Combining structural analysis of DNA with search routines for the detection of transcription regulatory elements

Karas, Holger; Knüppel, Rainer; Schulz, Wolfgang A.; Sklenar, Heinz; Wingender, Edgar

doi:10.1093/bioinformatics/12.5.441

Cited by 31 publications

(37 citation statements)

References 16 publications

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“…Based on the local structural characteristics of the DNA at the known binding sites, the proposed method was able to make more confident predictions about the presence of binding sites in promoters of co-expressed genes than the sequence-based methodology. These results support previous theories that structural DNA information can improve classifier performance by providing a higher level data source that is explicitly different from the nucleotide sequence itself (7,8). We could also show that some of the novel, CRoSSeD predicted binding sites (e.g.…”

Section: Discussionsupporting

confidence: 89%

“…These methods usually rely on different structural profiles, where each profile represents per position in the genome the values of a specific DNA structural property. Based on the structural profiles characteristics of known binding sites, a classifier can distinguish true from false positive binding sites, as was first demonstrated by Karas et al (7). Furthermore, the combination of these structural profiles with a higher order machine-learning classifier has demonstrated improved classification performance of true and false positive binding sites (8).…”

Section: Introductionmentioning

confidence: 99%

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Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli

Meysman

Dang

Laukens

et al. 2010

Nucleic Acids Research

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Recognition of genomic binding sites by transcription factors can occur through base-specific recognition, or by recognition of variations within the structure of the DNA macromolecule. In this article, we investigate what information can be retrieved from local DNA structural properties that is relevant to transcription factor binding and that cannot be captured by the nucleotide sequence alone. More specifically, we explore the benefit of employing the structural characteristics of DNA to create binding-site models that encompass indirect recognition for the Escherichia coli model organism. We developed a novel methodology [Conditional Random fields of Smoothed Structural Data (CRoSSeD)], based on structural scales and conditional random fields to model and predict regulator binding sites. The value of relying on local structural-DNA properties is demonstrated by improved classifier performance on a large number of biological datasets, and by the detection of novel binding sites which could be validated by independent data sources, and which could not be identified using sequence data alone. We further show that the CRoSSeD-binding-site models can be related to the actual molecular mechanisms of the transcription factor DNA binding, and thus cannot only be used for prediction of novel sites, but might also give valuable insights into unknown binding mechanisms of transcription factors.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli

Meysman

Dang

Laukens

et al. 2010

Nucleic Acids Research

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“…These steps are (i) TBP slides along DNA (Coleman and Pugh, 1995; Karas et al, 1996; Ponomarenko et al, 1999) ↔ (ii) TBP stops at a TBP-binding site (Berg and von Hippel, 1987; Bucher, 1990) ↔ (iii) the TBP–promoter complex is fixed by DNA helix's bending to the 90° angle (Ponomarenko et al, 1997; Flatters and Lavery, 1998; Powell et al, 2002). …”

Section: Methodsmentioning

confidence: 99%

Candidate SNP Markers of Familial and Sporadic Alzheimer's Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Пономаренко

Chadaeva

Рассказов

et al. 2017

Front. Aging Neurosci.

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While year after year, conditions, quality, and duration of human lives have been improving due to the progress in science, technology, education, and medicine, only eight diseases have been increasing in prevalence and shortening human lives because of premature deaths according to the retrospective official review on the state of US health, 1990-2010. These diseases are kidney cancer, chronic kidney diseases, liver cancer, diabetes, drug addiction, poisoning cases, consequences of falls, and Alzheimer's disease (AD) as one of the leading pathologies. There are familial AD of hereditary nature (~4% of cases) and sporadic AD of unclear etiology (remaining ~96% of cases; i.e., non-familial AD). Therefore, sporadic AD is no longer a purely medical problem, but rather a social challenge when someone asks oneself: “What can I do in my own adulthood to reduce the risk of sporadic AD at my old age to save the years of my lifespan from the destruction caused by it?” Here, we combine two computational approaches for regulatory SNPs: Web service SNP_TATA_Comparator for sequence analysis and a PubMed-based keyword search for articles on the biochemical markers of diseases. Our purpose was to try to find answers to the question: “What can be done in adulthood to reduce the risk of sporadic AD in old age to prevent the lifespan reduction caused by it?” As a result, we found 89 candidate SNP markers of familial and sporadic AD (e.g., rs562962093 is associated with sporadic AD in the elderly as a complication of stroke in adulthood, where natural marine diets can reduce risks of both diseases in case of the minor allele of this SNP). In addition, rs768454929, and rs761695685 correlate with sporadic AD as a comorbidity of short stature, where maximizing stature in childhood and adolescence as an integral indicator of health can minimize (or even eliminate) the risk of sporadic AD in the elderly. After validation by clinical protocols, these candidate SNP markers may become interesting to the general population [may help to choose a lifestyle (in childhood, adolescence, and adulthood) that can reduce the risks of sporadic AD, its comorbidities, and complications in the elderly].

