Editorial: Copy Number Variation in Rare Disorders

Characterizing Homozygous Variants in Bardet-Biedl Syndrome-Associated Genes Within Iranian Families: Unveiling a Founder Variant in BBS2, c.471G>A

Bardet-Biedl syndrome (BBS) is a rare inherited ciliopathy disorder characterized by a broad spectrum of clinical symptoms such as retinal dystrophy, obesity, polydactyly, genitourinary and kidney anomalies, learning disability, and hypogonadism. The understanding of the variants involved in BBS-causing genes remains incomplete, highlighting the need for further research to develop a molecular diagnostic strategy for this syndrome. Singleton whole-exome sequencing (WES) was performed on sixteen patients. Our study revealed (1) nine patients carried eight homozygous pathogenic variants with four of them being novel (2) Specifically, a synonymous splicing variant (c.471G > A) in BBS2 gene in six patients with Baloch ethnicity. The identification of runs of homozygosity (ROH) calling was performed using the BCFtools/RoH software on WES data of patients harboring c.471G > A variant. The presence of shared homozygous regions containing the identified variant was confirmed in these patients. In-silico analysis predicted the effect of the c.471G > A variants on BBS2 mRNA splicing. This variant results in disrupted wild-type donor site and intron retention in the mature mRNA. (3) And a deletion of exons 14 to 17 in the BBS1 gene was identified in one patient by Copy-Number Variation (CNV) analysis using the ExomeDepth pipeline. Our results identified the founder variant c.471G > A in the BBS2 gene in the Baloch ethnicity of the Iranian population. This finding can guide the diagnostic approach of this syndrome in future studies.

Detection of Structural Variants by NGS: Revealing Missing Alleles in Lysosomal Storage Diseases

Lysosomal storage diseases (LSDs) are a heterogeneous group of rare multisystem metabolic disorders occurring mostly in infancy and childhood, characterized by a gradual accumulation of non-degraded substrates inside the cells. Although biochemical enzymatic assays are considered the gold standard for diagnosis of symptomatic patients, genotyping is a requirement for inclusion in enzyme replacement programs and is a prerequisite for carrier tests in relatives and DNA-based prenatal diagnosis. The emerging next-generation sequencing (NGS) technologies are now offering a powerful diagnostic tool for genotyping LSDs patients by providing faster, cheaper, and higher-resolution testing options, and are allowing to unravel, in a single integrated workflow SNVs, small insertions and deletions (indels), as well as major structural variations (SVs) responsible for the pathology. Here, we summarize the current knowledge about the most recurrent and private SVs involving LSDs-related genes, review advantages and drawbacks related to the use of the NGS in the SVs detection, and discuss the challenges to bring this type of analysis in clinical diagnostics.

New Developments and Possibilities in Reanalysis and Reinterpretation of Whole Exome Sequencing Datasets for Unsolved Rare Diseases Using Machine Learning Approaches

Rare diseases impact the lives of 300 million people in the world. Rapid advances in bioinformatics and genomic technologies have enabled the discovery of causes of 20–30% of rare diseases. However, most rare diseases have remained as unsolved enigmas to date. Newer tools and availability of high throughput sequencing data have enabled the reanalysis of previously undiagnosed patients. In this review, we have systematically compiled the latest developments in the discovery of the genetic causes of rare diseases using machine learning methods. Importantly, we have detailed methods available to reanalyze existing whole exome sequencing data of unsolved rare diseases. We have identified different reanalysis methodologies to solve problems associated with sequence alterations/mutations, variation re-annotation, protein stability, splice isoform malfunctions and oligogenic analysis. In addition, we give an overview of new developments in the field of rare disease research using whole genome sequencing data and other omics.