The Genetic Basis of Moyamoya Disease

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by progressive spontaneous bilateral occlusion of the intracranial internal cerebral arteries (ICA) and their major branches with compensatory capillary collaterals resembling a "puff of smoke" (Japanese: Moyamoya) on cerebral angiography. These pathological alterations of the vessels are called Moyamoya arteriopathy or vasculopathy and a further distinction is made between primary and secondary MMD. Clinical presentation depends on age and population, with hemorrhage and ischemic infarcts in particular leading to severe neurological dysfunction or even death. Although the diagnostic suspicion can be posed by MRA or CTA, cerebral angiography is mandatory for diagnostic confirmation. Since no therapy to limit the stenotic lesions or the development of a collateral network is available, the only treatment established so far is surgical revascularization. The pathophysiology still remains unknown. Due to the early age of onset, familial cases and the variable incidence rate between different ethnic groups, the focus was put on genetic aspects early on. Several genetic risk loci as well as individual risk genes have been reported; however, few of them could be replicated in independent series. Linkage studies revealed linkage to the 17q25 locus. Multiple studies on the association of SNPs and MMD have been conducted, mainly focussing on the endothelium, smooth muscle cells, cytokines and growth factors. A variant of the RNF213 gene was shown to be strongly associated with MMD with a founder effect in the East Asian population. Although it is unknown how mutations in the RNF213 gene, encoding for a ubiquitously expressed 591 kDa cytosolic protein, lead to clinical features of MMD, RNF213 has been confirmed as a susceptibility gene in several studies with a gene dosage-dependent clinical phenotype, allowing preventive screening and possibly the development of new therapeutic approaches. This review focuses on the genetic basis of primary MMD only

Combining callers improves the detection of copy number variants from whole-genome sequencing

Copy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing

Engineering of Structural Variants using CRISPR/Cas in Mice

Structural variations (SVs) contribute to the variability of our genome and are often associated with disease. Their study in model systems was hampered until now by labor-intensive genetic targeting procedures and multiple mouse crossing steps. Here we present the use of CRISPR/Cas for the fast (10 weeks) and efficient generation of SVs in mice. We specifically produced deletions, inversions, and also duplications at six different genomic loci ranging from 1.1 kb to 1.6 Mb with efficiencies up to 42%. After PCR-based selection, clones were successfully used to create mice via aggregation. To test the practicability of the method, we reproduced a human 500 kb disease-associated deletion and were able to recapitulate the human phenotype in mice. Furthermore, we evaluated the regulatory potential of a large genomic interval by deleting a 1.5 Mb fragment. The method presented permits rapid in vivo modeling of genomic rearrangements

Gene identification and analysis of transcripts differentially regulated in fracture healing by EST sequencing in the domestic sheep

BACKGROUND: The sheep is an important model animal for testing novel fracture treatments and other medical applications. Despite these medical uses and the well known economic and cultural importance of the sheep, relatively little research has been performed into sheep genetics, and DNA sequences are available for only a small number of sheep genes. RESULTS: In this work we have sequenced over 47 thousand expressed sequence tags (ESTs) from libraries developed from healing bone in a sheep model of fracture healing. These ESTs were clustered with the previously available 10 thousand sheep ESTs to a total of 19087 contigs with an average length of 603 nucleotides. We used the newly identified sequences to develop RT-PCR assays for 78 sheep genes and measured differential expression during the course of fracture healing between days 7 and 42 postfracture. All genes showed significant shifts at one or more time points. 23 of the genes were differentially expressed between postfracture days 7 and 10, which could reflect an important role for these genes for the initiation of osteogenesis. CONCLUSION: The sequences we have identified in this work are a valuable resource for future studies on musculoskeletal healing and regeneration using sheep and represent an important head-start for genomic sequencing projects for Ovis aries, with partial or complete sequences being made available for over 5,800 previously unsequenced sheep genes

array CGH screening of 134 unrelated families

Background A growing number of non-coding regulatory mutations are being identified in congenital disease. Very recently also some exons of protein coding genes have been identified to act as tissue specific enhancer elements and were therefore termed exonic enhancers or “eExons”. Methods We screened a cohort of 134 unrelated families with split-hand/split-foot malformation (SHFM) with high resolution array CGH for CNVs with regulatory potential. Results In three families with an autosomal dominant non-syndromic SHFM phenotype we detected microdeletions encompassing the exonic enhancer (eExons) 15 and 17 of DYNC1I1. In a fourth family, who had hearing loss in addition to SHFM, we found a larger deletion of 510 kb including the eExons of DYNC1I1 and, in addition, the human brain enhancer hs1642. Exons 15 and 17 of DYNC1I1 are known to act as tissue specific limb enhancers of DLX5/6, two genes that have been shown to be associated with SHFM in mice. In our cohort of 134 unrelated families with SHFM, deletions of the eExons of DYNC1I1 account for approximately 3% of the cases, while 17p13.3 duplications were identified in 13% of the families, 10q24 duplications in 12%, and TP63 mutations were detected in 4%. Conclusions We reduce the minimal critical region for SHFM1 to 78 kb. Hearing loss, however, appears to be associated with deletions of a more telomeric region encompassing the brain enhancer element hs1642. Thus, SHFM1 as well as hearing loss at the same locus are caused by deletion of regulatory elements. Deletions of the exons with regulatory potential of DYNC1I1 are an example of the emerging role of exonic enhancer elements and their implications in congenital malformation syndromes

GLI3 variants causing isolated polysyndactyly are not restricted to the protein's C-terminal third

