
Gene regulatory networks (GRNs) comprising interactions between transcription factors (TFs) and regulatory loci control development and physiology. Numerous disease-associated mutations have been identified, the vast majority residing in non-coding regions of the genome. As current GRN mapping methods test one TF at a time and require the use of cells harboring the mutation(s) of interest, they are not suitable to identify TFs that bind to wild-type and mutant loci. Here, we use gene-centered yeast one-hybrid (eY1H) assays to interrogate binding of 1,086 human TFs to 246 enhancers, as well as to 109 non-coding disease mutations. We detect both loss and gain of TF interactions with mutant loci that are concordant with target gene expression changes. This work establishes eY1H assays as a powerful addition to the toolkit of mapping human GRNs and for the high-throughput characterization of genomic variants that are rapidly being identified by genome-wide association studies.
570, Biochemistry, Genetics and Molecular Biology(all), Systems Biology, Computational Biology, 610, Genomics, Molecular Genetics, Enhancer Elements, Genetic, Two-Hybrid System Techniques, Mutation, Humans, Disease, Gene Regulatory Networks, Molecular Biology, Genome-Wide Association Study, Transcription Factors
570, Biochemistry, Genetics and Molecular Biology(all), Systems Biology, Computational Biology, 610, Genomics, Molecular Genetics, Enhancer Elements, Genetic, Two-Hybrid System Techniques, Mutation, Humans, Disease, Gene Regulatory Networks, Molecular Biology, Genome-Wide Association Study, Transcription Factors
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 109 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
