Jannovar: a java library for exome annotation

Next-generation phenotyping integrated in a national framework for patients with ultrarare disorders improves genetic diagnostics and yields new molecular findings

Individuals with ultrarare disorders pose a structural challenge for healthcare systems since expert clinical knowledge is required to establish diagnoses. In TRANSLATE NAMSE, a 3-year prospective study, we evaluated a novel diagnostic concept based on multidisciplinary expertise in Germany. Here we present the systematic investigation of the phenotypic and molecular genetic data of 1,577 patients who had undergone exome sequencing and were partially analyzed with next-generation phenotyping approaches. Molecular genetic diagnoses were established in 32% of the patients totaling 370 distinct molecular genetic causes, most with prevalence below 1:50,000. During the diagnostic process, 34 novel and 23 candidate genotype-phenotype associations were identified, mainly in individuals with neurodevelopmental disorders. Sequencing data of the subcohort that consented to computer-assisted analysis of their facial images with GestaltMatcher could be prioritized more efficiently compared with approaches based solely on clinical features and molecular scores. Our study demonstrates the synergy of using next-generation sequencing and phenotyping for diagnosing ultrarare diseases in routine healthcare and discovering novel etiologies by multidisciplinary teams.

FANCM Gene Variants in a Male Diagnosed with Sertoli Cell-Only Syndrome and Diffuse Astrocytoma

Azoospermia is a form of male infertility characterized by a complete lack of spermatozoa in the ejaculate. Sertoli cell-only syndrome (SCOS) is the most severe form of azoospermia, where no germ cells are found in the tubules. Recently, FANCM gene variants were reported as novel genetic causes of spermatogenic failure. At the same time, FANCM variants are known to be associated with cancer predisposition. We performed whole-exome sequencing on a male patient diagnosed with SCOS and a healthy father. Two compound heterozygous missense mutations in the FANCM gene were found in the patient, both being inherited from his parents. After the infertility assessment, the patient was diagnosed with diffuse astrocytoma. Immunohistochemical analyses in the testicular and tumor tissues of the patient and adequate controls showed, for the first time, not only the existence of a cytoplasmic and not nuclear pattern of FANCM in astrocytoma but also in non-mitotic neurons. In the testicular tissue of the SCOS patient, cytoplasmic anti-FANCM staining intensity appeared lower than in the control. Our case report raises a novel possibility that the infertile carriers of FANCM gene missense variants could also be prone to cancer development.

Loss-of-function variants affecting the STAGA complex component SUPT7L cause a developmental disorder with generalized lipodystrophy

Generalized lipodystrophy is a feature of various hereditary disorders, often leading to a progeroid appearance. In the present study we identified a missense and a frameshift variant in a compound heterozygous state in SUPT7L in a boy with intrauterine growth retardation, generalized lipodystrophy, and additional progeroid features. SUPT7L encodes a component of the transcriptional coactivator complex STAGA. By transcriptome sequencing, we showed the predicted missense variant to cause aberrant splicing, leading to exon truncation and thereby to a complete absence of SUPT7L in dermal fibroblasts. In addition, we found altered expression of genes encoding DNA repair pathway components. This pathway was further investigated and an increased rate of DNA damage was detected in proband-derived fibroblasts and genome-edited HeLa cells. Finally, we performed transient overexpression of wildtype SUPT7L in both cellular systems, which normalizes the number of DNA damage events. Our findings suggest SUPT7L as a novel disease gene and underline the link between genome instability and progeroid phenotypes.

A novel variant in the FLNB gene associated with spondylocarpotarsal synostosis syndrome

OBJECTIVES

Genetic disorders involved in skeleton system arise due to the disturbance in skeletal development, growth and homeostasis. Filamin B is an actin binding protein which is large dimeric protein which cross link actin cytoskeleton filaments into dynamic structure. A single nucleotide changes in the FLNB gene causes spondylocarpotarsal synostosis syndrome, a rare bone disorder due to which the fusion of carpels and tarsals synostosis occurred along with fused vertebrae. In the current study we investigated a family residing in north-western areas of Pakistan.

METHODS

The whole exome sequencing of proband was performed followed by Sanger sequencing of all family members of the subject to validate the variant segregation within the family. Bioinformatics tools were utilized to assess the pathogenicity of the variant.

RESULTS

Whole Exome Sequencing revealed a novel variant (NM_001457: c.209C>T and p.Pro70Leu) in the FLNB gene which was homozygous missense mutation in the FLNB gene. The variant was further validated and visualized by Sanger sequencing and protein structure studies respectively as mentioned before.

CONCLUSIONS

The findings have highlighted the importance of the molecular diagnosis in SCT (spondylocarpotarsal synostosis syndrome) for genetic risk counselling in consanguineous families.

MVAR: A Mouse Variation Registry

The Mouse Variation Registry (MVAR) resource is a scalable registry of mouse single nucleotide variants and small indels and variant annotation. The resource accepts data in standard Variant Call Format (VCF) and assesses the uniqueness of the submitted variants via a canonicalization process. Novel variants are assigned a unique, persistent MVAR identifier; variants that are equivalent to an existing variant in the resource are associated with the existing identifier. Annotations for variant type, molecular consequence, impact, and genomic region in the context of specific transcripts and protein sequences are generated using Ensembl's Variant Effect Predictor (VEP) and Jannovar. Access to the data and annotations in MVAR are supported via an Application Programming Interface (API) and web application. Researchers can search the resource by gene symbol, genomic region, variant (expressed in Human Genome Variation Society syntax), refSNP identifiers, or MVAR identifiers. Tabular search results can be filtered by variant annotations (variant type, molecular consequence, impact, variant region) and viewed according to variant distribution across mouse strains. The registry currently comprises more than 99 million canonical single nucleotide variants for 581 strains of mice. MVAR is accessible from https://mvar.jax.org.

