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Stabilizing selection (not to be confused with negative or purifying selection [1] [2]) is a type of natural selection in which the population mean stabilizes on a particular non-extreme trait value. This is thought to be the most common mechanism of action for natural selection because most traits do not appear to change drastically over time ...
The K a /K s ratio is used to infer the direction and magnitude of natural selection acting on protein coding genes. A ratio greater than 1 implies positive or Darwinian selection (driving change); less than 1 implies purifying or stabilizing selection (acting against change); and a ratio of exactly 1 indicates neutral (i.e. no) selection.
Disruptive selection is a specific type of natural selection that actively selects against the intermediate in a population, favoring both extremes of the spectrum. Disruptive selection is inferred to oftentimes lead to sympatric speciation through a phyletic gradualism mode of evolution. Disruptive selection can be caused or influenced by ...
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This is an example of balancing selection between the fierce selection against homozygous sickle-cell sufferers, and the selection against the standard HgbA homozygotes by malaria. The heterozygote has a permanent advantage (a higher fitness) wherever malaria exists.
Middle (Graph 2) represents stabilizing selection with the moderate trait favored. Bottom (Graph 3) represents disruptive selection with both extremes being favored. In population genetics , directional selection is a type of natural selection in which one extreme phenotype is favored over both the other extreme and moderate phenotypes.
In natural selection, negative selection [1] or purifying selection is the selective removal of alleles that are deleterious. This can result in stabilising selection through the purging of deleterious genetic polymorphisms that arise through random mutations.
The first and most common function to estimate fitness of a trait is linear ω =α +βz, which represents directional selection. [1] [10] The slope of the linear regression line (β) is the selection gradient, ω is the fitness of a trait value z, and α is the y-intercept of the fitness function.