Dataset Information

Mutational processes in cancer preferentially affect binding of particular transcription factors.

ABSTRACT: Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs' binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.

SUBMITTER: Liu M

PROVIDER: S-EPMC7870974 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mutational processes in cancer preferentially affect binding of particular transcription factors.

Liu Mo M Boot Arnoud A Ng Alvin W T AWT Gordân Raluca R Rozen Steven G SG

Scientific reports 20210208 1

Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to pref ...[more]

PMID: 33558557

Similar Datasets

Project description:BackgroundThe enhanceosome is an enhancer located upstream of the human interferon β gene, bound by transcription factor (TF) complex of extremely rigid structure. Within these rigid constraints, even a slight change of distances between transcription factor binding sites (TFBS) results in loss of functionality of the enhanceosome. We hypothesized that smaller subunits of the enhanceosome may entail TF complex formation in other regulatory regions.ResultsIn order to verify this hypothesis we systematically searched for dimerization preferences of the TFs that have TFBS in the enhanceosome. For this we utilized our recently developed tool, TACO. We performed this computational experiment in a cell-type-specific manner by utilizing cell-type-specific DNase-seq data for 105 human cell types. We also used 20 TRANSFAC motifs comprising not only the usual TFs constituting the enhanceosome but also the architectural proteins of High Mobility Group I(Y) (HMG I). A similar experiment used 42 DNase-seq data sets for mouse cell types. We found 137 statistically significant dimer predictions in the human genome, and 37 predictions in the mouse genome, that matched the positioning on the enhanceosome with ±2 bp tolerance. To characterize these predicted TF dimers, we performed functional analysis (Gene Ontology enrichment) for sets of genes which were in the neighbourhood of predicted dimer instances. A notable feature of these instances is that (1) most of them are located in introns of genes, (2) they are enriched in regulatory states, and (3) those instances that are located near transcription start sites are enriched for inclusion in computationally predicted enhancers. We also investigated similarity of dimer predictions between human and mouse.ConclusionsIt follows from our experiments that, except for homodimer formed by IRF proteins, the rest of the dimers were formed exclusively between one of the transcriptional activators (ATF-2/c-Jun and IRF) and a HMG I protein. NF- κB did not participate in forming dimers with other proteins. Dimers predicted in mouse were fully contained in those predicted in human, with exactly the same spacing and orientation. Intriguingly, in most of the cases the enhanceosome motifs have 1 bp wider spacing than the corresponding dimers predicted genome-wide, which is likely caused by the overall 3D structure constraints of the enhanceosome-bound complex.

Dataset Information

Mutational processes in cancer preferentially affect binding of particular transcription factors.

Publications

Mutational processes in cancer preferentially affect binding of particular transcription factors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets