Patterns of molecular evolution in dioecious and non‐dioecious Silene

Dioecy (i.e. having separate sexes) is a rather rare breeding system in flowering plants. Such rareness may result from a high probability of extinction in dioecious species because of less efficient dispersal and the costs of sexual selection, which are expected to harm dioecious species' survival on the long term. These handicaps should decrease the effective population size () of dioecious species, which in turn should reduce the efficacy of selection. Moreover, sexual selection in dioecious species is expected to specifically affect some genes, which will evolve under positive selection. The relative contribution of these effects is currently unknown and we tried to disentangle them by comparing sequence evolution between dioecious and non‐dioecious species in the Silene genus (Caryophyllaceae), where dioecy has evolved at least twice. For the dioecious species in the section Melandrium, where dioecy is the oldest, we found a global reduction of purifying selection, while on some, male‐biased genes, positive selection was found. For section Otites, where dioecy evolved more recently, we found no significant differences between dioecious and non‐dioecious species. Our results are consistent with the view that dioecy is an evolutionary dead end in flowering plants, although other scenarios for explaining reduced cannot be ruled out. Our results also show that contrasting forces act on the genomes of dioecious plants, and suggest that some time is required before the genome of such plants bears the footprints of dioecy.     

Contemporary effective population and metapopulation size (Ne and meta‐Ne): comparison among three salmonids inhabiting a fragmented system and differing in gene flow and its asymmetries

We estimated local and metapopulation effective sizes ( and meta‐) for three coexisting salmonid species (Salmo salar, Salvelinus fontinalis, Salvelinus alpinus) inhabiting a freshwater system comprising seven interconnected lakes. First, we hypothesized that might be inversely related to within‐species population divergence as reported in an earlier study (i.e., F_ST: S. salar> S. fontinalis> S. alpinus). Using the approximate Bayesian computation method implemented in ONeSAMP, we found significant differences in () between species, consistent with a hierarchy of adult population sizes (). Using another method based on a measure of linkage disequilibrium (LDNE: ), we found more finite values for S. salar than for the other two salmonids, in line with the results above that indicate that S. salar exhibits the lowest among the three species. Considering subpopulations as open to migration (i.e., removing putative immigrants) led to only marginal and non‐significant changes in , suggesting that migration may be at equilibrium between genetically similar sources. Second, we hypothesized that meta‐ might be significantly smaller than the sum of local s (null model) if gene flow is asymmetric, varies among subpopulations, and is driven by common landscape features such as waterfalls. One ‘bottom‐up’ or numerical approach that explicitly incorporates variable and asymmetric migration rates showed this very pattern, while a number of analytical models provided meta‐ estimates that were not significantly different from the null model or from each other. Our study of three species inhabiting a shared environment highlights the importance and utility of differentiating species‐specific and landscape effects, not only on dispersal but also in the demography of wild populations as assessed through local s and meta‐s and their relevance in ecology, evolution and conservation.     

Superoxide anion radical scavenging property of catecholamines

The direct effect of the four catecholamines (adrenaline, noradrenaline, dopamine and isoproterenol) on superoxide anion radicals () was investigated. The reaction between 18‐crown‐6‐ether and potassium superoxide in dimethylsulfoxide was used as a source of . The reactivity of catecholamines with was examined using chemiluminescence, reduction of nitroblue tetrazolium and electron paramagnetic resonance spin‐trapping techniques. 5,5‐Dimethyl‐1‐pyrroline‐N‐oxide was included as the spin trap. The results showed that the four catecholamines were effective and efficient in inhibiting chemiluminescence accompanying the potassium superoxide/18‐crown‐6‐ether system in a dose‐dependent manner over the range 0.05–2 mm in the following order: adrenaline > noradrenaline > dopamine > isoproterenol, with, IC₅₀ = 0.15 ± 0.02 mm 0.21 ± 0.03 mm , 0.27 ± 0.03 mm and 0.50 ± 0.04 mm , respectively. The catecholamines examined also exhibited a strong scavenging effect towards when evaluated this property by the inhibition of nitroblue tetrazolium reduction (56–73% at 1 m concentration). A very similar capacity of scavenging was monitored in the 5,5‐dimethyl‐1‐pyrroline‐N‐oxide spin‐trapping assay. The results suggest that catecholamines tested may involve a direct effect on scavenging radicals. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterization of the superoxide anion radical scavenging activity by tetracycline antibiotics in aprotic media

