Identifying deleterious noncoding variation through gain and loss of CTCF binding activity

CCCTC binding factor (CTCF) regulates gene expression through DNA binding at thousands of genomic loci. Genetic variation in these CTCF binding sites (CBSs) is an important driver of phenotypic variation, yet extracting those that are likely to have functional consequences in whole-genome sequencing remains challenging. To address this, we develop a hypothesis-driven framework to identify and prioritize CBS variants in gnomAD. We synthesize CTCF's binding patterns at 1,063,878 genomic loci across 214 biological contexts into a summary of binding activity. We find that high binding activity significantly correlates with both conserved nucleotides (Pearson R = 0.35, p < 2.2 × 10<sup>-16</sup>) and sequences that contain high-quality CTCF binding motifs (Pearson R = 0.63, p = 2.9 × 10<sup>-12</sup>). We then use binding activity to evaluate high-confidence allelic binding predictions for 1,253,329 single-nucleotide variations (SNVs) in gnomAD that disrupt a CBS. We find a strong, positive relationship between the mutability-adjusted proportion of singletons (MAPS) metric and the loss of CTCF binding at loci with high in vitro activity (Pearson R = 0.74, p < 2.2 × 10<sup>-16</sup>). To contextualize these findings, we apply MAPS to other functional classes of variation and find that a subset of 339,380 loss of CTCF binding variants is observed as infrequently as missense variants are. This work nominates these thousands of rare, noncoding variants that disrupt CTCF binding for further functional studies while providing a blueprint for prioritizing variation in other transcription factor binding sequences.

Authors

Institutions

Publication Details

Journal
The American Journal of Human Genetics
Published
2025-03-05
DOI
https://doi.org/10.1016/j.ajhg.2025.02.009
Primary Topic
RNA Research and Splicing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying deleterious noncoding variation through gain and loss of CTCF binding activity

Evonne McArthur, John A. Capra, Colby A. Tubbs, Douglas M. Ruderfer et al.
The American Journal of Human Genetics
RNA Research and Splicing
article

Identifying deleterious noncoding variation through gain and loss of CTCF binding activity

Evonne McArthur, John A. Capra, Colby A. Tubbs, Douglas M. Ruderfer, Mary Lauren Benton
article en

Abstract

CCCTC binding factor (CTCF) regulates gene expression through DNA binding at thousands of genomic loci. Genetic variation in these CTCF binding sites (CBSs) is an important driver of phenotypic variation, yet extracting those that are likely to have functional consequences in whole-genome sequencing remains challenging. To address this, we develop a hypothesis-driven framework to identify and prioritize CBS variants in gnomAD. We synthesize CTCF's binding patterns at 1,063,878 genomic loci across 214 biological contexts into a summary of binding activity. We find that high binding activity significantly correlates with both conserved nucleotides (Pearson R = 0.35, p < 2.2 × 10<sup>-16</sup>) and sequences that contain high-quality CTCF binding motifs (Pearson R = 0.63, p = 2.9 × 10<sup>-12</sup>). We then use binding activity to evaluate high-confidence allelic binding predictions for 1,253,329 single-nucleotide variations (SNVs) in gnomAD that disrupt a CBS. We find a strong, positive relationship between the mutability-adjusted proportion of singletons (MAPS) metric and the loss of CTCF binding at loci with high in vitro activity (Pearson R = 0.74, p < 2.2 × 10<sup>-16</sup>). To contextualize these findings, we apply MAPS to other functional classes of variation and find that a subset of 339,380 loss of CTCF binding variants is observed as infrequently as missense variants are. This work nominates these thousands of rare, noncoding variants that disrupt CTCF binding for further functional studies while providing a blueprint for prioritizing variation in other transcription factor binding sequences.

The American Journal of Human GeneticsVol. 112(4)
Baylor University (US), Vanderbilt University (US), University of Washington (US), Vanderbilt University Medical Center (US)
National Institute of Mental Health
Zero hunger
Openalex Percentile: Top 96%
RNA Research and Splicing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.