In this thesis I apply new sequencing technologies and analytical methods derived from genomics and computer science to the neuroanatomy of gene expression. The first project explores characteristics of gene expression across adult neocortical layers in a representative mammal – the mouse. Amongst the thousands of genes and transcripts differentially expressed across layers, I found common functional characteristics of genes that define certain layers, candidate cases of isoform switching, and over a thousand apparent long intergenic non-coding RNA transcripts. The second project compares patterns of gene expression in the structurally diverged adult derivatives of the pallium in mice and chickens. Overall, gene expression levels were moderately correlated between the two species. While expression patterns of ‘marker’ genes were only poorly conserved in these regions, there nevertheless was significant conservation of cross-species marker genes for homologous structures, cell types and functionally analogous regions. Many aspects of these data from both projects can now be easily browsed and searched from custom-built web interfaces. In addition to generating unprecedented genome-wide resources for the neuroscience community to explore the functional and structural dimensions of gene expression amongst different pallial regions in mammals and birds, this work also provides new insights into the widespread evolutionary shuffling of adult marker gene expression.

Leishmania spp. undergo substantial adaptations from being promastigotes, found in sandflies, to being amastigotes, residing in parasitophorous vacuoles within mammalian macrophages. In the past, microarray studies have sought to elucidate these adaptations using axenic amastigote systems or amastigotes purified from host-cells, raising the question whether the observed transcriptomic signatures were a true reflection of intracellular amastigotes. Moreover, with ever-improving genome annotations being available, it is clear that these studies failed to address the transcriptomic behaviour of a considerable number of transcripts. In the work presented herein, I employed RNA-sequencing to obtain transcriptomic profiles of Leishmania mexicana axenic promastigotes (PRO), axenic amastigotes (AXA) and intracellular amastigotes (AMA) in murine bone-marrow derived macrophages. The intracellular amastigotes were not purified from host cells, but instead sequencing reads assigned to a hybrid L. mexicana - Mus musculus genome and the transcriptomes separated in silico. We were able to map pre-mRNA processing sites, thereby defining transcript boundaries, proposing 184 truncations and 1253 extensions of existing gene models as well as discovering 936 novel genes. Mass-spectrometric evidence was obtained for both proposed extended and novel proteins. Using this improved genome annotation, we generated gene expression profiles for AMA, AXA and PRO, identifying 3832 differentially expressed transcripts between PRO and AMA as well as 2176 between PRO and AXA and 1234 between AXA and AMA. Transcripts differentially expressed between AMA and PRO correlated well with previous reports, were enriched for novel transcripts identified in this study and contained an unprecedented wealth of yet uncharacterised transcripts. Guided by these data, I performed a GFP-tagging screen identifying two proteins which may play an important role in L. mexicana biology, LmxM.16.0500, a member of a small, divergent, amastin-derived gene family, which appears to be released from the cell body of PRO, and LmxM.09.1330 a specific marker of the amastigote flagellar pocket.

Chez les plantes à fleurs, l’ovaire est l’organe reproducteur femelle et il interagit de façon importante avec les gamètes mâles durant la croissance, le guidage, la réception et la rupture du tube pollinique ainsi que la fusion des gamètes. Le processus débute lorsque de nombreux gènes de l’ovule sont activés à longue distance lors de la réception du pollen sur le stigmate. Afin d’explorer les signaux provenant de l’ovule ayant un impact important sur les interactions pollen–pistil, particulièrement les molécules sécrétées impliquées dans la signalisation espècespécifique, l’expression génique des ovules sous forme d’ARNm ainsi et la sécrétion protéique ont été étudiées chez Solanum chacoense, une espèce diploïde de pomme de terre sauvage. S. chacoense a subi beaucoup d’hybridation interspécifique avec d’autres espèces sympathiques de solanacées, facilitant ainsi grandement l’étude des interactions pollen–ovule de façon espècespécifique ainsi que leur évolution. Dans ce projet, des ovules provenant de trois conditions différentes ont été comparés: des ovules matures de type sauvage, des ovules légèrement immatures, récoltés deux jours avant l’anthèse et des ovules provenant du mutant