Large scale assessment of regulatory evolution and transcriptome complexity in mammals

AbstractIn addition to genetic changes affecting the function of gene products, changes in gene expression have been suggested to underlie many or even most of the phenotypic differences among mammals. However, detailed gene expression comparisons were, until recently, restricted to closely related species, owing to technological limitations. Thus, we took advantage of the latest technologies (RNA-Seq) to generate extensive qualitative and quantitative transcriptome data for a unique collection of somatic and germline tissues from representatives of all major mammalian lineages (placental mammals, marsupials and monotremes) and birds, the evolutionary outgroup.In the first major project of my thesis, we performed global comparative analyses of gene expression levels based on these data. Our analyses provided fundamental insights into the dynamics of transcriptome change during mammalian evolution (e.g., the rate of expression change across species, tissues and chromosomes) and allowed the exploration of the functional relevance and phenotypic implications of transcription changes at a genome-wide scale (e.g., we identified numerous potentially selectively driven expression switches).In a second project of my thesis, which was also based on the unique transcriptome data generated in the context of the first project we focused on the evolution of alternative splicing in mammals. Alternative splicing contributes to transcriptome complexity by generating several transcript isoforms from a single gene, which can, thus, perform various functions. To complete the global comparative analysis of gene expression changes, we explored patterns of alternative splicing evolution. This work uncovered several general and unexpected patterns of alternative splicing evolution (e.g., we found that alternative splicing evolves extremely rapidly) as well as a large number of conserved alternative isoforms that may be crucial for the functioning of mammalian organs.Finally, the third and final project of my PhD consisted in analyzing in detail the unique functional and evolutionary properties of the testis by exploring the extent of its transcriptome complexity. This organ was previously shown to evolve rapidly both at the phenotypic and molecular level, apparently because of the specific pressures that act on this organ and are associated with its reproductive function. Moreover, my analyses of the amniote tissue transcriptome data described above, revealed strikingly widespread transcriptional activity of both functional and nonfunctional genomic elements in the testis compared to the other organs. To elucidate the cellular source and mechanisms underlying this promiscuous transcription in the testis, we generated deep coverage RNA-Seq data for all major testis cell types as well as epigenetic data (DNA and histone methylation) using the mouse as model system. The integration of these complete dataset revealed that meiotic and especially post-meiotic germ cells are the major contributors to the widespread functional and nonfunctional transcriptome complexity of the testis, and that this "promiscuous" spermatogenic transcription is resulting, at least partially, from an overall transcriptionally permissive chromatin state. We hypothesize that this particular open state of the chromatin results from the extensive chromatin remodeling that occurs during spermatogenesis which ultimately leads to the replacement of histones by protamines in the mature spermatozoa. Our results have important functional and evolutionary implications (e.g., regarding new gene birth and testicular gene expression evolution).Generally, these three large-scale projects of my thesis provide complete and massive datasets that constitute valuables resources for further functional and evolutionary analyses of mammalian genomes.

Incline, speed, and distance assessment during unconstrained walking.

Body accelerations during human walking were recorded by a portable measuring device. A new method for parameterizing body accelerations and finding the pattern of walking is outlined. Two neural networks were designed to recognize each pattern and estimate the speed and incline of walking. Six subjects performed treadmill walking followed by self-paced walking on an outdoor test circuit involving roads of various inclines. The neural networks were first "trained" by known patterns of treadmill walking. Then the inclines, the speeds, and the distance covered during overground walking (outdoor circuit) were estimated. The results show a good agreement between actual and predicted variables. The standard deviation of estimated incline was less than 2.6% and the maximum of the coefficient of variation of speed estimation is 6%. To the best of our knowledge, these results constitute the first assessment of speed, incline and distance covered during level and slope walking and offer investigators a new tool for assessing levels of outdoor physical activity.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

MicroRNAs shape circadian hepatic gene expression on a transcriptome-wide scale.

