A Method for the Simultaneous Estimation of Selection Intensities in Overlapping Genes Niv Sabath*, Giddy Landan, Dan Graur Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America Abstract Inferring the intensity of positive selection in protein-coding genes is important since it is used to shed light on the process of adaptation. Recently, it has been reported that overlapping genes, which are ubiquitous in all domains of life, seem to exhibit inordinate degrees of positive selection. Here, we present a new method for the simultaneous estimation of selection intensities in overlapping genes. We show that the appearance of positive selection is caused by assuming that selection operates independently on each gene in an overlapping pair, thereby ignoring the unique evolutionary constraints on overlapping coding regions. Our method uses an exact evolutionary model, thereby voiding the need for approximation or intensive computation. We test the method by simulating the evolution of overlapping genes of different types as well as under diverse evolutionary scenarios. Our results indicate that the independent estimation approach leads to the false appearance of positive selection even though the gene is in reality subject to negative selection. Finally, we use our method to estimate selection in two influenza A genes for which positive selection was previously inferred. We find no evidence for positive selection in both cases. Citation: Sabath N, Landan G, Graur D (2008) A Method for the Simultaneous Estimation of Selection Intensities in Overlapping Genes. PLoS ONE 3(12): e3996. doi:10.1371/journal.pone.0003996 Editor: Oliver G. Pybus, University of Oxford, United Kingdom Received September 22, 2008; Accepted November 21, 2008; Published December 22, 2008 Copyright: 2008 Sabath et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported in part by grant DBI-0543342 from the National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: nsabath@uh.edu Introduction Overlapping genes were first discovered in viruses [1] and later in all cellular domains of life [2–4]. The percentage of overlapping genes in a genome varies across species: 5–14% in vertebrates [5], 10–50% in bacteria [6], and up to 100% in viruses (e.g., hepatitis B virus)[7]. Overlapping genes were suggested to have multiple functions such as regulation of gene expression [8], translational coupling [9], and genome imprinting [10]. In addition, overlapping genes were hypothesized to be a means of genome size reduction [11], as well as a mechanism for creating new genes [12]. The interdependence between two overlapping coding regions results in unique evolutionary constraints [13,14], which vary among overlap types [13]. Several attempts at estimating selection intensity in overlapping genes have been made [15–26]. In some studies, one gene was found to exhibit positive selection while the overlapping gene showed signs of strong purifying selection (e.g., [15]). Inferences of positive selection in overlapping genes have been questioned [19,21,24], mostly because ignoring overlap constraints might bias selection estimates. Rogozin et al. [27] tried to overcome this problem by focusing on sites in which all changes are synonymous in one gene and nonsynonymous in the overlapping gene. A model for the nucleotide substitutions in overlapping genes was introduced by Hein and Stovlbaek [28], who followed approximate models for non-overlapping genes that classify sites according to degeneracy classes [29–31]. This model was later incorporated into a method for annotation of viral genomes [32– 34], and recently used for estimating selection on overlapping genes [35]. The main weakness of approximate methods is that it assumes a constant degeneracy class for each site, whereas degeneracy changes over time as substitutions occur. Pedersen and Jensen [36] suggested a non-stationary substitution model for overlapping reading frames that extended the codon-based model of Goldman and Yang [37]. This model encompasses the evolutionary process more accurately than the approximate model [28] by accounting for position dependency of each site in an overlap region [36]. However, this improvement disallowed the straightforward estimation of parameters and forced the authors to apply a computationally-expensive simulation procedure [36]. Surprisingly, these models for nucleotide substitutions in overlap- ping genes were rarely cited, not to mention used, by the majority of studies estimating selection in overlapping genes. One reason that these methods were seldom used might be the lack of an accessible implementation. Here, we describe a non-stationary method, similar to that of Pedersen and Jensen [36]. Our method simplifies selection estimation and avoids the need for costly simulation procedure. We test our method by simulating the evolution of overlapping genes of different types and under various selective regimes. Further, we describe the nature and magnitude of the error when selection is estimated as if the genes evolve independently. Finally, we use our method to estimate selection in two cases for which independent estimation has previously yielded indications of positive selection. Methods A gene can overlap another on the same strand or on the opposite strand. Each overlap orientation has 2 or 3 possible PLoS ONE | www.plosone.org 1 December 2008 | Volume 3 | Issue 12 | e3996