No abstract

BackgroundMany serious diseases have a genetic basis which, from an evolutionary point of view, should have been selected against, resulting in very low frequencies. The remarkable sustained prevalence of a number of disease-associated alleles is therefore surprising. We believe that antagonistic pleiotropy, when multiple effects of a gene have opposing effects on fitness (e.g., sickle cell disease), may be more widespread than typically considered. We hypothesize that, rather than being an exception to the rule of genetic disorders, antagonistic pleiotropy may be common.MethodsWe surveyed the medical literature in order to determine whether sufficient evidence exists to reassess the nature of antagonistic pleiotropy; from being considered an unusual scenario to one that is anticipated. We also used a simple population genetic model to examine the feasibility of antagonistic pleiotropy to act as a mechanism to maintain polymorphism for serious genetic disorders even if the benefits are subtle.ResultsWe identified a number of examples of antagonistic pleiotropy where the deleterious effect, the beneficial effect, and the exact molecular cause have been demonstrated. We also identified putative cases in which there is circumstantial evidence or a strong reason to expect antagonistic pleiotropy in a genetic disorder. The population genetic model demonstrates that alleles with severe deleterious health effects can be maintained at medically relevant frequencies with only minor beneficial pleiotropic effects.ConclusionWe believe that our identification of several cases of antagonistic pleiotropy, despite the lack of research on this question and the varied natures of the types of these disorders, speaks to both the underappreciated nature of this phenomenon and its potentially fundamental importance. If antagonistic pleiotropy is as common as our research suggests, this may explain why so many serious diseases, even apparently environmentally caused ones, have a genetic component. Furthermore, acceptance of a genome full of antagonistically pleiotropic genetic interactions poses important implications for clinical treatment and disease prevention research, especially genetically based therapies.

Background Ideally, the distribution of research funding for different types of cancer should be equitable with respect to the societal burden each type of cancer imposes. These burdens can be estimated in a variety of ways; “Years of Life Lost” (YLL) measures the severity of death in regard to the age it occurs, "Disability-Adjusted Life-Years" (DALY) estimates the effects of non-lethal disabilities incurred by disease and economic metrics focus on the losses to tax revenue, productivity or direct medical expenses. We compared research funding from the National Cancer Institute (NCI) to a variety of burden metrics for the most common types of cancer to identify mismatches between spending and societal burden. Methods Research funding levels were obtained from the NCI website and information for societal health and economic burdens were collected from government databases and published reports. We calculated the funding levels per unit burden for a wide range of different cancers and burden metrics and compared these values to identify discrepancies. Results Our analysis reveals a considerable mismatch between funding levels and burden. Some cancers are funded at levels far higher than their relative burden suggests (breast cancer, prostate cancer, and leukemia) while other cancers appear underfunded (bladder, esophageal, liver, oral, pancreatic, stomach, and uterine cancers). Conclusions These discrepancies indicate that an improved method of health care research funding allocation should be investigated to better match funding levels to societal burden.

We investigate the multilinear epistatic model under mutation-limited directional selection. We confirm previous results that only directional epistasis, in which genes on average reinforce or diminish each other's effects, contribute to the initial evolution of mutational effects. Thus, either canalization or decanalization can occur under directional selection, depending on whether positive or negative epistasis is prevalent. We then focus on the evolution of the epistatic coefficients themselves. In the absence of higher-order epistasis, positive pairwise epistasis will tend to weaken relative to additive effects, while negative pairwise epistasis will tend to become strengthened. Positive third-order epistasis will counteract these effects, while negative third-order epistasis will reinforce them. More generally, gene interactions of all orders have an inherent tendency for negative changes under directional selection, which can only be modified by higher-order directional epistasis. We identify three types of nonadditive quasi-equilibrium architectures that, although not strictly stable, can be maintained for an extended time: (1) nondirectional epistatic architectures; (2) canalized architectures with strong epistasis; and (3) near-additive architectures in which additive effects keep increasing relative to epistasis.

Adaptation is usually conceived as the fit of a population mean to a fitness optimum. Natural selection, however, does not act only to optimize the population mean. Rather, selection normally acts on the fitness of individual organisms in the population. Furthermore, individual genotypes do not produce invariant phenotypes, and their fitness depends on how precisely they are able to realize their target phenotypes. For these reasons we suggest that it is better to conceptualize adaptation as accuracy rather than as optimality. The adaptive inaccuracy of a genotype can be measured as a function of the expected distance of its associated phenotype from a fitness optimum. The less the distance, the more accurate is the adaptation. Adaptive accuracy has two components: the deviance of the genotypically set target phenotype from the optimum and the precision with which this target phenotype can be realized. The second component, the adaptive precision, has rarely been quantified as such. We survey the literature to quantify how much of the phenotypic variation in wild populations is due to imprecise development. We find that this component is often substantial and highly variable across traits. We suggest that selection for improved precision may be important for many traits.

No abstract

The evolution of cis-regulatory elements (or enhancers) appears to proceed at dramatically different rates in different taxa. Vertebrate enhancers are often very highly conserved in their sequences, and relative positions, across distantly related taxa. In contrast, functionally equivalent enhancers in closely related Drosophila species can differ greatly in their sequences and spatial organization. We present a populationgenetic model to explain this difference. The model examines the dynamics of ® xation of pairs of individually deleterious, but compensating, mutations. As expected, small populations are predicted to have a high rate of evolution, and the rate decreases with increasing population size. In contrast to previous models, however, this model predicts that the rate of evolution by pairs of compensatory mutations increases dramatically for population sizes above several thousand individuals, to the point of greatly exceeding the neutral rate. Application of this model predicts that species with moderate population sizes will have relatively conserved enhancers, whereas species with larger populations will be expected to evolve their enhancers at much higher rates. We propose that the different degree of conservation seen in vertebrate and Drosophila enhancers may be explained solely by differences in their population sizes and generation times.

Adaptation is usually conceived as the fit of a population mean to a fitness optimum. Natural selection, however, does not act only to optimize the population mean. Rather, selection normally acts on the fitness of individual organisms in the population. Furthermore, individual genotypes do not produce invariant phenotypes, and their fitness depends on how precisely they are able to realize their target phenotypes. For these reasons we suggest that it is better to conceptualize adaptation as accuracy rather than as optimality. The adaptive inaccuracy of a genotype can be measured as a function of the expected distance of its associated phenotype from a fitness optimum. The less the distance, the more accurate is the adaptation. Adaptive accuracy has two components: the deviance of the genotypically set target phenotype from the optimum and the precision with which this target phenotype can be realized. The second component, the adaptive precision, has rarely been quantified as such. We survey the literature to quantify how much of the phenotypic variation in wild populations is due to imprecise development. We find that this component is often substantial and highly variable across traits. We suggest that selection for improved precision may be important for many traits.