Detecting selection in the human genome

I've already mentioned the HapMap project [1], a collection of genotype data at roughly 3.2M SNPs in the human genome. The data in phase II of the project were collected from four populations:

• Yoruba (Ibadan, Nigeria)

• Japanese (Tokyo, Japan)

• Han Chinese (Beijing, China)

• ancestry from northern and western Europe (Utah, USA)

We expect genetic drift to result in allele frequency differences among populations, and we can summarize the extent of that differentiation at each locus with $F_{ST}$. If all HapMap SNPs are selectively neutral,⁴ then all loci should have the same $F_{ST}$ within the bounds of statistical sampling error and the evolutionary sampling due to genetic drift. A scan of human chromosome 7 reveals both a lot of variation in individual-locus estimates of $F_{ST}$ and a number of loci where there is substantially more differentiation among populations than is expected by chance (Figure 2). At very fine genomic scales we can detect even more outliers (Figure 3), suggesting that human populations have been subject to divergent selection pressures at many different loci.

Figure 2: Single-locus estimates of $F_{ST}$ along chromosome 7 in the HapMap data set. Blue dots denote outliers. Adjacent SNPs in this sample are separated, on average, by about 52kb.

Figure 3: Single-locus estimates of $F_{ST}$ along a portion of chromosome 7 in the HapMap data set. Black dots denote outliers. Solid bars refert to previously identified genes. Adjacent SNPs in this sample are separated, on average, by about 1kb.

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