When does frequency-independent selection maintain genetic variation?

Frequency-independent selection is generally considered as a force that acts to reduce the genetic variation in evolving populations, yet rigorous arguments for this idea are scarce. When selection fluctuates in time, it is unclear whether frequency-independent selection may maintain genetic polymorphism without invoking additional mechanisms. We show that constant frequency-independent selection with arbitrary epistasis on a well-mixed haploid population eliminates genetic variation if we assume linkage equilibrium between alleles. To this end, we introduce the notion of frequency-independent selection at the level of alleles, which is sufficient to prove our claim and contains the notion of frequency-independent selection on haploids. When selection and recombination are weak but of the same order, there may be strong linkage disequilibrium; numerical calculations show that stable equilibria are highly unlikely. Using the example of a diallelic two-locus model, we then demonstrate that frequency-independent selection that fluctuates in time can maintain stable polymorphism if linkage disequilibrium changes its sign periodically. We put our findings in the context of results from the existing literature and point out those scenarios in which the possible role of frequency-independent selection in maintaining genetic variation remains unclear

Inherent Load Measurement and Component Identification by multi-dimensional Coded Data in the Component's Subsurface Region

AbstractIn industrial production, the absence of component markings and unrecognized component failure can result in a lack of protection against product piracy and malfunctions of machinery and installations. A technique for storing data inherently in the subsurface region of the component was developed. Inherently stored data is highly resistant to external stresses and inseparably linked to the component. To evaluate the integrity of highly stressed components, material inherent sensors are induced in the subsurface region of the component to store the loading history. These techniques offer the potential for securely identifying and evaluating the status of components, and thus reducing failure costs

Effective Distance for DNA-Mediated Charge Transport between Repair Proteins

The stacked aromatic base pairs within the DNA double helix facilitate charge transport down its length in the absence of lesions, mismatches, and other stacking perturbations. DNA repair proteins containing [4Fe4S] clusters can take advantage of DNA charge transport (CT) chemistry to scan the genome for mistakes more efficiently. Here we examine the effective length over which charge can be transported along DNA between these repair proteins. We define the effective CT distance as the length of DNA within which two proteins are able to influence their ensemble affinity to the DNA duplex via CT. Endonuclease III, a DNA repair glycosylase containing a [4Fe4S] cluster, was incubated with DNA duplexes of different lengths (1.5–9 kb), and atomic force microscopy was used to quantify the binding of proteins to these duplexes to determine how the relative protein affinity changes with increasing DNA length. A sharp change in binding slope is observed at 3509 base pairs, or about 1.2 μm, that supports the existence of two regimes for protein binding, one within the range for DNA CT, one outside of the range for CT; DNA CT between the redox proteins bound to DNA effectively decreases the ensemble binding affinity of oxidized and reduced proteins to DNA. Utilizing an Endonuclease III mutant Y82A, which is defective in carrying out DNA CT, shows only one regime for protein binding. Decreasing the temperature to 4 °C or including metallointercalators on the duplex, both of which should enhance base stacking and decrease DNA floppiness, leads to extending the effective length for DNA charge transport to ∼5300 bp or 1.8 μm. These results thus support DNA charge transport between repair proteins over kilobase distances. The results furthermore highlight the ability of DNA repair proteins to search the genome quickly and efficiently using DNA charge transport chemistry

High Strain Rate and Stress-State-Dependent Martensite Transformation in AISI 304 at Low Temperatures

Deformation-induced martensitic transformation as the basis of a hardening process is dependent, among others, on the stress state. In applications such as cryogenic cutting, where a hardened martensitic subsurface can be produced in metastable austenitic steels, different stress states exist. Furthermore, cutting typically occurs at high strain rates greater than 103s−1. In order to gain a deeper insight into the behavior of a metastable austenitic steel (AISI 304) upon cryogenic cutting, the influence of high strain rates under different loading conditions was analyzed. It was observed that higher strain rates lead to a decrease in the α′-martensite content if exposed to tensile loads due to generated adiabatic heat. Furthermore, a lath-like α′-martensite was induced. Under shear stress, no suppression of α′-martensite formation by higher strain rates was found. A lath α′-martensite was formed, too. In the specimens that were subjected exclusively to compressive loading, almost no α′-martensite was present. The martensitic surface generated by cutting experiments showed deformation lines in which α′-martensite was formed in a wave-like shape. As for the shear specimens, more α′-martensite was formed with increasing strain rate, i.e., force. Additionally, magnetic etching proved to be an effective method to verify the transformation of ferromagnetic α′-martensite

Catch Me if You Can: Adaptation from Standing Genetic Variation to a Moving Phenotypic Optimum

International audienceAdaptation lies at the heart of Darwinian evolution. Accordingly, numerous studies have tried to provide a formal framework for the description of the adaptive process. Out of these, two complementary modelling approaches have emerged: While so-called adaptive-walk models consider adaptation from the successive fixation of de novo mutations only, quantitative genetic models assume that adaptation proceeds exclusively from pre-existing standing genetic variation. The latter approach, however, has focused on short-term evolution of population means and variances rather than on the statistical properties of adaptive substitutions. Our aim is to combine these two approaches by describing the ecological and genetic factors that determine the genetic basis of adaptation from standing genetic variation in terms of the effect-size distribution of individual alleles. Specifically, we consider the evolution of a quantitative trait to a gradually changing environment. By means of analytical approximations, we derive the distribution of adaptive substitutions from standing genetic variation, that is, the distribution of the phenotypic effects of those alleles from the standing variation that become fixed during adaptation. Our results are checked against individual-based simulations. We find that, compared to adaptation from de novo mutations, (i) adaptation from standing variation proceeds by the fixation of more alleles of small effect; (ii) populations that adapt from standing genetic variation can traverse larger distances in phenotype space and, thus, have a higher potential for adaptation if the rate of environmental change is fast rather than slow