Search

Robustness to genetic or environmental disturbances is often considered as a key property of living systems. Yet, in spite of being discussed since the 1950s, how robustness emerges from the complexity of genetic architectures and how it evolves still remains unclear. In particular, whether or not robustness is independent to various sources of perturbations conditions the range of adaptive scenarios that can be considered. For instance, selection for robustness to heritable mutations is likely to be modest and indirect, and its evolution might result from indirect selection on a pleiotropically-related character (e.g., homeostasis). Here, I propose to treat various robustness measurements as quantitative characters, and study theoretically, by individual-based simulations, their propensity to evolve independently. Based on a simple evolutionary model of a gene regulatory network, I showed that five measurements of the robustness of gene expression to genetic or non-genetic disturbances were substantially correlated. Yet, robustness was mutationally variable in several dimensions, and robustness components could evolve differentially under direct selection pressure. Therefore, the fact that the sensitivity of gene expression to mutations and environmental factors rely on the same gene networks does not preclude distinct evolutionary histories of robustness components.

In many studies, related individuals are phenotyped in order to infer how their genotype contributes to their phenotype, through the estimation of parameters such as breeding values or locus effects. When it is not possible to phenotype all the individuals, it is important to properly sample the population to improve the precision of the statistical analysis. This article studies how to optimize such sampling designs for pedigrees and association studies. Two sampling methods are developed, stratified sampling and D optimality. It is found that it is important to take account of mutation when sampling pedigrees with many generations: as the size of mutation effects increases, optimized designs sample more individuals in late generations. Optimized designs for association studies tend to improve the joint estimation of breeding values and locus effects, all the more as sample size is low and the genetic architecture of the trait is simple. When the trait is determined by few loci, they are reminiscent of classical experimental designs for regression models and tend to select homozygous individuals. When the trait is determined by many loci, locus effects may be difficult to estimate, even if an optimized design is used. [ABSTRACT FROM AUTHOR]

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 F2 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 alleles, 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.

Transposable elements are one of the major components of genomes. Some copies are fully efficient; i.e., they are able to produce the proteins needed for their own transposition, and they can move and duplicate into the genome. Other copies are mutated. They may have lost their moving ability, their coding capacity, or both, thus becoming pseudogenes slowly eliminated from the genome through deletions and natural selection. Little is known about the dynamics of such mutant elements, particularly concerning their interactions with autonomous copies. To get a better understanding of the transposable elements' evolution after their initial invasion, we have designed a population genetics model of transposable elements dynamics including mutants or nonfunctional sequences. We have particularly focused on the case where these sequences are nonautonomous elements, known to be able to use the transposition machinery produced by the autonomous ones. The results show that such copies generally prevent the system from achieving a stable transposition-selection equilibrium and that nonautonomous elements can invade the system at the expense of autonomous ones. The resulting dynamics are mainly cyclic, which highlights the similarities existing between genomic selfish DNA sequences and host-parasite systems.

Transposable elements are often considered as selfish DNA sequences able to invade the genome of their host species. Their evolutive dynamics are complex, due to the interaction between their intrinsic amplification capacity, selection at the host level, transposition regulation, and genetic drift. Here, we propose modeling the first steps of TE invasion, i.e., just after a horizontal transfer, when a single copy is present in the genome of one individual. If the element has a constant transposition rate, it will disappear in most cases: the elements with low-transposition rate are frequently lost through genetic drift, while those with high-transposition rate may amplify, leading to the sterility of their host. Elements whose transposition rate is regulated are able to successfully invade the populations, thanks to an initial transposition burst followed by a strong limitation of their activity. Self-regulation or hybrid dysgenesis may thus represent some genome-invasion parasitic strategies.

Abstract Background Many theoretical models predicting the dynamics of transposable elements (TEs) in genomes, populations, and species have already been proposed. However, most of them only focus on populations of sexual diploid individuals, and TE dynamics in populations partly composed by autogamous individuals remains poorly investigated. To estimate the impact of selfing on TE dynamics, the short- and long-term evolution of TEs was simulated in outcrossing populations with various proportions of selfing individuals. Results Selfing has a deep impact on TE dynamics: the higher the selfing rate, the lower the probability of invasion. Already known non-equilibrium dynamics (complete loss, domestication, cyclical invasion of TEs) can all be described whatever the mating system. However, their pattern and their respective frequencies greatly depend on the selfing rate. For instance, in cyclical dynamics resulting from interactions between autonomous and non-autonomous copies, cycles are faster when the selfing rate increases. Interestingly, an abrupt change in the mating system from sexuality to complete asexuality leads to the loss of all the elements over a few hundred generations. In general, for intermediate selfing rates, the transposition activity remains maintained. Conclusions Our theoretical results evidence that a clear and systematic contrast in TE content according to the mating system is expected, with a smooth transition for intermediate selfing rates. Several parameters impact the TE copy number, and all dynamics described in allogamous populations can be also observed in partly autogamous species. This study thus provides new insights to understand the complex signal from empirical comparison of closely related species with different mating systems.

Abstract Transposable elements (TEs) were first discovered more than 50 years ago, but were totally ignored for a long time. Over the last few decades they have gradually attracted increasing interest from research scientists. Initially they were viewed as totally marginal and anecdotic, but TEs have been revealed as potentially harmful parasitic entities, ubiquitous in genomes, and finally as unavoidable actors in the diversity, structure, and evolution of the genome. Since Darwin's theory of evolution, and the progress of molecular biology, transposable elements may be the discovery that has most influenced our vision of (genome) evolution. In this review, we provide a synopsis of what is known about the complex interactions that exist between transposable elements and the host genome. Numerous examples of these interactions are provided, first from the standpoint of the genome, and then from that of the transposable elements. We also explore the evolutionary aspects of TEs in the light of post-Darwinian theories of evolution. Reviewers This article was reviewed by Jerzy Jurka, Jürgen Brosius and I. King Jordan. For complete reports, see the Reviewers' reports section.

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.