The tetracycline family antibiotics are widely used as human and veterinary treatments. The drugs are effective as antibiotics and also show antimicrobial and non‐microbial action. However, the antioxidant properties of tetracyclines have not been characterized in aprotic media. To better understand their biological functions, the in vitro superoxide anion radical () scavenging activities of tetracycline, chlortetracycline, oxytetracycline, doxycycline and methacycline were characterized, along with a very efficient scavenger, tiron, in dimethyl sulphoxide (DMSO), using ultra‐weak chemiluminescence (CL). We found that tetracycline, chlortetracycline and doxycycline efficiently inhibited CL from the ‐generating system at concentration levels of 0.02–1.0 mmol/L. Methacycline and oxytetracycline were the scavengers at concentration levels of 0.01–0.1 mmol/L, whereas when their concentration was lowered the drugs were capable of generating , leading to CL enhancement. For all the data obtained in this study, the scavenging activity for the compounds tested decreased in the following order: tetracycline > doxycycline > chlortetracycline > tiron methacycline > oxytetracycline. These results indicate that the tetracycline drugs directly alter redox chemistry in aprotic media. Copyright © 2011 John Wiley & Sons, Ltd.     

Purging putative siblings from population genetic data sets: a cautionary view

Interest has surged recently in removing siblings from population genetic data sets before conducting downstream analyses. However, even if the pedigree is inferred correctly, this has the potential to do more harm than good. We used computer simulations and empirical samples of coho salmon to evaluate strategies for adjusting samples to account for family structure. We compared performance in full samples and sibling‐reduced samples of estimators of allele frequency (), population differentiation () and effective population size (). Results: (i) unless simulated samples included large family groups together with a component of unrelated individuals, removing siblings generally reduced precision of and ; (ii) based on the linkage disequilibrium method was largely unbiased using full random samples but became increasingly upwardly biased under aggressive purging of siblings. Under nonrandom sampling (some families over‐represented), using full samples was downwardly biased; removing just the right ‘Goldilocks’ fraction of siblings could produce an unbiased estimate, but this sweet spot varied widely among scenarios; (iii) weighting individuals based on the inferred pedigree (to produce a best linear unbiased estimator, BLUE) maximized precision of when the inferred pedigree was correct but performed poorly when the pedigree was wrong; (iv) a variant of sibling removal that leaves intact small sibling groups appears to be more robust to errors in inferences about family structure. Our results illustrate the complex challenges posed by presence of family structure, suggest that no single optimal solution exists and argue for caution in adjusting population genetic data sets for the presence of putative siblings without fully understanding the consequences.     

Estimators for QST and coalescence times

Comparisons of to can provide insights into the evolutionary processes that lead to differentiation, or lack thereof, among the phenotypes of different groups (e.g., populations, species), and these comparisons have been performed on a variety of taxa, including humans. Here, I show that for neutrally evolving (i.e., by genetic drift, mutation, and gene flow alone) quantitative characters, the two commonly used estimators have somewhat different interpretations in terms of coalescence times, particularly when the number of groups that have been sampled is small. A similar situation occurs for estimators. Consequently, when observations come from only a small number of groups, which is not an unusual situation, it is important to match estimators appropriately when comparing to .     

