Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Structure-function analysis of the human TFIIB-related factor II protein reveals an essential role for the C-terminal domain in RNA polymerase III transcription.

The transcription factors TFIIB, Brf1, and Brf2 share related N-terminal zinc ribbon and core domains. TFIIB bridges RNA polymerase II (Pol II) with the promoter-bound preinitiation complex, whereas Brf1 and Brf2 are involved, as part of activities also containing TBP and Bdp1 and referred to here as Brf1-TFIIIB and Brf2-TFIIIB, in the recruitment of Pol III. Brf1-TFIIIB recruits Pol III to type 1 and 2 promoters and Brf2-TFIIIB to type 3 promoters such as the human U6 promoter. Brf1 and Brf2 both have a C-terminal extension absent in TFIIB, but their C-terminal extensions are unrelated. In yeast Brf1, the C-terminal extension interacts with the TBP/TATA box complex and contributes to the recruitment of Bdp1. Here we have tested truncated Brf2, as well as Brf2/TFIIB chimeric proteins for U6 transcription and for assembly of U6 preinitiation complexes. Our results characterize functions of various human Brf2 domains and reveal that the C-terminal domain is required for efficient association of the protein with U6 promoter-bound TBP and SNAP(c), a type 3 promoter-specific transcription factor, and for efficient recruitment of Bdp1. This in turn suggests that the C-terminal extensions in Brf1 and Brf2 are crucial to specific recruitment of Pol III over Pol II.

Diversity and genetic structure of the wood ant Formica lugubris in unmanaged forests

Wood ant species show differences in their social structure, especially in the level of polygyny (number of laying queens per nest) and polydomy (number of nest per colony), both within and between species. We demonstrate here for the first time that Formica lugubris displays two different social forms in close proximity in alpine unmanaged forests of the Swiss National Park. The genetic data (7 microsatellite loci) and field data indicate that one population is mostly monogynous to weakly polygynous (r = 0.438) and monodomous, the second one being polygynous (r = 0.113) and polydomous. Within this latter population new nests are founded by budding, leading to the observed high density of nests. These two different social structures, possibly being two expressions of a same continuum, could be explained by several ecological or environmental factors (e.g. habitat saturation, resource competition) and also historical effects.

GuavaH: a compendium of host genomic data in HIV biology and disease.

BACKGROUND: There is an ever-increasing volume of data on host genes that are modulated during HIV infection, influence disease susceptibility or carry genetic variants that impact HIV infection. We created GuavaH (Genomic Utility for Association and Viral Analyses in HIV, http://www.GuavaH.org), a public resource that supports multipurpose analysis of genome-wide genetic variation and gene expression profile across multiple phenotypes relevant to HIV biology. FINDINGS: We included original data from 8 genome and transcriptome studies addressing viral and host responses in and ex vivo. These studies cover phenotypes such as HIV acquisition, plasma viral load, disease progression, viral replication cycle, latency and viral-host genome interaction. This represents genome-wide association data from more than 4,000 individuals, exome sequencing data from 392 individuals, in vivo transcriptome microarray data from 127 patients/conditions, and 60 sets of RNA-seq data. Additionally, GuavaH allows visualization of protein variation in ~8,000 individuals from the general population. The publicly available GuavaH framework supports queries on (i) unique single nucleotide polymorphism across different HIV related phenotypes, (ii) gene structure and variation, (iii) in vivo gene expression in the setting of human infection (CD4+ T cells), and (iv) in vitro gene expression data in models of permissive infection, latency and reactivation. CONCLUSIONS: The complexity of the analysis of host genetic influences on HIV biology and pathogenesis calls for comprehensive motors of research on curated data. The tool developed here allows queries and supports validation of the rapidly growing body of host genomic information pertinent to HIV research.