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis

Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait-variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

Pancreatic cancer acquires resistance to MAPK pathway inhibition by clonal expansion and adaptive DNA hypermethylation

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis. It is marked by extraordinary resistance to conventional therapies including chemotherapy and radiation, as well as to essentially all targeted therapies evaluated so far. More than 90% of PDAC cases harbor an activating KRAS mutation. As the most common KRAS variants in PDAC remain undruggable so far, it seemed promising to inhibit a downstream target in the MAPK pathway such as MEK1/2, but up to now preclinical and clinical evaluation of MEK inhibitors (MEKi) failed due to inherent and acquired resistance mechanisms. To gain insights into molecular changes during the formation of resistance to oncogenic MAPK pathway inhibition, we utilized short-term passaged primary tumor cells from ten PDACs of genetically engineered mice. We followed gain and loss of resistance upon MEKi exposure and withdrawal by longitudinal integrative analysis of whole genome sequencing, whole genome bisulfite sequencing, RNA-sequencing and mass spectrometry data.

RESULTS

We found that resistant cell populations under increasing MEKi treatment evolved by the expansion of a single clone but were not a direct consequence of known resistance-conferring mutations. Rather, resistant cells showed adaptive DNA hypermethylation of 209 and hypomethylation of 8 genomic sites, most of which overlap with regulatory elements known to be active in murine PDAC cells. Both DNA methylation changes and MEKi resistance were transient and reversible upon drug withdrawal. Furthermore, MEKi resistance could be reversed by DNA methyltransferase inhibition with remarkable sensitivity exclusively in the resistant cells.

CONCLUSION

Overall, the concept of acquired therapy resistance as a result of the expansion of a single cell clone with epigenetic plasticity sheds light on genetic, epigenetic and phenotypic patterns during evolvement of treatment resistance in a tumor with high adaptive capabilities and provides potential for reversion through epigenetic targeting.

GenomeMUSter mouse genetic variation service enables multi-trait, multi-population data integration and analyses

Hundreds of inbred laboratory mouse strains and intercross populations have been used to functionalize genetic variants that contribute to disease. Thousands of disease relevant traits have been characterized in mice and made publicly available. New strains and populations including the Collaborative Cross, expanded BXD and inbred wild-derived strains add to set of complex disease mouse models, genetic mapping resources and sensitized backgrounds against which to evaluate engineered mutations. The genome sequences of many inbred strains, along with dense genotypes from others could allow integrated analysis of trait - variant associations across populations, but these analyses are not feasible due to the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense data resource by harmonizing multiple variant datasets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extensible to other model organism species. The result is a web- and programmatically-accessible data service called GenomeMUSter ( https://muster.jax.org ), comprising allelic data covering 657 strains at 106.8M segregating sites. Interoperation with phenotype databases, analytic tools and other resources enable a wealth of applications including multi-trait, multi-population meta-analysis. We demonstrate this in a cross-species comparison of the meta-analysis of Type 2 Diabetes and of substance use disorders, resulting in the more specific characterization of the role of human variant effects in light of mouse phenotype data. Other applications include refinement of mapped loci and prioritization of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease.

TREX1 p.A129fs and p.Y305C variants in a large multi-ethnic cohort of CADASIL-like unrelated patients

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and retinal vasculopathy with cerebral leukodystrophy and systemic manifestations (RVCL-S) are the most common forms of rare monogenic early-onset cerebral small vessel disease and share clinical, and, to different extents, neuroradiological and neuropathological features. However, whether CADASIL and RVCL-S overlapping phenotype may be explained by shared genetic risk or causative factors such as TREX1 coding variants remains poorly understood. To investigate this intriguing hypothesis, we used exome sequencing to screen TREX1 protein-coding variability in a large multi-ethnic cohort of 180 early-onset independent familial and apparently sporadic CADASIL-like Caucasian patients from the USA, Portugal, Finland, Serbia and Turkey. We report 2 very rare and likely pathogenic TREX1 mutations: a loss of function mutation (p.Ala129fs) clustering in the catalytic domain, in an apparently sporadic 46-year-old patient from the USA and a missense mutation (p.Tyr305Cys) in the well conserved C-terminal region, in a 57-year-old patient with positive family history from Serbia. In concert with recent findings, our study expands the clinical spectrum of diseases associated with TREX1 mutations.

A novel case of two siblings harbouring homozygous variant in the NEUROG1 gene with autism as an additional phenotype: a case report

INTRODUCTION

NEUROG1 gene is yet to be associated with a set of human phenotypes in the OMIM database. Three cases have previously been diagnosed with cranial dysinnervation due to biallelic variants in the NEUROG1 gene. This is the fourth and a novel report of a sibling pair harboring a homozygous variant in the NEUROG1 gene with autism as an additional phenotype. A brief review of the literature in conjunction with a genotype-phenotype correlation has been described. A potential hypothesis for the presence of the autistic phenotype in the present case has also been elucidated.

CASE PRESENTATION

A female aged 6 years and 9 months born to endogamous and phenotypically healthy parents was diagnosed with global developmental delay, autism spectrum disorder, hearing loss, corneal opacity and no eye blinking. Her MRI of the brain revealed mild peritrigonal white matter hyperintensity, and MRI and CT scan of the temporal bones showed abnormal cranial nerves. The proband's younger sister, aged 4-years, was similarly affected. Whole exome sequencing was performed in the proband, which revealed a novel homozygous, likely pathogenic, truncating frameshift variant, c.228_231dup (p.Thr78ProfsTer122) in exon 1 of the NEUROG1 gene (ENST00000314744.4). Segregation analysis by Sanger sequencing showed the proband and her younger sister to be homozygotes and their parents to be heterozygous carriers.

CONCLUSION

This is the fourth report across the globe with a variant identified in the NEUROG1 gene to be associated with cranial dysinnervation phenotype. An additional phenotype of autism in two female siblings was a novel observation. We provide a hypothetical framework which could explain the pleiotropic effect of a dysfunctional NEUROG1 protein leading to autism and posit it as a candidate for diagnosis of autism spectrum disorder with congenital cranial dysinnervation disorder.

