| 1. |
- Alvarez-Castro, Jose M., et al.
(författare)
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How to perform meaningful estimates of genetic effects
- 2008
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Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 4:5, s. e1000062-
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Tidskriftsartikel (refereegranskat)abstract
- Although the genotype-phenotype map plays a central role both in Quantitative and Evolutionary Genetics, the formalization of a completely general and satisfactory model of genetic effects, particularly accounting for epistasis, remains a theoretical challenge. Here, we use a two-locus genetic system in simulated populations with epistasis to show the convenience of using a recently developed model, NOIA, to perform estimates of genetic effects and the decomposition of the genetic variance that are orthogonal even under deviations from the Hardy-Weinberg proportions. We develop the theory for how to use this model in interval mapping of quantitative trait loci using Halley-Knott regressions, and we analyze a real data set to illustrate the advantage of using this approach in practice. In this example, we show that departures from the Hardy-Weinberg proportions that are expected by sampling alone substantially alter the orthogonal estimates of genetic effects when other statistical models, like F-2 or G2A, are used instead of NOIA. Finally, for the first time from real data, we provide estimates of functional genetic effects as sets of effects of natural allele substitutions in a particular genotype, which enriches the debate on the interpretation of genetic effects as implemented both in functional and in statistical models. We also discuss further implementations leading to a completely general genotype-phenotype map.
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| 2. |
- Le Rouzic, Arnaud, et al.
(författare)
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Dissection of the genetic architecture of body weight in chicken reveals the impact of epistasis on domestication traits
- 2008
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Ingår i: Genetics. - : Oxford University Press (OUP). - 0016-6731 .- 1943-2631. ; 179:3, s. 1591-1599
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Tidskriftsartikel (refereegranskat)abstract
- In this contribution, we study the genetic mechanisms leading to differences in the observed growth patterns of domesticated White Leghorn chickens and their wild ancestor the red jungle fowl. An epistatic QTL analysis for several body-weight measures from hatch to adulthood confirms earlier findings that polymorphisms at > , 15 loci contribute to body-weight determination in an F-2 intercross between these populations and that many loci are involved in complex genetic interactions. Here, we use a new genetic model to decompose the genetic effects of this multilocus epistatic genetic network. The results show how the functional modeling of genetic effects provides new insights into how genetic interactions in a large set of loci jointly contribute to phenotypic expression. By exploring the functional effects of QTL allels, we show that some alleles can display temporal shifts in the expression of genetic effects due to their dependencies on the genetic background. Our results demonstrate that the effects of many genes are dependent on genetic interactions with other loci and how their involvement in the domestication process relies on these interactions.
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| 3. |
- Le Rouzic, Arnaud, et al.
(författare)
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Evolutionary potential of hidden genetic variation
- 2008
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Ingår i: Trends in Ecology & Evolution. - : Elsevier BV. - 0169-5347 .- 1872-8383. ; 23:1, s. 33-37
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Forskningsöversikt (refereegranskat)abstract
- The ability of a population to respond to natural or artificial selection pressures is determined by the genetic architecture of the selected trait. It is now widely acknowledged that a substantial part of genetic variability can be buffered or released as the result of complex genetic interactions. However, the impact of hidden genetic diversity on phenotypic evolution is still not clear. Here, we argue that a common term to describe the impact of hidden genetic variation on phenotypic change is needed and will help to provide new insights into the contribution of different components of genetic architectures to the evolvability of a character. We introduce the 'genetic charge' concept, to describe how the architecture of a trait can be 'charged' with potential for evolutionary change that can later be 'discharged' in response to selection.
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| 4. |
- Le Rouzic, Arnaud, et al.
(författare)
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Phenotypic evolution from genetic polymorphisms in a radial network architecture
- 2007
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Ingår i: BMC Biology. - : Springer Science and Business Media LLC. - 1741-7007. ; 5, s. 50-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The genetic architecture of a quantitative trait influences the phenotypic response to natural or artificial selection. One of the main objectives of genetic mapping studies is to identify the genetic factors underlying complex traits and understand how they contribute to phenotypic expression. Presently, we are good at identifying and locating individual loci with large effects, but there is a void in describing more complex genetic architectures. Although large networks of connected genes have been reported, there is an almost complete lack of information on how polymorphisms in these networks contribute to phenotypic variation and change. To date, most of our understanding comes from theoretical, model-based studies, and it remains difficult to assess how realistic their conclusions are as they lack empirical support. Results: A previous study provided evidence that nearly half of the difference in eight-week body weight between two divergently selected lines of chickens was a result of four loci organized in a 'radial' network (one central locus interacting with three 'radial' loci that, in turn, only interacted with the central locus). Here, we study the relationship between phenotypic change and genetic polymorphism in this empirically detected network. We use a model-free approach to study, through individual-based simulations, the dynamic properties of this polymorphic and epistatic genetic architecture. The study provides new insights to how epistasis can modify the selection response, buffer and reveal effects of major loci leading to a progressive release of genetic variation. We also illustrate the difficulty of predicting genetic architecture from observed selection response, and discuss mechanisms that might lead to misleading conclusions on underlying genetic architectures from quantitative trait locus (QTL) experiments in selected populations. Conclusion: Considering both molecular (QTL) and phenotypic (selection response) data, as suggested in this work, provides additional insights into the genetic mechanisms involved in the response to selection. Such dissection of genetic architectures and in-depth studies of their ability to contribute to short-or long-term selection response represents an important step towards a better understanding of the genetic bases of complex traits and, consequently, of the evolutionary properties of populations.
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