title: Evolution of human immunodeficiency virus under selection and weak recombination.
abstract: To predict emergence of drug resistance in patients undergoing antiretroviral therapy, we study accumulation of preexisting beneficial alleles in a haploid population of N genomes. The factors included in the model are selection with the coefficient s and recombination with the small rate per genome r (r << s sqrt of k, where k is the average number of less-fit loci per genome). Mutation events are neglected. To describe evolution at a large number of linked loci, we generalize the analytic method we developed recently for an asexual population. We show that the distribution of genomes over the deleterious allele number moves in time as a "solitary wave" that is quasi-deterministic in the middle (on the average) but has stochastic edges. We arrive at a single-locus expression for the average accumulation rate, in which the effects of linkage, recombination, and random drift are all accounted for by the effective selection coefficient s lnNr/lnNs(2)k/r. At large N, the effective selection coefficient approaches the single-locus value s. Below the critical size N(c) approximately 1/r, a population eventually becomes a clone, recombination cannot produce new sequences, and virus evolution stops. Taking into account finite mutation rate predicts a small, finite rate of evolution at N < N(c). We verify the accuracy of the results analytically and by Monte Carlo simulation. On the basis of our findings, we predict that partial depletion of the HIV population by combined anti-retroviral therapy can suppress emergence of drug-resistant strains.
authors.affiliation: School of Medicine, Tufts University, Boston, Massachusetts 02111, USA. irouzine@tufts.edu
authors.forename: I M
authors.initials: IM
authors.lastname: Rouzine
authors.forename: J M
authors.initials: JM
authors.lastname: Coffin
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D019143:Evolution, Molecular; D006678:HIV / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D009010:Monte Carlo Method; D009154:Mutation; D011153:Population; D011995:Recombination, Genetic; D012641:Selection, Genetic
references.citation: J Virol. 1999 Oct;73(10):8167-78
references.pmid: 10482567
references.citation: Proc Natl Acad Sci U S A. 1999 Sep 14;96(19):10758-63
references.pmid: 10485899
references.citation: J Virol. 2000 Jul;74(14):6262-8
references.pmid: 10864635
references.citation: Microbiol Mol Biol Rev. 2001 Mar;65(1):151-85
references.pmid: 11238990
references.citation: Nature. 2002 Jul 11;418(6894):144
references.pmid: 12110879
references.citation: Proc Natl Acad Sci U S A. 2003 Jan 21;100(2):587-92
references.pmid: 12525686
references.citation: Science. 1998 Sep 25;281(5385):1986-90
references.pmid: 9748151
references.citation: Genet Res. 1966 Dec;8(3):269-94
references.pmid: 5980116
references.citation: Genetics. 1974 Oct;78(2):737-56
references.pmid: 4448362
references.citation: Genet Res. 1995 Apr;65(2):123-45
references.pmid: 7605514
references.citation: J Virol. 1995 Aug;69(8):5087-94
references.pmid: 7541846
references.citation: Genetics. 1997 Oct;147(2):879-906
references.pmid: 9335621
references.citation: Genetics. 1998 Aug;149(4):2089-97
references.pmid: 9691060
references.citation: Proc Natl Acad Sci U S A. 2004 Mar 23;101(12):4204-9
references.pmid: 15010526