The Regulatory Mendelian Mutation score for GRCh38

BACKGROUND

Genome sequencing efforts for individuals with rare Mendelian disease have increased the research focus on the noncoding genome and the clinical need for methods that prioritize potentially disease causal noncoding variants. Some tools for assessment of variant pathogenicity as well as annotations are not available for the current human genome build (GRCh38), for which the adoption in databases, software, and pipelines was slow.

RESULTS

Here, we present an updated version of the Regulatory Mendelian Mutation (ReMM) score, retrained on features and variants derived from the GRCh38 genome build. Like its GRCh37 version, it achieves good performance on its highly imbalanced data. To improve accessibility and provide users with a toolbox to score their variant files and look up scores in the genome, we developed a website and API for easy score lookup.

CONCLUSIONS

Scores of the GRCh38 genome build are highly correlated to the prior release with a performance increase due to the better coverage of features. For prioritization of noncoding mutations in imbalanced datasets, the ReMM score performed much better than other variation scores. Prescored whole-genome files of GRCh37 and GRCh38 genome builds are cited in the article and the website; UCSC genome browser tracks, and an API are available at https://remm.bihealth.org.

Phenotype-aware prioritisation of rare Mendelian disease variants

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.

"Demystifying non-coding GWAS variants: an overview of computational tools and methods."

Genome-wide association studies (GWAS) have found the majority of disease-associated variants to be non-coding. Major efforts into the charting of the non-coding regulatory landscapes have allowed for the development of tools and methods which aim to aid in the identification of causal variants and their mechanism of action. In this review, we give an overview of current tools and methods for the analysis of non-coding GWAS variants in disease. We provide a workflow that allows for the accumulation of in silico evidence to generate novel hypotheses on mechanisms underlying disease and prioritize targets for follow-up study using non-coding GWAS variants. Lastly, we discuss the need for comprehensive benchmarks and novel tools for the analysis of non-coding variants.

Alternative splicing of BUD13 determines the severity of a developmental disorder with lipodystrophy and progeroid features

PURPOSE

In this study we aimed to identify the molecular genetic cause of a progressive multisystem disease with prominent lipodystrophy.

METHODS

In total, 5 affected individuals were investigated using exome sequencing. Dermal fibroblasts were characterized using RNA sequencing, proteomics, immunoblotting, immunostaining, and electron microscopy. Subcellular localization and rescue studies were performed.

RESULTS

We identified a lipodystrophy phenotype with a typical facial appearance, corneal clouding, achalasia, progressive hearing loss, and variable severity. Although 3 individuals showed stunted growth, intellectual disability, and died within the first decade of life (A1, A2, and A3), 2 are adults with normal intellectual development (A4 and A5). All individuals harbored an identical homozygous nonsense variant affecting the retention and splicing complex component BUD13. The nucleotide substitution caused alternative splicing of BUD13 leading to a stable truncated protein whose expression positively correlated with disease expression and life expectancy. In dermal fibroblasts, we found elevated intron retention, a global reduction of spliceosomal proteins, and nuclei with multiple invaginations, which were more pronounced in A1, A2, and A3. Overexpression of both BUD13 isoforms normalized the nuclear morphology.

CONCLUSION

Our results define a hitherto unknown syndrome and show that the alternative splice product converts a loss-of-function into a hypomorphic allele, thereby probably determining the severity of the disease and the survival of affected individuals.

SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing

Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phenotype data. SvAnna places 87% of deleterious SVs in the top ten ranks. The interpretable prioritizations offered by SvAnna will facilitate the widespread adoption of long-read sequencing in diagnostic genomics. SvAnna is available at https://github.com/TheJacksonLaboratory/SvAnn a .

A rare case of a male child with post-zygotic de novo mosaic variant c.538C > T in MECP2 gene: a case report of Rett syndrome

BACKGROUND

Rett syndrome (RTT) is characterized by a normal perinatal period with a normal head size at birth followed by normal development for the first 6 months of life followed by gradual deceleration of head growth, loss of acquired purposeful hand skills, severe expressive and receptive language impairment, severe intellectual disability and gait and truncal apraxia/ ataxia. It is caused due to mutations in the MECP2 gene and follows an X-linked dominant mode of inheritance. It was observed exclusively in females and was believed to be lethal in males. In contrast to this belief, several males were identified with RTT upon genetic analysis, however, most males expired by the age of 2 years due to neonatal encephalopathy. The ones that survived beyond the age of 2 years, were attributed to the presence of an extra X chromosome (co-occurrence of Klinefelter and RTT) or the ones having mosaic cell lines. Only 11 males with somatic mosaicism are known till date.

CASE PRESENTATION

This case reports an ultra-rare case of a male affected with RTT surviving beyond the age of 2 years due to post-zygotic de novo somatic mosaicism. He was identified with a known pathogenic variant c.538C > T (p.R180*), which to the best of our knowledge is exclusively seen in females and has never been reported in a male before.

CONCLUSION

The present case is the first report of a mosaic male affected with RTT from India. The present report also carried out genotype-phenotype correlations across surviving mosaic males with RTT. We also postulate the effect of variant type, position along the gene and the variant allele fraction in different tissue types to be correlated with disease severity.

Mouse Genome Informatics (MGI): latest news from MGD and GXD

The Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI's mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of the Gene Ontology and Disease Ontology and uses these ontologies as standard terminologies for annotation. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are MGI's two major knowledgebases. Here, we highlight some of the recent changes and enhancements to MGD and GXD that have been implemented in response to changing needs of the biomedical research community and to improve the efficiency of expert curation. MGI can be accessed freely at http://www.informatics.jax.org .

