2010
DOI: 10.1534/genetics.109.112920
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The Role of Advantageous Mutations in Enhancing the Evolution of a Recombination Modifier

Abstract: Although the evolution of recombination is still a major problem in evolutionary genetics, recent theoretical studies have shown that recombination can evolve by breaking down interference (''HillRobertson effects'') among multiple loci. This leads to selection on a recombination modifier in a population subject to recurrent deleterious mutation. Here, we use computer simulations to investigate the evolution of a recombination modifier under three different scenarios of recurrent mutation in a finite populatio… Show more

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Cited by 43 publications
(77 citation statements)
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“…For example, Muller's ratchet is strongest in small populations that often experience deleterious mutations, whereas the Fisher-Muller effect is strongest in large populations that often experience beneficial mutations. The increase in the strength of the Fisher-Muller effect between beneficial mutations with population size is intuitive because population size (N) affects the beneficial mutation supply rate (NU b ; where U b is the beneficial mutation rate).More surprising is the recent finding from evolutionary simulations that interference between deleterious mutations can, on its own, also generate a large benefit of sex that increases with population size (Otto and Barton 2001;Iles et al 2003;Barton and Otto 2005;Keightley and Otto 2006;Gordo and Campos 2008;Hartfield et al 2010). This finding is surprising because neither Muller's ratchet (Muller 1964;Haigh 1978;Gordo and Charlesworth 2000) nor background selection Kaplan 1994, 1995) is expected to increase in strength with population size.…”
mentioning
confidence: 99%
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“…For example, Muller's ratchet is strongest in small populations that often experience deleterious mutations, whereas the Fisher-Muller effect is strongest in large populations that often experience beneficial mutations. The increase in the strength of the Fisher-Muller effect between beneficial mutations with population size is intuitive because population size (N) affects the beneficial mutation supply rate (NU b ; where U b is the beneficial mutation rate).More surprising is the recent finding from evolutionary simulations that interference between deleterious mutations can, on its own, also generate a large benefit of sex that increases with population size (Otto and Barton 2001;Iles et al 2003;Barton and Otto 2005;Keightley and Otto 2006;Gordo and Campos 2008;Hartfield et al 2010). This finding is surprising because neither Muller's ratchet (Muller 1964;Haigh 1978;Gordo and Charlesworth 2000) nor background selection Kaplan 1994, 1995) is expected to increase in strength with population size.…”
mentioning
confidence: 99%
“…More surprising is the recent finding from evolutionary simulations that interference between deleterious mutations can, on its own, also generate a large benefit of sex that increases with population size (Otto and Barton 2001;Iles et al 2003;Barton and Otto 2005;Keightley and Otto 2006;Gordo and Campos 2008;Hartfield et al 2010). This finding is surprising because neither Muller's ratchet (Muller 1964;Haigh 1978;Gordo and Charlesworth 2000) nor background selection Kaplan 1994, 1995) is expected to increase in strength with population size.…”
mentioning
confidence: 99%
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“…Relative effects of segregation and recombination X Jiang et al contrast, smaller N e impedes the spread rate of the sex modifier (Hartfield et al, 2010). The decrease in u/u* was attributed to the dominance of the opposite effects of delaying the spread rate of the modifier exceeding the effects of increasing interference.…”
Section: Selection On a Recombination Modifiermentioning
confidence: 98%
“…The simulation programs used in this study (written in C þ þ and available upon request) were somewhat similar to those in haploid models used by Hartfield et al (2010), but our simulations were newly established. In both studies, an infinite number of possible alleles at each locus, the absence of epistasis and no dominance in mutations were considered.…”
Section: General Settings Of the Programmentioning
confidence: 99%