Measuring Selection in RNA . Naila Mimouni, Rune Lyngsoe and Jotun Hein

1. Measuring Selection in RNA. Naila Mimouni, Rune Lyngsoe and Jotun Hein Department of Statistics, Oxford University • Aim • •Extract selection information from conservation of secondary structure of alignments of homologous RNA sequences from different species, for different RNA families. • Motivation • RNA Evolution: + Mutation on the DNA (before it is translated to RNA). + Selection on the RNA to preserve structure stability and function. • Protein Selection: + Periodicity of the 3 bases forming the amino acid. + The genetic code. + Ka/Ks. • RNA Selection: No equivalent of Ka/Ks. Preliminary Results: Overall: Stem Classes: I: II: III: Loop Classes I: II: III: Method Basic idea: Exploit conservation of RNA secondary structure. Two Approaches: A) Counting Approach: + Reconstruct phylogeny: Non-directionality. + Count Substitution according to their location: stem lengthening/shortening in loops/stems respectively. + Class Definitions: B) Evolutionary Modelling: + Reconstructing phylogeny: directionality. + Novel Rates: Singlet, doublet and junk rates. + Homologous RNAs partitioned according to similar homology. + Likelihood test: Given a gene: pseudogene Vs functional. Data: + Rfam: RNA sequence alignments with conserved structure. + 503 different RNA families. + Largest dataset for investigating RNA selection. + Initial focus: 47 miRNA families, each containing aligned sequences with conserved structure. Future Work + Maximum likelihood for phylogeny recontruction. + Devise the singlet, doublet rates. + construct selection model + Expand to other RNA families. 1: Knudsen, B. & Hein, J. 2003. Pfold: RNA secondary structure prediction using stochastic context-free grammars. Nucleic Acids Research, 31(13), 3423-8. 2: Schroeder, S. J., Burkard, M. E. & Turner, D. H. 2001. The Energetics of Small Internal Loops in RNA. Biopolymers Nucleic Acid Sci., 52, 157-167.