Non-exomic and synonymous variants in ABCA4 are an important cause of Stargardt disease

Mutations in ABCA4 cause Stargardt disease and other blinding autosomal recessive retinal disorders. However, sequencing of the complete coding sequence in patients with clinical features of Stargardt disease sometimes fails to detect one or both mutations. For example, among 208 individuals with clear clinical evidence of ABCA4 disease ascertained at a single institution, 28 had only one disease-causing allele identified in the exons and splice junctions of the primary retinal transcript of the gene. Haplotype analysis of these 28 probands revealed 3 haplotypes shared among ten families, suggesting that 18 of the 28 missing alleles were rare enough to be present only once in the cohort. We hypothesized that mutations near rare alternate splice junctions in ABCA4 might cause disease by increasing the probability of mis-splicing at these sites. Next-generation sequencing of RNA extracted from human donor eyes revealed more than a dozen alternate exons that are occasionally incorporated into the ABCA4 transcript in normal human retina. We sequenced the genomic DNA containing 15 of these minor exons in the 28 one-allele subjects and observed five instances of two different variations in the splice signals of exon 36.1 that were not present in normal individuals (P < 10⁻⁶). Analysis of RNA obtained from the keratinocytes of patients with these mutations revealed the predicted alternate transcript. This study illustrates the utility of RNA sequence analysis of human donor tissue and patient-derived cell lines to identify mutations that would be undetectable by exome sequencing.

Advancing genetic testing for deafness with genomic technology

BACKGROUND

Non-syndromic hearing loss (NSHL) is the most common sensory impairment in humans. Until recently its extreme genetic heterogeneity precluded comprehensive genetic testing. Using a platform that couples targeted genomic enrichment (TGE) and massively parallel sequencing (MPS) to sequence all exons of all genes implicated in NSHL, we tested 100 persons with presumed genetic NSHL and in so doing established sequencing requirements for maximum sensitivity and defined MPS quality score metrics that obviate Sanger validation of variants.

METHODS

We examined DNA from 100 sequentially collected probands with presumed genetic NSHL without exclusions due to inheritance, previous genetic testing, or type of hearing loss. We performed TGE using post-capture multiplexing in variable pool sizes followed by Illumina sequencing. We developed a local Galaxy installation on a high performance computing cluster for bioinformatics analysis.

RESULTS

To obtain maximum variant sensitivity with this platform 3.2-6.3 million total mapped sequencing reads per sample were required. Quality score analysis showed that Sanger validation was not required for 95% of variants. Our overall diagnostic rate was 42%, but this varied by clinical features from 0% for persons with asymmetric hearing loss to 56% for persons with bilateral autosomal recessive NSHL.

CONCLUSIONS

These findings will direct the use of TGE and MPS strategies for genetic diagnosis for NSHL. Our diagnostic rate highlights the need for further research on genetic deafness focused on novel gene identification and an improved understanding of the role of non-exonic mutations. The unsolved families we have identified provide a valuable resource to address these areas.

Exon-level expression profiling of ocular tissues

The normal gene expression profiles of the tissues in the eye are a valuable resource for considering genes likely to be involved with disease processes. We profiled gene expression in ten ocular tissues from human donor eyes using Affymetrix Human Exon 1.0 ST arrays. Ten different tissues were obtained from six different individuals and RNA was pooled. The tissues included: retina, optic nerve head (ONH), optic nerve (ON), ciliary body (CB), trabecular meshwork (TM), sclera, lens, cornea, choroid/retinal pigment epithelium (RPE) and iris. Expression values were compared with publically available Expressed Sequence Tag (EST) and RNA-sequencing resources. Known tissue-specific genes were examined and they demonstrated correspondence of expression with the representative ocular tissues. The estimated gene and exon level abundances are available online at the Ocular Tissue Database.

AudioGene: predicting hearing loss genotypes from phenotypes to guide genetic screening

Autosomal dominant nonsyndromic hearing loss (ADNSHL) is a common and often progressive sensory deficit. ADNSHL displays a high degree of genetic heterogeneity and varying rates of progression. Accurate, comprehensive, and cost-effective genetic testing facilitates genetic counseling and provides valuable prognostic information to affected individuals. In this article, we describe the algorithm underlying AudioGene, a software system employing machine-learning techniques that utilizes phenotypic information derived from audiograms to predict the genetic cause of hearing loss in persons segregating ADNSHL. Our data show that AudioGene has an accuracy of 68% in predicting the causative gene within its top three predictions, as compared with 44% for a majority classifier. We also show that AudioGene remains effective for audiograms with high levels of clinical measurement noise. We identify audiometric outliers for each genetic locus and hypothesize that outliers may reflect modifying genetic effects. As personalized genomic medicine becomes more common, AudioGene will be increasingly useful as a phenotypic filter to assess pathogenicity of variants identified by massively parallel sequencing.

Prediction of cochlear implant performance by genetic mutation: the spiral ganglion hypothesis

BACKGROUND

Up to 7% of patients with severe-to-profound deafness do not benefit from cochlear implantation. Given the high surgical implantation and clinical management cost of cochlear implantation (>$1 million lifetime cost), prospective identification of the worst performers would reduce unnecessary procedures and healthcare costs. Because cochlear implants bypass the membranous labyrinth but rely on the spiral ganglion for functionality, we hypothesize that cochlear implant (CI) performance is dictated in part by the anatomic location of the cochlear pathology that underlies the hearing loss. As a corollary, we hypothesize that because genetic testing can identify sites of cochlear pathology, it may be useful in predicting CI performance.

METHODS

29 adult CI recipients with idiopathic adult-onset severe-to-profound hearing loss were studied. DNA samples were subjected to solution-based sequence capture and massively parallel sequencing using the OtoSCOPE(®) platform. The cohort was divided into three CI performance groups (good, intermediate, poor) and genetic causes of deafness were correlated with audiometric data to determine whether there was a gene-specific impact on CI performance.

RESULTS

The genetic cause of deafness was determined in 3/29 (10%) individuals. The two poor performers segregated mutations in TMPRSS3, a gene expressed in the spiral ganglion, while the good performer segregated mutations in LOXHD1, a gene expressed in the membranous labyrinth. Comprehensive literature review identified other good performers with mutations in membranous labyrinth-expressed genes; poor performance was associated with spiral ganglion-expressed genes.

CONCLUSIONS

Our data support the underlying hypothesis that mutations in genes preferentially expressed in the spiral ganglion portend poor CI performance while mutations in genes expressed in the membranous labyrinth portend good CI performance. Although the low mutation rate in known deafness genes in this cohort likely relates to the ascertainment characteristics (postlingual hearing loss in adult CI recipients), these data suggest that genetic testing should be implemented as part of the CI evaluation to test this association prospectively.