Literature DB >> 16606849

DNA motifs in human and mouse proximal promoters predict tissue-specific expression.

Andrew D Smith1, Pavel Sumazin, Zhenyu Xuan, Michael Q Zhang.   

Abstract

Comprehensive identification of cis-regulatory elements is necessary for accurately reconstructing gene regulatory networks. We studied proximal promoters of human and mouse genes with differential expression across 56 terminally differentiated tissues. Using in silico techniques to discover, evaluate, and model interactions among sequence elements, we systematically identified regulatory modules that distinguish elevated from inhibited expression in the corresponding transcripts. We used these putative regulatory modules to construct a single predictive model for each of the 56 tissues. These predictors distinguish tissue-specific elevated from inhibited expression with statistical significance in 80% of the tissues (45 of 56). The predictors also reveal synergy between cis-regulatory modules and explain large-scale tissue-specific differential expression. For testis and liver, the predictors include computationally predicted motifs. For most other tissues, the predictors reveal synergy between experimentally verified motifs and indicate genes that are regulated by similar tissue-specific machinery. The identification in proximal promoters of cis-regulatory modules with tissue-specific activity lays the groundwork for complete characterization and deciphering of cis-regulatory DNA code in mammalian genomes.

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Year:  2006        PMID: 16606849      PMCID: PMC1458868          DOI: 10.1073/pnas.0508169103

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  49 in total

1.  Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.

Authors:  G Z Hertz; G D Stormo
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2.  Similarity of position frequency matrices for transcription factor binding sites.

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-01-24       Impact factor: 11.205

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Review 8.  Going the distance: a current view of enhancer action.

Authors:  E M Blackwood; J T Kadonaga
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9.  Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals.

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10.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
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  66 in total

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9.  Comparative analysis of distinct non-coding characteristics potentially contributing to the divergence of human tissue-specific genes.

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10.  Identification of interacting transcription factors regulating tissue gene expression in human.

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