Loss of function variants of GLI3 are associated with a variety of forms of polysyndactyly: Pallister-Hall syndrome (PHS), Greig-Cephalopolysyndactyly syndrome (GCPS), and isolated polysyndactyly (IPD). Variants affecting the N-terminal and C-terminal thirds of the GLI3 protein have been associated with GCPS, those within the central third with PHS. Cases of IPD have been attributed to variants affecting the C-terminal third of the GLI3 protein. In this study, we further investigate these genotype-phenotype correlations. Sequencing of GLI3 was performed in patients with clinical findings suggestive of a GLI3-associated syndrome. Additionally, we searched the literature for reported cases of either manifestation with mutations in the GLI3 gene. Here, we report 48 novel cases from 16 families with polysyndactyly in whom we found causative variants in GLI3 and a review on 314 previously reported GLI3 variants. No differences in location of variants causing either GCPS or IPD were found. Review of published data confirmed the association of PHS and variants affecting the GLI3 protein's central third. We conclude that the observed manifestations of GLI3 variants as GCPS or IPD display different phenotypic severities of the same disorder and propose a binary division of GLI3-associated disorders in either PHS or GCPS/polysyndactyly

Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study

Background: Collectively, an estimated 5% of the population have a genetic disease. Many of them feature characteristics that can be detected by facial phenotyping. Face2Gene CLINIC is an online app for facial phenotyping of patients with genetic syndromes. DeepGestalt, the neural network driving Face2Gene, automatically prioritizes syndrome suggestions based on ordinary patient photographs, potentially improving the diagnostic process. Hitherto, studies on DeepGestalt’s quality highlighted its sensitivity in syndromic patients. However, determining the accuracy of a diagnostic methodology also requires testing of negative controls. Objective: The aim of this study was to evaluate DeepGestalt's accuracy with photos of individuals with and without a genetic syndrome. Moreover, we aimed to propose a machine learning–based framework for the automated differentiation of DeepGestalt’s output on such images. Methods: Frontal facial images of individuals with a diagnosis of a genetic syndrome (established clinically or molecularly) from a convenience sample were reanalyzed. Each photo was matched by age, sex, and ethnicity to a picture featuring an individual without a genetic syndrome. Absence of a facial gestalt suggestive of a genetic syndrome was determined by physicians working in medical genetics. Photos were selected from online reports or were taken by us for the purpose of this study. Facial phenotype was analyzed by DeepGestalt version 19.1.7, accessed via Face2Gene CLINIC. Furthermore, we designed linear support vector machines (SVMs) using Python 3.7 to automatically differentiate between the 2 classes of photographs based on DeepGestalt's result lists. Results: We included photos of 323 patients diagnosed with 17 different genetic syndromes and matched those with an equal number of facial images without a genetic syndrome, analyzing a total of 646 pictures. We confirm DeepGestalt’s high sensitivity (top 10 sensitivity: 295/323, 91%). DeepGestalt’s syndrome suggestions in individuals without a craniofacially dysmorphic syndrome followed a nonrandom distribution. A total of 17 syndromes appeared in the top 30 suggestions of more than 50% of nondysmorphic images. DeepGestalt’s top scores differed between the syndromic and control images (area under the receiver operating characteristic [AUROC] curve 0.72, 95% CI 0.68-0.76; P<.001). A linear SVM running on DeepGestalt’s result vectors showed stronger differences (AUROC 0.89, 95% CI 0.87-0.92; P<.001). Conclusions: DeepGestalt fairly separates images of individuals with and without a genetic syndrome. This separation can be significantly improved by SVMs running on top of DeepGestalt, thus supporting the diagnostic process of patients with a genetic syndrome. Our findings facilitate the critical interpretation of DeepGestalt’s results and may help enhance it and similar computer-aided facial phenotyping tools

Mammalian mitochondrial nitric oxide synthase: Characterization of a novel candidate

AbstractRecently a novel family of putative nitric oxide synthases, with AtNOS1, the plant member implicated in NO production, has been described. Here we present experimental evidence that a mammalian ortholog of AtNOS1 protein functions in the cellular context of mitochondria. The expression data suggest that a candidate for mammalian mitochondrial nitric oxide synthase contributes to multiple physiological processes during embryogenesis, which may include roles in liver haematopoesis and bone development

LRFN5 locus structure is associated with autism and influenced by the sex of the individual and locus conversions

LRFN5 is a regulator of synaptic development and the only gene in a 5.4 Mb mammalian-specific conserved topologically associating domain (TAD); the LRFN5 locus. An association between locus structural changes and developmental delay (DD) and/or autism was suggested by several cases in DECIPHER and own records. More significantly, we found that maternal inheritance of a specific LRFN5 locus haplotype segregated with an identical type of autism in distantly related males. This autism-susceptibility haplotype had a specific TAD pattern. We also found a male/female quantitative difference in the amount histone-3-lysine-9-associated chromatin around the LRFN5 gene itself (p < 0.01), possibly related to the male-restricted autism susceptibility. To better understand locus behavior, the prevalence of a 60 kb deletion polymorphism was investigated. Surprisingly, in three cohorts of individuals with DD (n = 8757), the number of deletion heterozygotes was 20%–26% lower than expected from Hardy–Weinberg equilibrium. This suggests allelic interaction, also because the conversions from heterozygosity to wild-type or deletion homozygosity were of equal magnitudes. Remarkably, in a control group of medical students (n = 1416), such conversions were three times more common (p = 0.00001), suggesting a regulatory role of this allelic interaction. Taken together, LRFN5 regulation appears unusually complex, and LRFN5 dysregulation could be an epigenetic cause of autism.publishedVersio

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