Investigation of a Pathogenic Inversion in and Comprehensive Analysis of Chromosomal Inversions Across Diverse Datasets.

Inversions are known contributors to the pathogenesis of genetic diseases. Identifying inversions poses significant challenges, making it one of the most demanding structural variants (SVs) to detect and interpret. Recent advancements in sequencing technologies and the development of publicly available SV datasets have substantially enhanced our capability to explore inversions. However, a cross-comparison in those datasets remains unexplored. In this study, we reported a proband with familial hemophagocytic lymphohistiocytosis type-3 carrying c.1389+1G>A with NC_000017.11:75576992_75829587inv disrupting , an inversion present in 0.006345% of individuals in gnomAD(v4.0). Based on this result, we investigate the features of potentially pathogenic inversions in public datasets. 98.9% of inversions are rare in gnomAD, and they disrupt 5% of protein-coding genes associated with a phenotype in OMIM. We then conducted a comparative analysis of the datasets, including gnomAD, DGV, and 1KGP, and two recent studies from the Human Genome Structural Variation Consortium revealed common and dataset-specific inversion characteristics suggesting methodology detection biases. Next, we investigated the genetic features of inversions disrupting the protein-coding genes by classifying the intersections between them into three categories. We found that most of the protein-coding genes in OMIM disrupted by inversions are associated with autosomal recessive phenotypes regardless of categories supporting the hypothesis that inversions in trans with other variants are hidden causes of monogenic diseases. This effort aims to fill the gap in our understanding of the molecular characteristics of inversions with low frequency in the population and highlight the importance of identifying them in rare disease studies.