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Adhesion G-protein coupled receptors (GPCRs) are the second largest class of GPCRs, yet their functions and ligands remain predominantly unidentified. Polymorphisms in the gene encoding the adhesion GPCR latrophilin 3 (ADGRL3) have been associated with an increased risk for attention deficit hyperactivity disorder (ADHD) and substance use disorder (SUD) in various linkage and association studies. Disrupting the function of ADGRL3 homologs across mammalian and invertebrate model systems leads to changes in various dopaminergic phenotypes such as hyperactivity, sleep impairment, and changes in sensitivity to psychostimulants, suggesting that ADGRL3 contributes to behavior by modulating dopamine signaling. Here, I use behavioral and imaging studies to delineate an important role for Cirl, the Drosophila homolog of ADGRL3, in a recently characterized dopaminergic sleep circuit. Sleep impairment is a common symptom in both SUD and ADHD, and sleep studies are well established in Drosophila. Our work shows that fruit flies that carry a null mutation for Cirl are hyperactive and display a deficit in sleep that is enhanced by adult thermogenetic activation of dopamine neurons. Though Cirl displays high expression within dopamine neurons, conditional knockout of Cirl in dopamine neurons does not recapitulate sleep deficits seen in Cirl null flies, and specific rescue of Cirl in a knockout background does not ameliorate them. Intriguingly, activating dopamine neurons in Cirl null flies throughout development rescued the sleep deficits, indicating that this dopaminergic intervention induces lasting changes that can ameliorate lack of Cirl function. Imaging studies reveal that Cirl shows high expression in the central complex, which is involved in sleep and receives dense dopaminergic input. I demonstrate that Cirl functions within different populations of the central complex downstream of dopaminergic innervation to differentially affect night and daytime sleep through both dopaminergic and non-dopaminergic mechanisms. This work delineates a novel role for an adhesion GPCR in modulating sleep behavior, and further characterizes ADGRL3 as a potential therapeutic target for disorders characterized by dysregulation of dopaminergic neurotransmission.

This study is primarily concerned with assessing the influence of the sex determination genes, transformer (tra), doublesex (dsx) and fruitless (fru) on three sexually dimorphic traits within Drosophila; pheromone blend, courtship song and sex comb tooth number. The sex determination loci have all been implicated as possible candidate genes affecting these important traits that contribute to sexual isolation, which is a major cause of speciation. Quantitative Trait Loci (QTL) analysis is used to assess the effects of these known candidate genes on the naturally occurring variation of mean interpulse interval (IPI) of courtship song and the differing pheromone blend profiles between Drosophila simulans and D. sechellia. The QTL analysis for both song and pheromone blend variation incorporated Multiple Interval Mapping (MIM), which enables the detection for epistasis. The desaturase loci desat1, desat2 and desatF were also included in the assessment on pheromone blends (cuticular hydrocarbon compounds), since they facilitate ecological adaptation and are also candidate genes, which are likely to exert a large affect on this particular trait. The sex determination genes were not significantly influential on the interspecific variation of the cuticular hydrocarbon compounds between these two sibling species. However significant effects were detected from two of the desaturase loci. desat1 was associated with a strong effect on the interspecific variation of a saturated hydrocarbon chain compound (unbranched-23). Additionally the candidate gene desatF potentially exerts an influence on the variation of 7,11-heptacosadiene, through a large epistatic effect with unidentified loci, situated between the markers pros and Mtn. The candidate gene eloF is situated in this region, and is known to affect the elongation of unsaturated hydrocarbon chains. The QTL associated with the marker desatF influenced the variation of both diene compounds (7,11-heptacosadiene and 7,11-pentacosadiene). Intriguingly epistasis was only detected for the variation of these two diene compounds. The MIM analysis assessing the affects of the sex determination genes on interspecific variation of mean IPI detected the candidate gene fru as the closest marker associated with a significant QTL on the third chromosome. The MIM also found a significant QTL associated with the marker Dgα situated on the second chromosome. Moreover significant epistatic interactions were detected between a further QTL situated nearest the marker forked on the X-chromosome with both of the other significant QTL situated on the third and second chromosomes. The analysis of a number of Recombinant Inbred (RI) lines was also carried out to test for the affects of the sex determination genes on both mean IPI and sex comb tooth number. The fru locus was associated with a significant increase in mean IPI, whereas the opposite was true for the dsx locus. In the analysis of sex comb tooth variation, it appears that all RI lines homozygous for D. sechellia alleles at the sex determination loci had significantly higher numbers of sex comb teeth. The final data chapter involves the sequence analysis of the fruitless locus, including all 13 fru proteins between ten recently sequenced Drosophilid genomes. The PAML program was used to detect the possible influence of natural selection on sequence divergence. There was no significant positive selection detected at the BTB functional domain and the sequences encoding for this domain were extremely conserved. Positive selection was found to be acting on the exon encoding for the Zinc-finger C domain. This domain is present in two protein isoforms including the male sex-specific isoform FRUMC, and the common non-sex-specific isoform FRUComC. Interestingly positive selection was also found at the non sex-specific Zinc-finger D domain.

