Mutational Variation and Long‐Term Selection Response

Keightley, Peter D.

doi:10.1002/9780470650240.ch10

Cited by 18 publications

(24 citation statements)

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“…6r10 x3 ) (Lynch, 1988 ;Houle et al, 1996;Keightley, 1998 ;Houle, 1998 ;Lynch et al, 1999;Keightley, 2004). 01 to 1% of s P 2 per generation, the mutational coefficient of variation being 0 .…”

Section: (B) Genetic Driftmentioning

confidence: 99%

A modelling framework for the analysis of artificial-selection time series

2011

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Artificial-selection experiments constitute an important source of empirical information for breeders, geneticists and evolutionary biologists. Selected characters can generally be shifted far from their initial state, sometimes beyond what is usually considered as typical inter-specific divergence. A careful analysis of the data collected during such experiments may thus reveal the dynamical properties of the genetic architecture that underlies the trait under selection. Here, we propose a statistical framework describing the dynamics of selection-response time series. We highlight how both phenomenological models (which do not make assumptions on the nature of genetic phenomena) and mechanistic models (explaining the temporal trends in terms of e.g. mutations, epistasis or canalization) can be used to understand and interpret artificial-selection data. The practical use of the models and their implementation in a software package are demonstrated through the analysis of a selection experiment on the shape of the wing in Drosophila melanogaster.

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Section: (B) Genetic Driftmentioning

confidence: 99%

A modelling framework for the analysis of artificial-selection time series

2011

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“…Furthermore, in Waxman and Peck's method of generating mutations, the mutants occurring most commonly have an effect equal to the bias. Empirical evidence shows, however, that the distribution of mutational effects on quantitative traits is leptokurtic, with most mutations having very small effects and a few having very large effects (Simmons and Crow 1977;Mackay et al 1992;Caballero and Keightley 1994;Garcia-Dorado et al 1999;Lynch et al 1999 (Falconer and Mackay 1996;Houle et al 1996;Lynch and Walsh 1998;Keightley 2004), where s 2 E is the environmental variance, l is the average number of mutations per generation per haploid genome, and a is the difference in value between mutant and wild-type homozygotes. As V M from published experiments depends on the mean square rather than the variance of mutational effects and the mutational bias on the trait implies that E(a) ¼ D 6 ¼ 0, this indicates that, even if all mutants had the same effect, the bias D could not exceed ffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2V M =l p (see 1 Vassilieva and Lynch 1999, p. 122).…”

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The Anomalous Effects of Biased Mutation Revisited: Mean–Optimum Deviation and Apparent Directional Selection Under Stabilizing Selection

Zhang

Hill

2008

Genetics

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Empirical evidence indicates that the distribution of the effects of mutations on quantitative traits is not symmetric about zero. Under stabilizing selection in infinite populations with normally distributed mutant effects having a nonzero mean, Waxman and Peck showed that the deviation of the population mean from the optimum is expected to be small. We show by simulation that genetic drift, leptokurtosis of mutational effects, and pleiotropy can increase the mean-optimum deviation greatly, however, and that the apparent directional selection thereby caused can be substantial.I N most models of the maintenance of genetic variance in quantitative traits by mutation-selection balance it is assumed, not least for mathematical simplicity, that the distribution of the effects of mutations on these traits is symmetric about zero (e.g., Bulmer 1980;Turelli 1984;Barton 1990;Keightley and Hill 1990;Zhang and Hill 2002). Mutation-accumulation experiments indicate, however, that mutations significantly affect average values of quantitative traits (Santiago et al. 1992;Lyman et al. 1996;Keightley and Ohnishi 1998;Lynch et al. 1998;Garcia-Dorado et al. 1999;Vassilieva and Lynch 1999;Ostrow et al. 2007; P. D. Keightley and D. L. Halligan, personal communication). For example, Garcia-Dorado et al. (1999) found that the mean effect of mutations on abdominal bristle number in Drosophila melanogaster is À0.24 environmental standard deviations.Recently, Waxman and Peck (2003) investigated a model in which this symmetry assumption was relaxed, i.e., a bias from zero in the mean of the distribution of mutational effects. They found that the deviation between the mean phenotypic value of the trait and the optimum (the mean-optimum deviation) is small. Similar estimates were previously obtained by Bü rger (2000; see p. 247, Equation 7.13). Both analyses were based on a number of other similar assumptions, however, which turn out to have an important influence on the mean-optimum deviation. In this note we consider some of these assumptions and focus on their impact on Waxman and Peck's (2003) conclusions.Waxman and Peck (2003) assumed a model in which the allelic effects of mutations at individual loci were normally distributed, but with a mean that departed from zero. Although they allowed differences among the parameters of the distribution of mutant effects at four different loci, in accordance with Welch and Waxman (2002), this generated overall distributions that did not deviate far from the normal (e.g., kurtosis $4 in the model for their Figure 3; cf. 3 for the normal). Furthermore, in Waxman and Peck's method of generating mutations, the mutants occurring most commonly have an effect equal to the bias. Empirical evidence shows, however, that the distribution of mutational effects on quantitative traits is leptokurtic, with most mutations having very small effects and a few having very large effects (Simmons and Crow 1977;Mackay et al. 1992;Caballero and Keightley 1994;Garcia-Dorado et al. 1999;Lynch et al. 1999; P. ...