Sexual antagonism and meiotic drive cause stable linkage disequilibrium and favour reduced recombination on the X chromosome

Sexual antagonism and meiotic drive are sex‐specific evolutionary forces with the potential to shape genomic architecture. Previous theory has found that pairing two sexually antagonistic loci or combining sexual antagonism with meiotic drive at linked autosomal loci augments genetic variation, produces stable linkage disequilibrium (LD) and favours reduced recombination. However, the influence of these two forces has not been examined on the X chromosome, which is thought to be enriched for sexual antagonism and meiotic drive. We investigate the evolution of the X chromosome under both sexual antagonism and meiotic drive with two models: in one, both loci experience sexual antagonism; in the other, we pair a meiotic drive locus with a sexually antagonistic locus. We find that LD arises between the two loci in both models, even when the two loci freely recombine in females and that driving haplotypes will be enriched for male‐beneficial alleles, further skewing sex ratios in these populations. We introduce a new measure of LD, , which accounts for population allele frequencies and is appropriate for instances where these are sex specific. Both models demonstrate that natural selection favours modifiers that reduce the recombination rate. These results inform observed patterns of congealment found on driving X chromosomes and have implications for patterns of natural variation and the evolution of recombination rates on the X chromosome.     

High‐throughput identification of protein mutant stability computed from a double mutant fitness landscape

The effect of a mutation on protein stability is traditionally measured by genetic construction, expression, purification, and physical analysis using low‐throughput methods. This process is tedious and limits the number of mutants able to be examined in a single study. In contrast, functional fitness effects can be measured in a high‐throughput manner by various deep mutational scanning tools. Using protein GB 1, we have recently demonstrated the feasibility of estimating the mutational stability effect ( G) of single‐substitution based on the functional fitness profile of all double‐substitutions. The principle is to identify genetic backgrounds that have an exhausted stability margin. The functional effect of an additional substitution on these genetic backgrounds can then be used to compute the mutational G based on the biophysical relationship between functional fitness and thermodynamic stability. However, to identify such genetic backgrounds, the approach described in our previous study required a benchmark dataset, which is a set of known mutational G. In this study, a benchmark‐independent approach is developed. The genetic backgrounds of interest are identified using k‐means clustering with the integration of structural information. We further demonstrated that a reasonable approximation of G can also be obtained without taking structural information into account. In summary, this study describes a novel method for computing G from double‐substitution functional fitness profiles alone, without relying on any known mutational G as a benchmark.     

Can Ebola virus evolve to be less virulent in humans?

Understanding Ebola virus (EBOV) virulence evolution not only is timely but also raises specific questions because it causes one of the most virulent human infections and it is capable of transmission after the death of its host. Using a compartmental epidemiological model that captures three transmission routes (by regular contact, via dead bodies and by sexual contact), we infer the evolutionary dynamics of case fatality ratio on the scale of an outbreak and in the long term. Our major finding is that the virus's specific life cycle imposes selection for high levels of virulence and that this pattern is robust to parameter variations in biological ranges. In addition to shedding a new light on the ultimate causes of EBOV's high virulence, these results generate testable predictions and contribute to informing public health policies. In particular, burial management stands out as the most appropriate intervention since it decreases the of the epidemics, while imposing selection for less virulent strains.     

Deep soil carbon dynamics are driven more by soil type than by climate: a worldwide meta‐analysis of radiocarbon profiles

The response of soil carbon dynamics to climate and land‐use change will affect both the future climate and the quality of ecosystems. Deep soil carbon (>20 cm) is the primary component of the soil carbon pool, but the dynamics of deep soil carbon remain poorly understood. Therefore, radiocarbon activity (C), which is a function of the age of carbon, may help to understand the rates of soil carbon biodegradation and stabilization. We analyzed the published C contents in 122 profiles of mineral soil that were well distributed in most of the large world biomes, except for the boreal zone. With a multivariate extension of a linear mixed‐effects model whose inference was based on the parallel combination of two algorithms, the expectation–maximization (EM) and the Metropolis–Hasting algorithms, we expressed soil C profiles as a four‐parameter function of depth. The four‐parameter model produced insightful predictions of soil C as dependent on depth, soil type, climate, vegetation, land‐use and date of sampling (). Further analysis with the model showed that the age of topsoil carbon was primarily affected by climate and cultivation. By contrast, the age of deep soil carbon was affected more by soil taxa than by climate and thus illustrated the strong dependence of soil carbon dynamics on other pedologic traits such as clay content and mineralogy.     

