Genetic hitchhiking, also called genetic draft or the hitchhiking effect, is when an allele changes frequency not because it itself is under natural selection, but because it is near another gene that is undergoing a selective sweep and that is on the same DNA chain. When one gene goes through a selective sweep, any other nearby polymorphisms that are in linkage disequilibrium will tend to change their allele frequencies too. Selective sweeps happen when newly appeared (and hence still rare) mutations are advantageous and increase in frequency. Neutral or even slightly deleterious alleles that happen to be close by on the chromosome 'hitchhike' along with the sweep. In contrast, effects on a neutral locus due to linkage disequilibrium with newly appeared deleterious mutations are called background selection. Both genetic hitchhiking and background selection are stochastic (random) evolutionary forces, like genetic drift.
The term hitchhiking was coined in 1974 by Maynard Smith and John Haigh. Subsequently the phenomenon was studied by John H. Gillespie and others.
Hitchhiking occurs when a polymorphism is in linkage disequilibrium with a second locus that is undergoing a selective sweep. The allele that is linked to the adaptation will increase in frequency, in some cases until it becomes fixed in the population. The other allele, which is linked to the non-advantageous version, will decrease in frequency, in some cases until extinction. Overall, hitchhiking reduces the amount of genetic variation. A hitchhiker mutation (or passenger mutation in cancer biology) may itself be neutral, advantageous, or deleterious.
Recombination can interrupt the process of genetic hitchhiking, ending it before the hitchhiking neutral or deleterious allele becomes fixed or goes extinct. The closer a hitchhiking polymorphism is to the gene under selection, the less opportunity there is for recombination to occur. This leads to a reduction in genetic variation near a selective sweep that is closer to the selected site.
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Understand and use the results and methods of population genetics, population dynamics, network theory, and reaction network dynamics to analyze and predict the behavior of living systems
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