1. MiRNA in computational biology 1 The Nobel Prize in Physiology or Medicine for 2006 Andrew Z. Fire and Craig C. Mello for their discovery of "RNA interference – gene silencing by double-stranded RNA"

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3. contents Introduction miRNA Computational identification of miRNA Computational identification of target miRNA miRNA database 3 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

4. Introduction miRNA MicroRNA are one class of newly identified riboregulators of gene expression in many eukaryotic organism. Mature miRNA have 20-24 nucleotides 4 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

5. Tasks of miRNA They play important roles in multiple biological and metabolic processes, including  Developmental timing  Signal transduction  Differentiation  Cell fate identity  Diseases and carcinogenesis 5 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

6. Coordinated action of miRNA nodes in developmental timing and tailoring leaf shape 6 www.cs.ucf.edu/~shzhang/CAP5510/lec14.ppt

7. Produce mature miRNA Mature miRNA formation requires a multiple –step process. I. miRNA gene is first transcribed to a primary miRNA by Pol II enzyme II. Cleaved to a stem loop intermediate termed pre- miRNA by Drosha III. Pre-miRNAs are further cleaved to miRNA: miRNA* duplex IV. Mature miRNA are releaseed for regulating targeted gene expression 7 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

8. How microRNA regulates the target mRNA genes 8 www.cs.ucf.edu/~shzhang/CAP5510/lec14.ppt

9. Major characterstics of microRNAs Hairpin-shaped secondary structures High conservation for some miRNA High minimal folding free energy index 9 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

10. History identification of miRNA miRNAS were initially identified by a genetic screening technology Recently, direct cloning of miRNAs, followed by small RNA isolation Computational approaches 10 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

11. Computational approaches The principles of computational approaches are base on I. Hairpin-shaped stem loop secondary structure II. High evolutionary conservation III. High minimal folding free energy index 11 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

12. classification The computational approaches can be classified into five major categories I. Homology search-based II. Gene search III. Neighbor stem loop search IV. Algorithms based on comparative genomics V. Phylogentic shadowing-based 12 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

13. Homology search-based approach Identifying miRNA genes by searching nucleotide database using BLOST program It was well recognized that miRNA are evolutionarily conserved Profile-based search programs, such as I. ERPIN II. miAlign 13 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

14. Classification of homology s.. I. GENOME-BASE SEARCH II. ESTS-BASE SEARCH Partial cDNA sequences of expressed gened cloned into a plasmid A powerfull approach to identify miRNA genes in species whose genome sequence are not available 14 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

15. GENE-FINDING APPROACH Gene-finding approaches are designed for predicting animal miRNA Not depend on homology or miRNA conservation 15 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

16. How gene-finding work I. First need to identify conserved genomic regions II. These regions into a window 110-n III. Using a specific computer program 16 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

17. How program work Window is folded with secondary structure program such as mfold or RNA fold hairpin-shaped stem loops for potential miRNA candidates 17 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

18. Computer programs homology search based MiRseeker  analyzing conserved sequences that adopt an extended stem loop secondary structure  Accuracy 75% for Drosophila miRNA miRscan  Identify miRNA base on common characteristics (such as base pairing and nucleotide bias ) 18 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

19. MiRscan Scan to find conserve hairpin structures Using known miRNA genes at training set 19 Yong Huang. The discovery approaches and detection methods of microRNAs

20. Processes of MiRscan I. A 110-nt window along both strand II. Folding the window with RNAfold III. A folding free energy of as a least -25 kcal/mol IV. Passing a 21-nt window along each stem-loop V. Assigning a log likelihood score to each position for its similarity to know miRNA 20 Yong Huang. The discovery approaches and detection methods of microRNAs

21. Program online 21 http:// bioinforma.weebly.com/mirna-prediction.html

22. MiRscan 22 http:// bioinforma.weebly.com/mirna-prediction.html

23. Computational identification of microRNA TARGETS A high degree of complementarity to the miRNAs This allows the prediction of miRNA targets by computational approaches 23 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

24. Computational approaches are based on MiRNA are perfectly or near perfectly complementary to their target miRNA The RNA-RNA duplex has a higher negative folding free energy Binding sites of mRNA and miRNA is highly conserved 24 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

25. programs Find miRNA Mir check Target scan MiRanda 25 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

26. miRNA database miR Base ASRP miRna AMap 26 Boahong zhang,xiaoping pan, 2006. computational identification of miroRNA

27. THANK YOU END 27