Diagnostics of common microdeletion syndromes using fluorescence in situ hybridization: single center experience in a developing country

Features of the Wolf-Hirschhorn Syndrome (WHS) from Infant to Young Teenager

Wolf-Hirschhorn syndrome is a rare condition caused by terminal deletions, of variable size, in the short arm of chromosome 4. The syndrome displays the combination of typical morphological facial variations, intellectual disability, language delay, and various malformations. This report describes the clinical aspect and developmental evolution of a male patient with Wolf-Hirschhorn syndrome, from infancy to adolescence. The patient was first examined and diagnosed at 11 months, with follow-up at the ages of 4 and 16.

Whole-genome sequencing of 1029 Indian individuals reveals unique and rare structural variants

Structural variants contribute to genetic variability in human genomes and they can be presented in population-specific patterns. We aimed to understand the landscape of structural variants in the genomes of healthy Indian individuals and explore their potential implications in genetic disease conditions. For the identification of structural variants, a whole genome sequencing dataset of 1029 self-declared healthy Indian individuals from the IndiGen project was analysed. Further, these variants were evaluated for potential pathogenicity and their associations with genetic diseases. We also compared our identified variations with the existing global datasets. We generated a compendium of total 38,560 high-confident structural variants, comprising 28,393 deletions, 5030 duplications, 5038 insertions, and 99 inversions. Particularly, we identified around 55% of all these variants were found to be unique to the studied population. Further analysis revealed 134 deletions with predicted pathogenic/likely pathogenic effects and their affected genes were majorly enriched for neurological disease conditions, such as intellectual disability and neurodegenerative diseases. The IndiGenomes dataset helped us to understand the unique spectrum of structural variants in the Indian population. More than half of identified variants were not present in the publicly available global dataset on structural variants. Clinically important deletions identified in IndiGenomes might aid in improving the diagnosis of unsolved genetic diseases, particularly in neurological conditions. Along with basal allele frequency data and clinically important deletions, IndiGenomes data might serve as a baseline resource for future studies on genomic structural variant analysis in the Indian population.

Microarray-Based Comparative Genomic Hybridization, Multiplex Ligation-Dependent Probe Amplification, and High-Resolution Karyotype for Differential Diagnosis Oculoauriculovertebral Spectrum: A Systematic Review

Oculoauriculovertebral spectrum (OAVS) is a rare class of heterogenous congenital craniofacial malformation conditions of unknown etiology. Although classic OAVS has been described as hemifacial microsomia with facial asymmetry and microtia, there is no consensus regarding clinical criteria for diagnosis or genetic cause. This systematic review aims to assess the applicability of high-resolution (HR) karyotype, fluorescence in situ hybridization, multiplex ligation-dependent probe amplification (MLPA), and microarray-based comparative genomic hybridization (array-CGH) for differential diagnosis of OAVS. A search was performed in PubMed and Web of Science using all entry terms to the following descriptors: Goldenhar's syndrome, cytogenetic analysis, hybridization in situ, fluorescent, comparative genomic hybridization, multiplex polymerase chain reaction, whole genome sequencing, and karyotype analysis methods. After screening, 25 articles met eligibility. Of the included studies, 59 individuals had a genetic alteration identified. Array-CGH, MLPA, and HR karyotype appear to be viable approaches for molecular diagnosis in OAVS. Heterogeneity is a hallmark of OAVS. Establishing an enhanced framework for diagnosis would inform clinical decision making, and better resource utilization could improve health care facility efficiency and economy.