Differential chromatin profiles partially determine transcription factor binding

• Main Authors: Chen, Rujian (Contributor), Gifford, David K (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
• Format: Article
• Language: English
• Published: Public Library of Science, 2018-01-22T16:19:32Z.
• Subjects: Article
• Online Access: Get fulltext

 This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. We characterize how genomic variants that alter chromatin accessibility influence regulatory factor binding with a new method called DeltaBind that predicts condition specific factor binding more accurately than other methods based on DNase-seq data. Using DeltaBind and DNase-seq experiments we predicted the differential binding of 18 factors in K562 and GM12878 cells with an average precision of 28% at 10% recall, with the prediction of individual factors ranging from 5% to 65% precision. We further found that genome variants that alter chromatin accessibility are not necessarily predictive of altering proximal factor binding. Taken together these findings suggest that DNase-seq or ATAC-seq Quantitative Trait Loci (dsQTLs), while important, must be considered in a broader context to establish causality for phenotypic changes.