Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 3 (11), e339

The Geographic Spread of the CCR5 Delta32 HIV-resistance Allele

Affiliations

The Geographic Spread of the CCR5 Delta32 HIV-resistance Allele

John Novembre et al. PLoS Biol.

Abstract

The Delta32 mutation at the CCR5 locus is a well-studied example of natural selection acting in humans. The mutation is found principally in Europe and western Asia, with higher frequencies generally in the north. Homozygous carriers of the Delta32 mutation are resistant to HIV-1 infection because the mutation prevents functional expression of the CCR5 chemokine receptor normally used by HIV-1 to enter CD4+ T cells. HIV has emerged only recently, but population genetic data strongly suggest Delta32 has been under intense selection for much of its evolutionary history. To understand how selection and dispersal have interacted during the history of the Delta32 allele, we implemented a spatially explicit model of the spread of Delta32. The model includes the effects of sampling, which we show can give rise to local peaks in observed allele frequencies. In addition, we show that with modest gradients in selection intensity, the origin of the Delta32 allele may be relatively far from the current areas of highest allele frequency. The geographic distribution of the Delta32 allele is consistent with previous reports of a strong selective advantage (>10%) for Delta32 carriers and of dispersal over relatively long distances (>100 km/generation). When selection is assumed to be uniform across Europe and western Asia, we find support for a northern European origin and long-range dispersal consistent with the Viking-mediated dispersal of Delta32 proposed by G. Lucotte and G. Mercier. However, when we allow for gradients in selection intensity, we estimate the origin to be outside of northern Europe and selection intensities to be strongest in the northwest. Our results describe the evolutionary history of the Delta32 allele and establish a general methodology for studying the geographic distribution of selected alleles.

Figures

Figure 1
Figure 1. Shaded Contour Map of Δ32 Allele Frequency Data
The sampling locations are marked by black points. The interpolation is masked in regions where data are unavailable.
Figure 2
Figure 2. An Example of the Allele Frequency Surface and Simulated Data
(A) The underlying allele frequency surface generated by the PDE model using MLEs for the parameters. The coarseness of the surface and irregular coastlines are due to the resolution of the simulated habitat (see Figure S1). (B and C) Two replicates of simulated data obtained using the same sampling locales and sample sizes as in the dataset and displayed using the same interpolation methods and contours as in Figure 1. The results show that underlying smooth, unimodal allele frequency surfaces can give rise to irregular, multimodal observed allele frequency surfaces.
Figure 3
Figure 3. Profile Likelihood for R
The grey line shows the log profile likelihood for R when selection is assumed to be uniform spatially (GNS = GEW = 0). The MLE of R in this case is 2.77 × 105 with a log-likelihood of −263.0. The black line shows the profile likelihood when selection gradients are incorporated into the model (GNS and GEW are free parameters). The corresponding MLE of R is 1.03 × 106 with a log likelihood of −247.7.
Figure 4
Figure 4. The Dispersal Parameter σ as a Function of the Selection Intensity s
The curves are drawn for the two MLEs of R and labeled accordingly. 1Based on estimates in [2] and [3]. 2From Table 1 of [27].
Figure 5
Figure 5. Profile Likelihood Surface for GNS and GEW
The plus signs indicate locations where the likelihood was evaluated. The dark contour at −250 marks the −2 log-likelihood support region for the estimates of GNS and GEW.
Figure 6
Figure 6. Likelihood Surfaces for the Origin of the Allele
(A) Assuming selection intensity is uniform spatially (i.e., GNS = GEW = 0). (B) Allowing for north–south and east–west spatial gradients in selection (i.e., GNS and GEW are free parameters). Likelihoods were calculated at each of the black points and the surface was obtained by interpolation.

Similar articles

See all similar articles

Cited by 56 articles

See all "Cited by" articles

References

    1. Samson M, Libert F, Doranz BJ, Rucker J, Liesnard C, et al. Resistance to HIV-1 infection in Caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene. Nature. 1996;382:722–725. - PubMed
    1. Stephens JC, Reich DE, Goldstein DB, Shin HD, Smith MW, et al. Dating the origin of the CCR5-Delta 32 AIDS-resistance allele by the coalescence of haplotypes. Am J Hum Genet. 1998;62:1507–1515. - PMC - PubMed
    1. Slatkin M. Simulating genealogies of selected alleles in a population of variable size. Genet Res. 2001;78:49–57. - PubMed
    1. Hummel S, Schmidt D, Kremeyer B, Herrmann B, Oppermann M. Detection of the CCR5-Delta32 HIV resistance gene in Bronze Age skeletons. Genes Immun. 2005;6:371–374. - PubMed
    1. Libert F, Cochaux P, Beckman G, Samson M, Aksenova M, et al. The delta CCR5 mutation conferring protection against HIV-1 in Caucasian populations has a single and recent origin in Northeastern Europe. Hum Mol Genet. 1998;7:399–406. - PubMed

Publication types

Substances

Feedback