VannoPortal: multiscale functional annotation of human genetic variants for interrogating molecular mechanism of traits and diseases

Interpreting the molecular mechanism of genomic variations and their causal relationship with diseases/traits are important and challenging problems in the human genetic study. To provide comprehensive and context-specific variant annotations for biologists and clinicians, here, by systematically integrating over 4TB genomic/epigenomic profiles and frequently-used annotation databases from various biological domains, we develop a variant annotation database, called VannoPortal. In general, the database has following major features: (i) systematically integrates 40 genome-wide variant annotations and prediction scores regarding allele frequency, linkage disequilibrium, evolutionary signature, disease/trait association, tissue/cell type-specific epigenome, base-wise functional prediction, allelic imbalance and pathogenicity; (ii) equips with our recent novel index system and parallel random-sweep searching algorithms for efficient management of backend databases and information extraction; (iii) greatly expands context-dependent variant annotation to incorporate large-scale epigenomic maps and regulatory profiles (such as EpiMap) across over 33 tissue/cell types; (iv) compiles many genome-scale base-wise prediction scores for regulatory/pathogenic variant classification beyond protein-coding region; (v) enables fast retrieval and direct comparison of functional evidence among linked variants using highly interactive web panel in addition to plain table; (vi) introduces many visualization functions for more efficient identification and interpretation of functional variants in single web page. VannoPortal is freely available at http://mulinlab.org/vportal.

Shared and oppositely regulated transcriptomic signatures in Huntington's disease and brain ischemia confirm known and unveil novel potential neuroprotective genes

Huntington's disease and subcortical vascular dementia display similar dementing features, shaped by different degrees of striatal atrophy, deep white matter degeneration and tau pathology. To investigate the hypothesis that Huntington's disease transcriptomic hallmarks may provide a window into potential protective genes upregulated during brain acute and subacute ischemia, we compared RNA sequencing signatures in the most affected brain areas of 2 widely used experimental mouse models: Huntington's disease, (R6/2, striatum and cortex and Q175, hippocampus) and brain ischemia-subcortical vascular dementia (BCCAS, striatum, cortex and hippocampus). We identified a cluster of 55 shared genes significantly differentially regulated in both models and we screened these in 2 different mouse models of Alzheimer's disease, and 96 early-onset familial and apparently sporadic small vessel ischemic disease patients. Our data support the prevalent role of transcriptional regulation upon genetic coding variability of known neuroprotective genes (Egr2, Fos, Ptgs2, Itga5, Cdkn1a, Gsn, Npas4, Btg2, Cebpb) and provide a list of potential additional ones likely implicated in different dementing disorders and worth further investigation.

PHACTR1 genetic variability is not critical in small vessel ischemic disease patients and PcomA recruitment in C57BL/6J mice

Recently, several genome-wide association studies identified PHACTR1 as key locus for five diverse vascular disorders: coronary artery disease, migraine, fibromuscular dysplasia, cervical artery dissection and hypertension. Although these represent significant risk factors or comorbidities for ischemic stroke, PHACTR1 role in brain small vessel ischemic disease and ischemic stroke most important survival mechanism, such as the recruitment of brain collateral arteries like posterior communicating arteries (PcomAs), remains unknown. Therefore, we applied exome and genome sequencing in a multi-ethnic cohort of 180 early-onset independent familial and apparently sporadic brain small vessel ischemic disease and CADASIL-like Caucasian patients from US, Portugal, Finland, Serbia and Turkey and in 2 C57BL/6J stroke mouse models (bilateral common carotid artery stenosis [BCCAS] and middle cerebral artery occlusion [MCAO]), characterized by different degrees of PcomAs patency. We report 3 very rare coding variants in the small vessel ischemic disease-CADASIL-like cohort (p.Glu198Gln, p.Arg204Gly, p.Val251Leu) and a stop-gain mutation (p.Gln273*) in one MCAO mouse. These coding variants do not cluster in PHACTR1 known pathogenic domains and are not likely to play a critical role in small vessel ischemic disease or brain collateral circulation. We also exclude the possibility that copy number variants (CNVs) or a variant enrichment in Phactr1 may be associated with PcomA recruitment in BCCAS mice or linked to diverse vascular traits (cerebral blood flow pre-surgery, PcomA size, leptomeningeal microcollateral length and junction density during brain hypoperfusion) in C57BL/6J mice, respectively. Genetic variability in PHACTR1 is not likely to be a common susceptibility factor influencing small vessel ischemic disease in patients and PcomA recruitment in C57BL/6J mice. Nonetheless, rare variants in PHACTR1 RPEL domains may influence the stroke outcome and are worth investigating in a larger cohort of small vessel ischemic disease patients, different ischemic stroke subtypes and with functional studies.

Ultrafast and scalable variant annotation and prioritization with big functional genomics data

The advances of large-scale genomics studies have enabled compilation of cell type–specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.

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.

Distinct immune evasion in APOBEC-enriched, HPV-negative HNSCC

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (n = 496) and a validation set (DKTK MASTER cohort, n = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately reanalyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy.

parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants

BACKGROUND

Several prediction problems in computational biology and genomic medicine are characterized by both big data as well as a high imbalance between examples to be learned, whereby positive examples can represent a tiny minority with respect to negative examples. For instance, deleterious or pathogenic variants are overwhelmed by the sea of neutral variants in the non-coding regions of the genome: thus, the prediction of deleterious variants is a challenging, highly imbalanced classification problem, and classical prediction tools fail to detect the rare pathogenic examples among the huge amount of neutral variants or undergo severe restrictions in managing big genomic data.

RESULTS

To overcome these limitations we propose parSMURF, a method that adopts a hyper-ensemble approach and oversampling and undersampling techniques to deal with imbalanced data, and parallel computational techniques to both manage big genomic data and substantially speed up the computation. The synergy between Bayesian optimization techniques and the parallel nature of parSMURF enables efficient and user-friendly automatic tuning of the hyper-parameters of the algorithm, and allows specific learning problems in genomic medicine to be easily fit. Moreover, by using MPI parallel and machine learning ensemble techniques, parSMURF can manage big data by partitioning them across the nodes of a high-performance computing cluster. Results with synthetic data and with single-nucleotide variants associated with Mendelian diseases and with genome-wide association study hits in the non-coding regions of the human genome, involhing millions of examples, show that parSMURF achieves state-of-the-art results and an 80-fold speed-up with respect to the sequential version.

