Journal of Molecular Evolution

, Volume 68, Issue 6, pp 679–687

Gene Conversion Among Paralogs Results in Moderate False Detection of Positive Selection Using Likelihood Methods


DOI: 10.1007/s00239-009-9241-6

Cite this article as:
Casola, C. & Hahn, M.W. J Mol Evol (2009) 68: 679. doi:10.1007/s00239-009-9241-6


Previous studies have shown that recombination between allelic sequences can cause likelihood-based methods for detecting positive selection to produce many false-positive results. In this article, we use simulations to study the impact of nonallelic gene conversion on the specificity of PAML to detect positive selection among gene duplicates. Our results show that, as expected, gene conversion leads to higher rates of false-positive results, although only moderately. These rates increase with the genetic distance between sequences, the length of converted tracts, and when no outgroup sequences are included in the analysis. We also find that branch-site models will incorrectly identify unconverted sequences as the targets of positive selection when their close paralogs are converted. Bayesian prediction of sites undergoing adaptive evolution implemented in PAML is affected by conversion, albeit in a less straightforward way. Our work suggests that particular attention should be devoted to the evolutionary analysis of recent duplicates that may have experienced gene conversion because they may provide false signals of positive selection. Fortunately, these results also imply that those cases most susceptible to false-positive results—i.e., high divergence between paralogs, long conversion tracts—are also the cases where detecting gene conversion is the easiest.


RecombinationAdaptive evolutionGene duplicatesPAML

Supplementary material

239_2009_9241_MOESM1_ESM.doc (37 kb)
Supplementary material 1 (DOC 37 kb)
239_2009_9241_MOESM2_ESM.pdf (181 kb)
Supplementary material 2 (PDF 181 kb)

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Biology and School of InformaticsIndiana UniversityBloomingtonUSA