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 Mutation- Taster’s pathogenicity predictions with a phenotypebased 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

AutozygosityMapper: Identification of disease-mutations in consanguineous families

With the shift from SNP arrays to high-throughput sequencing, most researchers studying diseases in consanguineous families do not rely on linkage analysis any longer, but simply search for deleterious variants which are homozygous in all patients. AutozygosityMapper allows the fast and convenient identification of disease mutations in patients from consanguineous pedigrees by focussing on homozygous segments shared by all patients. Users can upload multi-sample VCF files, including WGS data, without any pre-processing. Genome-wide runs of homozygosity and the underlying genotypes are presented in graphical interfaces. AutozygosityMapper extends the functions of its predecessor. HomozygosityMapper, to the search for autozygous regions, in which all patients share the same homozygous genotype. We provide export of VCF files containing only the variants found in homozygous regions, this usually reduces the number of variants by two orders of magnitude. These regions can also directly be analysed with our disease mutation identification tool MutationDistiller. The application comes with simple and intuitive graphical interfaces for data upload, analysis, and results. We kept the structure of HomozygosityMapper so that previous users will find it easy to switch. With AutozygosityMapper, we provide a fast web-based way to identify disease mutations in consanguineous families. AutozygosityMapper is freely available at https://www.genecascade. org/AutozygosityMapper/

VarFish: comprehensive DNA variant analysis for diagnostics and research

VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of DNA variant data with a focus on rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Variants passing the filter are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows users to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software's extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g. after update of genotype or phenotype databases

Molecular mechanism of CHRDL1-mediated X-linked megalocornea in humans and in Xenopus model

Chordin-Like 1 (CHRDL1) mutations cause non-syndromic X-linked megalocornea (XMC) characterized by enlarged anterior eye segments. Mosaic corneal degeneration, presenile cataract and secondary glaucoma are associated with XMC. Beside that CHRDL1 encodes Ventroptin, a secreted bone morphogenetic protein (BMP) antagonist, the molecular mechanism of XMC is not well understood yet. In a family with broad phenotypic variability of XMC, we identified the novel CHRDL1 frameshift mutation c.807_808delTC [p.H270Wfs*22] presumably causing CHRDL1 loss of function. Using Xenopus laevis as model organism, we demonstrate that chrdl1 is specifically expressed in the ocular tissue at late developmental stages. The chrdl1 knockdown directly resembles the human XMC phenotype and confirms CHRDL1 deficiency to cause XMC. Interestingly, secondary to this bmp4 is down-regulated in the Xenopus eyes. Moreover, phospho-SMAD1/5 is altered and BMP receptor 1A is reduced in a XMC patient. Together, we classify these observations as negative-feedback regulation due to the deficient BMP antagonism in XMC. As CHRDL1 is preferentially expressed in the limbal stem cell niche of adult human cornea, we assume that CHRDL1 plays a key role in cornea homeostasis. In conclusion, we provide novel insights into the molecular mechanism of XMC as well as into the specific role of CHRDL1 during cornea organogenesis, among others by the establishment of the first XMC in vivo model. We show that unravelling monogenic cornea disorders like XMC—with presumably disturbed cornea growth and differentiation—contribute to the identification of potential limbal stem cell niche factors that are promising targets for regenerative therapies of corneal injurie

Expanding the clinical and molecular spectrum of ATP6V1A related metabolic cutis laxa.

Several inborn errors of metabolism show cutis laxa as a highly recognizable feature. One group of these metabolic cutis laxa conditions is autosomal recessive cutis laxa type 2 caused by defects in v-ATPase components or the mitochondrial proline cycle. Besides cutis laxa, muscular hypotonia and cardiac abnormalities are hallmarks of autosomal recessive cutis laxa type 2D (ARCL2D) due to pathogenic variants in ATP6V1A encoding subunit A of the v-ATPase. Here, we report on three affected individuals from two families with ARCL2D in whom we performed whole exome and Sanger sequencing. We performed functional studies in fibroblasts from one individual, summarized all known probands' clinical, molecular, and biochemical features and compared them, also to other metabolic forms of cutis laxa. We identified novel missense and the first nonsense variant strongly affecting ATP6V1A expression. All six ARCL2D affected individuals show equally severe cutis laxa and dysmorphism at birth. While for one no information was available, two died in infancy and three are now adolescents with mild or absent intellectual disability. Muscular weakness, ptosis, contractures, and elevated muscle enzymes indicated a persistent myopathy. In cellular studies, a fragmented Golgi compartment, a delayed Brefeldin A-induced retrograde transport and glycosylation abnormalities were present in fibroblasts from two individuals. This is the second and confirmatory report on pathogenic variants in ATP6V1A as the cause of this extremely rare condition and the first to describe a nonsense allele. Our data highlight the tremendous clinical variability of ATP6V1A related phenotypes even within the same family

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise

Motivation: While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time such laboratories have accumulated large data sets and thus have the need to identify copy number variants on their data to close the diagnostic gap. Results: In this manuscript we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign data sets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world data sets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity. Availability: The software is available for free under a permissible license at {{https://github.com/bihealth/clear-cnv}}. Supplementary Information: Supplementary data are available at Bioinformatics online

Autosomal recessive cutis laxa type IIIA: Report of a patient with severe phenotype and review of the literature

Autosomal recessive cutis laxa type IIIA is a very rare genetic condition, caused by pathogenic variants in ALDH18A1, encoding delta-1-pyrroline-5-carboxylate synthase (P5CS). This enzyme catalyzes the reduction of glutamic acid to delta1-pyrroline-5-carboxylate, playing a key role in the de novo biosynthesis of proline, ornithine, and arginine. Autosomal recessive cutis laxa type IIIA is characterized by abundant and wrinkled skin, skeletal anomalies, cataract or corneal clouding and neuro-developmental disorders of variable degree. We report on a patient with autosomal recessive cutis laxa type IIIA, due to a homozygous missense c.1273C > T; p. (Arg425Cys) pathogenic variant in ALDH18A1. The patient presented a severe phenotype with serious urological involvement, peculiar cerebro-vascular abnormalities and neurodevelopmental compromise. This description contributes to better characterize the phenotypic spectrum associated with ALDH18A1 pathogenic variants, confirming the systemic involvement as a typical feature of autosomal recessive cutis laxa type IIIA