Chromosomal rearrangements and genetic structure at different evolutionary levels of the Sorex araneus group.

Robertsonian (Rb) fusions received large theoretical support for their role in speciation, but empirical evidence is often lacking. Here, we address the role of Rb rearrangements on the genetic differentiation of the karyotypically diversified group of shrews, Sorex araneus. We compared genetic structure between 'rearranged' and 'common' chromosomes in pairwise comparisons of five karyotypic taxa of the group. Considering all possible comparisons, we found a significantly greater differentiation at rearranged chromosomes, supporting the role of chromosomal rearrangements in the general genetic diversification of this group. Intertaxa structure and distance were larger across rearranged chromosomes for most of the comparisons, although these differences were not significant. This last result could be explained by the large variance observed among microsatellite-based estimates. The differences observed among the pairs of taxa analysed support the role of both the hybrid karyotypic complexity and the level of evolutionary divergence.

Large-system analysis of a CDMA dynamic channel under a Markovian input process

We study the minimum mean square error (MMSE) and the multiuser efficiency η of large dynamic multiple access communication systems in which optimal multiuser detection is performed at the receiver as the number and the identities of active users is allowed to change at each transmission time. The system dynamics are ruled by a Markov model describing the evolution of the channel occupancy and a large-system analysis is performed when the number of observations grow large. Starting on the equivalent scalar channel and the fixed-point equation tying multiuser efficiency and MMSE, we extend it to the case of a dynamic channel, and derive lower and upper bounds for the MMSE (and, thus, for η as well) holding true in the limit of large signal–to–noise ratios and increasingly large observation time T.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Reconciling global mammal prioritization schemes into a strategy.

The huge conservation interest that mammals attract and the large datasets that have been collected on them have propelled a diversity of global mammal prioritization schemes, but no comprehensive global mammal conservation strategy. We highlight some of the potential discrepancies between the schemes presented in this theme issue, including: conservation of species or areas, reactive and proactive conservation approaches, conservation knowledge and action, levels of aggregation of indicators of trend and scale issues. We propose that recently collected global mammal data and many of the mammal prioritization schemes now available could be incorporated into a comprehensive global strategy for the conservation of mammals. The task of developing such a strategy should be coordinated by a super-partes, authoritative institution (e.g. the International Union for Conservation of Nature, IUCN). The strategy would facilitate funding agencies, conservation organizations and national institutions to rapidly identify a number of short-term and long-term global conservation priorities, and act complementarily to achieve them.

A novel bioinformatics pipeline to discover genes related to arbuscular mycorrhizal symbiosis based on their evolutionary conservation pattern among higher plants.

BACKGROUND: Genes involved in arbuscular mycorrhizal (AM) symbiosis have been identified primarily by mutant screens, followed by identification of the mutated genes (forward genetics). In addition, a number of AM-related genes has been identified by their AM-related expression patterns, and their function has subsequently been elucidated by knock-down or knock-out approaches (reverse genetics). However, genes that are members of functionally redundant gene families, or genes that have a vital function and therefore result in lethal mutant phenotypes, are difficult to identify. If such genes are constitutively expressed and therefore escape differential expression analyses, they remain elusive. The goal of this study was to systematically search for AM-related genes with a bioinformatics strategy that is insensitive to these problems. The central element of our approach is based on the fact that many AM-related genes are conserved only among AM-competent species. RESULTS: Our approach involves genome-wide comparisons at the proteome level of AM-competent host species with non-mycorrhizal species. Using a clustering method we first established orthologous/paralogous relationships and subsequently identified protein clusters that contain members only of the AM-competent species. Proteins of these clusters were then analyzed in an extended set of 16 plant species and ranked based on their relatedness among AM-competent monocot and dicot species, relative to non-mycorrhizal species. In addition, we combined the information on the protein-coding sequence with gene expression data and with promoter analysis. As a result we present a list of yet uncharacterized proteins that show a strongly AM-related pattern of sequence conservation, indicating that the respective genes may have been under selection for a function in AM. Among the top candidates are three genes that encode a small family of similar receptor-like kinases that are related to the S-locus receptor kinases involved in sporophytic self-incompatibility. CONCLUSIONS: We present a new systematic strategy of gene discovery based on conservation of the protein-coding sequence that complements classical forward and reverse genetics. This strategy can be applied to diverse other biological phenomena if species with established genome sequences fall into distinguished groups that differ in a defined functional trait of interest.

Predation drives interpopulation differences in parental care expression.

Expressing parental care after oviposition or parturition is usually an obligate (evolved) trait within a species, despite evolutionary theory predicting that widespread species should vary in whether or not they express parental care according to local selection pressures. The lizard Eutropis longicaudata expresses maternal care only in a single population throughout its large geographical range, but why this pattern occurs is unknown. We used reciprocal translocation and predator exclusion experiments to test whether this intraspecific variation is a fixed trait within populations and whether predator abundance explains this perplexing pattern. Wild-caught female lizards that were reciprocally translocated consistently guarded or abandoned eggs in line with their population of origin. By contrast, most lizards raised in a common garden environment and subsequently released as adults adopted the maternal care strategy of the recipient population, even when the parents originated from a population lacking maternal care. Egg predation represents a significant fitness cost in the populations where females display egg-guarding behaviour, but guarding eggs outweighs this potential cost by increasing hatching success. These results imply that predators can be a driving force in the expression of parental care in instances where it is normally absent and that local selection pressure is sufficient to cause behavioural divergence in whether or not parental care is expressed.

