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Computational method for discovery of estrogen responsive genes.

ABSTRACT: 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.

SUBMITTER: Tang S

PROVIDER: S-EPMC535661 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature

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Computational method for discovery of estrogen responsive genes.

Tang Suisheng S Tan Sin Lam SL Ramadoss Suresh Kumar SK Kumar Arun Prashanth AP Tang Man-Hung Eric MH Bajic Vladimir B VB

Nucleic acids research 20041201 21

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 predi ...[more]

PMID: 15576347

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Project description:In women, the flow of psoriasis is influenced by each phase of a woman's life cycle. According to previous findings, significant changes in the levels of sex hormones affect the severity of the disease. Aim: The aim of this study was to identify the estrogen-responsive genes that could be responsible for the exacerbation of psoriasis in menopausal women. Methods: Skin samples of lesional skin donated by psoriasis patients (n = 5) were compared with skin samples of healthy volunteers (n = 5) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The set of differentially expressed proteins was subjected to protein ontology analysis to identify differentially expressed estrogen-responsive proteins. The expression of discovered proteins was validated by qPCR and ELISA on four groups of female participants. The first group included ten psoriasis patients without menopause; the second included eleven postmenopausal patients; the third included five healthy volunteers without menopause; and the fourth included six postmenopausal volunteers. Moreover, the participants' blood samples were used to assess the levels of estradiol, progesterone, and testosterone. Results: We found that the levels of estradiol and progesterone were significantly lower and the levels of testosterone were significantly higher in the blood of patients compared to the control. The protein ontology analysis of LC-MS/MS data identified six proteins, namely HMOX1, KRT19, LDHA, HSPD1, MAPK1, and CA2, differentially expressed in the lesional skin of female patients compared to male patients. ELISA and qPCR experiments confirmed differential expression of the named proteins and their mRNA. The genes encoding the named proteins were differentially expressed in patients compared to volunteers. However, KRT19 and LDHA were not differentially expressed when we compared patients with and without menopause. All genes, except MAPK1, were differentially expressed in patients with menopause compared to the volunteers with menopause. HMOX1, KRT19, HSPD1, and LDHA were differentially expressed in patients without menopause compared to the volunteers without menopause. However, no significant changes were found when we compared healthy volunteers with and without menopause. Conclusion: Our experiments discovered a differential expression of six estrogen-controlled genes in the skin of female patients. Identification of these genes and assessment of the changes in their expression provide insight into the biological effects of estrogen in lesional skin. The results of proteomic analysis are available via ProteomeXchange with identifier PXD021673.

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Computational method for discovery of estrogen responsive genes.

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Computational method for discovery of estrogen responsive genes.

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