Genome-wide mapping of DNA-protein interactions in eukaryotes
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The genome of an organism encodes thousands of genes, and their expression needs to be precisely controlled at the right place and time for normal cellular functioning. Control of gene expression occurs predominantly at the level of transcription and the transcription of a particular gene is determined by the interactions between diverse regulatory proteins and their specific cis-acting binding elements. However, our understanding about how and when transcription factors function in the context of the whole genome is limited. Hundreds to thousands of transcription factors can potentially interact with DNA in the genome and modulate the level of transcription of protein coding genes into mRNAs in response to regulatory signals. Identifying the chromosomal targets of regulatory transcription factors in various conditions is crucial for reconstructing the transcriptional regulatory networks underlying global gene expression programs. Recently-developed chromatin immunoprecipitation (ChIP)-based genome-wide studies such as ChIP-microarrays allow us to identify the genomic loci occupied by transcription factors in vivo. In combination with expression profiling analysis, the ChIP-microarray method is a powerful tool to study DNA-protein interactions in vivo. However, there are some limitations to applying this ChIP-microarray method to every sequenced large genome due to the complexity and size of large genomes such as human or mouse. To gain a better understanding of the functions of transcription factors in mediating eukaryotic gene regulation, we performed ChIP-microarray analysis in yeast and human systems. First, we determined the role of the yeast TATA-box binding protein (TBP) in controlling global gene expression and revealed that PolIII genes are the strongest targets of TBP in yeast. Second, we determined that the human oncogenic transcription factor Myc has more than a thousand target genes in human cells. Finally, to address some of the current limitations in ChIP-microarrays, we developed an alternative method, sequence tag analysis of genomic enrichment (STAGE), to study genome-wide mapping of DNA-protein interactions.