Crustal structure and reflectivity of the Swiss Alps from 3-Dimensional seismic modeling. 2. Penninic Nappes

Surface geological mapping, laboratory measurements of rock properties, and seismic reflection data are integrated through three-dimensional seismic modeling to determine the likely cause of upper crustal reflections and to elucidate the deep structure of the Penninic Alps in eastern Switzerland. Results indicate that the principal upper crustal reflections recorded on the south end of Swiss seismic line NFP20-EAST can be explained by the subsurface geometry of stacked basement nappes. In addition, modeling results provide improvements to structural maps based solely on surface trends and suggest the presence of previously unrecognized rock units in the subsurface. Construction of the initial model is based upon extrapolation of plunging surface. structures; velocities and densities are established by laboratory measurements of corresponding rock units. Iterative modification produces a best fit model that refines the definition of the subsurface geometry of major structures. We conclude that most reflections from the upper 20 km can be ascribed to the presence of sedimentary cover rocks (especially carbonates) and ophiolites juxtaposed against crystalline basement nappes. Thus, in this area, reflections appear to be principally due to first-order lithologic contrasts. This study also demonstrates not only the importance of three-dimensional effects (sideswipe) in interpreting seismic data, but also that these effects can be considered quantitatively through three-dimensional modeling.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Contribution of electrostatic interactions, compactness and quaternary structure to protein thermostability: lessons from structural genomics of Thermotoga maritima.

Studies of the structural basis of protein thermostability have produced a confusing picture. Small sets of proteins have been analyzed from a variety of thermophilic species, suggesting different structural features as responsible for protein thermostability. Taking advantage of the recent advances in structural genomics, we have compiled a relatively large protein structure dataset, which was constructed very carefully and selectively; that is, the dataset contains only experimentally determined structures of proteins from one specific organism, the hyperthermophilic bacterium Thermotoga maritima, and those of close homologs from mesophilic bacteria. In contrast to the conclusions of previous studies, our analyses show that oligomerization order, hydrogen bonds, and secondary structure play minor roles in adaptation to hyperthermophily in bacteria. On the other hand, the data exhibit very significant increases in the density of salt-bridges and in compactness for proteins from T.maritima. The latter effect can be measured by contact order or solvent accessibility, and network analysis shows a specific increase in highly connected residues in this thermophile. These features account for changes in 96% of the protein pairs studied. Our results provide a clear picture of protein thermostability in one species, and a framework for future studies of thermal adaptation.

Note préliminaire sur la structure, la phénologie et le régime alimentaire d'une super-colonie de formica lugubris zett

Formica lugubris apparaît comme une espèce hautement polycalique dans le Jura suisse et forme des super-colonies. La super-colonie étudiée comprend environ 1200 nids répartis sur 70 hectares. L'étude détaillée de 12 hectares permet de définir 4 types de nids:les nids principaux, secondaires, saisonniers etcommençants, ainsi que trois sortes de voies de communication:les routes de liaisons permanentes visibles sur le terrain, les pistes de liaisons non-permanentes non marquées sur le terrain etles chemins d'approvisionnement permanents marqués dans le terrain. L'auteur présente la phénologie deF. lugubris qui est fortement influencée par le climat de cette région avec une période moyenne d'activité de 150 jours. D'autre part, les premières données sur le régime alimentaire (analyse des proies récoltées par les fourmis) diffèrent considérablement des données connues pour les autres espèces du groupe rufa, notamment par le nombre élevé de pucerons, d'où l'idée d'une régulation des populations de pucerons par les fourmis. Enfin l'auteur aborde le problème de la faible densité de l'avifaune en relation avec les fourmis. Il semble que le climat et les ressources alimentaires conduisent les fourmis àune nouvelle stratégie écologique qui s'exprimerait par la création de super-colonies. Formica lugubris appears as a highly polycalic species in the Swiss Jura and creates super-colonies. The super-colony studied possesses about 1200 nests on about 70 hectares. The detailed study of 12 hectares allows the discrimination of 4 types of nests:the main nests, the secondary nests, the seasonal nests andthe starting nests, as well as 3 types of ant tracks:the constant connection routes visible on the soil, thenon-constant connection tracks not marked on the soil andthe constant foraging routes marked on the soil. The author presents the phenology ofF. lugubris who is strongly influenced by the climate of the region with a mean activity period of about 150 days. On the other hand, the first results about diet (analysis of the preys collected by the ants) differ considerably from the wellknown data for the others species of the rufa group, especially by the high number of aphids, which may be inferred the notion of a regulation of aphids population by the ants. Finally the author approaches the problem of the low density of avifauna in relation to the ants. It seems that climate and food resources lead the ants toa new ecological strategy which would express itself by the creation of super-colonies.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Modeling the Emergence of Social Structure from a Phylogenetic Point of View

