It is well known that microRNAs could play a fundamental role in regulation of diverse cellular functions. As key gene regulators, microRNAs work through a posttranscriptional repression mechanism. Increasing evidence indicates that deregulation of microRNA expression could lead to a variety of disorders including human cancer. Although significant progress has been made in the past years in discovery of microRNAs and their biogenesis, and their role in many cellular phenotypes, it is not fully understood how microRNAs exert their cellular functions because a single microRNA can have hundreds of targets. Hence, identification of microRNA targets is a critical step toward understanding of molecular mechanisms of microRNA-mediated gene expression in normal and disease processes. Currently, this largely relies on computer-aided algorithms, which unfortunately are still unable to provide a precise picture of microRNA regulatory networks, and thus the predicted targets need further experimental validations. It is evident that target validation is a bottle neck in our effort to dissect microRNA pathways. In this application, we propose to develop a novel selection method for microRNA target validation and identification through two complementary approaches. The first approach is to determine microRNA/mRNA interactions using our pre-microRNA collection against a specific target cloned in our selection plasmid;the second approach is to determine microRNA/mRNA interactions using a 3'-UTR (untranslated region) library against a specific microRNA. We believe that our selection method is innovative, simple and powerful. An additional benefit of this method will allow us to determine whether there are any new features, besides the seed sequence homology, which could contribute to the specificity of microRNA targeting. Accordingly, this study will greatly enhance our understanding of microRNA targeting and gene regulation by providing a valuable research tool.
MicroRNAs are master gene regulators that work through a posttranscriptional repression mechanism. A single microRNA could target hundreds of targets. However, we do not have a full picture of microRNA/mRNA interactions yet. This study will develop a selection system to systematically determine microRNA/mRNA interactions. The success of this study will benefit microRNA research fields by providing a simple but powerful tool for microRNA target validation and identification.
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