MBE Advance Access published online on February 1, 2006
Molecular Biology and Evolution, doi:10.1093/molbev/msj102
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1 Department of Microbiology and Molecular Biology, Brigham Young University, 84602 Provo, Utah USA; Departamento de Bioquímica, Genética e Inmunología. Universidad de Vigo, 36310 Vigo, Spain
* To whom correspondence should be addressed. The composite-likelihood estimator (CLE) of the population recombination rate considers only sites with exactly two alleles under a finite-sites mutation model (McVean, Awadalla, and Fearnhead 2002). While in such a model the identity of alleles is not considered, the CLE has been shown to be robust to minor misspecification of the underlying mutational model. However, there are many situations where the putative mutation and demographic history can be quite complex. One good example are rapidly evolving pathogens, like HIV-1. Here we evaluated the performance of the CLE and the LPT under more complex, realistic models, including a general time-reversible (GTR) substitution model, rate heterogeneity among sites (
Accepted January 25, 2006
Research Article
Recombination Estimation under Complex Evolutionary Models with the Coalescent Composite Likelihood Method
Antonio Carvajal-Rodríguez 1 *,
Keith A. Crandall 2,
and
David Posada 3
2 Department of Microbiology and Molecular Biology, Brigham Young University, 84602 Provo, Utah USA
3 Departamento de Bioquímica, Genética e Inmunología. Universidad de Vigo, 36310 Vigo, Spain
Antonio Carvajal-Rodríguez, E-mail: ac549{at}email.byu.edu
Abstract 
), positive selection, population growth, population structure and non-contemporaneous sampling. Second, we relaxed some of the assumptions of the CLE allowing for a four-allele, GTR+ model in an attempt to use the data more efficiently. Through simulations and the analysis of real data, we concluded that the CLE is robust to severe misspecifications of the substitution model, but underestimates the recombination rate in the presence of exponential growth, population mixture, selection or non-contemporaneous sampling. In such cases, the use of more complex models slightly increases performance in some occasions, especially in the case of the LPT. Thus, our results provide for a more robust application of the estimation of recombination rates.
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