A considerable proportion of mammalian gene expression undergoes circadian oscillations. Post-transcriptional mechanisms likely make important contributions to mRNA abundance rhythms. We have investigated how microRNAs (miRNAs) contribute to core clock and clock-controlled gene expression using mice in which miRNA biogenesis can be inactivated in the liver. While the hepatic core clock was surprisingly resilient to miRNA loss, whole transcriptome sequencing uncovered widespread effects on clock output gene expression. Cyclic transcription paired with miRNA-mediated regulation was thus identified as a frequent phenomenon that affected up to 30% of the rhythmic transcriptome and served to post-transcriptionally adjust the phases and amplitudes of rhythmic mRNA accumulation. However, only few mRNA rhythms were actually generated by miRNAs. Overall, our study suggests that miRNAs function to adapt clock-driven gene expression to tissue-specific requirements. Finally, we pinpoint several miRNAs predicted to act as modulators of rhythmic transcripts, and identify rhythmic pathways particularly prone to miRNA regulation.DOI: http://dx.doi.org/10.7554/eLife.02510.001.

A large-scale genetic validation study coupled with in vitro analyses reveal a role for vitamin Dsignaling in the pathogenesis and response to treatment of hepatitis C virus infection

Background and Aims: Vitamin D is an important modulatorof numerous cellular processes. Some of us recently observedan association of the 1a-hydroxylase promoter polymorphismCYP27B1-1260 rs10877012 with sustained virologic response (SVR)in a relatively small number of German patients with chronichepatitis C. In the present study, we aimed to validate thisassociation in a large and well characterized patient cohort, theSwiss Hepatitis C Cohort Study (SCCS). In addition, we examinedthe effect of vitamin D on the hepatitis C virus (HCV) life cyclein vitro.Methods: CYP27B1-1260 rs10877012 and IL28B rs12979860 singlenucleotide polymorphisms (SNPs) were genotyped in 1049 patientswith chronic hepatitis C from the SCCS, of whom 698 were treatedwith pegylated interferon-a (PEG-IFN-a) and ribavirin. In addition,112 patients with spontaneous clearance of HCV were examined.SNPs were correlated with variables reflecting the natural courseand treatment outcome of chronic hepatitis C. The effect of1,25-(OH)2D3 (calcitriol) on HCV replication and viral particleproduction was investigated in vitro using human hepatoma celllines (Huh-7.5) harbouring subgenomic replicons and cell culturederivedHCV.Results: The CYP27B1-1260 rs10877012 genotype was notassociated with SVR in patients with the good-response IL28Brs1279860 CC genotype. However, in patients with poor-responseIL28B rs1279860 genotype CT and TT, CYP27B1-1260 rs10877012was a significant independent predictor of SVR (15% difference inSVR between rs10877012 genotype AA vs. CC, p = 0.030, OR = 1.495,95% CI = 1.038-2.152). The CYPB27-1260 rs10877012 genotype wasneither associated with spontaneous clearance of HCV, nor withliver fibrosis progression rate, inflammatory activity of chronichepatitis C, or HCV viral load. Physiological doses of 1,25-(OH)2D3did not significantly affect HCVRNA replication or infectiousparticle production in vitro.Conclusions: The results of this large-scale genetic validationstudy reveal a role of vitamin D metabolism in the responseto treatment in chronic hepatitis C, but 1,25-(OH)2D3 does notexhibit a significant direct inhibitory antiviral effect. Thus, theability of vitamin D to modulate immunity against HCV shouldbe investigated.

Changes in leg spring behaviour, plantar loading and foot mobility magnitude induced by an exhaustive treadmill run in adolescent middle-distance runners.

OBJECTIVES: This study aimed to determine adjustments in spring-mass model characteristics, plantar loading and foot mobility induced by an exhaustive run. DESIGN: Within-participants repeated measures. METHODS: Eleven highly-trained adolescent middle-distance runners ran to exhaustion on a treadmill at a constant velocity corresponding to 95% of velocity associated with VO₂max (17.8 ± 1.4 kmh(-1), time to exhaustion=8.8 ± 3.4 min). Contact time obtained from plantar pressure sensors was used to estimate spring-mass model characteristics, which were recorded (during 30 s) 1 min after the start and prior to exhaustion using pressure insoles. Foot mobility magnitude (a composite measure of vertical and medial-lateral mobility of the midfoot) was measured before and after the run. RESULTS: Mean contact area (foot to ground), contact time, peak vertical ground reaction force, centre of mass vertical displacement and leg compression increased significantly with fatigue, while flight time, leg stiffness and mean pressure decreased. Leg stiffness decreased because leg compression increased to a larger extent than peak vertical ground reaction forces. Step length, step frequency and foot mobility magnitude did not change at exhaustion. CONCLUSIONS: The stride pattern of adolescents when running on a treadmill at high constant velocity deteriorates near exhaustion, as evidenced by impaired leg-spring behaviour (leg stiffness) and altered plantar loading.

