those CNVs that appear in individuals of similar clinical phenotype. For each gene of interest within a CNV, we provide a link to NCBI, ENSEMBL and the GeneDistiller search engine to browse for potential disease-associated genes. CONCLUSIONS: With its user-friendly handling, the integration of control data and the filtering options, CNVinspector will facilitate the daily work of clinical geneticists and accelerate the delineation of new syndromes and gene functions. CNVinspector is freely accessible under http://www.cnvinspector.org.

Systematic comparison of three methods for fragmentation of long-range PCR products for next generation sequencing.

Next Generation Sequencing (NGS) technologies are gaining importance in the routine clinical diagnostic setting. It is thus desirable to simplify the workflow for high-throughput diagnostics. Fragmentation of DNA is a crucial step for preparation of template libraries and various methods are currently known. Here we evaluated the performance of nebulization, sonication and random enzymatic digestion of long-range PCR products on the results of NGS. All three methods produced high-quality sequencing libraries for the 454 platform. However, if long-range PCR products of different length were pooled equimolarly, sequence coverage drastically dropped for fragments below 3,000 bp. All three methods performed equally well with regard to overall sequence quality (PHRED) and read length. Enzymatic fragmentation showed highest consistency between three library preparations but performed slightly worse than sonication and nebulization with regard to insertions/deletions in the raw sequence reads. After filtering for homopolymer errors, enzymatic fragmentation performed best if compared to the results of classic Sanger sequencing. As the overall performance of all three methods was equal with only minor differences, a fragmentation method can be chosen solely according to lab facilities, feasibility and experimental design.

GeneDistiller--distilling candidate genes from linkage intervals.

BACKGROUND: Linkage studies often yield intervals containing several hundred positional candidate genes. Different manual or automatic approaches exist for the determination of the gene most likely to cause the disease. While the manual search is very flexible and takes advantage of the researchers' background knowledge and intuition, it may be very cumbersome to collect and study the relevant data. Automatic solutions on the other hand usually focus on certain models, remain "black boxes" and do not offer the same degree of flexibility. METHODOLOGY: We have developed a web-based application that combines the advantages of both approaches. Information from various data sources such as gene-phenotype associations, gene expression patterns and protein-protein interactions was integrated into a central database. Researchers can select which information for the genes within a candidate interval or for single genes shall be displayed. Genes can also interactively be filtered, sorted and prioritised according to criteria derived from the background knowledge and preconception of the disease under scrutiny. CONCLUSIONS: GeneDistiller provides knowledge-driven, fully interactive and intuitive access to multiple data sources. It displays maximum relevant information, while saving the user from drowning in the flood of data. A typical query takes less than two seconds, thus allowing an interactive and explorative approach to the hunt for the candidate gene. ACCESS: GeneDistiller can be freely accessed at http://www.genedistiller.org.