A simple, semi-deterministic approximation to the distribution of selective sweeps in large populations

Martin, Guillaume; Lambert, Amaury

doi:10.1016/j.tpb.2015.01.004

Cited by 31 publications

(41 citation statements)

References 24 publications

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“…where H l = F +h−F h is the effective dominance coefficient for mutations at a low 270 frequency. This result is consistent with those of Martin and Lambert (2015), who 271 obtained a distribution of effective starting frequencies using stochastic differential 272 equations. This acceleration effect can create substantial increases in the effective 273 p 0 , especially for recessive mutations (Figure 2).…”

supporting

confidence: 83%

Selective sweeps under dominance and inbreeding

Hartfield

Bataillon

2018

Preprint

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1A major research goal in evolutionary genetics is to uncover loci expe-2 riencing positive selection. One approach involves finding 'selective sweeps' 3 patterns, which can either be 'hard sweeps' formed by de novo mutation, or 4 'soft sweeps' arising from recurrent mutation or existing standing variation. 5 Existing theory generally assumes outcrossing populations, and it is unclear 6 how dominance affects soft sweeps. We consider how arbitrary dominance 7 and inbreeding via self-fertilisation affect hard and soft sweep signatures. 8 With increased self-fertilisation, they are maintained over longer map dis-9 tances due to reduced effective recombination and faster beneficial allele 10 fixation times. Dominance can affect sweep patterns in outcrossers if the 11 derived variant originates from either a single novel allele, or from recurrent 12 mutation. These models highlight the challenges in distinguishing hard and 13 soft sweeps, and propose methods to differentiate between scenarios.

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supporting

confidence: 83%

Selective sweeps under dominance and inbreeding

Hartfield

Bataillon

2018

Preprint

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“…Beneficial mutations that increase in frequency faster than expected when rare are more able to overcome this stochastic loss and reach fixation. These beneficial mutations will hence display an apparent 'acceleration' in their logistic growth, equivalent to having a starting frequency that is greater than 1=ð2NÞ (Maynard Smith 1976;Barton 1998;Desai and Fisher 2007;Martin and Lambert 2015). Correcting for this acceleration is important to accurately model hard sweep signatures, and inform on the minimum level of standing variation needed to differentiate a hard sweep from one originating from standing variation.…”

Section: Probability Of Coalescence From Standing Variationmentioning

confidence: 99%

Selective Sweeps Under Dominance and Inbreeding

Hartfield

Bataillon

2020

G3 Genes|Genomes|Genetics

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A major research goal in evolutionary genetics is to uncover loci experiencing positive selection. One approach involves finding ‘selective sweeps’ patterns, which can either be ‘hard sweeps’ formed by de novo mutation, or ‘soft sweeps’ arising from recurrent mutation or existing standing variation. Existing theory generally assumes outcrossing populations, and it is unclear how dominance affects soft sweeps. We consider how arbitrary dominance and inbreeding via self-fertilization affect hard and soft sweep signatures. With increased self-fertilization, they are maintained over longer map distances due to reduced effective recombination and faster beneficial allele fixation times. Dominance can affect sweep patterns in outcrossers if the derived variant originates from either a single novel allele, or from recurrent mutation. These models highlight the challenges in distinguishing hard and soft sweeps, and propose methods to differentiate between scenarios.

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“…Therefore, an intriguing question is which of these two nonexclusive causal factors is more dominant (7,28,29); yet, the estimates differ substantially among different studies (35)(36)(37)(38)(39)(40)(41).…”

Section: Introductionmentioning

confidence: 99%

“…The relationship between intrapopulation diversity and interspecies divergence is then derived, which can be applied to analyze the patterns of inter-species divergence and intra-species diversity in lowrecombination regions, while the recombination rate is treated as a biological variable underlying the strength of killing functions. The current study focuses on two fundamental issues: first, which one, selective sweeps or (negative) background selection, is more dominant (7,24,(27)(28)(29)43); and second, whether either one of them is sufficient to explain the observed diversity and divergence pattern (35)(36)(37)(38)(39)(40)(41).…”

Section: Introductionmentioning

confidence: 99%

A New Model of Genetic Variation and Evolution Evaluates Relative Impacts of Background Selections and Selective Sweeps

2020

Preprint

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Intra-population genetic variation and interspecies divergence in chromosomeregions can be considerably affected by different local recombination rates. There are two models: (i) the selective sweeps that reduces the genetic diversity at linked sites and elevates the divergence rate; and (ii) the background selection that reduces the genetic diversity at linked sites and divergence rate. An intriguing question, yet highly controversial, is which one is dominant. In this paper, I develop a framework of generalize background selection, formulated by a diffusion model with two killing functions: the one associated with (negative) background selection is the rate to stop a fixation process of a mutation randomly, and the other associated with positive background selection (selective sweep) is the rate to stop a loss process of a mutation randomly. A simple relationship between the level of reduced diversity and the rate of divergence is derived, depending on the strength of generalized background selection (G) and the proportion of positive background selection (β). We analyzed the interspecies divergence and intra-population diversity in low-recombination regions of three organisms (fruitfly, soybean and human). Strikingly, all datasets demonstrated the dominance of (negative) background selection, and the positive background selection (selective sweeps) only has a small contribution (β~10%). However, our analysis rejects the notion of β =0, namely, a complete negative background selection is unlikely. These findings may shed some lights on the long-term debates around Neutral Theory.

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A simple, semi-deterministic approximation to the distribution of selective sweeps in large populations

Cited by 31 publications

References 24 publications

Selective sweeps under dominance and inbreeding

Selective sweeps under dominance and inbreeding

Selective Sweeps Under Dominance and Inbreeding

A New Model of Genetic Variation and Evolution Evaluates Relative Impacts of Background Selections and Selective Sweeps

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