Biomedical subjects

Suisheng Tang

Publications and source records attributed to Suisheng Tang.

5 recordsLinked to original sources

PubMed2006

KBERG: KnowledgeBase for Estrogen Responsive Genes.

Estrogen has a profound impact on human physiology affecting transcription of numerous genes. To decipher functional characteristics of estrogen responsive genes, we developed KnowledgeBase for Estrogen Responsive Genes (KBERG). Genes in KBERG were derived from Estrogen Responsive Gene Database (ERGDB) and were analyzed from multiple aspects. We explored the possible transcription regulation mechanism by capturing highly conserved promoter motifs across orthologous genes, using promoter regions that cover the range of [-1200, +500] relative to the transcription start sites. The motif detection is based on ab initio discovery of common cis-elements from the orthologous gene cluster from human, mouse and rat, thus reflecting a degree of promoter sequence preservation during evolution. The identified motifs are linked to transcription factor binding sites based on the TRANSFAC database. In addition, KBERG uses two established ontology systems, GO and eVOC, to associate genes with their function. Users may assess gene functionality through the description terms in GO. Alternatively, they can gain gene co-expression information through evidence from human EST libraries via eVOC. KBERG is a user-friendly system that provides links to other relevant resources such as ERGDB, UniGene, Entrez Gene, HomoloGene, GO, eVOC and GenBank, and thus offers a platform for functional exploration and potential annotation of genes responsive to estrogen. KBERG database can be accessed at http://research.i2r.a-star.edu.sg/kberg.

Animals↗

PubMed2004

Computational method for discovery of estrogen responsive genes.

Estrogen has a profound impact on human physiology and affects numerous genes. The classical estrogen reaction is mediated by its receptors (ERs), which bind to the estrogen response elements (EREs) in target gene's promoter region. Due to tedious and expensive experiments, a limited number of human genes are functionally well characterized. It is still unclear how many and which human genes respond to estrogen treatment. We propose a simple, economic, yet effective computational method to predict a subclass of estrogen responsive genes. Our method relies on the similarity of ERE frames across different promoters in the human genome. Matching ERE frames of a test set of 60 known estrogen responsive genes to the collection of over 18,000 human promoters, we obtained 604 candidate genes. Evaluating our result by comparison with the published microarray data and literature, we found that more than half (53.6%, 324/604) of predicted candidate genes are responsive to estrogen. We believe this method can significantly reduce the number of testing potential estrogen target genes and provide functional clues for annotating part of genes that lack functional information.

Computational Biology↗

PubMed2004

Discovery of estrogen receptor alpha target genes and response elements in breast tumor cells.

BACKGROUND: Estrogens and their receptors are important in human development, physiology and disease. In this study, we utilized an integrated genome-wide molecular and computational approach to characterize the interaction between the activated estrogen receptor (ER) and the regulatory elements of candidate target genes. RESULTS: Of around 19,000 genes surveyed in this study, we observed 137 ER-regulated genes in T-47D cells, of which only 89 were direct target genes. Meta-analysis of heterogeneous in vitro and in vivo datasets showed that the expression profiles in T-47D and MCF-7 cells are remarkably similar and overlap with genes differentially expressed between ER-positive and ER-negative tumors. Computational analysis revealed a significant enrichment of putative estrogen response elements (EREs) in the cis-regulatory regions of direct target genes. Chromatin immunoprecipitation confirmed ligand-dependent ER binding at the computationally predicted EREs in our highest ranked ER direct target genes, NRIP1, GREB1 and ABCA3. Wider examination of the cis-regulatory regions flanking the transcriptional start sites showed species conservation in mouse-human comparisons in only 6% of predicted EREs. CONCLUSIONS: Only a small core set of human genes, validated across experimental systems and closely associated with ER status in breast tumors, appear to be sufficient to induce ER effects in breast cancer cells. That cis-regulatory regions of these core ER target genes are poorly conserved suggests that different evolutionary mechanisms are operative at transcriptional control elements than at coding regions. These results predict that certain biological effects of estrogen signaling will differ between mouse and human to a larger extent than previously thought.

Binding Sites↗

PubMed2004

ERGDB: Estrogen Responsive Genes Database.

ERGDB is an integrated knowledge database dedicated to genes responsive to estrogen. Genes included in ERGDB are those whose expression levels are experimentally proven to be either up-regulated or down-regulated by estrogen. Genes included are identified based on publications from the PubMed database and each record has been manually examined, evaluated and selected for inclusion by biologists. ERGDB aims to be a unified gateway to store, search, retrieve and update information about estrogen responsive genes. Each record contains links to relevant databases, such as GenBank, LocusLink, Refseq, PubMed and ATCC. The unique feature of ERGDB is that it contains information on the dependence of gene reactions on experimental conditions. In addition to basic information about the genes, information for each record includes gene functional description, experimental methods used, tissue or cell type, gene reaction, estrogen exposure time and the summary of putative estrogen response elements if the gene's promoter sequence was available. Through a web interface at http://sdmc.i2r.a-star.edu.sg/ergdb/ cgi-bin/explore.pl users can either browse or query ERGDB. Access is free for academic and non-profit users.

Animals↗

PubMed2003

Dragon ERE Finder version 2: A tool for accurate detection and analysis of estrogen response elements in vertebrate genomes.

We present a unique program for identification of estrogen response elements (EREs) in genomic DNA and related analyses. The detection algorithm was tested on several large datasets and makes one prediction in 13 300 nt while achieving a sensitivity of 83%. Users can further investigate selected regions around the identified ERE patterns for transcription factor binding sites based on the TRANSFAC database. It is also possible to search for candidate human genes with a match for the identified EREs and their flanking regions within EPD annotated promoters. Additionally, users can search among the extended promoter regions of approximately 11 000 human genes for those that have a high degree of similarity to the identified ERE patterns. Dragon ERE Finder version 2 is freely available for academic and non-profit users (http://sdmc.lit.org.sg/ERE-V2/index).

Algorithms↗