frk1 pour lesquels le sac embryonnaire est absent. Un séquençage d’ARN à haut débit a d’abord été effectué sur les ovules de type sauvage de S. chacoense afin de générer un assemblage de référence comprenant 33852 séquences codantes. D’autres séquençages ont été effectués sur les trois conditions d’ovules et sur les feuilles afin de faire une analyse d’expression différentielle des gènes. En comparaison avec les ovules de type sauvage, 818 gènes sont réprimés dans les ovules du mutant frk1. Un sous-groupe de 284 gènes, étaient également sous-exprimés dans les ovules légèrement immatures, suggérant un rôle spécifique dans les stades tardifs de la maturation du sac embryonnaire (stade de développent FG6 à FG7) ainsi que du guidage du tube pollinique, puisque ni les ovules du mutant frk1 ni ceux légèrement immatures ne sont capables d’attirer les tubes polliniques lors d’essais de croissance semi in vivo. De plus, 21% de ces gènes sont des peptides riches en cystéines (CRPs). En utilisant un transcriptome assemblé de novo provenant de deux proches parents de S. chacoense, S. gandarillasii et S. tarijense, une analyse d’orthologie a été effectuée sur ces CRPs, révélant une grande variabilité et une évolution rapide chez les solanacées. De nouveaux motifs de cystéine uniques à cette famille ont également été découverts. En comparant avec des études similaires chez Arabidopsis, le sac embryonnaire de S. chacoense montre un transcriptome fortement divergent, particulièrement en en ce qui a trait à la catégorisation fonctionnelle des gènes et de la similarité entre les gènes orthologues. De plus,même si la glycosylation n’est pas requise lors du guidage mycropylaire du tube pollinique chez Arabidopsis, Torenia ou le maïs, des extraits d’ovules glycosylés de S. chacoense sont capables d’augmenter la capacité de guidage de 18%. Cette étude est donc la première à montrer une corrélation entre glycosylation et le guidage du tube pollinique par l’ovule. En complément à l’approche transcriptomique, une approche protéomique portant sur les protéine sécrétées par l’ovule (le secrétome) a été utilisée afin d’identifier des protéines impliquées dans l’interaction entre ovule et tube pollinique. Des exsudats d’ovules matures (capables d’attirer le tube pollinique) et d’ovules immatures (incapables d’attirer le tube pollinique) ont été récoltés en utilisant une nouvelle méthode d’extraction par gravité permettant de réduire efficacement les contaminants cytosoliques à moins de 1% de l’échantillon. Un total de 305 protéines sécrétées par les ovules (OSPs) ont été identifiées par spectrométrie de masse, parmi lesquelles 58% étaient spécifiques aux ovules lorsque comparées avec des données de protéines sécrétées par des tissus végétatifs. De plus, la sécrétion de 128 OSPs est augmentée dans les ovules matures par rapport aux ovules immatures. Ces 128 protéines sont donc considérées en tant que candidates potentiellement impliquées dans la maturation tardive de l’ovule et dans le guidage du tube pollinique. Cette étude a également montré que la maturation du sac embryonnaire du stade FG6 au stade FG7 influence le niveau de sécrétion de 44% du sécrétome total de l’ovule. De façon surprenante, la grande majorité (83%) de ces protéines n’est pas régulée au niveau de l’ARN, soulignant ainsi l’importance de cette approche dans l’étude du guidage du tube pollinique comme complément essentiel aux études transcriptomiques. Parmi tous les signaux sécrétés par l’ovule et reliés au guidage, obtenus à partir des approches transcriptomiques et protéomiques décrites ci-haut, nous avons spécifiquement évalué l’implication des CRPs dans le guidage du tube pollinique par l’ovule chez S. chacoense, vu l’implication de ce type de protéine dans les interactions pollen-pistil et le guidage du tube pollinique chez d’autres espèces. Au total, 28 CRPs étaient présentes dans les ovules capables d’attirer le tube pollinique tout en étant absentes dans les ovules incapables de l’attirer, et ce, soit au niveau de l’ARNm et/ou au niveau du sécrétome. De celles-ci, 17 CRPs ont été exprimées dans un système bactérien et purifiées en quantité suffisante pour tester le guidage. Alors que des exsudats d’ovules ont été utilisés avec succès pour attirer par chimiotactisme le tube pollinique, les candidats exprimés dans les bactéries n’ont quant à eux pas été capables d’attirer les tubes polliniques. Comme l’utilisation de systèmes d’expression hétérologue eucaryote peut permettre un meilleur repliement et une plus grande activité des protéines, les candidats restants seront de nouveau exprimés, cette fois dans un système de levure ainsi que dans un système végétal pour produire les peptides sécrétés. Ceux-ci seront ensuite utilisés lors d’essais fonctionnels pour évaluer leur capacité à guider les tubes polliniques et ainsi isoler