RNA binding proteins can have 100s to 1000s of target mRNAs thanks to flexibility in recognizing their binding sites. These sites can incorporate both sequence and structural elements and show tremendous variation when binding motifs of different RBPs are compared, even among members of the same RBP family. Until early 2000s, characterization of binding sites was mostly restricted to individual studies involving a particular RBP and a target gene/binding motif. Only in the last decade, en masse identification of in vivo binding motifs became possible;first with the RIP-chip approach and then with CLIP and RIP-seq. These last two methods incorporate the power of deep sequencing, allowing us not only to identify more binding sites but also to conduct a more refined mapping. One area that urges attention is the development of computational methods to perform comprehensive analyses of datasets generated by these techniques. In this project we will profile targets for five RBPs with RIP-seq in two colon cancer cell lines. We will design and implement a framework for characterizing the binding specificity of RNA binding proteins. We will evaluate and refine methodology for RBP target identification from such data. Finally, we will develop a database of information about RNA-binding proteins, their target genes, binding sites and binding specificities.

Public Health Relevance

The identification of sequence encoded factors that influence human gene expression is central to our understanding of how gene expression is regulated. Analytical methodology developed in this project will enable researchers to leverage the full potential of cutting-edge and emerging experimental technologies for profiling regulatory activities of RNA binding proteins. Understanding the regulatory functions of RNA binding proteins has implications for our understanding of several diseases, including cancers and developmental diseases.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
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Feingold, Elise A
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University of Southern California
Schools of Arts and Sciences
Los Angeles
United States
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Li, Wenzheng; Wang, Weili; Uren, Philip J et al. (2017) Riborex: fast and flexible identification of differential translation from Ribo-seq data. Bioinformatics 33:1735-1737
Chen, Haifeng; Smith, Andrew D; Chen, Ting (2016) WALT: fast and accurate read mapping for bisulfite sequencing. Bioinformatics 32:3507-3509
Uren, Philip J; Bahrami-Samani, Emad; de Araujo, Patricia Rosa et al. (2016) High-throughput analyses of hnRNP H1 dissects its multi-functional aspect. RNA Biol 13:400-11
Ennajdaoui, Hanane; Howard, Jonathan M; Sterne-Weiler, Timothy et al. (2016) IGF2BP3 Modulates the Interaction of Invasion-Associated Transcripts with RISC. Cell Rep 15:1876-83
de Araujo, Patricia Rosa; Gorthi, Aparna; da Silva, Acarizia E et al. (2016) Musashi1 Impacts Radio-Resistance in Glioblastoma by Controlling DNA-Protein Kinase Catalytic Subunit. Am J Pathol 186:2271-8
Uren, Philip J; Vo, Dat T; de Araujo, Patricia Rosa et al. (2015) RNA-Binding Protein Musashi1 Is a Central Regulator of Adhesion Pathways in Glioblastoma. Mol Cell Biol 35:2965-78
Bahrami-Samani, Emad; Vo, Dat T; de Araujo, Patricia Rosa et al. (2015) Computational challenges, tools, and resources for analyzing co- and post-transcriptional events in high throughput. Wiley Interdiscip Rev RNA 6:291-310
Bahrami-Samani, Emad; Penalva, Luiz O F; Smith, Andrew D et al. (2015) Leveraging cross-link modification events in CLIP-seq for motif discovery. Nucleic Acids Res 43:95-103
Cambuli, F M; Correa, B R; Rezza, A et al. (2015) A Mouse Model of Targeted Musashi1 Expression in Whole Intestinal Epithelium Suggests Regulatory Roles in Cell Cycle and Stemness. Stem Cells 33:3621-34
Tamim, Saleh; Vo, Dat T; Uren, Philip J et al. (2014) Genomic analyses reveal broad impact of miR-137 on genes associated with malignant transformation and neuronal differentiation in glioblastoma cells. PLoS One 9:e85591

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