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Transcription factors TFs exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing ChIP-seq sample. After quality control, we compiled a set of TF-binding specificity score profiles for 2, high-quality ChIP-seq samples, comprising TFs and cell types.
We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k -mers between two ChIP-seq samples and detected k -mers exhibiting statistically significant differences in binding specificity scores.
Moreover, we demonstrated that differences in the binding specificity scores between k -mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms SNPs as TF-affecting SNPs and provide candidates responsible for TFs and cell types.
Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans. The regulation of gene expression is one of the most important mechanisms underlying proper cell function.