Summary goodness‐of‐fit statistics for binary generalized linear models with noncanonical link functions

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness‐of‐fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer–Lemeshow () and Pigeon–Heyse (J²) statistics can be applied directly. In a simulation study, , , and J² were used to evaluate the fit of probit, log–log, complementary log–log, and log models, all calculated with a common grouping method. The statistic consistently maintained Type I error rates, while those of and J² were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, had more power than or J².     

Sensitivity analysis of effective population size to demographic parameters in house sparrow populations

The ratio between the effective and the census population size, , is an important measure of the long‐term viability and sustainability of a population. Understanding which demographic processes that affect most will improve our understanding of how genetic drift and the probability of fixation of alleles is affected by demography. This knowledge may also be of vital importance in management of endangered populations and species. Here, we use data from 13 natural populations of house sparrow (Passer domesticus) in Norway to calculate the demographic parameters that determine . Using the global variance‐based Sobol’ method for the sensitivity analyses, we found that was most sensitive to demographic variance, especially among older individuals. Furthermore, the individual reproductive values (that determine the demographic variance) were most sensitive to variation in fecundity. Our results draw attention to the applicability of sensitivity analyses in population management and conservation. For population management aiming to reduce the loss of genetic variation, a sensitivity analysis may indicate the demographic parameters towards which resources should be focused. The result of such an analysis may depend on the life history and mating system of the population or species under consideration, because the vital rates and sex–age classes that is most sensitive to may change accordingly.     

pKa predictions for proteins,RNAs, and DNAs with the Gaussian dielectric function using DelPhi pKa

We developed a Poisson‐Boltzmann based approach to calculate the values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian‐based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large shifts of various single point mutations in staphylococcal nuclease (SNase) from ‐cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa's. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves predictions for buried carboxyl residues. Finally, the calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. Proteins 2015; 83:2186–2197. © 2015 Wiley Periodicals, Inc.     

Effective size of density‐dependent populations in fluctuating environments

Reliable estimates of effective population size are of central importance in population genetics and evolutionary biology. For populations that fluctuate in size, harmonic mean population size is commonly used as a proxy for (multi‐) generational effective size. This assumes no effects of density dependence on the ratio between effective and actual population size, which limits its potential application. Here, we introduce density dependence on vital rates in a demographic model of variance effective size. We derive an expression for the ratio in a density‐regulated population in a fluctuating environment. We show by simulations that yearly genetic drift is accurately predicted by our model, and not proportional to as assumed by the harmonic mean model, where N is the total population size of mature individuals. We find a negative relationship between and N. For a given N, the ratio depends on variance in reproductive success and the degree of resource limitation acting on the population growth rate. Finally, our model indicate that environmental stochasticity may affect not only through fluctuations in N, but also for a given N at a given time. Our results show that estimates of effective population size must include effects of density dependence and environmental stochasticity.     

Age‐related increases in human lymphocyte DNA damage: is there a role of aerobic fitness?

Oxidative stress has been advanced as one of the major causes of damage to DNA and other macromolecules. Although physical exercise may also increase oxidative stress, an important role has been recognized for regular exercise in improving the overall functionality of the body, as indicated by an increase in maximal aerobic uptake (O_2max), and in resistance to cell damage. The aims of this study were 1) to evaluate the association between DNA damage in human lymphocytes and age and 2) to evaluate the association between DNA damage in human lymphocytes and O_2max. The sample was composed of 36 healthy and nonsmoking males, aged from 20 to 84 years. O_2max was evaluated through the Bruce protocol with direct measurement of oxygen consumption. The comet assay was used to evaluate the DNA damage, strand breaks and formamidopyrimidine DNA glycosylase (FPG)‐sensitive sites. We found a positive correlation of age with DNA strand breaks but not with FPG‐sensitive sites. O_2max was significantly inversely related with DNA strand breaks, but this relation disappeared when adjusted for age. A significantly positive relation between O_2max and FPG‐sensitive sites was verified. In conclusion, our results showed that younger subjects have lower DNA strand breaks and higher O_2max compared with older subjects and FPG‐sensitive sites are positively related with O_2max, probably as transient damage due to the acute effects of daily physical activity. Copyright © 2013 John Wiley & Sons, Ltd.     

