Integrative analysis of RUNX1 downstream pathways and target genes.

BACKGROUND: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. RESULTS: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFbeta, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFbeta. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. CONCLUSION: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications

On the Segregation of Genetically Modified, Conventional, and Organic Products in European Agriculture: A Multi-market Equilibrium Analysis, October 2005

Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU) this regulation envisions the “co-existence” of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products, and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Local-scale spatial variation in diversity of social wasps in an Amazonian rain forest in Caxiuanã, Pará, Brazil (Hymenoptera, Vespidae, Polistinae)

Polistine wasps are important in Neotropical ecosystems due to their ubiquity and diversity. Inventories have not adequately considered spatial attributes of collected specimens. Spatial data on biodiversity are important for study and mitigation of anthropogenic impacts over natural ecosystems and for protecting species. We described and analyzed local-scale spatial patterns of collecting records of wasp species, as well as spatial variation of diversity descriptors in a 2500-hectare area of an Amazon forest in Brazil. Rare species comprised the largest fraction of the fauna. Close range spatial effects were detected for most of the more common species, with clustering of presence-data at short distances. Larger spatial lag effects could also be identified in some species, constituting probably cases of exogenous autocorrelation and candidates for explanations based on environmental factors. In a few cases, significant or near significant correlations were found between five species (of Agelaia, Angiopolybia, and Mischocyttarus) and three studied environmental variables: distance to nearest stream, terrain altitude, and the type of forest canopy. However, association between these factors and biodiversity variables were generally low. When used as predictors of polistine richness in a linear multiple regression, only the coefficient for the forest canopy variable resulted significant. Some level of prediction of wasp diversity variables can be attained based on environmental variables, especially vegetation structure. Large-scale landscape and regional studies should be scheduled to address this issue.

Genome-wide association study to identify common variants associated with brachial circumference: a meta-analysis of 14 cohorts.

Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.

Comparative modular analysis of gene expression in vertebrate organs.

ABSTRACT: BACKGROUND: The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. RESULTS: Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. CONCLUSIONS: Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Bacterial bioassay for rapid and accurate analysis of arsenic in highly variable groundwater samples.

In this study, we report the first ever large-scale environmental validation of a microbial reporter-based test to measure arsenic concentrations in natural water resources. A bioluminescence-producing arsenic-inducible bacterium based on Escherichia coli was used as the reporter organism. Specific protocols were developed with the goal to avoid the negative influence of iron in groundwater on arsenic availability to the bioreporter cells. A total of 194 groundwater samples were collected in the Red River and Mekong River Delta regions of Vietnam and were analyzed both by atomic absorption spectroscopy (AAS) and by the arsenic bioreporter protocol. The bacterial cells performed well at and above arsenic concentrations in groundwater of 7 microg/L, with an almost linearly proportional increase of the bioluminescence signal between 10 and 100 microg As/L (r2 = 0.997). Comparisons between AAS and arsenic bioreporter determinations gave an overall average of 8.0% false negative and 2.4% false positive identifications for the bioreporter prediction at the WHO recommended acceptable arsenic concentration of 10 microg/L, which is far betterthan the performance of chemical field test kits. Because of the ease of the measurement protocol and the low application cost, the microbiological arsenic test has a great potential in large screening campaigns in Asia and in other areas suffering from arsenic pollution in groundwater resources.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Organisational reforms in active welfare states: A comparative analysis of the turn to 'single gateways' in Western Europe

Based on the case of reforms aimed at integrating the provision of income protection and employment services for jobless people in Europe, this thesis seeks to understand the reasons which may prompt governments to engage in large-scale organisational reforms. Over the last 20 years, several European countries have indeed radically redesigned the organisational structure of their welfare state by merging or bundling existing front-line offices in charge of benefit payment and employment services together into 'one-stop' agencies. Whereas in academic and political debates, these reforms are generally presented as a necessary and rational response to the problems and inconsistencies induced by fragmentation in a context of the reorientation of welfare states towards labour market activation, this thesis shows that the agenda setting of these reforms is in fact the result of multidimensional political dynamics. More specifically, the main argument of this thesis is that these reforms are best understood not so such from the problems induced by organisational compartmentalism, whose political recognition is often controversial, but from the various goals that governments may simultaneously achieve by means of their adoption. This argument is tested by comparing agenda-setting processes of large-scale reforms of coordination in the United Kingdom (Jobcentre Plus), Germany (Hartz IV reform) and Denmark (2005 Jobcentre reform), and contrasting them with the Swiss case where the government has so far rejected any coordination initiative involving organisational redesign. This comparison brings to light the importance, for the rise of organisational reforms, of the possibility to couple them with the following three goals: first, goals related to the strengthening of activation policies; second, institutional goals seeking to redefine the balance of responsibilities between the central state and non-state actors, and finally electoral goals for governments eager to maintain political credibility. The decisive role of electoral goals in the three countries suggests that these reforms are less bound by partisan politics than by the particular pressures facing governments arrived in office after long periods in opposition.

