MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate messenger RNAs (mRNAs) post-transcriptionally. miRNAs induce target messenger RNA degradation or translational inhibition, predominantly through cognitive binding sites in the 3 untranslated regions (3UTRs). Accurate identification of miRNA targets is essential for the understanding of their functions. Target identification has been a major challenge for understanding this recently recognized exciting dimension of gene regulation. To this end, computational target prediction methods have proven to be valuable. However, current prediction methods suffer from a number of limitations that hinder progress. Recently, biochemical purification and high throughput deep-sequencing have become feasible. Furthermore, we have developed a high-throughput methodology to experimentally test thousands of miRNA-3UTR interactions, and have acquired mRNA/miRNA expression data on hundreds of cancer cell lines. These experimental advances have presented us the opportunity to develop state-of-the-art miRNA target prediction algorithms. In this application, we propose to adapt an interdisciplinary approach to develop novel miRNA-target prediction algorithms to overcome the limitations of current prediction algorithms. Our complementary expertise in RNA Bioinformatics and Statistics and large scale experimental testing have placed us in a unique position to pursue the following specific aims: 1) Develop a target prediction algorithm based on deep sequencing data from biochemically purified miRNA-target complexes;2) Perform large-scale miRNA-3UTR reporter assays to derive functional miRNA-target interactions;3) Develop algorithms and perform analyses and validation for more informative predictions on the level of miRNA-mediated regulation and miRNA-regulated pathways and networks;4) Develop user-friendly software tools and database for distribution to the scientific community. This project will advance our understanding of miRNA-mediated gene regulation in molecular biology and systems biology, facilitate development of miRNA-based therapeutics, and in turn benefit human health.

Public Health Relevance

Novel Approaches to Mammalian MicroRNA Target Prediction Project Relevance Accurate identification of microRNA targets is essential for understanding the diverse functions of microRNAs in gene regulation. The computational tools developed from this project will be broadly applicable to mammalian species beyond human and mouse, as well as stem cells and viruses. Thus, this project will contribute to the advancement of microRNA biology, the understanding of microRNA functions in cancer and other human diseases, and the development of microRNA-based therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM099811-02
Application #
8513374
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
2012-07-18
Project End
2016-04-30
Budget Start
2013-05-01
Budget End
2014-04-30
Support Year
2
Fiscal Year
2013
Total Cost
$585,828
Indirect Cost
$100,481
Name
Wadsworth Center
Department
Type
DUNS #
153695478
City
Menands
State
NY
Country
United States
Zip Code
12204
Liu, Chaochun; Rennie, William A; Mallick, Bibekanand et al. (2014) MicroRNA binding sites in C. elegans 3' UTRs. RNA Biol 11:693-701
Liu, Chaochun; Rennie, William A; Carmack, C Steven et al. (2014) Effects of genetic variations on microRNA: target interactions. Nucleic Acids Res 42:9543-52
Rennie, William; Liu, Chaochun; Carmack, C Steven et al. (2014) STarMir: a web server for prediction of microRNA binding sites. Nucleic Acids Res 42:W114-8
Guo, Yanwen; Mastriano, Stephen; Lu, Jun (2014) A high-throughput microRNA expression profiling system. Methods Mol Biol 1176:33-44
Kallen, Amanda N; Zhou, Xiao-Bo; Xu, Jie et al. (2013) The imprinted H19 lncRNA antagonizes let-7 microRNAs. Mol Cell 52:101-12
Liu, Chaochun; Mallick, Bibekanand; Long, Dang et al. (2013) CLIP-based prediction of mammalian microRNA binding sites. Nucleic Acids Res 41:e138
Cheng, Jijun; Guo, Shangqin; Chen, Suning et al. (2013) An extensive network of TET2-targeting MicroRNAs regulates malignant hematopoiesis. Cell Rep 5:471-81