Evaluating the impact of single nucleotide variants on transcription factor binding

Abstract

Diseases and phenotypes caused by disrupted transcription factor (TF) binding are being identified, but progress is hampered by our limited capacity to predict such functional alterations. Improving predictions may be dependent on expanding the set of bona fide TF binding alterations. Allele-specific binding (ASB) events, where TFs preferentially bind to one of the two alleles at heterozygous sites, reveal the impact of sequence variations in altered TF binding. Here, we present the largest ASB compilation to our knowledge, 10 765 ASB events retrieved from 45 ENCODE ChIP-Seq data sets. Our analysis showed that ASB events were frequently associated with motif alterations of the ChIP'ed TF and potential partner TFs, allelic difference of DNase I hypersensitivity and allelic difference of histone modifications. For TF dimers bound symmetrically to DNA, ASB data revealed that central positions of the TF binding motifs were disproportionately important for binding. Lastly, the impact of variation on TF binding was predicted by a classification model incorporating all the investigated features of ASB events. Classification models using only DNase I hypersensitivity and sequence data exhibited predictive accuracy approaching the models with substantially more features. Taken together, the combination of ASB data and the classification model represents an important step toward elucidating regulatory variants across the human genome.

YY1 binding association with sex-biased transcription revealed through X-linked transcript levels and allelic binding analyses

“…Our in-house allelic binding pipeline was used to extract reads at heterozygous sites from GM12878 datasets and assess mapability for filtering71. We obtained the genotype data of GM12878 from the 1000 Genomes Project72, and a personalized hg19 genome for GM12878 was built by representing single nucleotide variations as degenerate IUPAC codes (eg.…”

RSAT Var-tools: an accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

“…It has been shown that taking advantage of specific biological insights ( e.g. identification of relevant TFs, reduction of genomic regions using functional genomic information) can significantly improve results, reducing the number of false positives [47,48] . In this respect, the evaluation set and case studies 3 and 4 focused on the analysis on TFs known to bind on the regions of interest, which enabled us to consistently evaluate the performance of the tool in the evaluation set, and further helped us to identify biologically relevant regulatory variants, affecting ePromoters function in case study 3, and VRN1 binding in barley in case study 4.…”

“…A) The number of heterozygous variants (x axis) within the same putative binding site will tend to have a greater impact on the TF binding probability when comparing haplotypes (weight difference, y axis). B) UCSC browser [48] screen shot, showing the locus of two SNPs that compose an heterozygous haplotype in one of the CEU individual, figure show the reference genome haplotype. The variants are located in the FUT10 promoter (top), variation-scan predicts an effect in three motifs that represent binding sites for GABPA, ETS1, ELF1 and ELK1, factors that have been proven to have binding sites in this region by the ENCODE project.…”

Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer

“…Interestingly, DNA sequence alterations that do not occur within regions that encode protein sequences directly (non‐coding mutations) represent ~ 98% of mutations in cancer and most still remain poorly characterized. Of these, mutations occurring in cis‐regulatory elements (i.e., enhancers and promoters) are of particular interest, as they can directly alter expression of associated gene products, by directly or indirectly altering DNA binding of TFs (Deplancke et al, ; Shi et al, ). Such mutations are frequent in breast cancer (Bailey et al, ; Zhou et al, ; Rheinbay et al, ; Gyorffy et al, ), but their significance is generally unclear (Nik‐Zainal et al, ).…”