Mutational load analysis of unrelated individuals

Targeted next-generation sequencing of deafness genes in hearing-impaired individuals uncovers informative mutations

Purpose:

Targeted next-generation sequencing provides a remarkable opportunity to identify variants in known disease genes, particularly in extremely heterogeneous disorders such as nonsyndromic hearing loss. The present study attempts to shed light on the complexity of hearing impairment.

Methods:

Using one of two next-generation sequencing panels containing either 80 or 129 deafness genes, we screened 30 individuals with nonsyndromic hearing loss (from 23 unrelated families) and analyzed 9 normal-hearing controls.

Results:

Overall, we found an average of 3.7 variants (in 80 genes) with deleterious prediction outcome, including a number of novel variants, in individuals with nonsyndromic hearing loss and 1.4 in controls. By next-generation sequencing alone, 12 of 23 (52%) probands were diagnosed with monogenic forms of nonsyndromic hearing loss; one individual displayed a DNA sequence mutation together with a microdeletion. Two (9%) probands have Usher syndrome. In the undiagnosed individuals (10/23; 43%) we detected a significant enrichment of potentially pathogenic variants as compared to controls.

Conclusion:

Next-generation sequencing combined with microarrays provides the diagnosis for approximately half of the GJB2 mutation–negative individuals. Usher syndrome was found to be more frequent in the study cohort than anticipated. The conditions in a proportion of individuals with nonsyndromic hearing loss, particularly in the undiagnosed group, may have been caused or modified by an accumulation of unfavorable variants across multiple genes.

Translational genetics for diagnosis of human disorders of sex development

Disorders of sex development (DSDs) are congenital conditions with discrepancies between the chromosomal, gonadal, and phenotypic sex of the individual. Such disorders have historically been difficult to diagnose and cause great stress to patients and their families. Genetic analysis of human samples has been instrumental in elucidating the molecules and pathways involved in the development of the bipotential gonad into a functioning testis or ovary. However, many DSD patients still do not receive a genetic diagnosis. New genetic and genomic technologies are expanding our knowledge of the underlying mechanism of DSDs and opening new avenues for clinical diagnosis. We review the genetic technologies that have elucidated the genes that are well established in sex determination in humans, discuss findings from more recent genomic technologies, and propose a new paradigm for clinical diagnosis of DSDs.

Multiple testing in high-throughput sequence data: experiences from Group 8 of Genetic Analysis Workshop 17

The use of high-throughput sequence data in genetic epidemiology allows the investigation of common and rare variants in the entire genome, thus increasing the amount of information and the potential number of statistical tests performed within one study. As a consequence, the problem of multiple testing may become even more pressing than in previous studies. As an important challenge, the exact number of statistical tests depends on the actual statistical method used. Furthermore, many statistical approaches for the analysis of sequence data require permutation. Thus it may be difficult to also use permutation to estimate correct type I error levels as in genome-wide association studies. In view of this, a separate group at Genetic Analysis Workshop 17 was formed with a focus on multiple testing. Here, we present the approaches used for the workshop. Apart from tackling the multiple testing problem, the new group focused on different issues. Some contributors developed and investigated modifications of existing collapsing methods. Others aimed at improving the identification of functional variants through a reduction and analysis of the underlying data dimensions. Two research groups investigated the overall accumulation of rare variation across the genome and its value in predicting phenotypes. Finally, other investigators left the path of traditional statistical analyses by reversing null and alternative hypotheses and by proposing a novel resampling method. We describe and discuss all these approaches.