Model-based identification of cis-acting elements from microarray data.
Identification of transcriptional regulatory motifs continues to be a challenging problem in computational biology. We report a model-based procedure, MotifModeler, that uses global gene expression data to (1) identify cis-acting elements (CAE) that regulate gene expression under a given condition and (2) estimate the effects of the CAE on gene expression. MotifModeler repeatedly tests random subsets of all possible motifs of a given size and selects those that best fit a combinatorial model of the expression levels. We tested MotifModeler using data from a microarray experiment on the effects of interferon-alpha in peripheral blood monocytes. Focusing on 6-bp motifs, we predicted 16 stimulatory and 4 inhibitory motifs. Motifs were extended and compared to known binding sites in the TRANSFAC database using position-specific scoring matrices. Many predicted CAE match sites known to be involved in interferon action. MotifModeler demonstrated the potential to computationally identify CAE important in gene regulation.
Liu
Yunlong
Y
Department of Biochemistry and Molecular Biology and Center for Medical Genomics, Indiana University School of Medicine, 635 Barnhill Drive MS 4063, Indianapolis, IN 46202, USA.
Taylor
Milton W
MW
Edenberg
Howard J
HJ
D020816:Amino Acid Motifs; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation; D006801:Humans; D016898:Interferon-alpha / Q000494:pharmacology; D008962:Models, Theoretical; D009000:Monocytes / Q000187:drug effects / Q000502:physiology; D020411:Oligonucleotide Array Sequence Analysis; D012045:Regulatory Sequences, Nucleic Acid; D020218:Response Elements; D014157:Transcription Factors / Q000378:metabolism*
D016898:Interferon-alpha; D014157:Transcription Factors