title: Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data.
abstract: BACKGROUND
  A key step in the regulation of gene expression is the sequence-specific binding of transcription factors (TFs) to their DNA recognition sites. However, elucidating TF binding site (TFBS) motifs in higher eukaryotes has been challenging, even when employing cross-species sequence conservation. We hypothesized that for human and mouse, many orthologous genes expressed in a similarly tissue-specific manner in both human and mouse gene expression data, are likely to be co-regulated by orthologous TFs that bind to DNA sequence motifs present within noncoding sequence conserved between these genomes.
  
  
  RESULTS
  We performed automated motif searching and merging across four different motif finding algorithms, followed by filtering of the resulting motifs for those that contain blocks of information content. Applying this motif finding strategy to conserved noncoding regions surrounding co-expressed tissue-specific human genes allowed us to discover both previously known, and many novel candidate, regulatory DNA motifs in all 18 tissue-specific expression clusters that we examined. For previously known TFBS motifs, we observed that if a TF was expressed in the specified tissue of interest, then in most cases we identified a motif that matched its TRANSFAC motif; conversely, of all those discovered motifs that matched TRANSFAC motifs, most of the corresponding TF transcripts were expressed in the tissue(s) corresponding to the expression cluster for which the motif was found.
  
  
  CONCLUSIONS
  Our results indicate that the integration of the results from multiple motif finding tools identifies and ranks highly more known and novel motifs than does the use of just one of these tools. In addition, we believe that our simultaneous enrichment strategies helped to identify likely human cis regulatory elements. A number of the discovered motifs may correspond to novel binding site motifs for as yet uncharacterized tissue-specific TFs. We expect this strategy to be useful for identifying motifs in other metazoan genomes.
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. bertrand_huber@student.hms.harvard.edu
authors.forename: Bertrand R
authors.initials: BR
authors.lastname: Huber
authors.forename: Martha L
authors.initials: ML
authors.lastname: Bulyk
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D001665:Binding Sites; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008322:Mammals; D008969:Molecular Sequence Data; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011485:Protein Binding; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D018511:Systems Integration; D014157:Transcription Factors / Q000235:genetics*
chemical_list: D014157:Transcription Factors