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Class 5:RNA Structure Prediction

RNA types

Messenger RNA (mRNA) Encodes protein sequences

Transfer RNA (tRNA) Adaptor between mRNA molecules and amino-acids

(protein building blocks) Ribosomal RNA (rRNA)

Part of the ribosome, a machine for translating mRNA to proteins

mi-RNA (micro-) Sn-RNA (small nuclear) RNA-I (interfering) Srp-RNA (Signal Recognition Particle)

Functions of RNAs

Information Transfer: mRNA

Codon -> Amino Acid adapter: tRNA

Enzymatic Reactions:

Other base pairing functions: ???

Structural:

Metabolic: ???

Regulatory: RNAi

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

Why is RNA structure important?

Messenger RNA is a linear, unstructured sequence, encoding an amino-acid sequence

Most non-coding RNA’s adopt 3D structures and catalyse bio-chemical reactions.

Predicting structure of a new RNA => information about its function

Terminology of RNA structure

RNA: a polymer of four different nucleotide subunits: adenine (A) , cytosine (C), guanine (G)and uracil (U)

Unlike DNA, RNA is a single stranded molecule folding intra-molecularly to form secondary structures.

RNA secondary structure = set of base pairings in the three dimensional structure of the molecule

G-C has 3 hydrogen bonds A-U has 2 hydrogen bonds Base pairs are almost always stacked onto other pairs,

creating stems.

Base Pairing in RNA

guanine cytosine

adenine uracil

Non-canonical pairs and pseudoknots

In addition to A-U and G-C pairs, non-canonical pairs also occur. Most common one is G-U pair.

G-U is thermodynamically favourable as Watson-Crick pairs (A-U, G-C) .

Base pairs almost always occur in nested fashion. Exception: pseudoknots.

Elements of RNA

secondary

structure

RNA Secondary Structure(more…)

AGCTACGGAGCGATCTCCGAGCTTTCGAGAAAGCCTCTATTAGC

RNA Tertiary Structure

•Do not obey “parantheses rule”

tRNA structure

Structure vs Sequence

Homologous RNA’s that have common secondary structure without sharing significant sequence similarity are important.

It is advantageous to search conserved secondary structure in addition to conserved sequence in databases.

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.

Problem I: Structure Prediction

Input: An RNA sequence X

Output: Most likely secondary structure of X

Algorithms: Nussinov, CYK, MFOLD, …

Problem II: RNA family modeling

Input: A family for RNA sequence X1, …, XN sharing a common secondary structure

Aligned / Not aligned

Output: A probabilistic generative model representing the RNA family

Model: Covariance model