A Semiparametric Estimator of the Crossing Point in the Two‐Sample Linear Shift Function: Application to Crossing Lifetime Distributions

Let X and Y be two random variables with continuous distribution functions F and G. Consider two independent observations X₁, … , X_m from F and Y₁, … , Y_n from G. Moreover, suppose there exists a unique x* such that F(x) > G(x) for x < x* and F(x) < G(x) for x > x* or vice versa. A semiparametric model with a linear shift function (Doksum, 1974) that is equivalent to a location‐scale model (Hsieh, 1995) will be assumed and an empirical process approach (Hsieh, 1995) is used to estimate the parameters of the shift function. Then, the estimated shift function is set to zero, and the solution is defined to be an estimate of the crossing‐point x*. An approximate confidence band of the linear shift function at the crossing‐point x* is also presented, which is inverted to yield an approximate confidence interval for the crossing‐point. Finally, the lifetime of guinea pigs in days observed in a treatment‐control experiment in Bjerkedal (1960) is used to demonstrate our procedure for estimating the crossing‐point. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Occurrence and genetics of black‐eyed migratory locusts,Locusta migratoria (Orthoptera: Acrididae)

Black‐eyed Locusta migratoria appeared in albino locusts as a result of crossing between a short‐winged strain originating from Tsushima Island, Japan, and an albino strain originating from Okinawa Island. The black eye trait was recessive to the white eye trait because the crosses between black‐ and white‐eyed albino locusts produced only individuals with white eyes in the F₁ generation. In the F₂ generation, black‐ and white‐eyed individuals appeared in a ratio of 1:3, indicating that the black eye trait was controlled by a simple Mendelian unit. The black eye trait showed no genetic association with other traits including wing morph, adult body dimensions and classical morphometric ratios such as hind femur length / head width and forewing length / hind femur length.     

MAXIMUM-LIKELIHOOD ESTIMATION OF POPULATION DIVERGENCE TIMES AND POPULATION PHYLOGENY IN MODELS WITHOUT MUTATION

In this paper we present a method for estimating population divergence times by maximum likelihood in models without mutation. The maximum-likelihood estimator is compared to a commonly applied estimator based on Wright's F_ST statistic. Simulations suggest that the maximum-likelihood estimator is less biased and has a lower variance than the F_ST-based estimator. The maximum-likelihood estimator provides a statistical framework for the analysis of population history given genetic data. We demonstrate how maximum-likelihood estimates of the branching pattern of divergence of multiple populations may be obtained. We also describe how the method may be applied to test hypotheses such as whether populations have maintained equal population sizes. We illustrate the method by applying it to two previously published sets of human restriction fragment length polymorphism (RFLP) data.     

Analysis of Diallel Table for Experiments in Block Designs

In this paper the analysis of genotypes obtained in diallel crossing system, including parents, one set of F₁s and reciprocal F₁'s, is given. This analysis is presented for data obtained from the experiments laid out in block designs. The analysis of variance, estimator of reciprocal effects, estimators of general and specific combining abilities as well as statistics for testing of hypotheses concerning those parameters are given.     

The use and abuse of genetic marker‐based estimates of relatedness and inbreeding

Genetic marker‐based estimators remain a popular tool for measuring relatedness (r_xy) and inbreeding (F) coefficients at both the population and individual level. The performance of these estimators fluctuates with the number and variability of markers available, and the relatedness composition and demographic history of a population. Several methods are available to evaluate the reliability of the estimates of r_xy and F, some of which are implemented in the program COANCESTRY. I used the simulation module in COANCESTRY since assess the performance of marker‐based estimators of r_xy and F in a species with very low genetic diversity, New Zealand's little spotted kiwi (Apteryx owenii). I also conducted a review of published papers that have used COANCESTRY as its release to assess whether and how the reliability of the estimates of r_xy and F produced by genetic markers are being measured and reported in published studies. My simulation results show that even when the correlation between true (simulated) and estimated r_xy or F is relatively high (Pearson's r = 0.66–0.72 and 0.81–0.85, respectively) the imprecision of the estimates renders them highly unreliable on an individual basis. The literature review demonstrates that the majority of studies do not report the reliability of marker‐based estimates of r_xy and F. There is currently no standard practice for selecting the best estimator for a given data set or reporting an estimator's performance. This could lead to experimental results being interpreted out of context and render the robustness of conclusions based on measures of r_xy and F debatable.     

