Work

NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction

Year: 2025

Type: article

Abstract: Once a suitable reference sequence has been generated, intra-species variation is often assessed by re-sequencing. Variant calling processes can reveal all differences between strains, accessions, genotypes, or individuals. These variants can be enriched with predictions about their functional implications based on available structural annotations, i.e., gene models. Although these functional impact predictions on a per-variant basis are often accurate, some challenging cases require the simultaneous incorporation of multiple adjacent variants into this prediction process. Examples include neighboring variants which modify each other's functional impact. The Neighborhood-Aware Variant Impact Predictor (NAVIP) considers all variants within a given protein coding sequence when predicting the effect. As a proof of concept, variants between the Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1 were annotated. NAVIP is freely available on GitHub (https://github.com/bpucker/NAVIP) and accessible through a web server (https://pbb-tools.de).

Source: PLoS Computational Biology

DOI: 10.1371/journal.pcbi.1012732

Authors: Jan-Simon Baasner, Andreas Rempel, Dakota Howard, Boas Pucker

Institutions: Bielefeld University, Furman University, Technische Universität Braunschweig

Language: English

Topic: Genomics and Rare Diseases

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,043

Funder: Technische Universität Braunschweig