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Biology subjects

Black, G. C.

Publications and source records attributed to Black, G. C..

3 recordsLinked to original sources

Whole genome sequencing enables definitive diagnosis of Cystic Fibrosis and Primary Ciliary Dyskinesia

Understanding the genomic basis of inherited respiratory disorders can assist in the clinical management of individuals with these rare disorders. We apply whole genome sequencing for the discovery of disease-causing variants in the non-coding regions of known disease genes for two individuals with inherited respiratory disorders. We describe analysis strategies to pinpoint candidate non-coding variants within the non-coding genome and demonstrate aberrant RNA splicing as a result of deep intronic variants in DNAH11 and CFTR. These findings confirm clinical diagnoses of primary ciliary dyskinesia and cystic fibrosis, respectively.

genomics

Deleterious genetic variants in NOTCH1 are a major contributor to the incidence of non-syndromic Tetralogy of Fallot

AimsFamilial recurrence studies provide strong evidence for a genetic component to the predisposition to sporadic, non-syndromic Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease (CHD) phenotype. Rare genetic variants have been identified as important contributors to the risk of CHD, but relatively small numbers of TOF cases have been studied to date. Here, we use whole exome sequencing to assess the prevalence of rare, potentially deleterious variants in candidate genes previously associated with both syndromic and non-syndromic TOF, in the largest cohort of non-syndromic TOF patients reported to date.\n\nMethods & Results829 non-syndromic TOF patients underwent whole exome sequencing. A systematic review of the literature was conducted which revealed 77 genes in which mutations had been reported in patients with TOF. The presence of rare, deleterious variants in the 77 candidate genes was determined, defined by a minor allele frequency of [≤] 0.001 and scaled combined annotation-dependent depletion (CADD) score of [≥] 20. We found a clustering of heterozygous rare, deleterious variants in NOTCH1 (P=1.89E-15), DOCK6 (P=2.93E-07), MYOM2 (P= 7.35E-05), TTC37 (P=0.016), MESP1 (P=0.024) and TBX1 (P=0.039), after correcting for multiple testing. NOTCH1 was most frequently found to harbour deleterious variants. Changes were observed in 49 patients (6%; 95% confidence interval [CI]: 4.5% - 7.8%) and included six truncating/frameshift variants and forty missense variants. Sanger sequencing of the unaffected parents of thirteen cases identified five de novo variants. Variants were not confined to a single functional domain of the NOTCH1 protein but significant clustering of variants was evident in the EGF-like repeats (P=0.018). Three NOTCH1 missense variants (p.G200R, p.C607Y and de novo p.N1875S) were subjected to functional evaluation and showed a reduction in Jagged1 ligand-induced NOTCH signalling. p.C607Y, which exhibited the most significant reduction in signalling, also perturbed S1 cleavage of the NOTCH1 receptor in the Golgi.\n\nConclusionThe NOTCH1 locus is a frequent site of genetic variants predisposing to non-syndromic TOF with 6% of patients exhibiting rare, deleterious variants. Our data supports the polygenic origin of TOF and suggests larger studies may identify additional loci.

genetics

Phenopolis: an open platform for harmonization and analysis of sequencing and phenotype data

SummaryPhenopolis is an open-source web server which provides an intuitive interface to genetic and phenotypic databases. It integrates analysis tools which include variant filtering and gene prioritisation based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare disease.\n\nAvailability and ImplementationA demo of the website is available at http://phenopolis.github.io (username: demo, password: demo123). If you wish to install a local copy, souce code and installation instruction are available at https://github.com/pontikos/phenopolis. The software is implemented using Python, MongoDB, HTML/Javascript and various bash shell scripts.\n\nContactn.pontikos@ucl.ac.uk\n\nSupplementary informationhttp://phenopolis.github.io

bioinformatics