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Activity Number: 354
Type: Topic Contributed
Date/Time: Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #305036
Title: Twisted Sisters: Disentangling Selection in Overlapping Reading Frames
Author(s): Wei-Chen Chen*+ and Karin S. Dorman
Companies: Iowa State University and Iowa State University
Address: Snedecor Hall, Ames, IA, 50010,
Keywords: overlapping open reading frames ; selection coefficient ; sequence evolution
Abstract:

To measure the force of selection on biological sequences, available statistical methods assume independent and identically distributed (iid) nucleotides, codons, or amino acids, etc. Overlapping open reading frames (OORFs) simultaneously code for two proteins in a way that severely violates the iid assumption. Extending the available methods to OORFs is easily done by Continuous Time Markov Chain, but the computations are prohibitive. Our approximate model allows estimation of selection coefficients in a reasonable time and can be used to test biological hypotheses. Our analysis of two Hepatitis B virus sequences found selection acts independently on the two proteins, as shown in Pedersen and Jensen (2001), but an analysis of 146 lentivirus sequences revealed a surprising interaction favoring mutations that alter both proteins simultaneously.

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