CONCLUSIONS

parSMURF is a parallel machine learning tool that can be trained to learn different genomic problems, and its multiple levels of parallelization and high scalability allow us to efficiently fit problems characterized by big and imbalanced genomic data. The C++ OpenMP multi-core version tailored to a single workstation and the C++ MPI/OpenMP hybrid multi-core and multi-node parSMURF version tailored to a High Performance Computing cluster are both available at https://github.com/AnacletoLAB/parSMURF.

Investigating APOE, APP-Aβ metabolism genes and Alzheimer's disease GWAS hits in brain small vessel ischemic disease

Alzheimer’s disease and small vessel ischemic disease frequently co-exist in the aging brain. However, pathogenic links between these 2 disorders are yet to be identified. Therefore we used Taqman genotyping, exome and RNA sequencing to investigate Alzheimer’s disease known pathogenic variants and pathways: APOE ε4 allele, APP-Aβ metabolism and late-onset Alzheimer’s disease main genome-wide association loci (APOE, BIN1, CD33, MS4A6A, CD2AP, PICALM, CLU, CR1, EPHA1, ABCA7) in 96 early-onset small vessel ischemic disease Caucasian patients and 368 elderly neuropathologically proven controls (HEX database) and in a mouse model of cerebral hypoperfusion. Only a minority of patients (29%) carried APOE ε4 allele. We did not detect any pathogenic mutation in APP, PSEN1 and PSEN2 and report a burden of truncating mutations in APP-Aß degradation genes. The single-variant association test identified 3 common variants with a likely protective effect on small vessel ischemic disease (0.54>OR > 0.32, adj. p-value <0.05) (EPHA1 p.M900V and p.V160A and CD33 p.A14V). Moreover, 5/17 APP-Aß catabolism genes were significantly upregulated (LogFC > 1, adj. p-val<0.05) together with Apoe, Ms4a cluster and Cd33 during brain hypoperfusion and their overexpression correlated with the ischemic lesion size. Finally, the detection of Aβ oligomers in the hypoperfused hippocampus supported the link between brain ischemia and Alzheimer’s disease pathology.

An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data

Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients' sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein-protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients' HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.

Biallelic variants in KYNU cause a multisystemic syndrome with hand hyperphalangism

Catel-Manzke syndrome is characterized by the combination of Pierre Robin sequence and radial deviation, shortening as well as clinodactyly of the index fingers, due to an accessory ossification center. Mutations in TGDS have been identified as one cause of Catel-Manzke syndrome, but cannot be found as causative in every patient with the clinical diagnosis. We performed a chromosome microarray and/or exome sequencing in three patients with hand hyperphalangism, heart defect, short stature, and mild to severe developmental delay, all of whom were initially given a clinical diagnosis of Catel-Manzke syndrome. In one patient, we detected a large deletion of exons 1-8 and the missense variant c.1282C > T (p.Arg428Trp) in KYNU (NM_003937.2), whereas homozygous missense variants in KYNU were found in the other two patients (c.989G > A (p.Arg330Gln) and c.326G > C (p.Trp109Ser)). Plasma and urine metabolomic analysis of two patients indicated a block along the tryptophan catabolic pathway and urine organic acid analysis showed excretion of xanthurenic acid. Biallelic loss-of-function mutations in KYNU were recently described as a cause of NAD deficiency with vertebral, cardiac, renal and limb defects; however, no hand hyperphalangism was described in those patients, and Catel-Manzke syndrome was not discussed as a differential diagnosis. In conclusion, we present unrelated patients identified with biallelic variants in KYNU leading to kynureninase deficiency and xanthurenic aciduria as a very likely cause of their hyperphalangism, heart defect, short stature, and developmental delay. We suggest performance of urine organic acid analysis in patients with suspected Catel-Manzke syndrome, particularly in those with cardiac or vertebral defects or without mutations in TGDS.

Generation and characterization of a mitotane-resistant adrenocortical cell line

Mitotane is the only drug approved for the therapy of adrenocortical carcinoma (ACC). Its clinical use is limited by the occurrence of relapse during therapy. To investigate the underlying mechanisms in vitro, we here generated mitotane-resistant cell lines. After long-term pulsed treatment of HAC-15 human adrenocortical carcinoma cells with 70 µM mitotane, we isolated monoclonal cell populations of treated cells and controls and assessed their respective mitotane sensitivities by MTT assay. We performed exome sequencing and electron microscopy, conducted gene expression microarray analysis and determined intracellular lipid concentrations in the presence and absence of mitotane. Clonal cell lines established after pulsed treatment were resistant to mitotane (IC50 of 102.2 ± 7.3 µM (n = 12) vs 39.4 ± 6.2 µM (n = 6) in controls (biological replicates, mean ± s.d., P = 0.0001)). Unlike nonresistant clones, resistant clones maintained normal mitochondrial and nucleolar morphology during mitotane treatment. Resistant clones largely shared structural and single nucleotide variants, suggesting a common cell of origin. Resistance depended, in part, on extracellular lipoproteins and was associated with alterations in intracellular lipid homeostasis, including levels of free cholesterol, as well as decreased steroid production. By gene expression analysis, resistant cells showed profound alterations in pathways including steroid metabolism and transport, apoptosis, cell growth and Wnt signaling. These studies establish an in vitro model of mitotane resistance in ACC and point to underlying molecular mechanisms. They may enable future studies to overcome resistance in vitro and improve ACC treatment in vivo.

VarSight: prioritizing clinically reported variants with binary classification algorithms

BACKGROUND

When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance.

METHODS

We tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network.

RESULTS

We treated the classifiers as variant prioritization systems and compared them to four variant prioritization algorithms and two single-measure controls. We showed that the trained classifiers outperformed all other tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported pathogenic variants in the top 20.

