Finding the approximate location of short read genome sequences by comparing them to an already available closely related organism's complete genome sequence is a challenging research issue. Predicting intron locations in the short form of mRNA called Expressed Sequence Tags (ESTs) and the variability of intron lengths are the major challenges. More specifically, finding the intron positions in an EST sequence by comparing it with a reference genome sequence is a time consuming task, as currently it is done manually. In my thesis, I designed a pipeline that can predict the intron positions in ESTs of non-model organisms. Initially, I compared the ESTs to the closest completely sequenced genome. The pipeline then finds the alignment of the ESTs, the reference genome sequence, and the coding region of the gene (known as Coding DNA Sequence or CDS) from the reference genome.

New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening.  It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions.  HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms.

In biomedical research, ontologies are widely used to represent knowledge as well as to annotate datasets. Many of the existing ontologies cover a single type of phenomena, such as a process, cell type, gene, pathological entity or anatomical structure. Consequently, there is a requirement to use multiple ontologies to fully characterize the observations in the datasets. Although this allows precise annotation of different aspects of a given dataset, it limits our ability to use the ontologies in data analysis, as the ontologies are usually disconnected and their combinations cannot be exploited. Motivated by this, here we present novel ontology design methods for combining pathology and anatomy concepts. To this end, we use a dataset of mouse models which has been characterized through two ontologies: one of them is the mouse pathology ontology (MPATH) covering pathological lesions while the other is the mouse anatomy ontology (MA) covering the anatomical site of the lesions. We propose four novel ontology design patterns for combining these ontologies, and use these patterns to generate four ontologies in a data-driven way. To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

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Afin de caractériser les voies de signalisation du système immunitaire inné, nous étudions l'interaction entre le ver C. elegans et le champignon Drechmeria coniospora. Une des réponses du ver à l'infection consiste en une augmentation de la production de peptides antimicrobiens (PAM) dans l'épiderme. Des vers transgéniques exprimant le gène rapporteur de la GFP sous le contrôle du promoteur d'un PAM, fluorescent vert après infection. Si un gène nécessaire à l'expression des PAM est inactivé, alors les vers transgéniques ne fluorescent plus après infection. Nous avons effectué un crible pour identifier les molécules de signalisation nécessaires à l'expression des PAM en utilisant une approche quantitative et semi-automatique par ARN interference (ARNi). Deux banques d'ARNi couvrant 95% du génome, soit 20 000 gènes, ont été criblées et 360 candidats bloquant l'induction de la GFP après infection ont été obtenus, correspondant à 343 gènes. Une caractérisation phénotypique a permis de placer les candidats dans différentes catégories fonctionnelles et permis d'identifier d'une part un récepteur agissant en amont de la voie de signalisation p38 nécessaire à l'activation des gènes PAM, d'autre part une implication des granules de stress lors de l'infection. Ces analyses sont le fondement pour l'établissement d'une description compréhensive du réseau génétique régulant le système immunitaire inné du ver et permettront de révéler les interactions complexes entre l'immunité et les processus physiologiques au niveau moléculaire, cellulaire et au niveau de l'organisme. / To investigate innate immune signaling, we study the interaction of C. elegans with the fungus Drechmeria coniospora. One of the responses of the worm to this infection is the up-regulation of a variety of antimicrobial peptide (AMP) genes in the epidermis. Transgenic worms carrying a GFP reporter gene under the control of an AMP promoter fluoresce green after infection by D. coniospora. If a gene required for AMP gene expression is inactivated, the reporter strain will not turn green upon infection. Using this fluorescent read-out, we have been able to screen for signaling molecules required for AMP gene expression using a quantitative semi-automated RNAi approach. We have screened two RNAi libraries that together cover 95% of the ca. 20,000 genes in the C. elegans genome and we obtained 360 high-confidence candidates that reduced the level of induction of green fluorescence after infection, and correspond to 343 genes. A further phenotypic characterization allowed the candidates to be grouped into distinct functional categories and allowed the identification of both a receptor acting upstream the p38 MAPK pathway necessary for the activation of the AMPs, and the implication of stress granules during infection. Altogether, the screen data and its analysis represent the foundation for the establishment of a comprehensive description of the signaling network regulating the innate immune system of the worm and will shed light on the complex interactions between immunity and other physiological processes at the molecular, cellular and organismal level.

