1. . Class 5: RNA Structure Prediction

2. RNA types u Messenger RNA (mRNA) l Encodes protein sequences u Transfer RNA (tRNA) l Adaptor between mRNA molecules and amino-acids (protein building blocks) u Ribosomal RNA (rRNA) l Part of the ribosome, a machine for translating mRNA to proteins u mi-RNA (micro-) u Sn-RNA (small nuclear) u RNA-I (interfering) u Srp-RNA (Signal Recognition Particle)

3. Functions of RNAs Information Transfer: mRNA Codon -> Amino Acid adapter: tRNA Enzymatic Reactions: Other base pairing functions: ??? Structural: Metabolic: ??? Regulatory: RNAi

4. RNA World Hypothesis  Before the “invention” of DNA and protein, early organisms relied on RNA for both genetic and enzymatic processes  DNA was a selective advantage because it greatly enhanced the fidelity of genetic replication  Proteins were a selective advantage because they make much more efficient enzymes  Remnants of the RNA world remain today in catalytic RNAs in ribosomes, polymereases and slicing molecules

5. Why is RNA structure important? uMuMessenger RNA is a linear, unstructured sequence, encoding an amino-acid sequence uMuMost non-coding RNA’s adopt 3D structures and catalyse bio-chemical reactions. uPuPredicting structure of a new RNA => information about its function

6. Terminology of RNA structure u RNA: a polymer of four different nucleotide subunits: l adenine (A), cytosine (C), guanine (G)and uracil (U) u Unlike DNA, RNA is a single stranded molecule folding intra-molecularly to form secondary structures. u RNA secondary structure = set of base pairings in the three dimensional structure of the molecule u G-C has 3 hydrogen bonds u A-U has 2 hydrogen bonds u Base pairs are almost always stacked onto other pairs, creating stems.

7. Base Pairing in RNA guaninecytosine adenineuracil

8. Non-canonical pairs and pseudoknots u In addition to A-U and G- C pairs, non-canonical pairs also occur. Most common one is G-U pair. u G-U is thermodynamically favourable as Watson- Crick pairs (A-U, G-C). u Base pairs almost always occur in nested fashion. Exception: pseudoknots.

9. Elements of RNA secondary structure

10. RNA Secondary Structure (more…)

11. AGCTACGGAGCGATCTCCGAGCTTTCGAGAAAGCCTCTATTAGC

12. RNA Tertiary Structure Do not obey “parantheses rule”

13. tRNA structure

14. Structure vs Sequence u Homologous RNA’s that have common secondary structure without sharing significant sequence similarity are important. u It is advantageous to search conserved secondary structure in addition to conserved sequence in databases.

15. Example – R17 phage coat protein Durbin, p. 264

16. Two Problems 1. RNA secondary structure for a single sequence. The dynamic programming algorithms – Nussinov and Zuker, SCFG algorithms. 2. Analysis of multiple alignments of families of RNA’s. Covariance Models – used for both multiple alignment and database searches.

17. Problem I: Structure Prediction u Input: An RNA sequence X u Output: Most likely secondary structure of X u Algorithms: Nussinov, CYK, MFOLD, …

18. Problem II: RNA family modeling u Input: A family for RNA sequence X1, …, XN sharing a common secondary structure l Aligned / Not aligned u Output: A probabilistic generative model representing the RNA family u Model: Covariance model