Evolutionary patchwork of an insecticidal toxin shared between plant-associated pseudomonads and the insect pathogens Photorhabdus and Xenorhabdus.

BACKGROUND: Root-colonizing fluorescent pseudomonads are known for their excellent abilities to protect plants against soil-borne fungal pathogens. Some of these bacteria produce an insecticidal toxin (Fit) suggesting that they may exploit insect hosts as a secondary niche. However, the ecological relevance of insect toxicity and the mechanisms driving the evolution of toxin production remain puzzling. RESULTS: Screening a large collection of plant-associated pseudomonads for insecticidal activity and presence of the Fit toxin revealed that Fit is highly indicative of insecticidal activity and predicts that Pseudomonas protegens and P. chlororaphis are exclusive Fit producers. A comparative evolutionary analysis of Fit toxin-producing Pseudomonas including the insect-pathogenic bacteria Photorhabdus and Xenorhadus, which produce the Fit related Mcf toxin, showed that fit genes are part of a dynamic genomic region with substantial presence/absence polymorphism and local variation in GC base composition. The patchy distribution and phylogenetic incongruence of fit genes indicate that the Fit cluster evolved via horizontal transfer, followed by functional integration of vertically transmitted genes, generating a unique Pseudomonas-specific insect toxin cluster. CONCLUSIONS: Our findings suggest that multiple independent evolutionary events led to formation of at least three versions of the Mcf/Fit toxin highlighting the dynamic nature of insect toxin evolution.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

A new method to estimate the infilling of alluvial sediment of glacial valleys using a sloping local base level

A new method is used to estimate the volumes of sediments of glacial valleys. This method is based on the concept of sloping local base level and requires only a digital terrain model and the limits of the alluvial valleys as input data. The bedrock surface of the glacial valley is estimated by a progressive excavation of the digital elevation model (DEM) of the filled valley area. This is performed using an iterative routine that replaces the altitude of a point of the DEM by the mean value of its neighbors minus a fixed value. The result is a curved surface, quadratic in 2D. The bedrock surface of the Rhone Valley in Switzerland was estimated by this method using the free digital terrain model Shuttle Radar Topography Mission (SRTM) (~92 m resolution). The results obtained are in good agreement with the previous estimations based on seismic profiles and gravimetric modeling, with the exceptions of some particular locations. The results from the present method and those from the seismic interpretation are slightly different from the results of the gravimetric data. This discrepancy may result from the presence of large buried landslides in the bottom of the Rhone Valley.

Local adaptation maintains clinal variation in melanin-based coloration of European barn owls (Tyto alba).

Ecological parameters vary in space, and the resulting heterogeneity of selective forces can drive adaptive population divergence. Clinal variation represents a classical model to study the interplay of gene flow and selection in the dynamics of this local adaptation process. Although geographic variation in phenotypic traits in discrete populations could be remainders of past adaptation, maintenance of adaptive clinal variation requires recurrent selection. Clinal variation in genetically determined traits is generally attributed to adaptation of different genotypes to local conditions along an environmental gradient, although it can as well arise from neutral processes. Here, we investigated whether selection accounts for the strong clinal variation observed in a highly heritable pheomelanin-based color trait in the European barn owl by comparing spatial differentiation of color and of neutral genes among populations. Barn owl's coloration varies continuously from white in southwestern Europe to reddish-brown in northeastern Europe. A very low differentiation at neutral genetic markers suggests that substantial gene flow occurs among populations. The persistence of pronounced color differentiation despite this strong gene flow is consistent with the hypothesis that selection is the primary force maintaining color variation among European populations. Therefore, the color cline is most likely the result of local adaptation.

Novel method to estimate the phenotypic variation explained by genome-wide association studies reveals large fraction of the missing heritability.

