Population genetic models can be used to study the evolution of the interacting behaviours of parents and their progeny

An example of the evolution of the interacting behaviours of parents and progeny is studied using iterative equations linking the frequencies of the gametes produced by the progeny to the frequencies of the gametes in the parental generation. This population genetics approach shows that a model in which both behaviours are determined by a single locus can lead to a stable equilibrium in which the two behaviours continue to segregate. A model in which the behaviours are determined by genes at two separate loci leads eventually to fixation of the alleles at both loci but this can take many generations of selection. Models of the type described in this paper will be needed to understand the evolution of complex behaviour when genomic or experimental information is available about the genetic determinants of behaviour and the selective values of different genomes. (c) 2007 Elsevier Inc. All rights reserved.

Recent developments in genetic data analysis: what can they tell us about human demographic history?

Over the last decade, a number of new methods of population genetic analysis based on likelihood have been introduced. This review describes and explains the general statistical techniques that have recently been used, and discusses the underlying population genetic models. Experimental papers that use these methods to infer human demographic and phylogeographic history are reviewed. It appears that the use of likelihood has hitherto had little impact in the field of human population genetics, which is still primarily driven by more traditional approaches. However, with the current uncertainty about the effects of natural selection, population structure and ascertainment of single-nucleotide polymorphism markers, it is suggested that likelihood-based methods may have a greater impact in the future.

Past, present and future mathematical models for buildings (i)

This is the first of two articles presenting a detailed review of the historical evolution of mathematical models applied in the development of building technology, including conventional buildings and intelligent buildings. After presenting the technical differences between conventional and intelligent buildings, this article reviews the existing mathematical models, the abstract levels of these models, and their links to the literature for intelligent buildings. The advantages and limitations of the applied mathematical models are identified and the models are classified in terms of their application range and goal. We then describe how the early mathematical models, mainly physical models applied to conventional buildings, have faced new challenges for the design and management of intelligent buildings and led to the use of models which offer more flexibility to better cope with various uncertainties. In contrast with the early modelling techniques, model approaches adopted in neural networks, expert systems, fuzzy logic and genetic models provide a promising method to accommodate these complications as intelligent buildings now need integrated technologies which involve solving complex, multi-objective and integrated decision problems.

Past, present and future mathematical models for buildings (ii)

This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future.

A note on the accuracy of PAC-likelihood inference with microsatellite data

Stephens and Donnelly have introduced a simple yet powerful importance sampling scheme for computing the likelihood in population genetic models. Fundamental to the method is an approximation to the conditional probability of the allelic type of an additional gene, given those currently in the sample. As noted by Li and Stephens, the product of these conditional probabilities for a sequence of draws that gives the frequency of allelic types in a sample is an approximation to the likelihood, and can be used directly in inference. The aim of this note is to demonstrate the high level of accuracy of "product of approximate conditionals" (PAC) likelihood when used with microsatellite data. Results obtained on simulated microsatellite data show that this strategy leads to a negligible bias over a wide range of the scaled mutation parameter theta. Furthermore, the sampling variance of likelihood estimates as well as the computation time are lower than that obtained with importance sampling on the whole range of theta. It follows that this approach represents an efficient substitute to IS algorithms in computer intensive (e.g. MCMC) inference methods in population genetics. (c) 2006 Elsevier Inc. All rights reserved.

Food restriction reverses the hyper-muscular phenotype and force generation capacity deficit of the myostatin null mouse

Food restriction has a great impact on skeletal muscle mass by inducing muscle protein breakdown to provide substrates for energy production through gluconeogenesis. Genetic models of hyper-muscularity interfere with the normal balance between protein synthesis and breakdown which eventually results in extreme muscle growth. Mutations or deletions in the myostatin gene result in extreme muscle mass. Here we evaluated the impact of food restriction for a period of 5 weeks on skeletal muscle size (i.e., fibre cross-sectional area), fibre type composition and contractile properties (i.e., tetanic and specific force) in myostatin null mice. We found that this hyper-muscular model was more susceptible to catabolic processes than wild type mice. The mechanism of skeletal muscle mass loss was examined and our data shows that the myostatin null mice placed on a low calorie diet maintained the activity of molecules involved in protein synthesis and did not up-regulate the expression of genes pivotal in ubiquitin-mediated protein degradation. However, we did find an increase in the expression of genes associated with autophagy. Surprisingly, the reduction on muscle size was followed by improved tetanic and specific force in the null mice compared to wild type mice. These data provide evidence that food restriction may revert the hyper-muscular phenotype of the myostatin null mouse restoring muscle function.

Protease-activated receptors: the role of cell-surface proteolysis in signalling

Certain extracellular proteases, derived from the circulation and inflammatory cells, can specifically cleave and trigger protease-activated receptors (PARs), a small, but important, sub-group of the G-protein-coupled receptor super-family. Four PARs have been cloned and they all share the same basic mechanism of activation: proteases cleave at a specific site within the extracellular N-terminus to expose a new N-terminal tethered ligand domain, which binds to and thereby activates the cleaved receptor. Thrombin activates PAR1, PAR3 and PAR4, trypsin activates PAR2 and PAR4, and mast cell tryptase activates PAR2 in this manner. Activated PARs couple to signalling cascades that affect cell shape, secretion, integrin activation, metabolic responses, transcriptional responses and cell motility. PARs are 'single-use' receptors: proteolytic activation is irreversible and the cleaved receptors are degraded in lysosomes. Thus, PARs play important roles in 'emergency situations', such as trauma and inflammation. The availability of selective agonists and antagonists of protease inhibitors and of genetic models has generated evidence to suggests that proteases and their receptors play important roles in coagulation, inflammation, pain, healing and protection. Therefore, selective antagonists or agonists of these receptors may be useful therapeutic agents for the treatment of human diseases.