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“…This is most likely a result of attempting to recognize binding sites independently of their context (Trifonov 1996). Functional context might include the presence of other binding sites, relative position and helical alignment to other binding sites (Fickett 1996), DNA structural characteristics (Benham 1996;Karas et al 1996) such as curvature (Shpigelman et al 1993;Ponomarenko et al 1997), or other local or distant sequence characteristics.…”

mentioning

confidence: 99%

Detection and Visualization of Compositionally Similar cis-Regulatory Element Clusters in Orthologous and Coordinately Controlled Genes

Jegga

Sherwood²,

Carman³

et al. 2002

Genome Res.

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Evolutionarily conserved noncoding genomic sequences represent a potentially rich source for the discovery of gene regulatory regions. However, detecting and visualizing compositionally similar cis-element clusters in the context of conserved sequences is challenging. We have explored potential solutions and developed an algorithm and visualization method that combines the results of conserved sequence analyses (BLASTZ) with those of transcription factor binding site analyses (MatInspector) (http://trafac.chmcc.org). We define hits as the density of co-occurring cis-element transcription factor (TF)-binding sites measured within a 200-bp moving average window through phylogenetically conserved regions. The results are depicted as a Regulogram, in which the hit count is plotted as a function of position within each of the two genomic regions of the aligned orthologs. Within a high-scoring region, the relative arrangement of shared cis-elements within compositionally similar TF-binding site clusters is depicted in a Trafacgram. On the basis of analyses of several training data sets, the approach also allows for the detection of similarities in composition and relative arrangement of cis-element clusters within nonorthologous genes, promoters, and enhancers that exhibit coordinate regulatory properties. Known functional regulatory regions of nonorthologous and less-conserved orthologous genes frequently showed cis-element shuffling, demonstrating that compositional similarity can be more sensitive than sequence similarity. These results show that combining sequence similarity with cis-element compositional similarity provides a powerful aid for the identification of potential control regions.In higher multicellular organisms, cell-type-specific nuclear machinery has an uncanny ability to direct precise patterns of gene expression through the recognition of arrays of ciselements specified by primary DNA sequence lying in the context of higher-order chromatin structure. Computationally, however, we have little ability to identify cis-regulatory regions from primary sequence and even less ability to predict cellular compartments into which expression is specified. Improved ability to do so will advance our understanding of eukaryotic gene regulatory mechanisms, facilitate improved annotation of the genome, and provide insight into the potential effects of sequence polymorphisms on gene expression patterns. Moreover, improved understanding of cis-element clusters present in coordinately regulated gene groups may allow for the prediction of gene regulatory network behaviors during development, homeostasis, and disease. To exploit the potential power of conserved cis-element clusters to contribute to our understanding of eukaryotic gene regulation, it is critical to create database resources from multiple sequence analysis methods on the basis of both phylogenetic conservation and known binding-site matches that can be mined for patterns that correlate with experimentally gathered expression profile data. As shown by man...

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Combining structural analysis of DNA with search routines for the detection of transcription regulatory elements

Cited by 31 publications

References 16 publications

Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli

Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli

Candidate SNP Markers of Familial and Sporadic Alzheimer's Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Detection and Visualization of Compositionally Similar cis-Regulatory Element Clusters in Orthologous and Coordinately Controlled Genes

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