期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 100, 期 6, 页码 3339-3344出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0630591100
关键词
sequence motif discovery; microarray data; correlation; transcription regulation
资金
- NHGRI NIH HHS [R01 HG002518, R01 HG 02518-01] Funding Source: Medline
- NLM NIH HHS [F37 LM007626, 1F37 LM 07626-01] Funding Source: Medline
We propose MOTIF REGRESSOR for discovering sequence motifs upstream of genes that undergo expression changes in a given condition. The method combines the advantages of matrix-based motif finding and oligomer motif-expression regression analysis, resulting in high sensitivity and specificity. MOTIF REGRESSOR is particularly effective in discovering expression-mediating motifs of medium to long width with multiple degenerate positions. When applied to Saccharomyces cerevisiae, MOTIF REGRESSOR identified the ROX1 and YAP1 motifs from Rox1p and Yap1p overexpression experiments, respectively; predicted that Gcn4p may have increased activity in YAP1 deletion mutants; reported a group of motifs (including GCN4, PHO4, MET4, STRE, USR1, RAN, M3A, and M3B) that may mediate the transcriptional response to amino acid starvation; and found all of the known cell-cycle regulation motifs from 18 expression microarrays over two cell cycles.
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