Genome-wide association studies (GWAS) are conducted with the promise to discover novel genetic variants associated with diverse traits. For most traits, associated markers individually explain just a modest fraction of the phenotypic variation, but their number can well be in the hundreds. We developed a maximum likelihood method that allows us to infer the distribution of associated variants even when many of them were missed by chance. Compared to previous approaches, the novelty of our method is that it (a) does not require having an independent (unbiased) estimate of the effect sizes; (b) makes use of the complete distribution of P-values while allowing for the false discovery rate; (c) takes into account allelic heterogeneity and the SNP pruning strategy. We applied our method to the latest GWAS meta-analysis results of the GIANT consortium. It revealed that while the explained variance of genome-wide (GW) significant SNPs is around 1% for waist-hip ratio (WHR), the observed P-values provide evidence for the existence of variants explaining 10% (CI=[8.5-11.5%]) of the phenotypic variance in total. Similarly, the total explained variance likely to exist for height is estimated to be 29% (CI=[28-30%]), three times higher than what the observed GW significant SNPs give rise to. This methodology also enables us to predict the benefit of future GWA studies that aim to reveal more associated genetic markers via increased sample size.

Local adaptation and matching habitat choice in female barn owls with respect to melanic coloration.

Local adaptation is a major mechanism underlying the maintenance of phenotypic variation in spatially heterogeneous environments. In the barn owl (Tyto alba), dark and pale reddish-pheomelanic individuals are adapted to conditions prevailing in northern and southern Europe, respectively. Using a long-term dataset from Central Europe, we report results consistent with the hypothesis that the different pheomelanic phenotypes are adapted to specific local conditions in females, but not in males. Compared to whitish females, reddish females bred in sites surrounded by more arable fields and less forests. Colour-dependent habitat choice was apparently beneficial. First, whitish females produced more fledglings when breeding in wooded areas, whereas reddish females when breeding in sites with more arable fields. Second, cross-fostering experiments showed that female nestlings grew wings more rapidly when both their foster and biological mothers were of similar colour. The latter result suggests that mothers should particularly produce daughters in environments that best match their own coloration. Accordingly, whiter females produced fewer daughters in territories with more arable fields. In conclusion, females displaying alternative melanic phenotypes bred in habitats providing them with the highest fitness benefits. Although small in magnitude, matching habitat selection and local adaptation may help maintain variation in pheomelanin coloration in the barn owl.

Multiplex ultra-performance liquid chromatography-tandem mass spectrometry method for simultaneous quantification in human plasma of fluconazole, itraconazole, hydroxyitraconazole, posaconazole, voriconazole, voriconazole-N-oxide, anidulafungin, and caspofungin.

Therapeutic drug monitoring (TDM) may contribute to optimizing the efficacy and safety of antifungal therapy because of the large variability in drug pharmacokinetics. Rapid, sensitive, and selective laboratory methods are needed for efficient TDM. Quantification of several antifungals in a single analytical run may best fulfill these requirements. We therefore developed a multiplex ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method requiring 100 μl of plasma for simultaneous quantification within 7 min of fluconazole, itraconazole, hydroxyitraconazole, posaconazole, voriconazole, voriconazole-N-oxide, caspofungin, and anidulafungin. Protein precipitation with acetonitrile was used in a single extraction procedure for eight analytes. After reverse-phase chromatographic separation, antifungals were quantified by electrospray ionization-triple-quadrupole mass spectrometry by selected reaction monitoring detection using the positive mode. Deuterated isotopic compounds of azole antifungals were used as internal standards. The method was validated based on FDA recommendations, including assessment of extraction yields, matrix effect variability (<9.2%), and analytical recovery (80.1 to 107%). The method is sensitive (lower limits of azole quantification, 0.01 to 0.1 μg/ml; those of echinocandin quantification, 0.06 to 0.1 μg/ml), accurate (intra- and interassay biases of -9.9 to +5% and -4.0 to +8.8%, respectively), and precise (intra- and interassay coefficients of variation of 1.2 to 11.1% and 1.2 to 8.9%, respectively) over clinical concentration ranges (upper limits of quantification, 5 to 50 μg/ml). Thus, we developed a simple, rapid, and robust multiplex UPLC-MS/MS assay for simultaneous quantification of plasma concentrations of six antifungals and two metabolites. This offers, by optimized and cost-effective lab resource utilization, an efficient tool for daily routine TDM aimed at maximizing the real-time efficacy and safety of different recommended single-drug antifungal regimens and combination salvage therapies, as well as a tool for clinical research.