les attractants chimiques responsable du guidage du tube pollinique chez les solanacées comme S. chacoense. / In flowering plants, the ovary is the female reproductive organ that interacts extensively with the male gametophyte during pollen tube (PT) growth, guidance, reception, discharge and gamete fusion. The process begins when numerous ovule-expressed genes are activated when pollen lands on the stigma. To explore the ovular signals that have a great impact on successful pollen–pistil interactions, especially the secreted molecules that mediate species-specific signalling events, ovule mRNA expression and protein secretion profiles were studied in Solanum chacoense, a wild diploid potato species. Solanum chacoense has undergone extensive interspecific hybridization with sympatric solanaceous species that greatly facilitates the study of species-specific pollen–ovule interactions and evolution. In this project, three ovule conditions were studied: wild-type mature ovules, slightly immature ovules at two days before anthesis (2DBA), and frk1 mutant ovules that lack an embryo sac (ES). RNA-seq was performed on S. chacoense ovules to provide a scaffold assembly comprising 33852 CDS-containing sequences, then to provide read counts for differential gene expression analyses on three ovule conditions as well as on leaf. Compared to wild-type ovules, 818 genes were downregulated in frk1 ovules. A subset of 284 genes was concurrently under-expressed in 2DBA ovules, suggestive of their specific involvement in late stages of ES maturation (female gametophyte (FG), FG6 to FG7 developmental stage), as well as in PT guidance processes, as neither frk1 nor 2DBA ovules attract semi in vivo-grown PTs. Of these 284, 21% encoded cysteine-rich peptides (CRPs). Using de novo assembled ovule transcriptomes of two close relatives, S. gandarillasii and S. tarijense, an orthology survey was conducted on these CRPs, revealing their highly polymorphic nature among species and rapid evolution. Interestingly, novel cysteine motifs unique to this family were also uncovered. As compared to parallel studies in Arabidopsis, S. chacoense was found to possess a highly divergent ES transcriptome, in terms of both functional categories and individual ortholog similarities. Although glycosylation is not required for micropylar guidance cues to attract PTs in Arabidopsis, Torenia or maize, glycosylated ovule extracts from S. chacoense showed enhanced PT guidance competency by 18%. This is the first time a positive regulation between glycosylation and ovular PT guidance has been observed. As a complement to the transcriptomic approach, a proteomic approach using secreted proteins from the ovule (secretome) was employed to identify proteins involved in pollen–pistil interactions. Ovule exudates were collected from mature ovules (PT attracting) and immature ovules at 2DBA (PT nonattracting), using a novel tissue free-gravity extraction method (tf-GEM), which efficiently reduced the cytosolic contamination to less than 1%. Through mass spectrometry analyses, a total of 305 ovule-secreted proteins (OSPs) were identified, of which 58% were considered ovule-specific when compared to secretome studies conducted in other plant tissues. The secretion of 128 OSPs was upregulated in mature ovules vs. immature ovules. These OSPs were considered as candidate proteins involved in late ovule maturation and PT guidance. This study demonstrated that the ES maturation from FG6 to FG7 stages influenced the secretion status of 44% of ovule secretome. Surprisingly, the majority (83%) of these proteins were not regulated at the RNA level, vindicating this novel approach in the study of PT guidance as a robust complement to transcriptomic studies. Among all identified guidance-related ovular signals from the transcriptomic and proteomic approaches described above, we focused on the evaluation of the involvement of CRPs in ovular PT guidance of S. chacoense, due to the implication of various CRPs in pollen–pistil interactions and, especially, in PT guidance. A total of 28 CRPs were present in PT attracting ovules while being low or absent in nonattracting ovules, at the mRNA and/or protein secretion levels. Of these, 17 CRPs were expressed in bacteria and purified in sufficient amount for PT guidance assays. However, while ovule exudates were shown to induce PT chemotropism in the bead assay, refolded candidates did not show guidance competency. Since the use of eukaryotic protein expression systems might lead to better refolding and higher protein activity, the remaining candidates will be expressed in both yeast and plant-based expression systems and tested for their ability to attract PTs in a semi in-vivo assay, in order to lead us toward the isolation of PT guidance chemoattractants in solanaceous species like S. chacoense.

