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 .     

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.     

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.     

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.     

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.     

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.     

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.     

The effect of biochar management on soil and plant community properties in a boreal forest

Biochar management has been proposed as a possible tool to mitigate anthropogenic CO₂ emissions, and thus far its impacts in forested environments remain poorly understood. We conducted a large‐scale, replicated field experiment using 0.05‐ha plots in the boreal region in northern Sweden to evaluate how soil and vegetation properties and processes responded to biochar application and the disturbance associated with burying biochar in the soil. We employed a randomized block design, where biochar and soil mixing treatments were established in factorial combination (i.e., control, soil mixing only, biochar only, and biochar and soil mixing; n = 6 plots of each). After two growing seasons, we found that biochar application enhanced net soil N mineralization rates and soil concentrations regardless of the soil mixing treatment, but had no impact on the availability of , the majority of soil microbial community parameters, or soil respiration. Meanwhile, soil mixing enhanced soil concentrations, but had negative impacts on net N mineralization rates and several soil microbial community variables. Many of the effects of soil mixing on soil nutrient and microbial community properties were less extreme when biochar was also added. Biochar addition had almost no effects on vegetation properties (except for a small reduction in species richness of the ground layer vegetation), while soil mixing caused significant reductions in graminoid and total ground layer vegetation cover, and enhanced seedling survival rates of P. sylvestris, and seed germination rates for four tree species. Our results suggest that biochar application can serve as an effective tool to store soil C in boreal forests while enhancing availability. They also suggest that biochar may serve as a useful complement to site preparation techniques that are frequently used in the boreal region, by enhancing soil fertility and reducing nutrient losses when soils are scarified during site preparation.     

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.     

Investigating the linkage between disease‐causing amino acid variants and their effect on protein stability and binding

Single amino acid variations (SAV) occurring in human population result in natural differences between individuals or cause diseases. It is well understood that the molecular effect of SAV can be manifested as changes of the wild type characteristics of the corresponding protein, among which are the protein stability and protein interactions. Typically the effect of SAV on protein stability and interactions was assessed via the changes of the wild type folding and binding free energies. However, in terms of SAV affecting protein functionally and disease susceptibility, one wants to know to what extend the wild type function is perturbed by the SAV. Here it is demonstrated that relative, rather than the absolute, change of the folding and binding free energy serves as a good indicator for SAV association with disease. Using HumVar as a source for disease‐causing SAV and experimentally determined free energy changes from ProTherm and SKEMPI databases, correlation coefficients (CC) between the disease index and relative folding and binding probability indexes, respectively, was achieved. The obtained CCs demonstrated the applicability of the proposed approach and it served as good indicator for SAV association with disease. Proteins 2016; 84:232–239. © 2015 Wiley Periodicals, Inc.     

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.     

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.     

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.     

Different fates of deposited and in a temperate forest in northeast China: a 15N tracer study

Increasing atmospheric reactive nitrogen (N) deposition due to human activities could change N cycling in terrestrial ecosystems. However, the differences between the fates of deposited and are still not fully understood. Here, we investigated the fates of deposited and , respectively, via the application of ¹⁵NH₄NO₃ and NH₄¹⁵NO₃ in a temperate forest ecosystem. Results showed that at 410 days after tracer application, most was immobilized in litter layer (50 ± 2%), while a considerable amount of penetrated into 0–5 cm mineral soil (42 ± 2%), indicating that litter layer and 0–5 cm mineral soil were the major N sinks of and , respectively. Broad‐leaved trees assimilated more ¹⁵N under NH₄¹⁵NO₃ treatment compared to under ¹⁵NH₄NO₃ treatment, indicating their preference for –N. At 410 days after tracer application, 16 ± 4% added ¹⁵N was found in aboveground biomass under treatment, which was twice more than that under treatment (6 ± 1%). At the same time, approximately 80% added ¹⁵N was recovered in soil and plants under both treatments, which suggested that this forest had high potential for retention of deposited N. These results provided evidence that there were great differences between the fates of deposited and , which could help us better understand the mechanisms and capability of forest ecosystems as a sink of reactive nitrogen.     

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.     

Thermodynamics of Aβ16–21 dissociation from a fibril: Enthalpy,entropy, and volumetric properties

Here, we provide insights into the thermodynamic properties of A dissociation from an amyloid fibril using all‐atom molecular dynamics simulations in explicit water. An umbrella sampling protocol is used to compute potentials of mean force (PMF) as a function of the distance ξ between centers‐of‐mass of the A peptide and the preformed fibril at nine temperatures. Changes in the enthalpy and the entropic energy are determined from the temperature dependence of these PMF(s) and the average volume of the simulation box is computed as a function of ξ. We find that the PMF at 310 K is dominated by enthalpy while the entropic energy does not change significantly during dissociation. The volume of the system decreases during dissociation. Moreover, the magnitude of this volume change also decreases with increasing temperature. By defining dock and lock states using the solvent accessible surface area (SASA), we find that the behavior of the electrostatic energy is different in these two states. It increases (unfavorable) and decreases (favorable) during dissociation in lock and dock states, respectively, while the energy due to Lennard‐Jones interactions increases continuously in these states. Our simulations also highlight the importance of hydrophobic interactions in accounting for the stability of A . Proteins 2015; 83:1963–1972. © 2015 Wiley Periodicals, Inc.     

Quantifying the impact of daily and seasonal variation in sap pH on xylem dissolved inorganic carbon estimates in plum trees

In studies on internal CO₂ transport, average xylem sap pH (pH_x) is one of the factors used for calculation of the concentration of dissolved inorganic carbon in the xylem sap ([]). Lack of detailed pH_x measurements at high temporal resolution could be a potential source of error when evaluating [] dynamics. In this experiment, we performed continuous measurements of CO₂ concentration ([CO₂]) and stem temperature (T_stem), complemented with pH_x measurements at 30‐min intervals during the day at various stages of the growing season (Day of the Year (DOY): 86 (late winter), 128 (mid‐spring) and 155 (early summer)) on a plum tree (Prunus domestica L. cv. Reine Claude d'Oullins). We used the recorded pH_x to calculate [] based on T_stem and the corresponding measured [CO₂]. No statistically significant difference was found between mean [] calculated with instantaneous pH_x and daily average pH_x. However, using an average pH_x value from a different part of the growing season than the measurements of [CO₂] and T_stem to estimate [] led to a statistically significant error. The error varied between 3.25 ± 0.01% under‐estimation and 3.97 ± 0.01% over‐estimation, relative to the true [] data. Measured pH_x did not show a significant daily variation, unlike [CO₂], which increased during the day and declined at night. As the growing season progressed, daily average [CO₂] (3.4%, 5.3%, 7.4%) increased and average pH_x (5.43, 5.29, 5.20) decreased. Increase in [CO₂] will increase its solubility in xylem sap according to Henry's law, and the dissociation of [] will negatively affect pH_x. Our results are the first quantifying the error in [] due to the interaction between [CO₂] and pH_x on a seasonal time scale. We found significant changes in pH_x across the growing season, but overall the effect on the calculation of [] remained within an error range of 4%. However, it is possible that the error could be more substantial for other tree species, particularly if pH_x is in the more sensitive range (pH_x > 6.5).