Effects of chronic elevated nitrate concentrations on the structure and function of river biofilms

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speed‐ne: Software to simulate and estimate genetic effective population size (Ne) from linkage disequilibrium observed in single samples

The genetic effective population size, N_e, can be estimated from the average gametic disequilibrium () between pairs of loci, but such estimates require evaluation of assumptions and currently have few methods to estimate confidence intervals. speed‐ne is a suite of matlab computer code functions to estimate from with a graphical user interface and a rich set of outputs that aid in understanding data patterns and comparing multiple estimators. speed‐ne includes functions to either generate or input simulated genotype data to facilitate comparative studies of estimators under various population genetic scenarios. speed‐ne was validated with data simulated under both time‐forward and time‐backward coalescent models of genetic drift. Three classes of estimators were compared with simulated data to examine several general questions: what are the impacts of microsatellite null alleles on , how should missing data be treated, and does disequilibrium contributed by reduced recombination among some loci in a sample impact . Estimators differed greatly in precision in the scenarios examined, and a widely employed estimator exhibited the largest variances among replicate data sets. speed‐ne implements several jackknife approaches to estimate confidence intervals, and simulated data showed that jackknifing over loci and jackknifing over individuals provided ~95% confidence interval coverage for some estimators and should be useful for empirical studies. speed‐ne provides an open‐source extensible tool for estimation of from empirical genotype data and to conduct simulations of both microsatellite and single nucleotide polymorphism (SNP) data types to develop expectations and to compare estimators.     

Soil moisture variations affect short‐term plant‐microbial competition for ammonium,glycine, and glutamate

We tested whether the presence of plant roots would impair the uptake of ammonium (), glycine, and glutamate by microorganisms in a deciduous forest soil exposed to constant or variable moisture in a short‐term (24‐h) experiment. The uptake of ¹⁵NH₄ and dual labeled amino acids by the grass Festuca gigantea L. and soil microorganisms was determined in planted and unplanted soils maintained at 60% WHC (water holding capacity) or subject to drying and rewetting. The experiment used a design by which competition was tested in soils that were primed by plant roots to the same extent in the planted and unplanted treatments. Festuca gigantea had no effect on microbial N uptake in the constant moist soil, but its presence doubled the microbial uptake in the dried and rewetted soil compared with the constant moist. The drying and rewetting reduced by half or more the uptake by F. gigantea, despite more than 60% increase in the soil concentration of . At the same time, the amino acid and ‐ N became equally valued in the plant uptake, suggesting that plants used amino acids to compensate for the lower acquisition. Our results demonstrate the flexibility in plant‐microbial use of different N sources in response to soil moisture fluctuations and emphasize the importance of including transient soil conditions in experiments on resource competition between plants and soil microorganisms. Competition between plants and microorganisms for N is demonstrated by a combination of removal of one of the potential competitors, the plant, and subsequent observations of the uptake of N in the organisms in soils that differ only in the physical presence and absence of the plant during a short assay. Those conditions are necessary to unequivocally test for competition.     

SEX RATIO AND DENSITY AFFECT SEXUAL SELECTION IN A SEX‐ROLE REVERSED FISH

Understanding how demographic processes influence mating systems is important to decode ecological influences on sexual selection in nature. We manipulated sex ratio and density in experimental populations of the sex‐role reversed pipefish Syngnathus typhle. We quantified sexual selection using the Bateman gradient (), the opportunity for selection (I), and sexual selection (I_s), and the maximum standardized sexual selection differential (). We also measured selection on body length using standardized selection differentials (s′) and mating differentials (m′), and tested whether the observed I and I_s differ from values obtained by simulating random mating. We found that I, I_s, and , but not , were higher for females under female than male bias and the opposite for males, but density did not affect these measures. However, higher density decreased sexual selection (m′ but not s′) on female length, but selection on body length was not affected by sex ratio. Finally, I_s but not I was higher than expected from random mating, and only for females under female bias. This study demonstrates that both sex ratio and density affect sexual selection and that disentangling interrelated demographic processes is essential to a more complete understanding of mating behavior and the evolution of mating systems.