CONCLUSIONS

We demonstrated how freely available binary classification algorithms can be used to prioritize variants even in the presence of real-world variability. Furthermore, these classifiers outperformed all other tested methods, suggesting that they may be well suited for working with real rare disease patient datasets.

Reflection of neuroblastoma intratumor heterogeneity in the new OHC-NB1 disease model

Accurate modeling of intratumor heterogeneity presents a bottleneck against drug testing. Flexibility in a preclinical platform is also desirable to support assessment of different endpoints. We established the model system, OHC-NB1, from a bone marrow metastasis from a patient diagnosed with MYCN-amplified neuroblastoma and performed whole-exome sequencing on the source metastasis and the different models and passages during model development (monolayer cell line, 3D spheroid culture and subcutaneous xenograft tumors propagated in mice). OHC-NB1 harbors a MYCN amplification in double minutes, 1p deletion, 17q gain and diploid karyotype, which persisted in all models. A total of 80-540 single-nucleotide variants (SNVs) was detected in each sample, and comparisons between the source metastasis and models identified 34 of 80 somatic SNVs to be propagated in the models. Clonal reconstruction using the combined copy number and SNV data revealed marked clonal heterogeneity in the originating metastasis, with four clones being reflected in the model systems. The set of OHC-NB1 models represents 43% of somatic SNVs and 23% of the cellularity in the originating metastasis with varying clonal compositions, indicating that heterogeneity is partially preserved in our model system.

Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts

Background

Although familial clustering of cancers is relatively common, only a small proportion of familial cancer risk can be explained by known cancer predisposition genes.

Methods

In this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, we conducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband (n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available.

Results

Variants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases.

Conclusions

Based on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0808-9) contains supplementary material, which is available to authorized users.

Genetic variants in components of the NALCN-UNC80-UNC79 ion channel complex cause a broad clinical phenotype (NALCN channelopathies)

NALCN is a conserved cation channel, which conducts a permanent sodium leak current and regulates resting membrane potential and neuronal excitability. It is part of a large ion channel complex, the "NALCN channelosome", consisting of multiple proteins including UNC80 and UNC79. The predominant neuronal expression pattern and its function suggest an important role in neuronal function and disease. So far, biallelic NALCN and UNC80 variants have been described in a small number of individuals leading to infantile hypotonia, psychomotor retardation, and characteristic facies 1 (IHPRF1, OMIM 615419) and 2 (IHPRF2, OMIM 616801), respectively. Heterozygous de novo NALCN missense variants in the S5/S6 pore-forming segments lead to congenital contractures of the limbs and face, hypotonia, and developmental delay (CLIFAHDD, OMIM 616266) with some clinical overlap. In this study, we present detailed clinical information of 16 novel individuals with biallelic NALCN variants, 1 individual with a heterozygous de novo NALCN missense variant and an interesting clinical phenotype without contractures, and 12 individuals with biallelic UNC80 variants. We report for the first time a missense NALCN variant located in the predicted S6 pore-forming unit inherited in an autosomal-recessive manner leading to mild IHPRF1. We show evidence of clinical variability, especially among IHPRF1-affected individuals, and discuss differences between the IHPRF1- and IHPRF2 phenotypes. In summary, we provide a comprehensive overview of IHPRF1 and IHPRF2 phenotypes based on the largest cohort of individuals reported so far and provide additional insights into the clinical phenotypes of these neurodevelopmental diseases to help improve counseling of affected families.

Hematopoietic lineage distribution and evolutionary dynamics of clonal hematopoiesis

Clonal hematopoiesis of indeterminate potential (CHIP) occurs in an age-related manner and associates with an increased risk of hematologic cancer, atherosclerotic disease, and shorter overall survival. Little is known about the cell of origin, repartition patterns of clonal mutations within the hematopoietic differentiation tree, and its dynamics under evolutionary pressure. Using targeted sequencing, CHIP was identified in 121 out of 437 elderly individuals (27.7%). Variant allele frequencies (VAFs) of 91 mutations were studied in six peripheral blood cell fractions. VAFs were significantly higher in monocytes, granulocytes, and NK-cells compared to B- or T cells. In all cases with available bone marrow material, mutations could be identified in Lin^-CD34⁺CD38^- HSCs with subsequent expansion to myeloid primed progenitors. In 22 patients with solid cancer receiving (radio-)chemotherapy, longitudinal study of 32 mutations at 121 time points identified relative VAF changes of at least 50% in 13/32 mutations. VAFs of DNMT3A, were stable in 12/13 cases (P < .001). Cancer patients with a clonal mutation other than DNMT3A required more often red blood cell transfusions and dose reductions. Our results provide novel insights into cellular distribution of clonal mutations, their dynamics under chemotherapy, and advocate for systematic analyses for CHIP in cancer patients.

De Novo Mutations in SLC25A24 Cause a Craniosynostosis Syndrome with Hypertrichosis, Progeroid Appearance, and Mitochondrial Dysfunction

Gorlin-Chaudhry-Moss syndrome (GCMS) is a dysmorphic syndrome characterized by coronal craniosynostosis and severe midface hypoplasia, body and facial hypertrichosis, microphthalmia, short stature, and short distal phalanges. Variable lipoatrophy and cutis laxa are the basis for a progeroid appearance. Using exome and genome sequencing, we identified the recurrent de novo mutations c.650G>A (p.Arg217His) and c.649C>T (p.Arg217Cys) in SLC25A24 in five unrelated girls diagnosed with GCMS. Two of the girls had pronounced neonatal progeroid features and were initially diagnosed with Wiedemann-Rautenstrauch syndrome. SLC25A24 encodes a mitochondrial inner membrane ATP-Mg/P_i carrier. In fibroblasts from affected individuals, the mutated SLC25A24 showed normal stability. In contrast to control cells, the probands' cells showed mitochondrial swelling, which was exacerbated upon treatment with hydrogen peroxide (H₂O₂). The same effect was observed after overexpression of the mutant cDNA. Under normal culture conditions, the mitochondrial membrane potential of the probands' fibroblasts was intact, whereas ATP content in the mitochondrial matrix was lower than that in control cells. However, upon H₂O₂ exposure, the membrane potential was significantly elevated in cells harboring the mutated SLC25A24. No reduction of mitochondrial DNA copy number was observed. These findings demonstrate that mitochondrial dysfunction with increased sensitivity to oxidative stress is due to the SLC25A24 mutations. Our results suggest that the SLC25A24 mutations induce a gain of pathological function and link mitochondrial ATP-Mg/P_i transport to the development of skeletal and connective tissue.

