Evolutionary experiments on mate recognition in the Drosophila serrata species complex

It is becoming increasingly apparent that at least some aspects of the evolution of mate recognition may be amenable to manipulation in evolutionary experiments. Quantitative genetic analyses that focus on the genetic consequences of evolutionary processes that result in mate recognition evolution may eventually provide an understanding of the genetic basis of the process of speciation. We review a series of experiments that have attempted to determine the genetic basis of the response to natural and sexual selection on mate recognition in the Drosophila serrata species complex. The genetic basis of mate recognition has been investigated at three levels: (1) between the species of D. serrata and D. birchii using interspecific hybrids, (2) between populations of D. serrata that are sympatric and allopatric with respect to D. birchii, and (3) within populations of D. serrata. These experiments suggest that it may be possible to use evolutionary experiments to observe important events such as the reinforcement of mate recognition, or the generation of the genetic associations that are central to many sexual selection models.

Conditional simulation of random fields by successive residuals

This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.

Modelling High-Dimensional Data by Mixtures of Factor Analyzers

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

Sex differences in heritability of BMI: A comparative study of results from twin studies in eight countries

Body mass index (BMI), a simple anthropometric measure, is the most frequently used measure of adiposity and has been instrumental in documenting the worldwide increase in the prevalence of obesity witnessed during the last decades. Although this increase in overweight and obesity is thought to be mainly due to environmental changes, i.e., sedentary lifestyles and high caloric diets, consistent evidence from twin studies demonstrates high heritability and the importance of genetic differences for normal variation in BMI. We analysed self-reported data on BMI from approximately 37,000 complete twin pairs (including opposite sex pairs) aged 20-29 and 30-39 from eight different twin registries participating in the GenomEUtwin project. Quantitative genetic analyses were conducted and sex differences were explored. Variation in BMI was greater for women than for men, and in both sexes was primarily explained by additive genetic variance in all countries. Sex differences in the variance components were consistently significant. Results from analyses of opposite sex pairs also showed evidence of sex-specific genetic effects suggesting there may be some differences between men and women in the genetic factors that influence variation in BMI. These results encourage the continued search for genes of importance to the body composition and the development of obesity. Furthermore, they suggest that strategies to identify predisposing genes may benefit from taking into account potential sex specific effects.

Exploring the Etiology of the Association Between Birthweight and IQ in an Adolescent Twin Sample

The negative effects of very low birthweight on intellectual development have been well documented, and more recently this effect has been shown to generalise to birthweights within the normal range. In this study we investigate the etiology of this relationship by using a classical twin design to disentangle the contributions of genes and environment. A previous Dutch study (Boomsma et al., 2001) examining these effects indicated that genes were important in mediating the association of birthweight to full IQ measured at ages 7 and 10, but not at ages 5 and 12. Here the association between birthweight and IQ at age 16 is considered (N = 523 twin pairs). Using variance components modeling we found that the genetic variance in birthweight (4%) completely overlapped with that in verbal IQ but not performance or full IQ. Results further showed the importance of shared environmental effects on birthweight (similar to 60%) but not on IQ (with genes explaining up to 72% of IQ variance). Models incorporating a direction of causation parameter between birthweight and IQ provided adequate fit to the data in either causal direction for performance and full IQ, but the model with verbal 10 causing birthweight was preferred to one in which birthweight influenced verbal IQ. As the measurement of birthweight precedes the measurement of twins' IQ at age 16, the influence of verbal IQ might be better considered as a proxy for parents' 10 or education, and it is possible that brighter mothers provide better prenatal environments for their children.

Effect of environment and genotype on bread-making quality of spring-sown spring wheat cultivars in China

