A rare genomic duplication in 2p14 underlies autosomal dominant hearing loss DFNA58

Here we define a ~ 200Kb genomic duplication in 2p14 as the genetic signature that segregates with post-lingual progressive sensorineural autosomal dominant hearing loss in 20 affected individuals from the DFNA58 family, first reported in 2009. The duplication includes two entire genes, PLEK and CNRIP1, and the first exon of PPP3R1 (protein-coding), in addition to four uncharacterized long noncoding (lnc) RNA genes and part of a novel protein-coding gene. Quantitative analysis of mRNA expression in blood samples revealed selective overexpression of CNRIP1 and of two lncRNA genes (LOC107985892 and LOC102724389) in all affected members tested, but not in unaffected ones. Qualitative analysis of mRNA expression identified also fusion transcripts involving parts of PPP3R1, CNRIP1 and an intergenic region between PLEK and CNRIP1, in the blood of all carriers of the duplication, but were heterogeneous in nature. By in situ hybridization and immunofluorescence, we showed that Cnrip1, Plek and Ppp3r1 genes are all expressed in the adult mouse cochlea including the spiral ganglion neurons, suggesting changes in expression levels of these genes in the hearing organ could underlie the DFNA58 form of deafness. Our study highlights the value of studying rare genomic events leading to hearing loss such as copy number variations. Further studies will be required to determine which of these genes, either coding proteins or non-coding RNAs, is or are responsible for DFNA58 hearing loss

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

Background Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25–30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. Methods We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. Results Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. Conclusions Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing