Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes

Колчанов, Н. А.; Меркулова, Т. И.; Ignatieva, E. V.; Ananko, E. A.; Oshchepkov, Dmitry; Levitsky, Victor G.; Vasiliev, Gennady V.; Klimova, Nataly V.; Меркулов, В. М.; Hodgman, Charlie

doi:10.1093/bib/bbm027

Cited by 29 publications

(18 citation statements)

References 65 publications

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“…There are also resources, predicting GWAS SNPs effects on affinity of putative TFBS motifs found in known regulatory regions [51]; [52]. However, the genome-scale application of computational methods is usually complicated by the absence of direct experimental verification, making it difficult to set a threshold to avoid recognition of too many false-positive TFBSs as well as to considerably reduce the level of under-predictions [53].…”

Section: Discussionmentioning

confidence: 99%

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data

et al. 2013

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A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project.

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Section: Discussionmentioning

confidence: 99%

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data

et al. 2013

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“…Experimental identification of gene regulatory modules complemented by computational approaches proved to be efficacious [24]. Depending on the source data and objectives many different computational programs have been developed [1,2].…”

Section: Discussionmentioning

confidence: 99%

An integrative computational approach to effectively guide experimental identification of regulatory elements in promoters

2012

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BackgroundTranscriptional activity of genes depends on many factors like DNA motifs, conformational characteristics of DNA, melting etc. and there are computational approaches for their identification. However, in real applications, the number of predicted, for example, DNA motifs may be considerably large. In cases when various computational programs are applied, systematic experimental knock out of each of the potential elements obviously becomes nonproductive. Hence, one needs an approach that is able to integrate many heterogeneous computational methods and upon that suggest selected regulatory elements for experimental verification.ResultsHere, we present an integrative bioinformatic approach aimed at the discovery of regulatory modules that can be effectively verified experimentally. It is based on combinatorial analysis of known and novel binding motifs, as well as of any other known features of promoters. The goal of this method is the identification of a collection of modules that are specific for an established dataset and at the same time are optimal for experimental verification. The method is particularly effective on small datasets, where most statistical approaches fail. We apply it to promoters that drive tumor-specific gene expression in tumor-colonizing Gram-negative bacteria. The method successfully identified a number of potential modules, which required only a few experiments to be verified. The resulting minimal functional bacterial promoter exhibited high specificity of expression in cancerous tissue.ConclusionsExperimental analysis of promoter structures guided by bioinformatics has proved to be efficient. The developed computational method is able to include heterogeneous features of promoters and suggest combinatorial modules for experimental testing. Expansibility and robustness of the methodology implemented in the approach ensures good results for a wide range of problems.

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“…To shed light on the molecular mechanisms involved in GR mediated regulation of the OXPHOS pathway bioinformatic analysis using the TRED or CCTFSP software [129,130,131] was performed to identify potential glucocorticoid responsive elements (GREs) in the promoters of genes encoding Surf-1, and SCO2 enzymes which are essential for the assembly of the Cytochrome c Oxidase (COX) wholoenzyme [132,133,134]. Similar approaches were used to detect possible existence of potential GREs in the regulatory region of the promoter of the nuclear gene encoding COX-Va. Putative GREs were identified in the regulatory regions of the promoters of Surf-1, SCO2, and COX-Va using this approach.…”

Section: Mitochondrial Gr Glucocorticoids and Cellular Energy Metabomentioning

confidence: 99%

Molecular Mechanisms Conferring Resistance/Sensitivity to Glucocorticoid-Induced Apoptosis

Berrou¹,

Krstic‐Demonacos²,

Demonacos³

2012

Glucocorticoids - New Recognition of Our Familiar Friend

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Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes

Cited by 29 publications

References 65 publications

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data

Detection of Regulatory SNPs in Human Genome Using ChIP-seq ENCODE Data

An integrative computational approach to effectively guide experimental identification of regulatory elements in promoters

Molecular Mechanisms Conferring Resistance/Sensitivity to Glucocorticoid-Induced Apoptosis

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