Contrasting methods of quantifying fine structure of human recombination

Abstract

There has been considerable excitement over the ability to construct linkage maps based only on genome-wide genotype data for single nucleotide polymorphic sites (SNPs) in a population sample. These maps, which are derived from estimates of linkage disequilibrium (LD), rely on population genetics theory to relate the decay of LD to the local rate of recombination, but other population processes also come into play. Here we contrast these LD maps to the classically derived, pedigree-based human recombination maps. The LD maps have a level of resolution greatly exceeding that of the pedigree maps, and at this fine scale, sperm typing allows a means of validation. While at a gross level both the pedigree maps and the sperm typing methods generally agree with LD maps, there are significant local differences between them, and the fact that these maps measure different genetic features should be remembered when using them for other genetic inferences.

Figure 1

Genetic versus physical maps. (a) Genetic map location versus physical location for markers in a 20-Mb region of human chromosome 10. The local slope of this relationship provides an estimate of the local recombination intensity in cM/Mbp. (b) Sex-averaged recombination intensity in the same region. Most human chromosomes have very low recombination intensity at centromeres and high recombination intensity at telomeres. Data are from the Rutgers human linkage map version 2 (67).

Figure 2

Relationship between population demography and the linkage disequilibrium (LD) map. Colored boxes indicate the size of recurrently observed haplotypes in the sample. A small population undergoes strong genetic drift, which results in large haplotype blocks, and as the population size increases, these blocks get smaller. We believe that human demography is dominated by an out-of-Africa bottleneck, so that the picture moves from small haplotype blocks in Africa to larger blocks in the out-of-Africa populations due to founder effects and drift. But note that the breaks between the blocks in Africa will often remain breaks outside of Africa, preserving the locations of recombination hotspots. Redrawn from (91). Abbreviations: N_e, effective population size; ρ, the population recombination rate, also written as ρ = 4N_eμ, where μ is the mutation rate.

Figure 3

Sex-specific recombination intensity across the human genome. The observations that females produce gametes with more recombination than males, centromeres have low recombination, and telomeres have high recombination are all discernable. To obtain the genome-wide local recombination intensity (in cM/Mb), we performed a local regression on the Rutgers human linkage map version 2 (67). The local polynomial degree and weight function parameters were optimized by minimizing the local likelihood within a three-dimensional parameter grid for each chromosome arm (66). The optimal parameter combinations were selected by minimizing local Akaike information criterion (AIC) for male-specific and female-specific linkage maps separately. Computation was done using the Locfit package in the R statistical software v. 2.60 (http://www.r-project.org). Abbreviation: Chr, chromosome.

Figure 4

A substantial portion of all human recombination occurs in hotspots. If small windows of the genome are put in rank order of recombination intensity, the lowest 80% of the genome includes only 20% of the recombination events, according to the red curve, adapted from Myers et al. (73). The blue curve presents the result of using pedigree-based recombination data from Coop et al. (15, tbl. S7).

Figure 5

Structural variation and recombination. In copy number variation (CNV) regions, there is a deficit of markers in the Rutgers human linkage map (67) (left). The (HapMap) CNV data are from Redon et al. (27, 85). The CNV regions also have a lower sex-averaged recombination intensity compared with the rest of the genome (right). The asterisks indicate that the two contrasts are significant at P < 0.001. Abbreviation: CNV, copy number variation.

Figure 6

Among-population heterogeneity in linkage disequilibrium (LD). A collection of 107 single nucleotide polymorphisms (SNPs) spanning 1 Mbp of chromosome 22q was genotyped by Graffelman et al. (31) in samples from 28 different human populations. Plotted are the estimates of rho across this region in the major population groups studied in the HapMap project. There is an overall similarity across populations but also pronounced local differences.