CAGI4 SickKids clinical genomes challenge: A pipeline for identifying pathogenic variants

Compared with earlier more restricted sequencing technologies, identification of rare disease variants using whole-genome sequence has the possibility of finding all causative variants, but issues of data quality and an overwhelming level of background variants complicate the analysis. The CAGI4 SickKids clinical genome challenge provided an opportunity to assess the landscape of variants found in a difficult set of 25 unsolved rare disease cases. To address the challenge, we developed a three-stage pipeline, first carefully analyzing data quality, then classifying high-quality gene-specific variants into seven categories, and finally examining each candidate variant for compatibility with the often complex phenotypes of these patients for final prioritization. Variants consistent with the phenotypes were found in 24 out of the 25 cases, and in a number of these, there are prioritized variants in multiple genes. Data quality analysis suggests that some of the selected variants are likely incorrect calls, complicating interpretation. The data providers followed up on three suggested variants with Sanger sequencing, and in one case, a prioritized variant was confirmed as likely causative by the referring physician, providing a diagnosis in a previously intractable case.

The germline variants in DNA repair genes in pediatric medulloblastoma: a challenge for current therapeutic strategies

BACKGROUND

The defects in DNA repair genes are potentially linked to development and response to therapy in medulloblastoma. Therefore the purpose of this study was to establish the spectrum and frequency of germline variants in selected DNA repair genes and their impact on response to chemotherapy in medulloblastoma patients.

METHODS

The following genes were investigated in 102 paediatric patients: MSH2 and RAD50 using targeted gene panel sequencing and NBN variants (p.I171V and p.K219fs*19) by Sanger sequencing. In three patients with presence of rare life-threatening adverse events (AE) and no detected variants in the analyzed genes, whole exome sequencing was performed. Based on combination of molecular and immunohistochemical evaluations tumors were divided into molecular subgroups. Presence of variants was tested for potential association with the occurrence of rare life-threatening AE and other clinical features.

RESULTS

We have identified altogether six new potentially pathogenic variants in MSH2 (p.A733T and p.V606I), RAD50 (p.R1093*), FANCM (p.L694*), ERCC2 (p.R695C) and EXO1 (p.V738L), in addition to two known NBN variants. Five out of twelve patients with defects in either of MSH2, RAD50 and NBN genes suffered from rare life-threatening AE, more frequently than in control group (p = 0.0005). When all detected variants were taken into account, the majority of patients (8 out of 15) suffered from life-threatening toxicity during chemotherapy.

CONCLUSION

Our results, based on the largest systematic study performed in a clinical setting, provide preliminary evidence for a link between defects in DNA repair genes and treatment related toxicity in children with medulloblastoma. The data suggest that patients with DNA repair gene variants could need special vigilance during and after courses of chemotherapy.

[Diagnostics in human genetics : Integration of phenotypic and genomic data]

The development of reliable methods for annotation of clinical phenotypes and algorithms to calculate similarity values for clinical phenotype profiles will be a major challenge for genomic personalized medicine, since combined analysis of phenotypic features and genetic variants can increase diagnostic yield, especially with exome or genome sequencing. The Human Phenotype Ontology project (HPO; www.human-phenotype-ontology.org ) provides an ontology for capturing phenotypic abnormalities in human disease in a precise and comprehensive fashion. The HPO not only enables reliable integration of disease-relevant information from numerous databases, but it also allows for similarity between patients or between patients and disease descriptions to be calculated algorithmically. The HPO thereby represents a solid foundation for differential diagnostic applications as well as for translational research and prioritization of novel disease genes in exome or genome sequencing projects.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

Alternate-locus aware variant calling in whole genome sequencing

Background

The last two human genome assemblies have extended the previous linear golden-path paradigm of the human genome to a graph-like model to better represent regions with a high degree of structural variability. The new model offers opportunities to improve the technical validity of variant calling in whole-genome sequencing (WGS).

Methods

We developed an algorithm that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38 genome assembly, and infers whether a given sample is most likely to contain sequences from the primary assembly, an alternate locus, or their heterozygous combination at each of these 178 regions. We investigate 121 in-house WGS datasets that have been aligned to the GRCh37 and GRCh38 assemblies.

Results

We show that stretches of sequences that are largely but not entirely identical between the primary assembly and an alternate locus can result in multiple variant calls against regions of the primary assembly. In WGS analysis, this results in characteristic and recognizable patterns of variant calls at positions that we term alignable scaffold-discrepant positions (ASDPs). In 121 in-house genomes, on average 51.8±3.8 of the 178 regions were found to correspond best to an alternate locus rather than the primary assembly sequence, and filtering these genomes with our algorithm led to the identification of 7863 variant calls per genome that colocalized with ASDPs. Additionally, we found that 437 of 791 genome-wide association study hits located within one of the regions corresponded to ASDPs.

Conclusions

Our algorithm uses the information contained in the 178 structurally variable regions of the GRCh38 genome assembly to avoid spurious variant calls in cases where samples contain an alternate locus rather than the corresponding segment of the primary assembly. These results suggest the great potential of fully incorporating the resources of graph-like genome assemblies into variant calling, but also underscore the importance of developing computational resources that will allow a full reconstruction of the genotype in personal genomes. Our algorithm is freely available at https://github.com/charite/asdpex.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0383-z) contains supplementary material, which is available to authorized users.