Outcome evaluation of ankle osteoarthritis treatments: plantar pressure analysis during relatively long-distance walking.

Background : This study aimed to use plantar pressure analysis in relatively long-distance walking for objective outcome evaluation of ankle osteoarthritis treatments, i.e., ankle arthrodesis and total ankle replacement.Methods : Forty-seven subjects in four groups: three patient groups and controls, participated in the study. Each subject walked twice in 50-m trials. Plantar pressure under the pathological foot was measured using pressure insoles. Six parameters: initial contact time, terminal contact time, maximum force time, peak pressure time, maximum force and peak pressure were calculated and averaged over trials in ten regions of foot. The parameters in each region were compared between patient groups and controls and their effect size was estimated. Besides, the correlations between pressure parameters and clinical scales were calculated.Findings : We observed based on temporal parameters that patients postpone the heel-off event, when high force in forefoot and high ankle moment happens. Also based on maximum force and peak pressure, the patients apply smoothened maximum forces on the affected foot. In ten regions, some parameters showed improvements after total ankle replacement, some showed alteration of foot function after ankle arthrodesis and some others showed still abnormality after both surgical treatments. These parameters showed also significant correlation with clinical scales in at least two regions of foot.Interpretation : Plantar pressure parameters in relatively long-distance trials showed to be strong tools for outcome evaluation of ankle osteoarthritis treatments. (C) 2010 Elsevier Ltd. All rights reserved.

Scale decisions can reverse conclusions on community assembly processes.

AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.

Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked. RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data. AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system. CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Environment and dispersal paths override life strategies and residence time in determining regional patterns of invasion by alien plants.

We describe a novel dissimilarity framework to analyze spatial patterns of species diversity and illustrate it with alien plant invasions in Northern Portugal. We used this framework to test the hypothesis that patterns of alien invasive plant species richness and composition are differently affected by differences in climate, land use and landscape connectivity (i.e. Geographic distance as a proxy and vectorial objects that facilitate dispersal such as roads and rivers) between pairs of localities at the regional scale. We further evaluated possible effects of plant life strategies (Grime's C-S-R) and residence time. Each locality consisted of a 1 km(2) landscape mosaic in which all alien invasive species were recorded by visiting all habitat types. Multi-model inference revealed that dissimilarity in species richness is more influenced by environmental distance (particularly climate), whereas geographic distance (proxies for dispersal limitations) is more important to explain dissimilarity in species composition, with a prevailing role for ecotones and roads. However, only minor differences were found in the responses of the three C-S-R strategies. Some effect of residence time was found, but only for dissimilarity in species richness. Our results also indicated that environmental conditions (e.g. climate conditions) limit the number of alien species invading a given site, but that the presence of dispersal corridors determines the paths of invasion and therefore the pool of species reaching each site. As geographic distances (e.g. ecotones and roads) tend to explain invasion at our regional scale highlights the need to consider the management of alien invasions in the context of integrated landscape planning. Alien species management should include (but not be limited to) the mitigation of dispersal pathways along linear infrastructures. Our results therefore highlight potentially useful applications of the novel multimodel framework to the anticipation and management of plant invasions. (C) 2013 Elsevier GmbH. All rights reserved.

Glasgow Coma Score für den Patienten mit Schädel-Hirn-Trauma [Glasgow Coma Scale in traumatic brain injury].

Even 30 years after its first publication the Glasgow Coma Scale (GCS) is still used worldwide to describe and assess coma. The GCS consists of three components, the ocular, motor and verbal response to standardized stimulation, and is used as a severity of illness indicator for coma of various origins. The GCS facilitates information transfer and monitoring changes in coma. In addition, it is used as a triage tool in patients with traumatic brain injury. Its prognostic value regarding the outcome after a traumatic brain injury still lacks evidence. One of the main problems is the evaluation of the GCS in sedated, paralysed and/or intubated patients. A multitude of pseudoscores exists but a universal definition has yet to be defined.