Alternative Promoter Usage in Specific Gene Expression

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DESCRIPTION: (provided by applicant) Transcriptional regulation is extremely important and highly complex in humans. In this project, we focus on the transcriptional regulation of alternative first exons in a tissue specific manner. First exons are often poorly characterized in eukaryotic genomes. Furthermore, alternative first exons can reside in genomic locations that are far apart from each other, leading to distinct usage of proximal promoters. There are numerous examples in the literature on widely separated alternative promoters that are responsible for tissue specific expression. The central hypothesis of this proposal is that alternative splicing of first exons is indicative of alternative proximal promoter usage, which will be an important factor in our identification of functional cis-element clusters that regulate differential tissue-specific gene expressions. The project tightly couples the computational expertise in Weng's laboratory with the extremely sensitive and quantitative gene expression technique recently developed by Ding and Cantor at Boston University. We will computationally characterize all genes in the 30 Mb of human sequence selected by the ENCODE project, identify ~ 100 genes with alternative first exon splicing, study the expression levels of splicing variants in major tissue types, and investigate the cis-elements in the promoters of these genes that could account for their transcriptional regulation. The project has four specific aims: 1) Computationally analyze the ENCODE sequences and select ~100 genes that exhibit both alternative first exon usage and tissue specific expression patterns; 2) Experimentally validate first exon usage for all genes identified in Aim 1 and measure their expression levels in ten major tissue types; 3) Computationally predict cis-element clusters in the alternative proximal promoters of the genes and select ~40 most confident predictions that may account for tissue-specific expressions; and 4) Experimentally test the ~40 computational predictions using transfection assays in five cell lines.