Improvement of end-use quality in bread wheat depends on a thorough understanding of current wheat quality and the influences of genotype (G), environment (E), and genotype by environment interaction (G x E) on quality traits. Thirty-nine spring-sown spring wheat (SSSW) cultivars and advanced lines from China were grown in four agro-ecological zones comprising seven locations during the 1998 and 1999 cropping seasons. Data on 12 major bread-making quality traits were used to investigate the effect of G, E, and G x E on these traits. Wide range variability for protein quantity and quality, starch quality parameters and milling quality in Chinese SSSW was observed. Genotype and environment were found to significantly influence all quality parameters as major effects. Kernel hardness, flour yield, Zeleny sedimentation value and mixograph properties were mainly influenced by the genetic variance components, while thousand kernel weight, test weight, and falling number were mostly influenced by the environmental variance components. Genotype, environment, and their interaction had important effects on test weight, mixing development time and RVA parameters. Cultivars originating from Zone VI (northeast) generally expressed high kernel hardness, good starch quality, but poor milling and medium to weak mixograph performance; those from Zone VII (north) medium to good gluten and starch quality, but low milling quality; those from Zone VIII (central northwest) medium milling and starch quality, and medium to strong mixograph performance; those from Zone IX (western/southwestern Qinghai-Tibetan Plateau) medium milling quality, but poor gluten strength and starch parameters; and those from Zone X (northwest) high milling quality, strong mixograph properties, but low protein content. Samples from Harbin are characterized by good gluten and starch quality, but medium to poor milling quality; those from Hongxinglong by strong mixograph properties, medium to high milling quality, but medium to poor starch quality and medium to low protein content; those from Hohhot by good gluten but poor milling quality; those from Linhe by weak gluten quality, medium to poor milling quality; those from Lanzhou by poor bread-making and starch quality; those from Yongning by acceptable bread-making and starch quality and good milling quality; and those from Urumqi by good milling quality, medium gluten quality and good starch pasting parameters. Our findings suggest that Chinese SSSW quality could be greatly enhanced through genetic improvement for targeted well-characterized production environments.

Modeling the relationships between adult attachment patterns and borderline personality disorder: The role of impulsivity and aggressiveness

To obtain a better understanding of the associations among Borderline Personality Disorder (BPD), adult attachment patterns, impulsivity, and aggressiveness, we tested four competing models of these relationships: a) BPD is associated with the personality traits of impulsivity and aggressiveness, but adult attachment patterns predict neither BPD nor impulsive/aggressive features; b) adult attachment patterns are significant predictors of BPD but not of impulsive/aggressive traits, although these traits correlate with BPD; c) adult attachment patterns are significant predictors of impulsive and aggressive traits, which in turn predict BPD; and d) adult attachment patterns significantly predict both BPD and impulsive/aggressive traits. We assessed 466 consecutively admitted outpatients using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (V. 2.0), the Attachment Style Questionnaire, the Barratt Impulsiveness Scale-11, and the Aggression Questionnaire. Maximum likelihood structural equation modeling of the covariance matrix showed that model (c) was the best fitting model (chi(2) (21) = 31.67, p >.05, RMSEA = .023, test of close fit p >.85). This result indicates that adult attachment patterns act indirectly as risk factors for BPD because of their relationships with aggressive/impulsive personality traits.

On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

Matching conditional moments in PDF modelling of nonpremixed combustion

The rate of generation of fluctuations with respect to the scalar values conditioned on the mixture fraction, which significantly affects turbulent nonpremixed combustion processes, is examined. Simulation of the rate in a major mixing model is investigated and the derived equations can assist in selecting the model parameters so that the level of conditional fluctuations is better reproduced by the models. A more general formulation of the multiple mapping conditioning (MMC) model that distinguishes the reference and conditioning variables is suggested. This formulation can be viewed as a methodology of enforcing certain desired conditional properties onto conventional mixing models. Examples of constructing consistent MMC models with dissipation and velocity conditioning as well as of combining MMC with large eddy simulations (LES) are also provided. (c) 2005 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Opposite effects of androgen receptor CAG repeat length on increased risk of left-handedness in males and females

Prenatal exposure to testosterone has been hypothesised to effect lateralization by influencing cell death in the foetal brain. Testosterone binds to the X chromosome linked androgen receptor, which contains a polymorphic polyglutamine CAG repeat, the length of which is positively correlated with testosterone levels in males, and negatively correlated in females. To determine whether the length of the androgen receptor mediates the effects of testosterone on laterality, we examined the association between the number of CAG repeats in the androgen receptor gene and handedness for writing. Association was tested by adding regression terms for the length of the androgen receptor alleles to a multi-factorial-threshold model of liability to left-handedness. In females we found the risk of left-handedness was greater in those with a greater number of repeats (p=0.04), this finding was replicated in a second independent sample of female twins (p=0.014). The length of the androgen receptor explained 6% of the total variance and 24% of the genetic variance in females. In males the risk of left-handedness was greater in those with fewer repeats (p=0.02), with variation in receptor length explaining 10% of the total variance and 24% of the genetic variance. Thus, consistent with Witelson's theory of testosterone action, in all three samples the likelihood of left handedness increased in those individuals with variants of the androgen receptor associated with lower testosterone levels.

Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within- family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components.

The implications of simultaneous smoking initiation for inferences about the genetics of smoking behavior from twin data

We examined early social influences across stages of smoking within the context of a twin study using an environmental exposure specific to smoking: whether twins started smoking at the same time (simultaneous smoking initiation: SSI). We expected that SSI would be a good index of shared social influences on smoking initiation. Rates of SSI were indeed significantly higher in MZ twins and in twins who shared peers and classes, as well as in male twins. With the exception of regular smoking in females, we found no significant difference in estimates of genetic and environmental parameters between SSI and non-SSI pairs for any of the smoking measures that we examined (DSM-IV and Fagerstrom HSI measures of nicotine dependence; DSM-IV nicotine withdrawal; heavy smoking; and in males, regular smoking). For regular smoking in females, allowing for additional shared environmental influences associated with SSI only modestly reduced our estimates of additive genetic variance (56% vs. 68%). These results indicate the important social influences that may occur for smoking initiation do not appear to seriously bias estimates of genetic effects on later stages of smoking.

Animal migration: is there a common migratory syndrome?

Ornithologists, and especially northern hemisphere ornithologists, have traditionally thought of migration as an annual return movement of populations between regular breeding and non-breeding grounds. Problems arise because selection does not ordinarily act on populations and because organisms of many taxa (including birds) are clearly migrants, but fail to undertake movements of the kind described. There are also extensive return movements that are not migratory. I propose that it is more useful to think of migration as a syndrome of behavioral and other traits that function together within individuals, and that such a syndrome provides a common ground across taxa from aphids to albatrosses. Large-scale return movements of populations are one outcome of the syndrome. Similar behavioral and physiological traits serve both to define migration and to provide a test for it. I use two insect (Hemipteran) examples to illustrate migratory syndromes and to demonstrate that, in many migrants, behavior and physiology correlate with life history and morphological traits to form syndromes at two levels. I then compare the two Hemipterans with migration in birds, butterflies, and fish to assess the question of whether there are migratory syndromes in common between these diverse migrants. Syndromes are more similar at the level of behavior than when morphology and life history traits are included. Recognizing syndromes leads to important evolutionary questions concerning migration strategies, trade-offs, the maintenance of genetic variance and the responses of migratory syndromes to both similar and different selective regimes.

The cost of uniqueness in groundwater model calibration

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a Solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The cost of uniqueness is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, ill turn, can lead to erroneous predictions made by a model that is ostensibly well calibrated. Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as all inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based oil pilot points, and calibration is Implemented using both zones of piecewise constancy and constrained minimization regularization. (C) 2005 Elsevier Ltd. All rights reserved.

The roles of natural and sexual selection during adaptation to a novel environment

The net effect of sexual selection on nonsexual fitness is controversial. On one side, elaborate display traits and preferences for them can be costly, reducing the nonsexual fitness of individuals possessing them, as well as their offspring, In contrast, sexual selection may reinforce nonsexual fitness if an individual's attractiveness and quality are genetically correlated. According to recent models, such good-genes mate choice should increase both the extent and rate of adaptation. We evolved 12 replicate populations of Drosophila serrata in a powerful two-way factorial experimental design to test the separate and combined contributions of natural and sexual selection to adaptation to a novel larval food resource. Populations evolving in the presence of natural selection had significantly higher mean nonsexual fitness when measured over three generations (13-15) during the course of experimental evolution (16-23% increase). The effect of natural selection was even more substantial when measured in a standardized, monogamous mating environment at the end of the experiment (generation 16; 52% increase). In contrast, and despite strong sexual selection on display traits, there was no evidence from any of the four replicate fitness measures that sexual selection promoted adaptation. In addition, a comparison of fitness measures conducted under different mating environments demonstrated a significant direct cost of sexual selection to females, likely arising from some form of male-induced harm. Indirect benefits of sexual selection in promoting adaptation to this novel resource environment therefore appear to be absent in this species, despite prior evidence suggesting the operation of good-genes mate choice in their ancestral environment. How novel environments affect the operation of good-genes mate choice is a fundamental question for future sexual selection research.