A current trend in biological science is the increased use of computational tools for both the production and analysis of experimental data. This is especially true in the field of genomics, where advancements in DNA sequencing technology have dramatically decreased the time and cost associated with DNA sequencing resulting in increased pressure on the time required to prepare and analyze data generated during these experiments. As a result, the role of computational science in such biological research is increasing. This thesis seeks to address several major questions with respect to the development and application of single nucleotide polymorphism (SNP) resources in non-model organisms. Traditional SNP discovery using polymerase chain reaction (PCR) amplification and low-throughput DNA sequencing is a time consuming and laborious process, which is often limited by the time required to design intron-spanning PCR primers. While next-generation DNA sequencing (NGS) has largely supplanted low-throughput sequencing for SNP discovery applications, the PCR based SNP discovery method remains in use for cost effective, targeted SNP discovery. This thesis seeks to develop an automated method for intron-spanning PCR design which would remove a significant bottleneck in this process. This work develops algorithms for combining SNP data from multiple individuals, independent of the DNA sequencing platforms, for the purpose of developing SNP genotyping arrays. Additionally, tools for the filtering and selection of SNPs will be developed, providing start to finish support for the development of SNP genotyping arrays in complex polyploids using NGS. The result of this work includes two automated pipelines for the design of intron-spanning PCR primers, one which designs a single primer pair per target and another that designs multiple primer pairs per target. These automated pipelines are shown to reduce the time required to design primers from one hour per primer pair using the semi-automated method to 10 minutes per 100 primer pairs while maintaining a very high efficacy. Efficacy is tested by comparing the number of successful PCR amplifications of the semi- automated method with that of the automated pipelines. Using the Chi-squared test, the semi-automated and automated approaches are determined not to differ in efficacy. Three algorithms for combining SNP output from NGS data from multiple individuals are developed and evaluated for their time and space complexities. These algorithms were found to be computationally efficient, requiring time and space linear to the size of the input. These algorithms are then implemented in the Perl language and their time and memory performance profiled using experimental data. Profiling results are evaluated by applying linear models, which allow for predictions of resource requirements for various input sizes. Additional tools for the filtering of SNPs and selection of SNPs for a SNP array are developed and applied to the creation of two SNP arrays in the polyploid crop Brassica napus. These arrays, when compared to arrays in similar species, show higher numbers of polymorphic markers and better 3-cluster genotype separation, a viable method for determining the efficacy of design in complex genomes.

Since a proper balance between anabolic and catabolic reactions is essential for all eukaryotes, the basic mechanisms for regulation of the energy and carbon metabolism have been conserved throughout evolution. The moss Physcomitrella patens, which belongs to one of the basal clades among land plants, has many unique properties that make it an excellent plant model system. We have used a yeast two-hybrid system to identify novel possible regulators or targets of the moss Snf1-related kinases, previously shown to regulate energy homeostasis. The function of the identified interactors PpSki1 and PpSki2 was analyzed in order to better understand the biological role of plant Snf1-related kinases. The recently completed genome sequence of Physcomitrella was used in a comparative approach to study to what extent key enzyme and gene families involved in transport and metabolism of sugars and in regulation of the energy and carbon metabolism are conserved between mosses and vascular plants. It has long been known that transformed DNA can replicate episomally in Physcomitrella. We have now shown that such DNA can be rescued back into E. coli. Surprisingly, we found that the original plasmid can be recovered from moss transformants obtained with circular DNA. Plasmids rescued from transformants obtained with linearized DNA had been repaired either by homologous recombination or by cohesive end re-ligation. These findings suggest that methods using shuttle plasmids are feasible in Physcomitrella. Hexokinase, a key enzyme in the carbon metabolism, catalyzes the first step in hexose metabolism, but is also involved in sugar sensing and signaling. We have now made an initial characterization of the complete hexokinase family in Physcomitrella which is encoded by 11 genes. Two new types of plant hexokinases, types C and D, were found in addition to the previously described types A and B.