Global Nash convergence of Foster and Young's regret testing

We construct an uncoupled randomized strategy of repeated play such that, if every player follows such a strategy, then the joint mixed strategy profiles converge, almost surely, to a Nash equilibrium of the one-shot game. The procedure requires very little in terms of players' information about the game. In fact, players' actions are based only on their own past payoffs and, in a variant of the strategy, players need not even know that their payoffs are determined through other players' actions. The procedure works for general finite games and is based on appropriate modifications of a simple stochastic learningrule introduced by Foster and Young.

Input chains and industrialization

A key aspect of industrialization is theadoption of increasing-returns-to-scale, industrial,technologies. Two other, well-documented aspects arethat industrial technologies are adopted throughoutintermediate-input chains and that they use intermediateinputs intensively relative to the technologies theyreplace. These features of industrial technologiescombined imply that countries with access to similartechnologies may have very different levels ofindustrialization and income, even if the degree ofincreasing returns to scale at the firm level is relativelysmall. Furthermore, a small improvement in theproductivity of industrial technologies can trigger full-scaleindustrialization and a large increase in income.

Effect of genetic convergence on phylogenetic inference.

Phylogenetic reconstructions are a major component of many studies in evolutionary biology, but their accuracy can be reduced under certain conditions. Recent studies showed that the convergent evolution of some phenotypes resulted from recurrent amino acid substitutions in genes belonging to distant lineages. It has been suggested that these convergent substitutions could bias phylogenetic reconstruction toward grouping convergent phenotypes together, but such an effect has never been appropriately tested. We used computer simulations to determine the effect of convergent substitutions on the accuracy of phylogenetic inference. We show that, in some realistic conditions, even a relatively small proportion of convergent codons can strongly bias phylogenetic reconstruction, especially when amino acid sequences are used as characters. The strength of this bias does not depend on the reconstruction method but varies as a function of how much divergence had occurred among the lineages prior to any episodes of convergent substitutions. While the occurrence of this bias is difficult to predict, the risk of spurious groupings is strongly decreased by considering only 3rd codon positions, which are less subject to selection, as long as saturation problems are not present. Therefore, we recommend that, whenever possible, topologies obtained with amino acid sequences and 3rd codon positions be compared to identify potential phylogenetic biases and avoid evolutionarily misleading conclusions.

An inequality for uniform deviations of sample averages from their means

We derive a new inequality for uniform deviations of averages from their means. The inequality is a common generalization of previous results of Vapnik and Chervonenkis (1974) and Pollard (1986). Usingthe new inequality we obtain tight bounds for empirical loss minimization learning.

North-South convergence and the allocation of CO2 emissions

We postulate a two-region world, comprised of North (calibrated after the US) and South(calibrated after China). Our optimization results show the compatibility of the following threedesiderata:(1) Global CO2 emissions follow a conservative path that leads to the stabilizationof concentrations at 450 ppm.(2) North and South converge to a path of sustained growth at 1% per year (28.2%per generation) in 2075.(3) During the transition to the steady state, North also grows at 1% per year whileSouth s rates of growth are markedly higher.The transition paths require a drastic reduction of the share of emissions allocated to North,large investments in knowledge, both in North and South, as well as very large investments ineducation in South. Surprisingly, in order to sustain North s utility growth rate, some output mustbe transferred from South to North during the transition.Although undoubtedly subject to many caveats, our results support a degree of optimism byproviding prima facie evidence of the possibility of tackling climate change in a way that is fairboth across generations and across regions while allowing for positive rates of humandevelopment.

Molecular basis of odor detection in insects.

Olfactory systems are evolutionarily ancient, underlying the common requirement for all animals to sense and respond to diverse volatile chemical signals in their environment. Odor detection is mediated by odorant receptors (ORs) that, in most olfactory systems, comprise large families of divergent G protein-coupled receptors. Here, I discuss our and others' recent investigations of ORs in the fruit fly, Drosophila melanogaster, which have revealed insights into the distinct evolutionary origin and molecular function of insect ORs. I also describe a bioinformatics strategy that we developed to identify molecules that function with these insect-specific receptors in odor detection.

Scale-dependent adaptive evolution and morphological convergence to climatic niche in Californian eriogonoids (Polygonaceae)

Aim Macroevolutionary patterns and processes change substantially depending on levels of taxonomic and ecological organization, and the resolution of environmental and spatial variability. In comparative methods, the resolution of environmental and spatial variability often defines the number of selective regimes used to test whether phenotypic characteristics are adaptively correlated with the environment. Here, we examine how investigator choice of the number of selective regimes, determined by varying the resolution of among-species variability in the species climatic niche (hereafter called ecological scale'), influences trait morphological diversification among Eriogonoideae species. We assess whether adaptive or neutral processes drive the evolution of several morphological traits in these species. Location South-western North America. Methods We applied a phylogenetic framework of three evolutionary models to four morphological traits and the climatic niches of Eriogonoideae (in the buckwheat family, Polygonaceae). We tested whether morphological traits evolve in relation to climate by adaptive or neutral process, and whether the resulting patterns of morphological variability are conserved or convergent across the clade. We inspected adaptive models of evolution under different levels of resolution of among-species variability of the climatic niche. Results We show that morphological traits and climate niches of Eriogonoideae species are not phylogenetically conserved. Further, adaptive evolution of phenotypic traits is specific to climatic niche occupancy across this clade. Finally, the likely evolutionary process and the level of detectable niche conservatism change depending on the resolution of environmental variability of the climatic niche. Main conclusions Our study demonstrates the need to consider both the resolution of environmental variability and alternative evolutionary models to understand the morphological diversification that accompanies divergent adaptive evolution of lineages to climatic conditions.

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.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.