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Related Experiment Video

Updated: May 1, 2026

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

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This study develops a new method to understand how genetic variants in non-coding DNA affect gene expression and disease. It maps regulatory links to pinpoint functional variants and their impact on cellular processes.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Most human genetic variants are in non-coding regions, impacting gene regulation and disease.
  • Identifying the functional role of non-coding variation is a significant challenge in genomics.

Purpose of the Study:

  • To develop a generalizable strategy for interpreting non-coding regulatory variation.
  • To map the impact of genetic variants in their native regulatory context using personal genomics and deep learning.

Main Methods:

  • Integration of personal genomics, allele-specific gene regulation analysis, and deep learning predictions.
  • Leveraging whole-chromosome haplotypes and allele-specific analyses to establish regulatory links.
  • Identification and validation of cell-type-specific transcription factor binding events affected by genetic variants.

Main Results:

  • Hundreds of transcription factor binding events disrupted by genetic variants were identified and validated.
  • Novel mechanisms underlying allele-specific chromatin accessibility and gene expression were revealed.
  • A rare variant disrupting an OCT2 binding site and modulating PIK3R5 gene expression was discovered.

Conclusions:

  • The study presents a robust framework for interpreting non-coding regulatory variation.
  • This approach enables systematic dissection of variant effects across diverse biological systems.
  • The findings offer a new framework for investigating genetic disease mechanisms.