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“…The generally reduced contribution of domestication QTL regions, and to a lesser extent the domestication sweep regions, to domestication-related traits variation in maize is likely a direct result of selection purging variants that favor the teosinte morphology in these regions. Theory and analysis of response to long-term artificial selection in a number of plant and animal species indicate that initial generations of selection response are due to standing variation in the initial population, but that genetic variation in later generations is usually mostly due to the effects of new mutations (Keightley 2004;Walsh 2004). Thus, mutation is expected to be an important generator of genetic variation over the several thousand generations of selection and evolution of distinct maize types from a common ancestral population following the domestication bottleneck.…”

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Genetic Architecture of Domestication-Related Traits in Maize

et al. 2016

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Strong directional selection occurred during the domestication of maize from its wild ancestor teosinte, reducing its genetic diversity, particularly at genes controlling domestication-related traits. Nevertheless, variability for some domestication-related traits is maintained in maize. The genetic basis of this could be sequence variation at the same key genes controlling maize-teosinte differentiation (due to lack of fixation or arising as new mutations after domestication), distinct loci with large effects, or polygenic background variation. Previous studies permit annotation of maize genome regions associated with the major differences between maize and teosinte or that exhibit population genetic signals of selection during either domestication or postdomestication improvement. Genome-wide association studies and genetic variance partitioning analyses were performed in two diverse maize inbred line panels to compare the phenotypic effects and variances of sequence polymorphisms in regions involved in domestication and improvement to the rest of the genome. Additive polygenic models explained most of the genotypic variation for domesticationrelated traits; no large-effect loci were detected for any trait. Most trait variance was associated with background genomic regions lacking previous evidence for involvement in domestication. Improvement sweep regions were associated with more trait variation than expected based on the proportion of the genome they represent. Selection during domestication eliminated large-effect genetic variants that would revert maize toward a teosinte type. Small-effect polygenic variants (enriched in the improvement sweep regions of the genome) are responsible for most of the standing variation for domestication-related traits in maize.KEYWORDS quantitative trait loci; nested association mapping; genome-wide association study; variance components; Zea mays T HE domestication of all major crop plants occurred in a relatively short period in human history, starting 10,000 years ago (Harlan 1992). During the domestication process, seeds of preferred forms were selected and saved to plant subsequent generations. Some alleles favored under domestication may have been neutral or even deleterious for the survival of wild plant species; for example, seed shattering promotes seed dispersal in wild grasses, but alleles for nondisarticulating seed structures were strongly selected for under domestication (Galinat 1983). Consequently, rare alleles favorable for growth and development under agricultural conditions or for traits desired by humans increased in frequency, often reaching fixation and reducing genetic variation very near causal sequence sites (Wang et al. 1999). In addition, domestication was often accompanied by severe genetic bottlenecks from the use of small founder populations. The reduction in effective population sizes also resulted in reduced genetic diversity genome-wide. Population genetics methods to model the strength and duration of bottlenecks provide a means to ...

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Mutational Variation and Long‐Term Selection Response

Cited by 18 publications

References 74 publications

A modelling framework for the analysis of artificial-selection time series

A modelling framework for the analysis of artificial-selection time series

The Anomalous Effects of Biased Mutation Revisited: Mean–Optimum Deviation and Apparent Directional Selection Under Stabilizing Selection

Genetic Architecture of Domestication-Related Traits in Maize

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