Evolution of discrimination in populations at equilibrium between selfishness and altruism

Where there is genetically based variation in selfishness and altruism, as in man, altruists with an innate ability to recognise and thereby only help their altruistic relatives may evolve. Here we use diploid population genetic models to chart the evolution of genetically-based discrimination in populations initially in stable equilibrium between altruism and selfishness. The initial stable equilibria occur because help is assumed subject to diminishing returns. Similar results were obtained whether we used a model with two independently inherited loci, one controlling altruism the other discrimination, or a one locus model with three alleles. The latter is the opposite extreme to the first model, and can be thought of as involving complete linkage between two loci on the same chromosome. The introduction of discrimination reduced the benefits obtained by selfish individuals, more so as the number of discriminators increased, and selfishness was eventually eliminated in some cases. In others selfishness persisted and the evolutionary outcome was a stable equilibrium involving selfish individuals and both discriminating and non-discriminating altruists. Heritable variation in selfishness, altruism and discrimination is predicted to be particularly evident among full sibs. The suggested coexistence of these three genetic dispositions could explain widespread interest within human social groups as to who will and who will not help others. These predictions merit experimental and observational investigation by primatologists, anthropologists and psychologists. Keywords: Population genetics, Diploid, Heritability, Prosocial, Behaviour genetics

Signaling via NF-kappaB in the nervous system

Nuclear factor kappa B (NF-kappaB) is an inducible transcription factor present in neurons and glia. Recent genetic models identified a role for NF-kappaB in neuroprotection against various neurotoxins. Furthermore, genetic evidence for a role in learning and memory is now emerging. This review highlights our current understanding of neuronal NF-kappaB in response to synaptic transmission and summarizes potential physiological functions of NF-kappaB in the nervous system. This article contains a listing of NF-kappaB activators and inhibitors in the nervous system, furthermore specific target genes are discussed. Synaptic NF-kappaB activated by glutamate and Ca2+ will be presented in the context of retrograde signaling. A controversial role of NF-kappaB in neurodegenerative diseases will be discussed. A model is proposed explaining this paradox as deregulated physiological NF-kappaB activity, where novel results are integrated, showing that p65 could be turned from an activator to a repressor of anti-apoptotic genes.

Direct versus indirect sexual selection: genetic basis of colour, size and recruitment in a wild bird

Indirect and direct models of sexual selection make different predictions regarding the quantitative genetic relationships between sexual ornaments and fitness. Indirect models predict that ornaments should have a high heritability and that strong positive genetic covariance should exist between fitness and the ornament. Direct models, on the other hand, make no such assumptions about the level of genetic variance in fitness and the ornament, and are therefore likely to be more important when environmental sources of variation are large. Here we test these predictions in a wild population of the blue tit (Parus caeruleus), a species in which plumage coloration has been shown to be under sexual selection. Using 3 years of cross-fostering data from over 250 breeding attempts, we partition the covariance between parental coloration and aspects of nestling fitness into a genetic and environmental component. Contrary to indirect models of sexual selection, but in agreement with direct models, we show that variation in coloration is only weakly heritable (h(2) < 0.11), and that two components of offspring fitness-nestling size and fledgling recruitment-are strongly dependent on parental effects, rather than genetic effects. Furthermore, there was no evidence of significant positive genetic covariation between parental colour and offspring traits. Contrary to direct benefit models, however, we find little evidence that variation in colour reliably indicates the level of parental care provided by either males or females. Taken together, these results indicate that the assumptions of indirect models of sexual selection are not supported by the genetic basis of the traits reported on here.

Statistical evaluation of alternative models of human evolution

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximate to 141 thousand years ago (Kya), an exit out-of-Africa approximate to 51 Kya, and a recent colonization of the Americas approximate to 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Ratio selection for classification models

This paper is concerned with the selection of inputs for classification models based on ratios of measured quantities. For this purpose, all possible ratios are built from the quantities involved and variable selection techniques are used to choose a convenient subset of ratios. In this context, two selection techniques are proposed: one based on a pre-selection procedure and another based on a genetic algorithm. In an example involving the financial distress prediction of companies, the models obtained from ratios selected by the proposed techniques compare favorably to a model using ratios usually found in the financial distress literature.

Speciation as an active force in promoting genetic evolution

There is a growing appreciation among evolutionary biologists that the rate and tempo of molecular evolution might often be altered at or near the time of speciation, i.e. that speciation is in some way a special time for genes. Molecular phylogenies frequently reveal increased rates of genetic evolution associated with speciation and other lines of investigation suggest that various types of abrupt genomic disruption can play an important role in promoting speciation via reproductive isolation. These phenomena are in conflict with the gradual view of molecular evolution that is implicit in much of our thinking about speciation and in the tools of modern biology. This raises the prospect of studying the molecular evolutionary consequences of speciation per se and studying the footprint of speciation as an active force in promoting genetic divergence. Here we discuss the reasons to believe that speciation can play such a role and elaborate on possible mechanisms for accelerated rates of evolution following speciation. We provide an example of how it is possible detect whether accelerated bursts of evolution occur in neutral and/or adaptive regions of genes and discuss the implications of rapid episodes of change for conventional models of molecular evolution. Speciation might often owe more to ephemeral and essentially arbitrary events that cause reproductive isolation than to the gradual and regular tug of natural selection that draws a species into a new niche.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.