Genetic Variation in Pleiotropy: Differential Epistasis as a Source of Variation in the Allometric Relationship Between Long Bone Lengths and Body Weight

Pavličev, Mihaela; Kenney-Hunt, Jane P.; Norgard, Elizabeth A.; Roseman, Charles C.; Wolf, Jason B.; Cheverud, James M.

doi:10.1111/j.1558-5646.2007.00255.x

Cited by 107 publications

(160 citation statements)

References 42 publications

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“…At the phenotypic level, selection for compatible trait values of functionally and developmentally related traits is predicted to cause their co-inheritance and hence their genetic and phenotypic correlation (Olsen and Miller 1958;Lande 1980;Cheverud 1982Cheverud , 1984. More recently, Cheverud and colleagues (Cheverud et al 2004;Pavlicev et al 2007;Wagner et al 2007) have suggested that pleiotropic relationships should reflect the coselection of traits such that pleiotropic effects would be favored among traits selected together and not favored among traits selected independently. Our analysis of the relationship between pleiotropy and phenotypic correlation indicates that these two measures of trait relationship are relatively strongly correlated.…”

Section: Discussionmentioning

confidence: 99%

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

et al. 2008

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Quantitative trait locus (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N ¼ 1040), using QTL analysis on 70 skeletal traits. We identify 798 singletrait QTL, coalescing to 105 loci that affect on average 7-8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When dominance does occur, the LG/J allele tends to be dominant to the SM/J allele (30% vs. 8%). Over-and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.

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Section: Discussionmentioning

confidence: 99%

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

et al. 2008

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“…Instead, statistical approaches have been applied to inbred cross data and typically find evidence for pleiotropy, for example, as in studies of weight and morphometry (Brockmann et al 2000;Leamy et al 2002;Wolf et al 2005Wolf et al , 2006Pavlicev et al 2008). However, these methods leave open the possibility that pleiotropy at a locus is attributable to multiple genes of different function that happen to reside next to each on the genome.…”

Section: Genetic Architecture: Pleiotropymentioning

confidence: 99%

Genetic architecture of quantitative traits in mice, flies, and humans

Flint¹,

Mackay²

2009

Genome Res.

409

364

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We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.Recent successes in mapping quantitative trait loci (QTLs) that contribute to phenotypic variation in humans and model organisms make it possible to address important questions about the genetic architecture of quantitative phenotypes, such as the likely number of loci, their mode of genetic action, and interaction with each other and with the environment. An understanding of the genetic architecture of quantitative traits is not only important in its own right, it will also inform studies that seek to proceed to the identification of the quantitative trait genes (QTGs) and the quantitative trait nucleotide (QTN) variants, the functional changes in DNA sequence that contribute to trait variation.In this work we use examples from two genetically wellcharacterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, to discuss how an understanding of the genetic architecture of quantitative phenotypes in model organisms informs mapping experiments in human genetics. In our discussion of the latter, we draw upon the recent successful application of genome-wide association studies (GWAS) to both quantitative phenotypes (such as height and weight) and disease phenotypes (assuming that the genetic architecture of common disease is similar, if not identical, to that of quantitative phenotypes).Genetic architecture has been the subject of a number of recent reviews, most of which deal with information from a single model organism (Mackay 2004) or review a small number of phenotypes (Kendler and Greenspan 2006). Here, our purpose is different. We tackle three relate...

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“…2000; Pavlicev et al. 2008; Wagner and Zhang 2011). This conflict between selection and the maintenance of genetic variation in multiple traits remains a fundamental and puzzling problem in evolutionary biology (Walsh and Blows 2009).…”

mentioning

confidence: 99%

“…2005, 2006; Pavlicev et al. 2008). Simulations using the information that epistatic interactions can provide variation in pleiotropy and covariance patterns have shown how selection can promote changes in pleiotropy that can change covariation (Jones et al.…”

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confidence: 99%

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

et al. 2017

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Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection.

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Genetic Variation in Pleiotropy: Differential Epistasis as a Source of Variation in the Allometric Relationship Between Long Bone Lengths and Body Weight

Cited by 107 publications

References 42 publications

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

Pleiotropic Patterns of Quantitative Trait Loci for 70 Murine Skeletal Traits

Genetic architecture of quantitative traits in mice, flies, and humans

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

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