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion mutant, PAO∆ampR were analyzed. Transcriptome analysis demonstrates that the AmpR regulon is much more extensive than previously thought influencing the differential expression of over 500 genes. In addition to regulating resistance to β-lactam antibiotics via AmpC, AmpR also regulates non-β-lactam antibiotic resistance by modulating the MexEF-OprN efflux pump. Virulence mechanisms including biofilm formation, QS-regulated acute virulence, and diverse physiological processes such as oxidative stress response, heat-shock response and iron uptake are AmpR-regulated. Real-time PCR and phenotypic assays confirmed the transcriptome data. Further, Caenorhabditis elegans model demonstrates that a functional AmpR is required for full pathogenicity of P. aeruginosa. AmpR, a member of the core genome, also regulates genes in the regions of genome plasticity that are acquired by horizontal gene transfer. The extensive AmpR regulon included other transcriptional regulators and sigma factors, accounting for the extensive AmpR regulon. Gene expression studies demonstrate AmpR-dependent expression of the QS master regulator LasR that controls expression of many virulence factors. Using a chromosomally tagged AmpR, ChIP-Seq studies show direct AmpR binding to the lasR promoter. The data demonstrates that AmpR functions as a global regulator in P. aeruginosa and is a positive regulator of acute virulence while negatively regulating chronic infection phenotypes. In summary, my dissertation sheds light on the complex regulatory circuit in P. aeruginosa to provide a better understanding of the bacterial response to antibiotics and how the organism coordinately regulates a myriad of virulence factors.

No description available.

[pt] Prever com precisão a resposta a drogas para uma dada amostra baseado em características moleculares pode ajudar a otimizar o desenvolvimento de drogas e explicar mecanismos por trás das respostas aos tratamentos. Nessa dissertação, dois estudos de caso foram gerados, cada um aplicando diferentes dados genômicos para a previsão de resposta a drogas. O estudo de caso 1 avaliou dados de perfis de metilação de DNA como um tipo de característica molecular que se sabe ser responsável por causar tumorigênese e modular a resposta a tratamentos. Usando perfis de metilação de 987 linhagens celulares do genoma completo na base de dados Genomics of Drug Sensitivity in Cancer (GDSC), utilizamos algoritmos de aprendizado de máquina para avaliar o potencial preditivo de respostas citotóxicas para oito drogas contra o câncer. Nós comparamos a performance de cinco algoritmos de classificação e quatro algoritmos de regressão representando metodologias diversas, incluindo abordagens tree-, probability-, kernel-, ensemble- e distance-based. Aplicando sub-amostragem artificial em graus variados, essa pesquisa procura avaliar se o treinamento baseado em resultados relativamente extremos geraria melhoria no desempenho. Ao utilizar algoritmos de classificação e de regressão para prever respostas discretas ou contínuas, respectivamente, nós observamos consistentemente excelente desempenho na predição quando os conjuntos de treinamento e teste consistiam em dados de linhagens celulares. Algoritmos de classificação apresentaram melhor desempenho quando nós treinamos os modelos utilizando linhagens celulares com valores de resposta a drogas relativamente extremos, obtendo valores de area-under-the-receiver-operating-characteristic-curve de até 0,97. Os algoritmos de regressão tiveram melhor desempenho quando treinamos os modelos utilizado o intervalo completo de valores de resposta às drogas, apesar da dependência das métricas de desempenho utilizadas. O estudo de caso 2 avaliou dados de RNA-seq, dados estes comumente utilizados no estudo da eficácia de drogas. Aplicando uma abordagem de aprendizado semi-supervisionado, essa pesquisa busca avaliar o impacto da combinação de dados rotulados e não-rotulados para melhorar a predição do modelo. Usando dados rotulados de RNA-seq do genoma completo de uma média de 125 amostras de tumor AML rotuladas da base de dados Beat AML (separados por tipos de droga) e 151 amostras de tumor AML não-rotuladas na base de dados The Cancer Genome Atlas (TCGA), utilizamos uma estrutura de modelo semi-supervisionado para prever respostas citotóxicas para quatro drogas contra câncer. Modelos semi-supervisionados foram gerados, avaliando várias combinações de parâmetros e foram comparados com os algoritmos supervisionados de classificação. / [en] Accurately predicting drug responses for a given sample based on molecular features may help to optimize drug-development pipelines and explain mechanisms behind treatment responses. In this dissertation, two case studies were generated, each applying different genomic data to predict drug response. Case study 1 evaluated DNA methylation profile data as one type of molecular feature that is known to drive tumorigenesis and modulate treatment responses. Using genome-wide, DNA methylation profiles from 987 cell lines in the Genomics of Drug Sensitivity in Cancer (GDSC) database, we used machine-learning algorithms to evaluate the potential to predict cytotoxic responses for eight anti-cancer drugs. We compared the performance of five classification algorithms and four regression algorithms representing diverse methodologies, including tree-, probability-, kernel-, ensemble- and distance-based approaches. By applying artificial subsampling in varying degrees, this research aims to understand whether training based on relatively extreme outcomes would yield improved performance. When using classification or regression algorithms to predict discrete or continuous responses, respectively, we consistently observed excellent predictive performance when the training and test sets consisted of cell-line data. Classification algorithms performed best when we trained the models using cell lines with relatively extreme drug-response values, attaining area-under-the-receiver-operating-characteristic-curve values as high as 0.97. The regression algorithms performed best when we trained the models using the full range of drug-response values, although this depended on the performance metrics we used. Case study 2 evaluated RNA-seq data as one of the most popular molecular data used to study drug efficacy. By applying a semi-supervised learning approach, this research aimed to understand the impact of combining labeled and unlabeled data to improve model prediction. Using genome-wide RNA-seq labeled data from an average of 125 AML tumor samples in the Beat AML database (varying by drug type) and 151 unlabeled AML tumor samples in The Cancer Genome Atlas (TCGA) database, we used a semi-supervised model structure to predict cytotoxic responses for four anti-cancer drugs. Semi-supervised models were generated, while assessing several parameter combinations and were compared against supervised classification algorithms.

