A predictive framework for stop-loss variants with C-terminal extensions.

ABSTRACT: Stop codons dictate translation termination, and variants occurring at these sites can result in stop-loss variants, leading to C-terminal extensions with significant functional consequences. Despite their clinical relevance, existing prediction tools, primarily developed for missense variants, lack sufficient accuracy for assessing stop-loss variants, mainly due to inadequate consideration of the sequence features of the extended peptide. To address this gap, we developed TAILVAR (Terminal extension Analysis for Improved prediction of Lengthened VARiants), a machine-learning classifier that integrates multi-omics features spanning transcript- and protein-level properties, along with variant effect annotations. Our analyses showed that transcripts lacking downstream stop codons in the 3' u

SUBMITTER: Yoon JG 

PROVIDER: S-EPMC12817085 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature