Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Area of Science:

• Genomics and Molecular Biology
• Epigenetics and Gene Regulation
• Disease Risk Prediction

Background:

• Distinguishing deleterious non-coding DNA variations is challenging for common diseases.
• Non-coding variations disrupting cis-overlapping motifs (CisOMs) of opposing transcription factors impact enhancer activity.
• Understanding the interplay between P53 and cMYC in gene regulation is key for disease insights.

Approach:

• Analyzed ChIP-seq data for P53 and cMYC co-occupancy in human and mouse cells.
• Investigated the effects of doxorubicin treatment on P53 and cMYC levels and binding.
• Utilized computational motif-matching and reporter gene assays to assess DNA variation impact on binding affinity and gene expression.

Key Points:

• ~344-366 genomic regions are co-occupied by P53 and cMYC, with conserved CisOMs across vertebrates.
• Doxorubicin treatment altered P53 and cMYC levels and binding, leading to changes in ~187 nearby gene expressions.
• DNA variations in CisOMs of co-occupied elements significantly correlate with reporter gene expression alterations.

Conclusions:

• A significant correlation exists between SNP-induced changes in cMYC binding affinity within CisOMs and altered gene expression.
• This research advances a method for filtering etiological non-coding variations in P53 and cMYC-dependent diseases.
• The findings contribute to improved disease risk prediction and potential therapeutic strategies.