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pubmed:abstractText |
A computer algorithm, p53MH, was developed, which identifies putative p53 transcription factor DNA-binding sites on a genomewide scale with high power and versatility. With the sequences from the human and mouse genomes, putative p53 DNA-binding elements were identified in a scan of 2,583 human genes and 1,713 mouse orthologs based on the experimental data of el-Deiry et al. [el-Deiry, W. S., Kern, S. E., Pietenpol, J. A., Kinzler, K. W. & Vogelstein, B. (1992) Nat. Genet. 1, 45-49] and Funk et al. [Funk, W. D., Pak, D. T., Karas, R. H., Wright, W. E. & Shay, J. W. (1992) Mol. Cell. Biol. 12, 2866-2871] (http://linkage.rockefeller.edu/p53). The p53 DNA-binding motif consists of a 10-bp palindrome and most commonly a second related palindrome linked by a spacer region. By scanning from the 5' to 3' end of each gene with an additional 10-kb nucleotide sequence appended at each end (most regulatory DNA elements characterized in the literature are in these regions), p53MH computes the binding likelihood for each site under a discrete discriminant model and then outputs ordered scores, corresponding site positions, sequences, and related information. About 300 genes receiving scores greater than a theoretical cut-off value were identified as potential p53 targets. Semiquantitative reverse transcription-PCR experiments were performed in 2 cell lines on 16 genes that were previously unknown regarding their functional relationship to p53 and were found to have high scores in either proximal promoter or possible distal enhancer regions. Ten (approximately 63%) of these genes responded to the presence of p53.
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pubmed:affiliation |
Laboratories of Statistical Genetics and Cancer Biology of The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu
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