Variation d'expression des récepteurs hormonaux et d'HER-2 dans l'évolution du cancer du sein : quelles implications en pratique clinique [Hormone receptors and HER-2 changes during breast cancer progression: clinical implications].

Breast cancer remains a major public health problem. Even if there is an increase in this cancer curability, metastatic breast cancer remains a lethal disease in the vast majority of cases. Therapeutic advances in the chemotherapeutic and targeted therapies fields induced an increase in survival, however the proportion of long survivors remains low. Phenotypic instability, an early process initiated during tumour progression, and continued on the metastatic stage of the disease, can be one of the putative hypotheses explaining these results. An increasing amount of scientific data are pledging for a reanalysis of the phenotypic profile regarding hormone receptors and HER-2 status of metastatic lesions in order to identify drugable targets and allow individualisation of the treatment of these metastatic breast cancer patients. Phenotypic changes between the primary tumour and the paired metastatic lymph nodes are a challenging pitfall, raising the question of which site has to be assessed in the adjuvant treatment decision process. This article presents a comprehensive analysis of the frequency of theses phenotypic changes altogether with new modalities to evaluate this phenotypic status.

Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Free-breathing inner-volume black-blood imaging of the human heart using two-dimensionally selective local excitation at 3 T.

Black-blood fast spin-echo imaging is a powerful technique for the evaluation of cardiac anatomy. To avoid fold-over artifacts, using a sufficiently large field of view in phase-encoding direction is mandatory. The related oversampling affects scanning time and respiratory chest motion artifacts are commonly observed. The excitation of a volume that exclusively includes the heart without its surrounding structures may help to improve scan efficiency and minimize motion artifacts. Therefore, and by building on previously reported inner-volume approach, the combination of a black-blood fast spin-echo sequence with a two-dimensionally selective radiofrequency pulse is proposed for selective "local excitation" small field of view imaging of the heart. This local excitation technique has been developed, implemented, and tested in phantoms and in vivo. With this method, small field of view imaging of a user-specified region in the human thorax is feasible, scanning becomes more time efficient, motion artifacts can be minimized, and additional flexibility in the choice of imaging parameters can be exploited.

Hybrid Multiscale Finite Volume method for two-phase flow in porous media

We present a novel hybrid (or multiphysics) algorithm, which couples pore-scale and Darcy descriptions of two-phase flow in porous media. The flow at the pore-scale is described by the Navier?Stokes equations, and the Volume of Fluid (VOF) method is used to model the evolution of the fluid?fluid interface. An extension of the Multiscale Finite Volume (MsFV) method is employed to construct the Darcy-scale problem. First, a set of local interpolators for pressure and velocity is constructed by solving the Navier?Stokes equations; then, a coarse mass-conservation problem is constructed by averaging the pore-scale velocity over the cells of a coarse grid, which act as control volumes; finally, a conservative pore-scale velocity field is reconstructed and used to advect the fluid?fluid interface. The method relies on the localization assumptions used to compute the interpolators (which are quite straightforward extensions of the standard MsFV) and on the postulate that the coarse-scale fluxes are proportional to the coarse-pressure differences. By numerical simulations of two-phase problems, we demonstrate that these assumptions provide hybrid solutions that are in good agreement with reference pore-scale solutions and are able to model the transition from stable to unstable flow regimes. Our hybrid method can naturally take advantage of several adaptive strategies and allows considering pore-scale fluxes only in some regions, while Darcy fluxes are used in the rest of the domain. Moreover, since the method relies on the assumption that the relationship between coarse-scale fluxes and pressure differences is local, it can be used as a numerical tool to investigate the limits of validity of Darcy's law and to understand the link between pore-scale quantities and their corresponding Darcy-scale variables.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Quantifying network properties in multi-electrode recordings: spatiotemporal characterization and inter-trial variation of evoked gamma oscillations in mouse somatosensory cortex in vitro.

Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

Copy number variation and chromatin structure

The functional consequences of structural variation in the human genome range from adaptation, to phenotypic variation, to predisposition to diseases. Copy number variation (CNV) was shown to influence the phenotype by modifying, in a somewhat dose-dependent manner, the expression of genes that map within them, as well as that of genes located on their flanks. To assess the possible mechanism(s) behind this neighboring effect, we compared histone modification status of cell lines from patients affected by Williams-Beuren, Williams-Beuren region duplication, Smith-Magenis or DiGeorge Syndrome and control individuals using a high-throughput version of chromatin immuno-precipitation method (ChIP), called ChlP-seq. We monitored monomethylation of lysine K20 on histone H4 and trimethylation of lysine K27 on histone H3, as proxies for open and condensed chromatin, respectively. Consistent with the changes in expression levels observed for multiple genes mapping on the entire length of chromosomes affected by structural variants, we also detected regions with modified histone status between samples, up- and downstream from the critical regions, up to the end of the rearranged chromosome. We also gauged the intrachromosomal interactions of these cell lines utilizing chromosome conformation capture (4C-seq) technique. We observed that a set of genes flanking the Williams-Beuren Syndrome critical region (WBSCR) were often looping together, possibly forming an interacting cluster with each other and the WBSCR. Deletion of the WBSCR disrupts the expression of this group of flanking genes, as well as long-range interactions between them and the rearranged interval. We conclude, that large genomic rearrangements can lead to changes in the state of the chromatin spreading far away from the critical region, thus possibly affecting expression globally and as a result modifying the phenotype of the patients. - Les conséquences fonctionnelles des variations structurelles dans le génome humain sont vastes, allant de l'adaptation, en passant par les variations phénotypiques, aux prédispositions à certaines maladies. Il a été démontré que les variations du nombre de copies (CNV) influencent le phénotype en modifiant, d'une manière plus ou moins dose-dépendante, l'expression des gènes se situant à l'intérieur de ces régions, mais également celle des gènes se trouvant dans les régions flanquantes. Afin d'étudier les mécanismes possibles sous-jacents à cet effet de voisinage, nous avons comparé les états de modification des histones dans des lignées cellulaires dérivées de patients atteints du syndrome de Williams-Beuren, de la duplication de la région Williams-Beuren, du syndrome de Smith-Magenis ou du syndrome de Di- George et d'individus contrôles en utilisant une version haut-débit de la méthode d'immunoprécipitation de la chromatine (ChIP), appelée ChIP-seq. Nous avons suivi la mono-méthylation de la lysine K20 sur l'histone H4 et la tri-méthylation de la lysine K27 sur l'histone H3, marqueurs respectifs de la chromatine ouverte et fermée. En accord avec les changements de niveaux d'expression observés pour de multiples gènes tout le long des chromosomes affectés par les CNVs, nous avons aussi détecté des régions présentant des modifications d'histones entre les échantillons, situées de part et d'autre des régions critiques, jusqu'aux extrémités du chromosome réarrangé. Nous avons aussi évalué les interactions intra-chromosomiques ayant lieu dans ces cellules par l'utilisation de la technique de capture de conformation des chromosomes (4C-seq). Nous avons observé qu'un groupe de gènes flanquants la région critique du syndrome de Williams-Beuren (WBSCR) forment souvent une boucle, constituant un groupe d'interactions privilégiées entre ces gènes et la WBSCR. La délétion de la WBSCR perturbe l'expression de ce groupe de gènes flanquants, mais également les interactions à grande échelle entre eux et la région réarrangée. Nous en concluons que les larges réarrangements génomiques peuvent aboutir à des changements de l'état de la chromatine pouvant s'étendre bien plus loin que la région critique, affectant donc potentiellement l'expression de manière globale et ainsi modifiant le phénotype des patients.