Primary cilia are evolutionarily conserved organelles required in a number of signalling pathways influencing the development and behaviour of a diverse range of organisms. More recently, studies into a new class of human diseases known as ciliopathies have helped to shed light on the critical role of this once-ignored signalling centre. Bardet-Biedl syndrome (BBS) proteins localize to the primary cilium and participate in cilium biogenesis and function. BBS is a pleiotropic human disorder with variable severity that is suitable as a disease model for investigating the pathogenesis of a number of common ciliopathy features such as photoreceptor degeneration, renal cysts, and obesity. The C. elegans genome encodes a number of BBS proteins which undergo intraflagellar transport (IFT) at the primary cilium. Given the conservation between C. elegans and human BBS proteins, I hypothesize the existence of unidentified conserved genetic pathways related to the functions of these proteins. Using C. elegans, I characterize novel features of bbs mutants while identifying sources of genomic variation that may elucidate the variability of human BBS features. I show that C. elegans bbs mutants exhibit smaller body size, delayed development, and decreased exploration behaviour. Moreover, I identify a role for the soluble guanylate cyclases GCY-35/GCY-36 in modifying these bbs phenotypes. I conclude that BBS proteins non-cell autonomously influence a set of body cavity neurons in which GCY-35/GCY-36 function genetically upstream of a cGMP-dependent protein kinase (PKG), EGL-4, to control body size. Furthermore, the role of GCY-35/GCY-36 is unique amongst a large number of guanylate cyclases and BBS proteins may influence body size via an IFT-independent function. I explore the biological functions of EGL-4 and conclude that it may regulate body size through multiple cellular mechanisms. I also examine potential candidate genes related to cGMP production and turnover, confirming that additional cGMP-related factors can influence body size although not necessarily in body cavity neurons. In conclusion, I propose a model where BBS-expressing sensory neurons influence body size and development through cGMP-PKG signalling in body cavity neurons while functioning in parallel with additional sensory neurons (possibly BBS-independent) that use similar cGMP-PKG signalling dynamics.

Primary cilia are evolutionarily conserved organelles required in a number of signalling pathways influencing the development and behaviour of a diverse range of organisms. More recently, studies into a new class of human diseases known as ciliopathies have helped to shed light on the critical role of this once-ignored signalling centre. Bardet-Biedl syndrome (BBS) proteins localize to the primary cilium and participate in cilium biogenesis and function. BBS is a pleiotropic human disorder with variable severity that is suitable as a disease model for investigating the pathogenesis of a number of common ciliopathy features such as photoreceptor degeneration, renal cysts, and obesity. The C. elegans genome encodes a number of BBS proteins which undergo intraflagellar transport (IFT) at the primary cilium. Given the conservation between C. elegans and human BBS proteins, I hypothesize the existence of unidentified conserved genetic pathways related to the functions of these proteins. Using C. elegans, I characterize novel features of bbs mutants while identifying sources of genomic variation that may elucidate the variability of human BBS features. I show that C. elegans bbs mutants exhibit smaller body size, delayed development, and decreased exploration behaviour. Moreover, I identify a role for the soluble guanylate cyclases GCY-35/GCY-36 in modifying these bbs phenotypes. I conclude that BBS proteins non-cell autonomously influence a set of body cavity neurons in which GCY-35/GCY-36 function genetically upstream of a cGMP-dependent protein kinase (PKG), EGL-4, to control body size. Furthermore, the role of GCY-35/GCY-36 is unique amongst a large number of guanylate cyclases and BBS proteins may influence body size via an IFT-independent function. I explore the biological functions of EGL-4 and conclude that it may regulate body size through multiple cellular mechanisms. I also examine potential candidate genes related to cGMP production and turnover, confirming that additional cGMP-related factors can influence body size although not necessarily in body cavity neurons. In conclusion, I propose a model where BBS-expressing sensory neurons influence body size and development through cGMP-PKG signalling in body cavity neurons while functioning in parallel with additional sensory neurons (possibly BBS-independent) that use similar cGMP-PKG signalling dynamics.

This thesis is dedicated to developments and applications of metabolomics, exploiting high field NMR spectroscopy. The first part is dedicated to a general presentation of metabolomics. We also report results about the introduction of reduced dimensionality techniques for the characterization of complex mixtures, coined targeted projection NMR spectroscopy. The second part of this manuscript reports results about three different metabolomic studies carried out in human populations. The first analysis demonstrates the suitability for metabolomics of serum samples collected in the framework of the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The second study investigates a serum metabolic signature of metastatic breast cancer. The last analysis establishes potential plasma metabolic signatures for different liver pathologies, like hepatocellular carcinoma. The third part of this thesis is dedicated to the characterization of various model organisms. The first study presents a characterization of plasma and urine metabolic differences between four rat strains commonly used as controls in genetic studies. In the second study, we investigate the effects of physiological aging in Caenorhabditis elegans (C. elegans) and observe that dietary restriction buffers metabolic changes associated with aging. We further identify that perturbations in phosphocholine metabolism correlate with life expectancy. The third analysis of this part characterizes the ahr-1 C. elegans mutant, showing strong metabolic changes in ahr-1 mutants, which suggest an involvement in development and aging processes. We finally investigate in the last study the effects at the metabolic level of the interaction between an endogenous protein E4F1 and a viral protein HBx in liver cells infected by hepatitis B virus.