Background selection and FST: Consequences for detecting local adaptation

Background selection is a process whereby recurrent deleterious mutations cause a decrease in the effective population size and genetic diversity at linked loci. Several authors have suggested that variation in the intensity of background selection could cause variation in F_ST across the genome, which could confound signals of local adaptation in genome scans. We performed realistic simulations of DNA sequences, using recombination maps from humans and sticklebacks, to investigate how variation in the intensity of background selection affects F_ST and other statistics of population differentiation in sexual, outcrossing species. We show that, in populations connected by gene flow, Weir and Cockerham's (1984; Evolution, 38 , 1358) estimator of F_ST is largely insensitive to locus‐to‐locus variation in the intensity of background selection. Unlike F_ST, however, d_XY is negatively correlated with background selection. Moreover, background selection does not greatly affect the false‐positive rate in F_ST outlier studies in populations connected by gene flow. Overall, our study indicates that background selection will not greatly interfere with finding the variants responsible for local adaptation.     

EDENetworks: A user‐friendly software to build and analyse networks in biogeography,ecology and population genetics

The recent application of graph‐based network theory analysis to biogeography, community ecology and population genetics has created a need for user‐friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy‐to‐use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray‐Curtis or Sorensen distance, or population genetic metrics such as F_ST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.     

Latitudinal and altitudinal growth patterns of brown trout Salmo trutta at different spatial scales

Spatial variation in growth of stream‐dwelling brown trout Salmo trutta was explored in 13 populations using a long‐term study (1993–2004) in the Bay of Biscay drainage, northern Spain. The high variability in fork length (L_F) of S. trutta in the study area was similar to the body‐size range found in the entire European distribution of the species. Mean L_F at age varied: 0+ years, 57·4–100·7 mm; 1+ years, 111·6–176·0 mm; 2+ years, 155·6–248·4 mm and 3+ years, 194·3–290·9 mm. Average L_F at age was higher in main courses and lower reaches compared with small tributaries and upper reaches. Annual specific growth rates (G_L) were: 0+ to 1+ years, 0·634–0·825 mm mm⁻¹ year⁻¹; 1+ to 2+ years, 0·243–0·342 mm mm⁻¹ year⁻¹; 2+ to 3+ years, 0·166–0·222 mm mm⁻¹ year⁻¹, showing a great homogeneity. Regression models showed that water temperature and altitude were the major determinants of L_F at age variability within the study area. A broader spatial analysis using available data from stream‐dwelling S. trutta populations throughout Europe indicated a negative relationship between latitude and L_F of individuals and a negative interaction between latitude and altitude. These findings support previous evidence of the pervasive role of water temperature on the L_F of this species. Altitude appeared as the overall factor that includes the local variation of other variables, such as water temperature or food availability. At a larger scale, latitude was the factor that encompassed these environmental gradients and explained the differences in L_F of S. trutta. In summary, L_F at age in stream‐dwelling S. trutta decreases with latitude in Europe, the converse of Bergmann's rule.     

Enhancement of the hydrolysis activity of F0F1‐ATPases using 60 Hz magnetic fields

The effects of extremely low frequency (ELF) magnetic fields on membrane F₀F₁‐ATPase activity have been studied. When the F₀F₁‐ATPase was exposed to 60 Hz magnetic fields of different magnetic intensities, 0.3 and 0.5 mT magnetic fields enhanced the hydrolysis activity, whereas 0.1 mT exposure caused no significant changes. Even if the F₀F₁‐ATPase was inhibited by N,N‐dicyclohexylcarbodiimide, its hydrolysis activity was enhanced by a 0.5 mT 60 Hz magnetic field. Moreover, when the chromatophores which were labeled with F‐DHPE were exposed to a 0.5 mT, 60 Hz magnetic field, it was found that the pH of the outer membrane of the chromatophore was unchanged, which suggested that the magnetic fields used in this work did not affect the activity of F0. Taken together, our results show that the effects of magnetic fields on the hydrolysis activity of the membrane F₀F₁‐ATPases were dependent on magnetic intensity and the threshold intensity is between 0.1 and 0.3 mT, and suggested that the F1 part of F₀F₁‐ATPase may be an end‐point affected by magnetic fields. Bioelectromagnetics 30:663–668, 2009. © 2009 Wiley‐Liss, Inc.     

