A range of approaches has been used to identify genes that are likely to have been targeted by selection. The most common ones involve analysing the ratio of non-synonymous to synonymous mutations by inter- and intra-specific sequence comparisons, or using SNPs to identify extremes in allele frequencies. However, variability in the genome depends not only on selection but also on the rate of mutation and recombination, and on the influence of the demographic history of the population — including changes in population size, migration and divergence. Demography, in particular, can have a significant effect on allele frequencies and so can confound the inference of selection from such data.
Nielsen and colleagues sought to control for demographic influences in their new allele frequency-based analysis of the action of selection in human genome evolution. In their study of 20 European-American and 19 African-American individuals, they incorporated a complex model of human demography: they modelled parameters for population growth, migration between the populations, a bottleneck in the European population and admixture in the African population. Previous scans for selection in the human genome have either ignored the issue of confounding demographic effects or have used much simpler models. Importantly, these authors also used data from direct sequencing of 9,315 genes, rather than focusing on SNPs from available databases, thus avoiding ascertainment bias owing to the reference set of SNPs being based on a panel of just a few individuals. This study is the first to provide analysis on a genome-wide scale of allele frequency distributions in humans from directly sequenced data.
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