Prioritization of oligogenic variant combinations in whole exomes.

Motivation: Whole exome sequencing (WES) has emerged as a powerful tool for genetic research, enabling the collection of a tremendous amount of data about human genetic variation. However, properly identifying which variants are causative of a genetic disease remains an important challenge, often due to the number of variants that need to be screened. Expanding the screening to combinations of variants in two or more genes, as would be required under the oligogenic inheritance model, simply blows this problem out of proportion.

Faster and more accurate pathogenic combination predictions with VarCoPP2.0.

Background: The prediction of potentially pathogenic variant combinations in patients remains a key task in the field of medical genetics for the understanding and detection of oligogenic/multilocus diseases. Models tailored towards such cases can help shorten the gap of missing diagnoses and can aid researchers in dealing with the high complexity of the derived data. The predictor VarCoPP (Variant Combinations Pathogenicity Predictor) that was published in 2019 and identified potentially pathogenic variant combinations in gene pairs (bilocus variant combinations), was the first important step in this direction.

Toward reporting standards for the pathogenicity of variant combinations involved in multilocus/oligogenic diseases.

Although standards and guidelines for the interpretation of variants identified in genes that cause Mendelian disorders have been developed, this is not the case for more complex genetic models including variant combinations in multiple genes. During a large curation process conducted on 318 research articles presenting oligogenic variant combinations, we encountered several recurring issues concerning their proper reporting and pathogenicity assessment. These mainly concern the absence of strong evidence that refutes a monogenic model and the lack of a proper genetic and functional assessment of the joint effect of the involved variants.

Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database.

Unlabelled: Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature.

Visualizing structure-mediated interactions in supercoiled DNA molecules.

We directly visualize the topology-mediated interactions between an unwinding site on a supercoiled DNA plasmid and a specific probe molecule designed to bind to this site, as a function of DNA supercoiling and temperature. The visualization relies on containing the DNA molecules within an enclosed array of glass nanopits using the Convex Lens-induced Confinement (CLiC) imaging method. This method traps molecules within the focal plane while excluding signal from out-of-focus probes.