Scalable DNA-Protein Binding Changer Test for Insertion and Deletion of Bases in the Genome

• Activity Number: 74 - Invited E-Poster Session I
• Type: Invited
• Date/Time: Sunday, August 7, 2022 : 8:30 PM to 9:25 PM
• Sponsor: Biometrics Section
• Author(s): Sunyoung Shin* and Chandler Zuo and Min Chen and Yuannyu Zhang and Jian Xu and Qinyi Zhou
• Companies: University of Texas at Dallas and University of Texas at Dallas and University of Texas at Dallas and University of Texas Southwestern Medical Center and University of Texas Southwestern Medical Center and University of Texas at Dallas
• Keywords: Importance sampling; Insertions and deletions; Noncoding mutations; Position weight matrix; p-value based test statistic; Transcription factor binding

Abstract

Mutations in the noncoding genome have been crucial to understanding of disease mechanisms through dysregulation of disease-associated genes. One key element in gene regulation that noncoding mutations mediate is the binding of proteins to DNA sequences. Insertion and deletion of bases (InDels) are the second most common type of mutations that may impact DNA-protein binding. However, no existing methods could be utilized to determine the quantitative effects on DNA-protein binding driven by InDels. We develop a novel statistical test, named binding changer test, to evaluate the impact of InDels on DNA binding changes using DNA-binding motifs and single sequence modeling. The test predicts binding changer InDels of regulatory importance with an efficient importance sampling algorithm in generating background sequences from an importance distribution more weighting large binding affinity changes. The test provides a general statistical framework for any disease types in any species genomes. The application to genome sequencing datasets in human leukemia samples uncovers candidate pathologic InDels by modulating MYC binding in leukemic genomes.