Analysis of gene expression patterns in animals

During my PhD, my aim was to provide new tools to increase our capacity to analyse gene expression patterns, and to study on a large-scale basis the evolution of gene expression in animals. Gene expression patterns (when and where a gene is expressed) are a key feature in understanding gene function, notably in development. It appears clear now that the evolution of developmental processes and of phenotypes is shaped both by evolution at the coding sequence level, and at the gene expression level.Studying gene expression evolution in animals, with complex expression patterns over tissues and developmental time, is still challenging. No tools are available to routinely compare expression patterns between different species, with precision, and on a large-scale basis. Studies on gene expression evolution are therefore performed only on small genes datasets, or using imprecise descriptions of expression patterns.The aim of my PhD was thus to develop and use novel bioinformatics resources, to study the evolution of gene expression. To this end, I developed the database Bgee (Base for Gene Expression Evolution). The approach of Bgee is to transform heterogeneous expression data (ESTs, microarrays, and in-situ hybridizations) into present/absent calls, and to annotate them to standard representations of anatomy and development of different species (anatomical ontologies). An extensive mapping between anatomies of species is then developed based on hypothesis of homology. These precise annotations to anatomies, and this extensive mapping between species, are the major assets of Bgee, and have required the involvement of many co-workers over the years. My main personal contribution is the development and the management of both the Bgee database and the web-application.Bgee is now on its ninth release, and includes an important gene expression dataset for 5 species (human, mouse, drosophila, zebrafish, Xenopus), with the most data from mouse, human and zebrafish. Using these three species, I have conducted an analysis of gene expression evolution after duplication in vertebrates.Gene duplication is thought to be a major source of novelty in evolution, and to participate to speciation. It has been suggested that the evolution of gene expression patterns might participate in the retention of duplicate genes. I performed a large-scale comparison of expression patterns of hundreds of duplicated genes to their singleton ortholog in an outgroup, including both small and large-scale duplicates, in three vertebrate species (human, mouse and zebrafish), and using highly accurate descriptions of expression patterns. My results showed unexpectedly high rates of de novo acquisition of expression domains after duplication (neofunctionalization), at least as high or higher than rates of partitioning of expression domains (subfunctionalization). I found differences in the evolution of expression of small- and large-scale duplicates, with small-scale duplicates more prone to neofunctionalization. Duplicates with neofunctionalization seemed to evolve under more relaxed selective pressure on the coding sequence. Finally, even with abundant and precise expression data, the majority fate I recovered was neither neo- nor subfunctionalization of expression domains, suggesting a major role for other mechanisms in duplicate gene retention.

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Mesoscale numerical analysis of the historical November 1982 heavy precipitation event over Andorra (Eastern Pyrenees)

From 6 to 8 November 1982 one of the most catastrophic flash-flood events was recorded in the Eastern Pyrenees affecting Andorra and also France and Spain with rainfall accumulations exceeding 400 mm in 24 h, 44 fatalities and widespread damage. This paper aims to exhaustively document this heavy precipitation event and examines mesoscale simulations performed by the French Meso-NH non-hydrostatic atmospheric model. Large-scale simulations show the slow-evolving synoptic environment favourable for the development of a deep Atlantic cyclone which induced a strong southerly flow over the Eastern Pyrenees. From the evolution of the synoptic pattern four distinct phases have been identified during the event. The mesoscale analysis presents the second and the third phase as the most intense in terms of rainfall accumulations and highlights the interaction of the moist and conditionally unstable flows with the mountains. The presence of a SW low level jet (30 m s-1) around 1500 m also had a crucial role on focusing the precipitation over the exposed south slopes of the Eastern Pyrenees. Backward trajectories based on Eulerian on-line passive tracers indicate that the orographic uplift was the main forcing mechanism which triggered and maintained the precipitating systems more than 30 h over the Pyrenees. The moisture of the feeding flow mainly came from the Atlantic Ocean (7-9 g kg-1) and the role of the Mediterranean as a local moisture source was very limited (2-3 g kg-1) due to the high initial water vapour content of the parcels and the rapid passage over the basin along the Spanish Mediterranean coast (less than 12 h).

Reconciling phonological neighborhood effects in speech production through single trial analysis

A crucial step for understanding how lexical knowledge is represented is to describe the relative similarity of lexical items, and how it influences language processing. Previous studies of the effects of form similarity on word production have reported conflicting results, notably within and across languages. The aim of the present study was to clarify this empirical issue to provide specific constraints for theoretical models of language production. We investigated the role of phonological neighborhood density in a large-scale picture naming experiment using fine-grained statistical models. The results showed that increasing phonological neighborhood density has a detrimental effect on naming latencies, and re-analyses of independently obtained data sets provide supplementary evidence for this effect. Finally, we reviewed a large body of evidence concerning phonological neighborhood density effects in word production, and discussed the occurrence of facilitatory and inhibitory effects in accuracy measures. The overall pattern shows that phonological neighborhood generates two opposite forces, one facilitatory and one inhibitory. In cases where speech production is disrupted (e.g. certain aphasic symptoms), the facilitatory component may emerge, but inhibitory processes dominate in efficient naming by healthy speakers. These findings are difficult to accommodate in terms of monitoring processes, but can be explained within interactive activation accounts combining phonological facilitation and lexical competition.