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Caltech Wold Lab MicroRNA Target Prediction Using Muscle Atrophy Genes As Models Qing Yuan Mentors: Dr. Barbara Wold Diane Trout Brandon King Gilberto Hernandez, M.D. MicroRNA and MicroRNA Target Prediction Programs A. What are microRNAs? B. What biological function or functions do they perform? C. With which biomolecules do they interact? D. How do microRNA target detection programs predict mRNA/target interaction? E. What information do microRNA target detection programs provide? MicroRNAs: Gene Regulation at the Post-transcriptional Level MicroRNAs are small (17 to 25 nt.) RNA molecules which regulate gene expression by degrading mRNAs of certain genes or interfering with translational machinery of mRNAs. mRNA Degradation mRNA Suppression RISC - RNA induced silencing complex UTR - untranslated region of an mRNA Images from Bartel. (2004) Cell, Vol 116: 281-297 MicroRNA Target Prediction Programs rely on MicroRNA Targeting Promiscuity microRNA1 microRNA1 mRNA 3’ UTR microRNA1 microRNA2 microRNA2 microRNA 1. Multiple 2. One microRNA microRNAs can bind can target bind to theto3’the UTR 3’ UTR of an Known previously unknown mRNA. of one mRNA. target mRNA1 3’ UTR microRNA1 mRNA3 3’ UTR microRNA1 mRNA2 3’ UTR microRNA1 3. A single microRNA can have many distinct mRNA targets. MicroInspector: MicroRNA Target Prediction Using Databases of Known MicroRNAs 3’ 1 2 Region of High Complementarity TGACGTA AUUGCAU 5’ mRNA microRNA 3’ Predicted Structure of mRNA:microRNA Complex mRNA microRNA U Output mRNA 3’UTR miR-A miR-B miR-B miR-C 5’ miR-A miR-A miR-A miR-B miR-B miR-C miR-C Biological Interest: Muscle Atrophy Causes: Prolonged disuse Microgravity Disease Result: Upregulation of muscle protein degradation genes, such as MuRF-1 and MAFbx (ubiquitin ligases) --> Loss of muscle mass NASA Evidence of MicroRNA Involvement in Transcriptional Regulation of Muscle Differentiation A Model miR-1/133 clusters MicroRNAs regulate genes which MEF2 - muscle-related miR-133 miR-1 makefactor muscle. transcription HDAC4 - inhibitor of muscle differentiation SRF SRF - Could myoblast microRNAs regulate proliferation which destroy muscle? MyoD - myogenic differentiation prolif. Myoblast HDAC4 genes MEF2 MyoD diff. Myotube See Chen et al. 2006 for more information Potential MicroRNA Involvement in Muscle Degradation miR-1/133 clusters miR-133 miR-1 SRF HDAC4 MuRF-1 MAFbx MyoD MEF2 prolif. Myoblast diff. Myotube microRNAregulated? Could microRNA target detection programs be used to identify the microRNAs regulating MuRF-1 and MAFbx? Chen et al. 2006 migo: Identifying Genes with Multiple Common microRNA Binding Sites • Created by Diane Trout from the Caltech Wold Lab • Identification of microRNA binding sites by known microRNAs for multiple genes • Visualization of binding site profile for genes using TreeView List of Genes: Gene1 Gene2 Gene3 miRBase … miRNA 1 miRNA 3 miRNA 5 miRNA 2 … miRNA 1 miRNA 2 miRNA 3 Gene 1 3 1 10 Gene 2 5 2 0 Gene 3 17 5 2 Microinspector microRNA target detection XClust 2-D hierarchical clustering TreeView 2-D hierarchical clustering Microinspector - Tabler Lab XClust - Eisen Lab TreeView - Eisen Lab migo Visualization Problem • Linkage analysis: how subtrees are combined single, average and complete • XClust bug identical entries not grouped together immediately problem avoided by using complete linkage analysis instead of average linkage analysis • Alternative: PyCluster offers different types of linkage analysis; user can avoid the bug associated with average linkage analysis migo Screenshot: Results Viewed Using TreeView list of microRNAs which target one or multiple mRNA transcript submitted Gene Info (retrieved by migo from NCBI) migo mRNA:microRNA binding profile migo Screenshot: Results Viewed Using TreeView microLink - A First Addition To Migo MuRF1 • It allows the user to use genes for positive or negative control to select or exclude microRNA candidates. • It allows the user to visually inspect results and select strong microRNA candidates with ease. MAFbx miRs How is migo different from MicroInspector? a list of microRNAs and their putative binding sites a mRNA sequence or a Gene ID Disadvantage: High Number of False Positives a list of Gene IDs migo a list of microRNAs shared between every two genes Helps the user select microRNA candidates microLink Screenshot Figure 1: a microLink analysis for a list of genes (GUI) • Center is the target gene which the user wants to examine. • On the peripheral are the other genes also submitted. • Thickness of each line connecting every two genes reflect the number of microRNAs they have in common. microLink Screenshot (Cont.) Figure 3: a microLink analysis in text format (right) Figure 4: binding site positions and mRNA:microRNA interaction free energy (below) Future Work • Complete the graphical user interface • Improve the visualization scheme for migo • Implement migo’s own microRNA target detection procedures Acknowledgments • Caltech Wold Lab For your guidance and encouragement • NIH/NSF For supporting our summer program • SoCalBSI2006 faculty and staff For your guidance, encouragement, subways, brownies and much much more…