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In a significant leap forward in the understanding of how specific types of tissue are determined to develop in mammals, an international team of scientists has succeeded in mapping the entire network of DNA-binding transcription factors and their interactions. This global network, indicating which factors can combine to determine cell fate, will be published in the March 5 issue of the journal Cell.
Transcription factors (TFs) are proteins that bind to specific DNA sequences in order to direct which genes should be turned on or off in a tissue. Tissue specificity whether embryonic tissue develops into lungs or kidneys or skin, for example is determined by how and which TFs bind to genes. Between 2,000 and 3,000 transcription factor proteins are encoded by the human genome, potentially creating more than 4 million potential protein pairings.
It has long been appreciated that different combinations of TFs are active in different tissues. But given the enormous number of TFs and potential pairings, it has been difficult to precisely identify which combinations are functional, according to principal investigator Trey Ideker, PhD, chief of the Division of Genetics at the University of California, San Diego, School of Medicine.
The integrated approach to systematically map all possible combinations of TFs in mammals has generated large data sets in both humans and mice. The complete network contains 762 human and 877 mouse interactions between TFs, indicating TF pairs that can work in combination.
"The availability of this large combinatorial network of transcription factors will provide scientists with many opportunities to study gene regulation, tissue differentiation and evolution in mammals," said Ideker, professor in the Department of Medicine and at UCSD's Jacobs School of Engineering. He added that analysis of the network shows that highly connected TFs are broadly expressed across tissues, and that roughly hal
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| Contact: Debra Kain ddkain@ucsd.edu 619-543-6163 University of California - San Diego Source:Eurekalert |
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