A Beta-mixture model for assessing genetic population structure

Summary An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F‐statistics. In this article, we propose a new Bayesian beta‐mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F_ST s from the sample. The model also has important application for codominant markers and single‐nucleotide polymorphism (SNP) data. The number of F_ST is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F_ST s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F_ST s also incorporate uncertainty about the magnitude of within‐population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.     

Age and growth of Carcharhinus leucas in the northern Gulf of Mexico: incorporating variability in size at birth

Age and growth rates of bull shark Carcharhinus leucas[n = 255; 555–2230 mm fork length (L_F)] from the northern Gulf of Mexico were estimated from ring counts on vertebral sections collected from fishery‐dependent and ‐independent surveys. Two growth models were fitted to observed data: the von Bertalanffy growth model (VBGM) with t₀ as the third parameter and a modified version of the VBGM using a fixed size‐at‐birth intercept as the third parameter. To address the variability in size‐at‐birth, a Monte Carlo simulation was incorporated into the size‐at‐birth intercept. The sex‐specific growth models were not significantly different, allowing a sexes combined model to be generated. The traditional VBGM predicted a theoretical maximum size (L_∞) of 3007·1 mm L_F, a growth coefficient (K) of 0·042 year^?1 and a theoretical age at zero length (t₀) of –6·844 years. The modified VBGM with a fixed size‐at‐birth intercept of 565 mm L_F predicted an L_∞ of 2289·2 mm L_F and a K value of 0·089 year^?1. When comparing model estimates to previously published information, the traditional VBGM predicted a significantly lower theoretical maximum size and a higher growth coefficient than those produced using data collected during the 1980s. Overall, results obtained using the VBGM with a fixed size‐at‐birth produced more biologically realistic parameters than that of the VBGM with t₀. The Monte‐Carlo simulation incorporating variability in size‐at‐birth produced similar results to the VBGM using a fixed size‐at‐birth. This study provides the first attempt to incorporate variability at size‐at‐birth and provide measurements of variability around the individual parameter estimates for an elasmobranch.     

The Nonparametric Behrens‐Fisher Problem: Asymptotic Theory and a Small‐Sample Approximation

A generalization of the Behrens‐Fisher problem for two samples is examined in a nonparametric model. It is not assumed that the underlying distribution functions are continuous so that data with arbitrary ties can be handled. A rank test is considered where the asymptotic variance is estimated consistently by using the ranks over all observations as well as the ranks within each sample. The consistency of the estimator is derived in the appendix. For small samples (n₁, n₂ ≥ 10), a simple approximation by a central t‐distribution is suggested where the degrees of freedom are taken from the Satterthwaite‐Smith‐Welch approximation in the parametric Behrens‐Fisher problem. It is demonstrated by means of a simulation study that the Wilcoxon‐Mann‐Whitney‐test may be conservative or liberal depending on the ratio of the sample sizes and the variances of the underlying distribution functions. For the suggested approximation, however, it turns out that the nominal level is maintained rather accurately. The suggested nonparametric procedure is applied to a data set from a clinical trial. Moreover, a confidence interval for the nonparametric treatment effect is given.     

A novel F420‐dependent anti‐oxidant mechanism protects Mycobacterium tuberculosis against oxidative stress and bactericidal agents

Mycobacterium tuberculosis (Mtb) is an aerobic bacterium that persists intracellularly in host macrophages and has evolved diverse mechanisms to combat and survive oxidative stress. Here we show a novel F₄₂₀‐dependent anti‐oxidant mechanism that protects Mtb against oxidative stress. Inactivation of the fbiC gene in Mtb results in a cofactor F₄₂₀‐deficient mutant that is hypersensitive to oxidative stress and exhibits a reduction in NADH/NAD⁺ ratios upon treatment with menadione. In agreement with the recent hypothesis on oxidative stress being an important component of the pathway resulting in cell death by bactericidal agents, F₄₂₀^? mutants are hypersensitive to mycobactericidal agents such as isoniazid, moxifloxacin and clofazimine that elevate oxidative stress. The Mtb deazaflavin‐dependent nitroreductase (Ddn) and its two homologues Rv1261c and Rv1558 encode for an F₄₂₀H₂‐dependent quinone reductase (Fqr) function leading to dihydroquinones. We hypothesize that Fqr proteins catalyse an F₄₂₀H₂‐specific obligate two‐electron reduction of endogenous quinones, thereby competing with the one‐electron reduction pathway and preventing the formation of harmful cytotoxic semiquinones, thus protecting mycobacteria against oxidative stress and bactericidal agents. These findings open up an avenue for the inhibition of the F₄₂₀ biosynthesis pathway or Fqr‐class proteins as a mechanism to potentiate the action of bactericidal agents.     

