Evolution of the Human Genome: Adaptive Changes


The study of human evolution is of interest to many both for the potential it has to improve our understanding of heritable disease, as well as for the possibility of illuminating evidence for adaptations that may help to tell the story of our origin. But uncovering evidence of positive selection at the genetic level has been a challenge. It remains unclear how much of the human genome has been affected by positive selection, what the main mechanism of selection is, and what types of patterns we should be looking for to identify adaptations. With whole‐genome sequencing and high performance computation, we are quickly shifting to a field in which data is no longer a limiting factor. Here we will discuss the progress that has been made towards these ends, explore the best examples of human‐specific adaptations to date, and discuss the implications of these findings within the context of classical population genetic theory.

Key Concepts:

  • An abundance of genomic data allows for a genotype‐first approach to discover selection in humans.

  • Ancient hominin genomic sequences provide a nearer outgroup to humans than chimpanzee, and therefore can help elucidate selective targets in humans.

  • Hard sweeps may have been rare in human evolution, whereas soft sweeps are a much more likely mechanism of selection.

  • The genomic signatures of sweeps, background selection, and demography all look similar and can be difficult to distinguish.

  • Genomic scans for selection make use of various signatures of selection and they rarely identify overlapping targets.

  • More accurate modelling of selection in humans is needed to find true signals of selection.

Keywords: ancient hominin genomes; demography; genome scans; hitchhiking; human adaptation; human evolution; selective sweeps; soft sweeps

Figure 1.

Phylogeny of the great apes and approximate divergence times. Branches are not drawn to scale. The Neanderthal and Denisova branches are intentionally truncated to indicate extinct versus extant.

Figure 2.

The hitchhiking effect. Each grey or red line represents a chromosome from a single individual. (a) A beneficial mutation arises in the population and is closely linked to a neutral allele. (b) As the mutation rises in frequency, it brings with it linked neutral alleles. Only alleles that recombine onto the beneficial haplotype are not lost from the sample. (c) After the sweep is completed the closely linked allele is fixed. Thus only high frequency alleles that have ‘hitchhiked’ with the beneficial mutation are visible as variation within the sample, and subsequent new mutations appear as rare variants.

Figure 3.

A comparison of the site frequency spectrum under equilibrium and nonequilibrium conditions. Plots are based on simulation of a 5 Kb region using either msms (a–c) or sfscode (d) with human‐like parameters (effective population size of 10 000, per site mutation rate of 2.35×10−8, and per site recombination rate of 2.56×10−8). Counts on the y‐axis are the total number of mutations based on 1000 iterations. (a) Equilibrium neutral population. (b) 1% positive selection at a single locus. (c) Nonequilibrium neutral population. Demographic parameters include an 80% reduction in population size 50 Kya, with an exponential growth of 5% for the last 1000 years. (d) Background selection, with 80% of sites experiencing negative selection (coefficient of selection=0.01). It is apparent from this figure that both demography and selection greatly reduce the number of mutations compared to neutrality.



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Further Reading

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Crisci, Jessica L, and Jensen, Jeffrey D(May 2012) Evolution of the Human Genome: Adaptive Changes. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0023987]