The TRANSFAC system on gene expression regulation

Wingender, Edgar; Chen, Xin; Fricke, Ellen; Geffers, Robert; Hehl, Reinhard; Liebich, Ines; Krull, Mathias; Matys, Volker; Michael, Holger; Ohnhäuser, R.; Prüß, M.; Schacherer, Frank; Thiele, Susanne; Urbach, Serge

doi:10.1093/nar/29.1.281

Cited by 589 publications

(413 citation statements)

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“…31 The TRANSFAC V R 7 database contains data on transcription factors, their experimentally proven binding sites, and regulated genes. The TRANSFAC V R 7 32 programs (such as PATCH and MATCH TM ) use the integrated matrices and site sequences in TRANSFAC V R 7 to perform matrix-or pattern-based searches of factor binding sites in regulatory DNA sequences. The results obtained through in silico analysis of the promoter variants identified in the CP gene are shown in Table 5.…”

Section: Resultsmentioning

confidence: 99%

“…Several bioinformatic databases are available for in silico analysis of the promoter region, of which the following two were used in this study: JASPAR CORE 31 and TRANSFAC V R 7. 32 From TRANS-FAC V R 7, two programs were used, namely PATCH and MATCH TM (v1.0). 33 The default parameters were employed in the use of both of these databases.…”

Section: Computational Analysismentioning

confidence: 99%

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Molecular analysis of Ceruloplasmin in a South African cohort presenting with oesophageal cancer

Strickland

Matsha

Erasmus

et al. 2011

Intl Journal of Cancer

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Oesophageal cancer (OC) is a disease characterized by the development of malignant tumors in the epithelial cells lining the oesophagus. It demonstrates marked ethnic variation, with squamous cell carcinoma (SCC) being more prevalent in the Black population and adenocarcinoma (ADC) occurring more often in Caucasians. The etiology of this complex disease has been attributed to a variety of factors, including an excess of iron (resulting in increased tumourigenesis), oesophageal injury and inflammation (due in part to Barrett's oesophagus and smoking among others). The aim of this study was to determine if genetic variations identified in the ceruloplasmin (CP) gene (implicated in iron homeostasis) contribute to OC pathogenesis or susceptibility. The study cohort consisted of 96 unrelated OC patients from the Black Xhosa-speaking South African population and 88 population-matched control individuals. The promoter and coding regions of the CP gene were analyzed for DNA sequence variation using heteroduplex single-strand conformation polymorphism (HEX-SSCP) analysis, restriction fragment length polymorphism (RFLP) analysis and semi-automated bidirectional DNA sequencing analysis. Fourteen previously described and four novel variants were identified. Statistically significant associations were revealed for two of the novel variants with OC in this study and could, therefore, potentially contribute to disease susceptibility. In silico analysis of the region of the promoter spanning the identified variants sought to identify putative transcription factor binding sites (TFBSs) that could possibly regulate the expression of CP. To our knowledge, this is the first study to examine CP with respect to OC in the Black South African population.

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Section: Resultsmentioning

confidence: 99%

Section: Computational Analysismentioning

confidence: 99%

Molecular analysis of Ceruloplasmin in a South African cohort presenting with oesophageal cancer

Strickland

Matsha

Erasmus

et al. 2011

Intl Journal of Cancer

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“…promoter sequences, on the basis of experimentally determined sites 16 , de novo identification or evolutionary conservation 17,18 . Finally, similar expression profiles allow us to identify target genes that are controlled by a shared regulatory mechanism.…”

Section: From Modules To Regulatory Mechanismsmentioning

confidence: 99%

From signatures to models: understanding cancer using microarrays

et al. 2005

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Genomics has the potential to revolutionize the diagnosis and management of cancer by offering an unprecedented comprehensive view of the molecular underpinnings of pathology. Computational analysis is essential to transform the masses of generated data into a mechanistic understanding of disease. Here we review current research aimed at uncovering the modular organization and function of transcriptional networks and responses in cancer. We first describe how methods that analyze biological processes in terms of higherlevel modules can identify robust signatures of disease mechanisms. We then discuss methods that aim to identify the regulatory mechanisms underlying these modules and processes. Finally, we show how comparative analysis, combining human data with model organisms, can lead to more robust findings. We conclude by discussing the challenges of generalizing these methods from cells to tissues and the opportunities they offer to improve cancer diagnosis and management.

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“…47 48 The MATCHt program 49 (http://www.gene-regulation.com/cgi-bin/pub/programs/match/bin/match.cgi), which is connected to the TRANSFAC s database, 50 was used to determine if the non-coding SNPs located in putative regulatory regions create or destroy any predicted transcription factor binding sites. Two sequences (50 bp) containing the alternate alleles for the SNP of interest were submitted.…”

Section: Bioinformatics Analysismentioning

confidence: 99%

Association analysis of the chromosome 4p-located G protein-coupled receptor 78 (GPR78) gene in bipolar affective disorder and schizophrenia

et al. 2006

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The orphan G protein-coupled receptor 78 (GPR78) gene lies within a region of chromosome 4p where we have previously shown linkage to bipolar affective disorder (BPAD) in a large Scottish family. GPR78 was screened for single-nucleotide polymorphisms (SNPs) and a linkage disequilibrium map was constructed. Six tagging SNPs were selected and tested for association on a sample of 377 BPAD, 392 schizophrenia (SCZ) and 470 control individuals. Using standard v 2 statistics and a backwards logistic regression approach to adjust for the effect of sex, SNP rs1282, located approximately 3 kb upstream of the coding region, was identified as a potentially important variant in SCZ (v 2 P = 0.044; LRT P = 0.065). When the analysis was restricted to females, the strength of association increased to an uncorrected allele P-value of 0.015 (odds ratios (OR) = 1.688, 95% confidence intervals (CI): 1.104-2.581) and uncorrected genotype P-value of 0.015 (OR = 5.991, 95% CI: 1.545-23.232). Under the recessive model, the genotype P-value improved further to 0.005 (OR = 5.618, 95% CI: 1.460-21.617) and remained significant after correcting for multiple testing (P = 0.017). No single-marker association was detected in the SCZ males, in the BPAD individuals or with any other SNP. Haplotype analysis of the case-control samples revealed several global and individual haplotypes, with P-values < 0.05, all but one of which contained SNP rs1282. After correcting for multiple testing, two haplotypes remained significant in both the female BPAD individuals (P = 0.038 and 0.032) and in the full sample of affected female individuals (P = 0.044 and 0.033). Our results provide preliminary evidence for the involvement of GPR78 in susceptibility to BPAD and SCZ in the Scottish population.

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The TRANSFAC system on gene expression regulation

Cited by 589 publications

References 10 publications

Molecular analysis of Ceruloplasmin in a South African cohort presenting with oesophageal cancer

Molecular analysis of Ceruloplasmin in a South African cohort presenting with oesophageal cancer

From signatures to models: understanding cancer using microarrays

Association analysis of the chromosome 4p-located G protein-coupled receptor 78 (GPR78) gene in bipolar affective disorder and schizophrenia

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