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Does GATA3 act in tissue-specific pathways? A meta-analysis-based approach.

ABSTRACT: The GATA3 transcription factor is expressed in many tissues such as the immune system, kidney, brain, endometrium, and mammary epithelial cells. As such it must co-ordinate a diverse transcriptional program to achieve specific outcomes in different tissues. One of the most interesting questions raised is whether GATA3 will be involved in the same pathways in every tissue or will be involved in distinct regulatory networks within different tissue types? While previous studies may imply the latter, with some known targets of GATA3 perhaps being specific to cell-type or tissue-type, the question has not been systematically addressed until now. With the advent of techniques such as co-expression meta-analysis a better understanding of the pathway partners of GATA3 can be obtained and specifically the partners within different tissue types can be found, yielding leads for future studies. Here, a recent technique of meta-analysis from the Oncomine database has been employed to probe this very question. Data obtained implies that GATA3 is involved in distinct pathways in different tissue types.

SUBMITTER: Wilson BJ

PROVIDER: S-EPMC2669725 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Does GATA3 act in tissue-specific pathways? A meta-analysis-based approach.

Wilson Brian J BJ

Journal of carcinogenesis 20080101

The GATA3 transcription factor is expressed in many tissues such as the immune system, kidney, brain, endometrium, and mammary epithelial cells. As such it must co-ordinate a diverse transcriptional program to achieve specific outcomes in different tissues. One of the most interesting questions raised is whether GATA3 will be involved in the same pathways in every tissue or will be involved in distinct regulatory networks within different tissue types? While previous studies may imply the latter ...[more]

PMID: 19008565

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Project description:BackgroundIn the recent years, there has been a rise in gene expression profiling reports. Unfortunately, it has not been possible to make maximum use of available gene expression data. Many databases and programs can be used to derive the possible expression patterns of mammalian genes, based on existing data. However, these available resources have limitations. For example, it is not possible to obtain a list of genes that are expressed in certain conditions. To overcome such limitations, we have taken up a new strategy to predict gene expression patterns using available information, for one tissue at a time.ResultsThe first step of this approach involved manual collection of maximum data derived from large-scale (genome-wide) gene expression studies, pertaining to mammalian testis. These data have been compiled into a Mammalian Gene Expression Testis-database (MGEx-Tdb). This process resulted in a richer collection of gene expression data compared to other databases/resources, for multiple testicular conditions. The gene-lists collected this way in turn were exploited to derive a 'consensus' expression status for each gene, across studies. The expression information obtained from the newly developed database mostly agreed with results from multiple small-scale studies on selected genes. A comparative analysis showed that MGEx-Tdb can retrieve the gene expression information more efficiently than other commonly used databases. It has the ability to provide a clear expression status (transcribed or dormant) for most genes, in the testis tissue, under several specific physiological/experimental conditions and/or cell-types.ConclusionsManual compilation of gene expression data, which can be a painstaking process, followed by a consensus expression status determination for specific locations and conditions, can be a reliable way of making use of the existing data to predict gene expression patterns. MGEx-Tdb provides expression information for 14 different combinations of specific locations and conditions in humans (25,158 genes), 79 in mice (22,919 genes) and 23 in rats (14,108 genes). It is also the first system that can predict expression of genes with a 'reliability-score', which is calculated based on the extent of agreements and contradictions across gene-sets/studies. This new platform is publicly available at the following web address: http://resource.ibab.ac.in/MGEx-Tdb/.

Dataset Information

Does GATA3 act in tissue-specific pathways? A meta-analysis-based approach.

Publications

Does GATA3 act in tissue-specific pathways? A meta-analysis-based approach.

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