Amino Acid Covariation in a Functionally Important Human Immunodeficiency Virus Type 1 Protein Region Is Associated With Population Subdivision

The frequently reported amino acid covariation of the highly polymorphic human immunodeficiency virus type 1 (HIV-1) exterior envelope glycoprotein V3 region has been assumed to reflect fitness epistasis between residues. However, nonrandom association of amino acids, or linkage disequilibrium, has many possible causes, including population subdivision. If the amino acids at a set of sequence sites differ in frequencies between subpopulations, then analysis of the whole population may reveal linkage disequilibrium even if it does not exist in any subpopulation. HIV-1 has a complex population structure, and the effects of this structure on linkage disequilibrium were investigated by estimating withinand among-subpopulation components of variance in linkage disequilibrium. The amino acid covariation previously reported is explained by differences in amino acid frequencies among virus subpopulations in different patients and by nonsystematic disequilibrium among patients. Disequilibrium within patients appears to be entirely due to differences in amino acid frequencies among sampling time points and among chemokine coreceptor usage phenotypes of virus particles, but not source tissues. Positive selection explains differences in allele frequencies among time points and phenotypes, indicating that these differences are adaptive rather than due to genetic drift. However, the absence of a correlation between linkage disequilibrium and phenotype suggests that fitness epistasis is an unlikely cause of disequilibrium. Indeed, when population structure is removed by analyzing sequences from a single time point and phenotype, no disequilibrium is detectable within patients. These results caution against interpreting amino acid covariation and coevolution as evidence for fitness epistasis. LINKAGE disequilibrium refers to the nonrandom association of alleles among loci or the nonrandom association of residues among molecular sequence sites. The departure of alleles from random association is of considerable interest because it reflects important population genetic processes (reviewed by Slatkin 2008) and may have important consequences for the efficiency of natural selection and the evolution of recombination (Felsenstein 1988; Kondrashov 1993). But, although linkage disequilibrium is easy to measure, ascertaining its causes is not. Disequilibrium may be generated by interactions among alleles at different loci in their effects on fitness, known as fitness epistasis (e.g., Kimura 1956; Lewontin and Kojima 1960; Felsenstein 1965; Karlin and Feldman 1970). Genetic drift may also cause disequilibrium simply because sampling a finite number of haplotypes will generate nonrandom associations (Hill and Robertson 1968; Ohta and Kimura 1969; Hudson 1985; Slatkin 1994). Similarly, population bottlenecks may create disequilibrium because of the chance loss of some haplotypes. Other forces, such as inbreeding, genomic inversions, and gene conversion, may also generate disequilibrium (see Slatkin 2008). Finally, population subdivision may produce linkage disequilibrium if subpopulations differ in allele frequencies. In this situation, even if subpopulations exhibit linkage equilibrium, disequilibrium may be evident at the whole population level (Mitton and Koehn 1973; Nei and Li 1973). In the extreme case, if the alleles fixed at a set of loci differ between two subpopulations, neither subpopulation will exhibit disequilibrium, but the alleles will be seen to be in disequilibrium at the whole population level. Additionally, if there is gene flow between such subpopulations, then disequilibrium will also be evident within subpopulations (Li and Nei 1974; Slatkin 1975). The first step in determining the causes of linkage disequilibrium is to test for the effects of population subdivision (Slatkin 2008). If population subdivision can be ruled out, or is a minor contributor, then other forces such as epistasis or genetic drift may be considered. Ohta (1982) describes a method of partitioning the total variance in linkage disequilibrium into withinAddress for correspondence: University of Adelaide, Molecular Life Sciences Bldg., Gate 8, Victoria Dr., Adelaide, SA 5005, Australia. E-mail: [email protected] Genetics 182: 265–275 (May 2009) and among-subpopulation components that is analogous to Wright’s (1940) measures of population subdivision for single loci, FIS and FST. This method is commonly used to determine how much of disequilibrium is attributable to population structure (Slatkin