The genetical theory of social behaviour.

We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

Revising the Cannabis Use Disorders Identification Test (CUDIT) by means of Item Response Theory.

Cannabis use among adolescents and young adults has become a major public health challenge. Several European countries are currently developing short screening instruments to identify 'problematic' forms of cannabis use in general population surveys. One such instrument is the Cannabis Use Disorders Identification Test (CUDIT), a 10-item questionnaire based on the Alcohol Use Disorders Identification Test. Previous research found that some CUDIT items did not perform well psychometrically. In the interests of improving the psychometric properties of the CUDIT, this study replaces the poorly performing items with new items that specifically address cannabis use. Analyses are based on a sub-sample of 558 recent cannabis users from a representative population sample of 5722 individuals (aged 13-32) who were surveyed in the 2007 Swiss Cannabis Monitoring Study. Four new items were added to the original CUDIT. Psychometric properties of all 14 items, as well as the dimensionality of the supplemented CUDIT were then examined using Item Response Theory. Results indicate the unidimensionality of CUDIT and an improvement in its psychometric performance when three original items (usual hours being stoned; injuries; guilt) are replaced by new ones (motives for using cannabis; missing out leisure time activities; difficulties at work/school). However, improvements were limited to cannabis users with a high problem score. For epidemiological purposes, any further revision of CUDIT should therefore include a greater number of 'easier' items.

Mutations leading to X-linked hypohidrotic ectodermal dysplasia affect three major functional domains in the tumor necrosis factor family member ectodysplasin-A.

Mutations in the epithelial morphogen ectodysplasin-A (EDA), a member of the tumor necrosis factor (TNF) family, are responsible for the human disorder X-linked hypohidrotic ectodermal dysplasia (XLHED) characterized by impaired development of hair, eccrine sweat glands, and teeth. EDA-A1 and EDA-A2 are two splice variants of EDA, which bind distinct EDA-A1 and X-linked EDA-A2 receptors. We identified a series of novel EDA mutations in families with XLHED, allowing the identification of the following three functionally important regions in EDA: a C-terminal TNF homology domain, a collagen domain, and a furin protease recognition sequence. Mutations in the TNF homology domain impair binding of both splice variants to their receptors. Mutations in the collagen domain can inhibit multimerization of the TNF homology region, whereas those in the consensus furin recognition sequence prevent proteolytic cleavage of EDA. Finally, a mutation affecting an intron splice donor site is predicted to eliminate specifically the EDA-A1 but not the EDA-A2 splice variant. Thus a proteolytically processed, oligomeric form of EDA-A1 is required in vivo for proper morphogenesis.

Interleukin-12p40 overexpression promotes interleukin-12p70 and interleukin-23 formation but does not affect bacille Calmette-Guérin and Mycobacterium tuberculosis clearance.

Interleukin (IL)-12p40, a subunit of IL-12p70 and IL-23, has previously been shown to inhibit IL-12p70 activity and interferon-gamma (IFN-gamma) production. However, recent evidence has suggested that the role of IL-12p40 is more complex. To study the contribution of IL-12p40 to immune responses against mycobacterial infections, we have used transgenic (tg) mice overexpressing IL-12p40 under the control of a major histocompatibility complex-II promoter. The IL-12p40 transgene was expressed during steady state at concentrations of 129 +/- 25 ng/ml of serum and 75 +/- 13 ng per spleen, while endogenous IL-12p40 was hardly detectable in control littermates. Bacille Calmette-Guérin (BCG) infection strongly induced the expression of IL-12p40 transgene in infected organs, and IL-12p40 monomeric and dimeric forms were identified in spleen of IL-12p40 tg mice. Excessive production of IL-12p40 resulted in a 14-fold increase in IL-12p70 serum levels in tg mice versus non-transgenic mice. IL-23 was also strongly elevated in the serum and spleens of IL-12p40 tg mice through BCG infection. While IFN-gamma and tumour necrosis factor protein levels were similar in IL-12p40 tg and non-transgenic mice, Th2 type immune responses were reduced in IL-12p40 tg mice. The number of BCG granulomas and macrophage expressing inducible nitric oxide synthase were similar in IL-12p40 tg and non-transgenic mice. IL-12p40 tg mice were as resistant as non-transgenic mice to BCG and Mycobacterium tuberculosis infections as they could efficiently control bacillary growth. These data show that high amounts of IL-12p40 promotes IL-12p70 and IL-23 formation, but that does not affect T helper 1 type immune responses and granuloma function, thus leading to normal mycobacterial clearance in infected organs.

The major genetic determinants of HIV-1 control affect HLA class I peptide presentation.

Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified >300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alleles. These results implicate the nature of the HLA-viral peptide interaction as the major factor modulating durable control of HIV infection.

