TranCi identifies noncoding mutations affecting gene regulation in esophageal squamous cell cancer, suggesting impactful mechanisms.
Noncoding variants and mutations outnumber their coding counterparts but remain challenging to interpret functionally. We present TranCi, a method that prioritises human genetic variations by integrating enhancer RNA (eRNA) expression with eRNA-mRNA interactome maps. By linking variant-associated changes in eRNA to downstream gene regulation, TranCi captures functional effects missed by sequence-based or chromatin-centric approaches. In esophageal squamous cell cancer, TranCi identifies noncoding mutations with roles in disease initiation and progression. A personalised mode enables analysis at single-patient resolution, uncovering potential individual-specific regulatory variants. TranCi thus provides a mechanistic framework for interpreting noncoding variations and uniquely identifies their downstream targets, where standard methods often fall short. TranCi is available as a module within the eRNAkit R package (https://github.com/AneneLab/eRNAkit), leveraging its database of eRNA expression and interactions for functional variant interpretation.
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Benova et al. (2025) studied this question.
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