MicroRNAs (miRNAs) are extensively involved in many diverse biological processes and a single miRNA can regulate the expression of hundreds of gene targets. Changes in miRNA expression can have profound biological impacts, leading to a variety of human diseases. Thus, functional characterization of miRNAs has become one of the most active research fields in biology in recent years. Despite rapid progress in miRNA research, one major obstacle in this field is the lack of robust computational and experimental methods for functional miRNA analysis. 1) On the experimental side, there is a strong demand to develop new methods that can potently suppress the expression of miRNAs for loss-of-function analysis. 2) On the computational side, improved target prediction tools are strongly demanded, as accurate prediction of miRNA targets is a critical first step for miRNA functional analysis. Further, there is a lack of comprehensive online resources for functional analysis of miRNAs by accessing data from both computational and experimental sources. To address these issues, we propose to develop new methods for both computational and experimental analyses of miRNAs. These new methods will be based on recent progress from our research supported by this R01 grant. All newly generated computational and experimental resources will be integratively presented in an online miRNA database, with experimental reagents freely distributed to the research community.

Public Health Relevance

MicroRNAs are involved in many diverse biological processes and a single microRNA can modulate the expression of hundreds of gene targets. The major goal of this study is to develop new methods for both computational and experimental analyses of miRNAs. The successful completion of this project will significantly advance our ability to understand the gene regulation by microRNAs in a variety of normal physiological processes and disease states.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM089784-09
Application #
9731508
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Ravichandran, Veerasamy
Project Start
2010-04-01
Project End
2020-02-29
Budget Start
2019-07-01
Budget End
2020-02-29
Support Year
9
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Washington University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
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Wong, Nathan W; Chen, Yuhao; Chen, Shuai et al. (2018) OncomiR: an online resource for exploring pan-cancer microRNA dysregulation. Bioinformatics 34:713-715
Liu, Weijun; Chen, Hanxiang; Wong, Nathan et al. (2017) Pseudohypoxia induced by miR-126 deactivation promotes migration and therapeutic resistance in renal cell carcinoma. Cancer Lett 394:65-75
Wong, Nathan; Khwaja, Shariq S; Baker, Callie M et al. (2016) Prognostic microRNA signatures derived from The Cancer Genome Atlas for head and neck squamous cell carcinomas. Cancer Med 5:1619-28
Zhou, Yunying; Zhang, Qishu; Gao, Ge et al. (2016) Role of WDHD1 in Human Papillomavirus-Mediated Oncogenesis Identified by Transcriptional Profiling of E7-Expressing Cells. J Virol 90:6071-6084
Wang, Xiaowei (2016) Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies. Bioinformatics 32:1316-22
Wong, Nathan; Liu, Weijun; Wang, Xiaowei (2015) WU-CRISPR: characteristics of functional guide RNAs for the CRISPR/Cas9 system. Genome Biol 16:218
Wong, Nathan; Wang, Xiaowei (2015) miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res 43:D146-52
Liu, Weijun; Gao, Ge; Hu, Xiaoxia et al. (2014) Activation of miR-9 by human papillomavirus in cervical cancer. Oncotarget 5:11620-30
Wang, Xiaowei (2014) Composition of seed sequence is a major determinant of microRNA targeting patterns. Bioinformatics 30:1377-83

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