Generalization of the QST framework in hierarchically structured populations: Impacts of inbreeding and dominance

Q_ST is a differentiation parameter based on the decomposition of the genetic variance of a trait. In the case of additive inheritance and absence of selection, it is analogous to the genic differentiation measured on individual loci, F_ST. Thus, Q_ST?F_ST comparison is used to infer selection: selective divergence when Q_ST > F_ST, or convergence when Q_ST < F_ST. The definition of Q‐statistics was extended to two‐level hierarchical population structures with Hardy–Weinberg equilibrium. Here, we generalize the Q‐statistics framework to any hierarchical population structure. First, we developed the analytical definition of hierarchical Q‐statistics for populations not at Hardy–Weinberg equilibrium. We show that the Q‐statistics values obtained with the Hardy–Weinberg definition are lower than their corresponding F‐statistics when F_IS > 0 (higher when F_IS < 0). Then, we used an island model simulation approach to investigate the impact of inbreeding and dominance on the Q_ST?F_ST framework in a hierarchical population structure. We show that, while differentiation at the lower hierarchical level (Q_SR) is a monotonic function of migration, differentiation at the upper level (Q_RT) is not. In the case of additive inheritance, we show that inbreeding inflates the variance of Q_RT, which can increase the frequency of Q_RT > F_RT cases. We also show that dominance drastically reduces Q‐statistics below F‐statistics for any level of the hierarchy. Therefore, high values of Q‐statistics are good indicators of selection, but low values are not in the case of dominance.     

Enhanced Photovoltaic Performance of Amorphous Donor–Acceptor Copolymers Based on Fluorine‐Substituted Benzodioxocyclohexene‐Annelated Thiophene

Donor–acceptor (D‐A) type π‐conjugated copolymers with crystalline behavior have been extensively investigated as donor semiconductors in organic photovoltaics (OPVs). On the other hand, the development of high‐performance amorphous donor materials is still behind. The amorphous donor copolymer DTS‐C₀(F₂) consisting of dithieno[3,2‐b:2′,3′‐d]silole ( DTS ) donor unit and the recently developed fluorine‐substituted naphtho[2,3‐c]thiophene‐4,9‐dione ( C₀(F₂) ) acceptor unit shows moderate photovoltaic performance upon blending with PC₇₁BM. In this work, to enhance the hole‐transporting characteristics, a 3‐hexylthiophene ( HT ) spacer unit is integrated into the conjugated backbone, resulting in a new amorphous copolymer DTS‐HT‐C₀(F₂) . The strong electron‐accepting nature of C₀(F₂) allows the introduction of the HT spacer without affecting the frontier orbital energies and thus the D‐A character. Without using solvent additives and thermal annealing, OPVs based on DTS‐HT‐C₀(F₂) and [6,6]‐phenyl‐C71‐butyric acid methyl ester PC₇₁BM show an improved power conversion efficiency of 9.12%. Investigation of the device physics unambiguously reveals that the hole mobility of the copolymer in the blend is increased by an order of magnitude by the introduction of HT , while keeping an amorphous film nature, leading to higher short‐circuit current density and fill factor. These results demonstrate the realization of high‐performance OPVs based on amorphous active layers.     