Based on provious (Hemelrijk 1998; Puga-González, Hildenbrant & Hemelrijk 2009), we have developed an agent-based model and software, called A-KinGDom, which allows us to simulate the emergence of the social structure in a group of non-human primates. The model includes dominance and affiliative interactions and incorporate s two main innovations (preliminary dominance interactions and a kinship factor), which allow us to define four different attack and affiliative strategies. In accordance with these strategies, we compared the data obtained under four simulation conditions with the results obtained in a provious study (Dolado & Beltran 2012) involving empirical observations of a captive group of mangabeys (Cercocebus torquatus)

Reliable selfing rate estimates from imperfect population genetic data.

Genotypic frequencies at codominant marker loci in population samples convey information on mating systems. A classical way to extract this information is to measure heterozygote deficiencies (FIS) and obtain the selfing rate s from FIS = s/(2 - s), assuming inbreeding equilibrium. A major drawback is that heterozygote deficiencies are often present without selfing, owing largely to technical artefacts such as null alleles or partial dominance. We show here that, in the absence of gametic disequilibrium, the multilocus structure can be used to derive estimates of s independent of FIS and free of technical biases. Their statistical power and precision are comparable to those of FIS, although they are sensitive to certain types of gametic disequilibria, a bias shared with progeny-array methods but not FIS. We analyse four real data sets spanning a range of mating systems. In two examples, we obtain s = 0 despite positive FIS, strongly suggesting that the latter are artefactual. In the remaining examples, all estimates are consistent. All the computations have been implemented in a open-access and user-friendly software called rmes (robust multilocus estimate of selfing) available at http://ftp.cefe.cnrs.fr, and can be used on any multilocus data. Being able to extract the reliable information from imperfect data, our method opens the way to make use of the ever-growing number of published population genetic studies, in addition to the more demanding progeny-array approaches, to investigate selfing rates.

Comparison of the organization and fine structure of a chicken and a Xenopus laevis vitellogenin gene.

The structural organization and the coding nucleotide sequence of the Xenopus laevis A2 and the chicken major vitellogenin genes have been compared. Both genes show the same exon-intron organization. However, the degree of homology between the nucleotide and derived amino acid sequences varies extensively along the genes. Several of the 35 exons are quite similar, and a unique cysteine motif in the lipovitellin II domain is conserved between the two genes. In contrast, one internal region is quite divergent. Part of this region encodes phosvitin, which appears to have evolved rapidly by both point mutations and duplications of serines or short other amino acid stretches. On the basis of these observations, we discuss the possible mechanism of evolution of phosvitin in vertebrates.

Structure and kinematics of the Siviez-Mischabel nappe in the Mattertal (western Alps of Switzerland) = Structure et cinématique de la nappe de Siviez-Mischabel le long de la vallée de Zermatt (Alpes de Suisse occidentale)