Ziel dieser Doktorarbeit ist eine umfassende Untersuchung der Heterogenität von Mikroglia aus morphologischer, elektrophysiologischer und transkriptioneller Perspektive mit dem Schwerpunkt auf Unterschiede zwischen weißer und grauer Substanz. Im ersten Kapitel diskutiere ich die morphologische Heterogenität von Mikroglia mit dem Fokus auf Satelliten- und Parenchymale-Mikroglia. Wir führten eine eingehende Analyse mehrerer Hirnareale durch und quantifizierten die Anzahl der Satellitenmikroglia, die mit verschiedenen neuronalen Subtypen in Kontakt stehen. Wir fanden heraus, dass die Anzahl der Satellitenmikroglia stark mit der neuronalen Dichte eines bestimmten Bereichs korreliert. Im zweiten Kapitel dieser Arbeit untersuche ich die transkriptionelle Heterogenität von Mikroglia aus weißer und grauer Substanz, wobei ich die in Gliazellen neu etablierte Patch-seq-Methode anwende. Diese Methode ermöglicht es eine Kombination aus morphologischen, lektrophysiologischen und transkriptionellen Profilen einzelner Zellen zu erhalten, die es erlauben, zelluläre Unterschiede zu charakterisieren. Wir identifizieren einen zellulären Subtyp, wenn wir den Patch-seq-Datensatz mit FACS-basierter Einzelzell-RNA-seq-Datensätzen vergleichen. Dieser Subtyp gehört eindeutig zu dissoziierten Gewebeproben und ist durch die Expression von Stress-assoziierten Genen charakterisiert. Im dritten Kapitel wende ich mich der Frage zu, wie Transkripte mittels SLAM-seq nachverfolgt werden können, die während der Dissoziation des Gewebes entstehen. Das Verfahren ermöglicht es mRNA, die während der Dissoziation der Probe entsteht, metabolisch zu markieren, rechnerisch zu identifizieren und zu entfernen. Indem wir die markierten Transkripte aus dem Mikroglia “entfernen”, beobachten wir, dass ein „aktivierter Mikroglia“-Subtyp zur allgemeinen Mikroglia-Population gehört. / The aim of this doctoral work is to provide a comprehensive study and overview on the topic of the heterogeneity of microglia in the normal adult mouse brain from the morphological, electrophysiological and transcriptional perspective with the focus on differences between white and grey matters. In the first Chapter, I discuss the morphological heterogeneity of microglia in the brain with the focus on two morphologically distinct classes: satellite and parenchymal microglia. We performed an in-depth analysis of multiple brain areas and quantified the number of satellite microglia which is in contact with different neuronal subtypes. We found that satellite microglia numbers are highly correlated with neuronal densities of a certain area, while showing no preferences for any of the neuronal types. In Chapter two of this work, I study transcriptional heterogeneity of microglia from white and grey matters. For this I am employing Patch-seq, which we newly established in glial cells. This method allows a combination of morphological, electrophysiological and transcriptional profiles of single cells to assess their differences. When comparing Patch-seq dataset to the previously published FACS isolated single cell RNA-seq microglia datasets, we find a subtype of cells which uniquely belongs to FACS sample and is characterized by expression of stress-associated genes. This finding points out to the fact of dissociation-related artifacts in the single cell RNA-seq data which are not present in situ. In the third chapter, I identified transcripts which are induced during the dissociation of the tissue by employing the SLAM-seq method. This procedure allows to metabolically label newly transcribed mRNA and computationally remove transcripts from the sample. By removing the labeled transcripts from the dataset of cells isolated from the hippocampus via enzymatic dissociation, we observe that an “activated microglia” subtype merges with the general microglia population.

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