Detecting Wahlund effects together with amplification problems: Cryptic species,null alleles and short allele dominance in Glossina pallidipes populations from Tanzania

Population genetics is a convenient tool to study the population biology of non‐model and hard to sample species. This is particularly true for parasites and vectors. Heterozygote deficits and/or linkage disequilibrium often occur in such studies and detecting the origin of those (Wahlund effect, reproductive system or amplification problems) is uneasy. We used new tools (correlation between the number of times a locus is found in significant linkage disequilibrium and its genetic diversity, correlations between Wright's F_IS and F_ST, F_IS and number of missing data, F_IT and allele size and standard errors comparisons) for the first time on a real data set of tsetse flies, a vector of dangerous diseases to humans and domestic animals in sub‐Saharan Africa. With these new tools, and cleaning data from null allele, temporal heterogeneity and short allele dominance effects, we unveiled the coexistence of two highly divergent cryptic clades in the same sites. These results are in line with other studies suggesting that the biodiversity of many taxa still largely remain undescribed, in particular pathogenic agents and their vectors. Our results also advocate that including individuals from different cohorts tends to bias subdivision measures and that keeping loci with short allele dominance and/or too frequent missing data seriously jeopardize parameter's estimations. Finally, separated analyses of the two clades suggest very small tsetse densities and relatively large dispersal.     

WFABC: a Wright–Fisher ABC‐based approach for inferring effective population sizes and selection coefficients from time‐sampled data

With novel developments in sequencing technologies, time‐sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright–Fisher model for inferring selection coefficients (s) given effective population size (N_e), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)‐based method that is able to correctly infer genomewide average N_e from time‐serial data, which is then set as a prior for inferring per‐site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time‐serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).     

Global patterns of population genetic differentiation in seed plants

Evaluating the factors that drive patterns of population differentiation in plants is critical for understanding several biological processes such as local adaptation and incipient speciation. Previous studies have given conflicting results regarding the significance of pollination mode, seed dispersal mode, mating system, growth form and latitudinal region in shaping patterns of genetic structure, as estimated by F_ST values, and no study to date has tested their relative importance together across a broad scale. Here, we assembled a 337‐species data set for seed plants from publications with data on F_ST from nuclear markers and species traits, including variables pertaining to the sampling scheme of each study. We used species traits, while accounting for sampling variables, to perform phylogenetic multiple regressions. Results demonstrated that F_ST values were higher for tropical, mixed‐mating, non‐woody species pollinated by small insects, indicating greater population differentiation, and lower for temperate, outcrossing trees pollinated by wind. Among the factors we tested, latitudinal region explained the largest portion of variance, followed by pollination mode, mating system and growth form, while seed dispersal mode did not significantly relate to F_ST. Our analyses provide the most robust and comprehensive evaluation to date of the main ecological factors predicted to drive population differentiation in seed plants, with important implications for understanding the basis of their genetic divergence. Our study supports previous findings showing greater population differentiation in tropical regions and is the first that we are aware of to robustly demonstrate greater population differentiation in species pollinated by small insects.     

Regression on Quantile Residual Life

Summary A time‐specific log‐linear regression method on quantile residual lifetime is proposed. Under the proposed regression model, any quantile of a time‐to‐event distribution among survivors beyond a certain time point is associated with selected covariates under right censoring. Consistency and asymptotic normality of the regression estimator are established. An asymptotic test statistic is proposed to evaluate the covariate effects on the quantile residual lifetimes at a specific time point. Evaluation of the test statistic does not require estimation of the variance–covariance matrix of the regression estimators, which involves the probability density function of the survival distribution with censoring. Simulation studies are performed to assess finite sample properties of the regression parameter estimator and test statistic. The new regression method is applied to a breast cancer data set with long‐term follow‐up to estimate the patients' median residual lifetimes, adjusting for important prognostic factors.     

A method for adjusting allele frequencies in the case of microsatellite allele drop‐out

A new method is proposed to adjust allele frequencies when allelic drop‐out is common. This method assumes Hardy–Weinberg equilibrium (HWE), and treats the problematic alleles as a one‐locus two‐allele system with dominance. By assuming that the homozygote frequency of the ‘recessive’ allele is measured correctly, we can back calculate the allele frequency of the ‘dominant’ allele, and adjust the heterozygote frequency accordingly. The drawback is that multilocus genotypes cannot be constructed and tests that use deviations from Hardy–Weinberg such as tests for bottlenecks become impossible. An example is given where a large homozygote excess (F_IS = 0.44) is adjusted to a reasonable level (F_IS = 0.046). The effect of scoring error was set in relation to sampling error and while F_IS values can be seriously biased, F_ST values are not necessarily so, if scoring error and sample size are both low. As sample size increases, the effect of scoring error increases.