Mapping functional non-coding variation in individual human genomes through haplotyping, multiomics, and deep learning

However, identifying such functionally relevant genetic variation remains challenging. Here we integrate personal genomics, allele-specific gene regulation, and deep learning predictions to map the impact of non-coding variation in its native allelic and regulatory context.

We identify and validate hundreds of cell-type-specific transcription factor binding events disrupted by genetic variants, providing mechanistic insights underlying allele-specific gene regulation. Using this framework, we discover a rare variant that modulates PIK3R5 gene expression by disrupting an OCT2 binding site within a distal enhancer. Our study establishes a generalisable strategy for interpreting non-coding regulatory variation, enabling systematic dissection of variant effects across diverse biological systems and offering an alternative framework to investigate the disease mechanisms.