A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease

The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance to discover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as the top candidate in 77% of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Expanding the clinical spectrum of the 'HDAC8-phenotype' - implications for molecular diagnostics, counseling and risk prediction

Cornelia de Lange syndrome (CdLS) is a clinically heterogeneous disorder characterized by typical facial dysmorphism, cognitive impairment and multiple congenital anomalies. Approximately 75% of patients carry a variant in one of the five cohesin-related genes NIPBL, SMC1A, SMC3, RAD21 and HDAC8. Herein we report on the clinical and molecular characterization of 11 patients carrying 10 distinct variants in HDAC8. Given the high number of variants identified so far, we advise sequencing of HDAC8 as an indispensable part of the routine molecular diagnostic for patients with CdLS or CdLS-overlapping features. The phenotype of our patients is very broad, whereas males tend to be more severely affected than females, who instead often present with less canonical CdLS features. The extensive clinical variability observed in the heterozygous females might be at least partially associated with a completely skewed X-inactivation, observed in seven out of eight female patients. Our cohort also includes two affected siblings whose unaffected mother was found to be mosaic for the causative mutation inherited to both affected children. This further supports the urgent need for an integration of highly sensitive sequencing technology to allow an appropriate molecular diagnostic, genetic counseling and risk prediction.

Strategies to improve the performance of rare variant association studies by optimizing the selection of controls

MOTIVATION

When analyzing a case group of patients with ultra-rare disorders the ethnicities are often diverse and the data quality might vary. The population substructure in the case group as well as the heterogeneous data quality can cause substantial inflation of test statistics and result in spurious associations in case-control studies if not properly adjusted for. Existing techniques to correct for confounding effects were especially developed for common variants and are not applicable to rare variants.

RESULTS

We analyzed strategies to select suitable controls for cases that are based on similarity metrics that vary in their weighting schemes. We simulated different disease entities on real exome data and show that a similarity-based selection scheme can help to reduce false positive associations and to optimize the performance of the statistical tests. Especially when data quality as well as ethnicities vary a lot in the case group, a matching approach that puts more weight on rare variants shows the best performance. We reanalyzed collections of unrelated patients with Kabuki make-up syndrome, Hyperphosphatasia with Mental Retardation syndrome and Catel-Manzke syndrome for which the disease genes were recently described. We show that rare variant association tests are more sensitive and specific in identifying the disease gene than intersection filters and should thus be considered as a favorable approach in analyzing even small patient cohorts.

AVAILABILITY AND IMPLEMENTATION

Datasets used in our analysis are available at ftp://ftp.1000genomes.ebi.ac.uk./vol1/ftp/

CONTACT

: peter.krawitz@charite.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Next-generation diagnostics and disease-gene discovery with the Exomiser

Exomiser is an application that prioritizes genes and variants in next-generation sequencing (NGS) projects for novel disease-gene discovery or differential diagnostics of Mendelian disease. Exomiser comprises a suite of algorithms for prioritizing exome sequences using random-walk analysis of protein interaction networks, clinical relevance and cross-species phenotype comparisons, as well as a wide range of other computational filters for variant frequency, predicted pathogenicity and pedigree analysis. In this protocol, we provide a detailed explanation of how to install Exomiser and use it to prioritize exome sequences in a number of scenarios. Exomiser requires ∼3 GB of RAM and roughly 15-90 s of computing time on a standard desktop computer to analyze a variant call format (VCF) file. Exomiser is freely available for academic use from http://www.sanger.ac.uk/science/tools/exomiser.

Phenolyzer: phenotype-based prioritization of candidate genes for human diseases

Prior biological knowledge and phenotype information may help to identify disease genes from human whole-genome and whole-exome sequencing studies. We developed Phenolyzer (http://phenolyzer.usc.edu), a tool that uses prior information to implicate genes involved in diseases. Phenolyzer exhibits superior performance over competing methods for prioritizing Mendelian and complex disease genes, based on disease or phenotype terms entered as free text.

Confirmation of TTC8 as a disease gene for nonsyndromic autosomal recessive retinitis pigmentosa (RP51)

Nonsyndromic retinitis pigmentosa (RP) is genetically highly heterogeneous, with >100 disease genes identified. However, mutations in these genes explain only 60% of all RP cases. Blood samples were collected from 12 members of an autosomal recessive RP family. Whole genome homozygosity mapping and haplotype analysis placed the RP locus in this family at chromosome 14q31.3. Whole-exome sequencing (WES) in proband revealed a mutation in TTC8, which was flagged as most likely candidate gene by bioinformatic analysis. TTC8 is mutated in Bardet-Biedl syndrome 8 (BBS8), and once reported previously in a family with nonsyndromic RP. Sequencing of amplified products of exon 13 of TTC8 validated c.1347G>C (p.Gln449His), a novel change that affects the final nucleotide of exon 13 and might deleteriously affect splicing. This mutation segregated completely with the disease in the family and was not observed in 100 ethnically matched controls from same population. This represents second report of a TTC8 mutation in nonsyndromic RP, thus confirming the identity of TTC8 as causative gene for RP51.

Phenotype-driven strategies for exome prioritization of human Mendelian disease genes

Whole exome sequencing has altered the way in which rare diseases are diagnosed and disease genes identified. Hundreds of novel disease-associated genes have been characterized by whole exome sequencing in the past five years, yet the identification of disease-causing mutations is often challenging because of the large number of rare variants that are being revealed. Gene prioritization aims to rank the most probable candidate genes towards the top of a list of potentially pathogenic variants. A promising new approach involves the computational comparison of the phenotypic abnormalities of the individual being investigated with those previously associated with human diseases or genetically modified model organisms. In this review, we compare and contrast the strengths and weaknesses of current phenotype-driven computational algorithms, including Phevor, Phen-Gen, eXtasy and two algorithms developed by our groups called PhenIX and Exomiser. Computational phenotype analysis can substantially improve the performance of exome analysis pipelines.