1. 1 RNA Bioinformatics Genes and Secondary Structure Anne Haake Rhys Price Jones & Tex Thompson

2. 2 Types of RNA Coding –mRNA (messenger) Non-Coding –rRNA (ribosomal) –tRNA (transfer) –snRNA (small nuclear;splicing) –RNAseP (ribozyme) –siRNA (small inhibitory) –Others…

3. 3 RNA genes? Recall: Protein-coding genes; we have relatively good methods –Ab initio –Homology-based RNA genes –Poor sequence homology –Secondary structure useful

4. 4 Pictures from the Web

5. 5 Functional Roles: RNA Secondary Structure mRNA –Regulation of transcription termination –Regulation of translation initiation rRNA – ribosomal structure tRNA –adaptor in translation RNA interference –Regulation of gene expression –Anti-viral activity

6. 6 mRNAs have functional secondary structures e.g. Transcription Termination Signal

7. 7 rRNA

8. tRNA

9. 9 Ribozymes: Enzymes made of RNA RNA molecules in Tetrahymena were shown to splice out introns without the aid of proteins Ribozymes have been discovered in higher organisms, and may play a role in processing mRNA

10. 10 Ribonuclease P Enzyme found in many organisms, cleaves the 5’ end of tRNA molecules Heterodimer consisting of a protein molecule and an RNA molecule Without RNA molecule, Ribonuclease P loses all activity Without protein, Ribonuclease P shows only reduced activity

11. 11 Pictures from the Web http://www.mbio.ncsu.edu/RNaseP/rna/t hreed/threed.htmlhttp://www.mbio.ncsu.edu/RNaseP/rna/t hreed/threed.html http://proteinexplorer.org (molecule 1d6t)http://proteinexplorer.org

12. 12 Discovery of Ribonuclease P http://www.mun.ca/biochem/courses/3107 /Lectures/Topics/Splicing.html

13. 13 Can identify RNA genes that belong to a known family Infer secondary structure by comparing sequences (multiple alignments) –e.g. Look for covariance; positions that covary to maintain Watson-Crick base-pairing;implies role in secondary structure Rfam: a collection of multiple alignments and covariance models for ncRNAs Rfam

14. 14 Prediction of RNA Secondary Structure Find the configuration that maximizes the number of base pairs –Scoring all possibilities would be computationally expensive –Use dynamic programming Thermodynamics approach –Mfold: uses an energy minimization method of Zuker –http://www.bioinfo.rpi.edu/applications/mfold/http://www.bioinfo.rpi.edu/applications/mfold/ –http://bioweb.pasteur.fr/seqanal/interfaces/mfold- simple.htmlhttp://bioweb.pasteur.fr/seqanal/interfaces/mfold- simple.html

15. 15 RNA Interference Breakthrough of the year in 2002 Discovered in C. elegans dsRNA involved in sequence-specific gene silencing Post-transcriptional gene silencing 21-25 nucleotide dsRNAs (siRNAs) facilitate the degradation of homologous RNAs

16. 16 RNAi Useful for gene targeting to study function Other techniques for gene targeting –“knock-out” by homologous recombination –Antisense siRNA-direct “knock-down” has potential to allow systematic study of each gene in a pathway siRNA might allow silencing of pathogenic genes or pathogens (e.g. viruses)

17. 17 Mechanism siRNAs: 21-23 nt dsRNA with 2-3 nt 3’ overhangs Produced from cleavage of long dsRNAs by “Dicer” enzyme Form a siRNA-protein complex “RISC” Cleaves homologous mRNA target Also can start with a hairpin precursor rather than dsRNA

18. 18 siRNA demo RNA Interference links and refs

19. 19 Introduction to Proteomics Techniques & Computational Issues

20. 20 Experimental Techniques As with transcriptome analysis, proteome analysis is limited by the techniques currently available But, proteome analysis even more difficult and less precise due to the nature of proteins

21. 21 Two-dimensional Gel Electrophoresis 2D gels First dimension: isoelectric focusing –Separates proteins on basis of charge Second dimension: SDS-PAGE Able to resolve thousands of proteins in a single gel Proteins are usually radioactively labeled

22. 22 Challenges of 2D gel Analysis Reproducibility –Software is available to assist in aligning the spots between gels and integrating the intensities of the spots Identification of the proteins of interest –Some underrepresented e.g. membrane proteins –Some below levels of detection –Which protein is represented by each spot? Mass spectrometry has greatly enhanced ability to identify individual proteins

23. 2-Dimensional Gel Electrophoresis http://us.expasy.org/ For other examples and tools

24. 24 Mass Spectrometry Able to uniquely identify the proteins associated with individual spots in 2D gels –Spots are excised from gels –Proteins are digested into peptide fragments using proteases such as trypsin –Trypsin cleaves peptide bonds next to the amino acids lysine and arginine. –Peptides are ionized for Mass Spec analysis For a quick explanation of Mass Spec see: http://www.jeol.com/ms/docs/whatisms.html

25. 25 Mass Spectrometry Generates a peptide mass fingerprint Computational challenge: the fingerprint must be matched up with the theoretical mass spectrum of the proteins derived from genomics databases Analysis software ProteinProspector

26. 26 Protein Microarrays High-throughput techniques similar to gene chips –Probes (e.g. antibodies) attached to chips –Fluorescently-labeled proteins washed over chips –Fluorescence intensity indicative of relative levels Variations include protein-compound (drug) interactions, protein-DNA etc.

27. 27 Protein Microarrays Major problems with analysis of proteins in this way –Protein-protein binding not determined by strict rules as it is in nucleic acids (base-pairing) One protein may bind several others on the chip –Protein interactions very sensitive to chemistry Application of protein arrays often used as a follow-up to gene chip studies

28. 28 http://speedy.embl- heidelberg.de/gtsp/flowchart2.htmlhttp://speedy.embl- heidelberg.de/gtsp/flowchart2.html