Résumé Cette étude porte sur le flanc inverse de la nappe de Siviez-Mischabel et sur les unités tectoniques sous jacentes (zone de Stalden supérieur et zone Houillère) dans la vallée menant à Zermatt. L'étude structurale du granite permien de Randa (orthogneiss oeillé) permet de mieux comprendre les effets de la déformation alpine sur les roches de socle. La cartographie détaillée de l'orthogneiss et de son encaissant, ainsi que l'étude lithostratigraphique des terrains sédimentaires associés permettent de proposer un schéma structural et cinématique du flanc inverse de la nappe de Siviez-Mischabel et de mieux comprendre ses relations avec les unités tectoniques sous-jacentes. L'analyse structurale de l'orthogneiss de Randa et de son encaissant révèle la superposition de plusieurs phases de déformation ductile. Cet orthogneiss formé sous des conditions métamorphiques du faciès schiste vert possède une forte schistosité alpine avec au moins deux linéations d'extension. La première, L1, orientée NW-SE est associée à la mise en place de la nappe. La seconde, L2, orientée SW-NE, se corrèle au cisaillement ductile du Simplon. La quantification de la déformation au moyen de la méthode de Fry sur les faciès porphyriques donne des ellipses à rapports axiaux compris entre 1.9 et 5.3, en accord avec les valeurs obtenues par d'autres marqueurs {tourmalines étirées, fibres). Les valeurs mesurées parallèlement à L1 ou L2 sont très semblables. La méthode de Fry a nécessité une étude théorique préalable afin de vérifier son applicabilité aux orthogneiss oeillés. La méthode requiert une distribution spatiale homogène et isotrope des marqueurs utilisés. Les tests statistiques effectués ont révélé que les phénocristaux de feldspath alcalin satisfont à cette condition et qu'ils peuvent être utilisés comme marqueur de la déformation au moyen de la méthode de Fry. Les valeurs obtenues révèlent l'importance du cisaillement ductile du Simplon sur la géométrie de la nappe dans la région d'étude. Le levé cartographique a permis d'améliorer la lithostratigraphie de la base de la nappe de Siviez-Mischabel. Trois formations en position renversée peuvent être observées sous les gneiss formant le coeur de la nappe. Ces trois formations forment le coeur du synclinal de St-Niklaus qui connecte la nappe de Siviez-Mischabel à la zone de Stalden supérieur. La datation par U-Pb de zircons détritiques et magmatiques par LA-ICP-MS permet de contraindre l'âge des formations observées (probablement Carbonifère à Trias précoce). Ces données ont des répercussions importantes sur la structure de la nappe dans la région, prouvant l'existence de plusieurs plis avec des séries normales et renversées bien préservées. La définition et la datation de ces formations, ainsi que leur identification dans la-Zone- Houillère avoisinante permettent de mieux comprendre la géométrie initiale et les relations tectoniques des nappes du Pennique moyen dans la vallée de Zermatt. Summary This study investigates the overturned limb of the Siviez-Mischabel nappe and underlying tectonic units (Upper Stalden zone and Houillère zone) in the Mattertal area. Detailed structural analysis in the Permian Randa granite (augen orthogneiss) allows a better understanding of the Alpine deformation effects on basement rocks. Detailed mapping of this orthogneiss and surrounding rocks, and the study of the lithostratigraphy in the related sedimentary horizons allow the proposition of a structural and kinematic model for the overturned limb of the Siviez-Mischabel and to better understand the relations with the underlying tectonic units. The structural analysis of the Randa orthogneiss and surrounding rocks revealed the superposition of several phases of ductile deformation. This orthogneiss formed under greenschist facies metamorphic conditions displays a strong Alpine foliation with at least two stretching lineations. The first lineation, L1, is oriented NW-SE and is related to the nappe emplacement northward. The second one, L2, is related to the Simplon ductile shear zone. Strain estimation using the Fry method has been performed on porphyritic facies of the Randa orthogneiss. The obtained ellipses have axial ratios varying between 1.9 and 5.3, in agreement with strain estimation obtained from other markers (stretched turmalines, fringes). The strain values are very similar if measured parallel to L1 or to L2. A theoretical approach was necessary to verify the relevant application of the Fry method to augen orthogneiss. This method requires that the distribution of the used markers has to be homogeneous and isotropic. Statistical tests have been done and revealed that K-feldspar phenocrysts satisfy these conditions and can be used as strain markers with the Fry method. The obtained strain measurements revealed the importance of the Simplon ductile shear zone on the geometry of the nappe in the studied area. Mapping has improved the lithostratigraphy at the base of the Siviez-Mischabel nappe. Three overturned formations can be observed below the gneisses forming the core of the nappe. These three formations form the St-Niklaus syncline, which connects the Siviez-Mischabel nappe to the underlying Upper Stalden zone. U-Pb dating of detrital and magmatic zircons by LA-ICPMS allowed the age of the observed formations to be constrained (presumably Carboniferous to Early Triassic). This data has critical implications for nappe structure in the region, composed of few recumbent folds with well preserved normal and overturned limbs. The definition and dating of these formations, as well as their identification in the adjacent "Houillère Zone" improve the understanding of the geometry and tectonic relations of the Middle Penninic nappes in the Mattertal.