Integrating binding and expression data to predict transcription factors combined function
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Integrating binding and expression data to predict transcription factors combined function Mahmoud Ahmed1 , Do Sik Min2 and Deok Ryong Kim1*
Abstract Background: Transcription factor binding to the regulatory region of a gene induces or represses its gene expression. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins. These proteins form complexes which bind to the DNA as one-units. The binding of two factors to a shared site does not always lead to a functional interaction. Results: We propose a method to predict the combined functions of two factors using comparable binding and expression data (target). We based this method on binding and expression target analysis (BETA), which we re-implemented in R and extended for this purpose. target ranks the factor’s targets by importance and predicts the dominant type of interaction between two transcription factors. We applied the method to simulated and real datasets of transcription factor-binding sites and gene expression under perturbation of factors. We found that Yin Yang 1 transcription factor (YY1) and YY2 have antagonistic and independent regulatory targets in HeLa cells, but they may cooperate on a few shared targets. Conclusion: We developed an R package and a web application to integrate binding (ChIP-seq) and expression (microarrays or RNA-seq) data to determine the cooperative or competitive combined function of two transcription factors. Keywords: BETA, DNA-binding, Cooperative-binding, Competitive-binding, Transcription-factor, R-package, YY1
Background Motivation
The binding of a transcription factor to the regulatory region (e.g. gene promoter or enhancer) of a particular gene induces or represses its gene expression [1]. High-throughput chromatin immunoprecipitation (ChIP) experiments identify hundreds or thousands of binding sites for most factors [2]. Therefore, methods are needed to determine which of these sites are true targets and whether they are functional [3]. Perturbing *Correspondence: [email protected] Department of Biochemistry and Convergence Medical Sciences and Institute of Health Sciences, Gyeongsang National University School of Medicine, 52727 Jinju, Republic of Korea Full list of author information is available at the end of the article 1
the transcription factor coding gene by overexpression or knockdown and measuring the effects on cellular gene expression provides useful information on the function of the factor [4]. Methods exist to integrate binding and gene expression data of the factor perturbation to predict the direct target regions (e.g. genes) [5, 6]. Transcription factors share their binding sites with other factors, co-factors and/or DNA-binding proteins [7, 8]. These transcriptional proteins form one-unit complexes which bind to the regulatory regions. Moreover, the binding of a protein to a specific region of the DNA can modulate the binding of other proteins elsewhere [7]. In the former case, the binding site of two or more factors can
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