Evolutionary forces affect multigenomic arbuscular mycorhizal fungi : an experimental approach using Glomus intraradices

Abstract Arbuscular Mycorhizal Fungi (AMF) are important plant symbionts that can improve floristic diversity and ecosystem productivity. These important fungi are obligate biotrophs and form symbioses with roots of the majority of plant species, improving plant nutrient acquisition in exchange of photosynthates. AM fungi are successful both ecologically as they occupy a very large spectrum of environments as well as host range and evolutionarily, as this symbiosis is over 400 million years old. These fungi grow and reproduce clonally by hyphae and multinucleate spores. AMF are coenocytic and recent work has shown that they harbor genetically different nuclei and that AMF populations are genetically diverse. How AMF species diversity is maintained has been addressed theoretically and experimentally at the community level. Much less attention has been drawn to understand how genetic diversity is maintained within populations although closely related individuals are more likely to compete for the same resources and occupy similar niches. How infra-individual genetic diversity is shaped and maintained has received even less attention. In Chapter 2, we show that individuals from a field population may differ in their symbiotic efficiency under reduced phosphate availability: We show there is genetic variation in an AMF field population for fitness-related growth traits in response to different phosphate availability acid host species. Furthermore, AFLP fingerprints of the same individuals growing in contrasting environments diverged suggesting that the composition in nuclei of AMF is dynamical and affected by environmental factors. Thus environmental heterogeneity is likely to play an important role for the maintenance of genetic diversity at the population level. In Chapter 3 we show that single spores do not inherit necessarily the same genetic material. We have found genetic divergences using two different types of molecular marker, as well as phenotypic divergences among single spore lines. Our results stress the importance of considering these organisms as a multilevel hierarchical system and of better knowing their life cycle. They have important consequences for the understanding of AMF genetics, ecology and the development of commercial AMF inocculum. Résumé Les champignons endomycorhiziens arbusculaires (CEA) sont d'importants symbiontes pour les plantes, car ils augmentent la diversité et la productivité des écosystèmes. Ces importants symbiontes sont des biotrophes obligatoires et forment une symbiose avec la plupart des plantes terrestres. Ils améliorent l'acquisition de substances nutritives de leurs hôtes en échange de sucres obtenus par photosynthèse. Ces champignons ont un grand succès écologique, ils colonisent une grande rangée d'environnements ainsi que d'hôtes. Ils ont aussi un succès évolutif certain de part le fait que cette symbiose existe depuis plus de 400 millions d'années. Les CEA sont asexués et croissent clonalement en formant des hyphes et des spores multinuclées. Les CEA sont des coenocytes et des travaux de recherche récents ont montré qu'ils possèdent des noyaux génétiquement différents. D'autres travaux ont aussi révélé que les populations de CEA sont génétiquement diversifiées. Comment la diversité des CEA est maintenue a seulement été adressée par des études théoriques et expérimentalement au niveau des communautés. Très peu d'attention a été portée sur le maintien de la diversité génétique infra et inter populationnelle, or ce sont les individus les plus proches génétiquement qui vont entrer en compétition pour des ressources et niches similaires. La formation et le maintien de la diversité intra-individu des CEA a reçu très peu d'attention. Dans le chapitre 2, nous montrons que des individus CEA d'un même champ différent dans leur efficacité symbiotique lorsque la concentration en phosphoré est réduite. Nous montrons qu'il existe de la variance génétique dans une population de CEA provenant d'un même champ en réponse à différentes concentrations de phosphore, ainsi qu'en réponse à différentes espèces d'hôtes, et ceci pour des traits de croissance vraisemblablement liés au succès reproducteur. De plus grâce à des AFLP nous avons pu montrer que le génome de ces individus subissent des changements lorsqu'ils croissent dans des environnements contrastés. Ceci suggère que les noyaux génétiquement différents des CEA sont des entités dynamiques. Il est fort probable que l'hétérogénéité environnementale joue un rôle dans le maintien de la diversité génétique des populations de CEA. Dans le chapitre 3, nous montrons que toutes les spores d'un même mycélium parental de CEA ne reçoivent pas exactement le même contenu génétique. Nous avons mis en évidence des divergences entre des Lignées monosporales en utilisant deux types de marqueur moléculaires, ainsi que des différences phénotypiques. Nos résutats soulignent l'importance de considézer ces organismes comme dés systëmes hiérarchiques mufti-niveaux, ainsi que de mieux connaître leur cycle de vie. Nos résultats ont d'importantes conséquences pour la compréhension du système génétique des CEA, ainsi que de leur évolution, leur écológie, mais également des conséquences pour la production d' inoccultim commercial.

Taking "Galton's problem" Seriously : Towards a Theory of Policy Diffusion

This article builds on the recent policy diffusion literature and attempts to overcome one of its major problems, namely the lack of a coherent theoretical framework. The literature defines policy diffusion as a process where policy choices are interdependent, and identifies several diffusion mechanisms that specify the link between the policy choices of the various actors. As these mechanisms are grounded in different theories, theoretical accounts of diffusion currently have little internal coherence. In this article we put forward an expected-utility model of policy change that is able to subsume all the diffusion mechanisms. We argue that the expected utility of a policy depends on both its effectiveness and the payoffs it yields, and we show that the various diffusion mechanisms operate by altering these two parameters. Each mechanism affects one of the two parameters, and does so in distinct ways. To account for aggregate patterns of diffusion, we embed our model in a simple threshold model of diffusion. Given the high complexity of the process that results, strong analytical conclusions on aggregate patterns cannot be drawn without more extensive analysis which is beyond the scope of this article. However, preliminary considerations indicate that a wide range of diffusion processes may exist and that convergence is only one possible outcome.

Evolutionary branching in deme-structured populations.

Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).