The imbalance in the levels of certain microRNAs (miRNAs) in Alzheimer’s disease (AD) brains promotes alterations in tau proteostasis and neurodegeneration. However, potential mechanisms governing how specific miRNAs are dysregulated in AD brains are still under investigation. Epitranscriptomics is a mode of post-transcriptional regulation that can control brain functions during development and adulthood. NOP2/Sun RNA methyltransferase 2 (NSun2) is one of the few known brain-enriched methyltransferases that has the ability to modify mammalian non-coding RNAs. Importantly, autosomal-recessive loss of function mutations in NSun2 have been associated with neurological abnormalities in humans. Here, we report that dysregulation of NSun2 can induce alterations in tau phosphorylation by modulating the levels of miR-125b, a main player in tau pathology. We were able to provide supporting evidence by utilizing several model systems such as Drosophila, human induced pluripotent stem cell (iPSC) derived neurons, rat primary neuronal cultures and mice. Our Western blot analysis not only shows that NSun2 is expressed in adult human neurons in the hippocampal formation and prefrontal cortex, but also NSun2 protein expression levels are downregulated in post-mortem brain tissues from AD patients. Remarkably, we also found decreased NSun2 protein levels in AD mice and human cellular models. To prove these observed alterations were unique to AD, we further evaluated brain tissues from other tauopathies. Strikingly, NSun2 protein levels were similar between tauopathy cases and controls indicating that dysregulation of NSun2 might be unique to AD cases. Further, we investigated the pathological role of NSun2 by utilizing a well-established Drosophila melanogaster model of tau-induced toxicity. We found that a reduction of NSun2 protein levels exacerbated tau toxicity while overexpression of NSun2 partially abrogated toxicity proving bidirectionality. We used a lentiviral system to knock down NSun2 expression in iPSC derived neuronal cultures. Western blot analysis and immunofluorescence staining showed a significant change in tau phosphorylation levels. To investigate what could be triggering observed alterations in NSun2 levels, we performed experiments in rat primary hippocampal neurons. We found that the treatment with oligomeric amyloid-beta A caused a decrease in NSun2 protein levels and at the same time, increased tau phosphorylation levels in primary hippocampal neurons. Lastly, we performed RNA immunoprecipitation coupled with qPCR and histological analysis using NSun2 conditional knockout (KO) mice and observed that NSun2 deficiency promoted aberrant levels of m6A methylated miR-125b and tau hyperphosphorylation. Altogether, our study demonstrates that neuronal NSun2 deficiency in AD promotes neurodegeneration by altering tau phosphorylation and tau toxicity through an epitranscriptomic regulatory mechanism and highlights a potential novel therapeutic target.

Cette thèse de doctorat s’inscrit dans le développement et l’utilisation de méthodes mathématiques et informatiques qui exploitent les données temporelles d’expression des gènes issues de puces à ADN afin de rationaliser et de modéliser les réseaux de régulation génique. Dans cette optique, nous nous sommes principalement intéressés aux données d’expression des gènes de la drosophile (Drosophila melanogaster) pendant son développement, du stade embryonnaire au stade adulte. Nous avons également étudié des données concernant le développement d’autres eucaryotes supérieurs, la réponse d’une bactérie soumises à différents stress et le cycle cellulaire d’une levure. Ce travail a été réalisé selon trois volets principaux :la détection des stades de développement et des perturbations, les classifications de profils d’expression et la modélisation de réseaux de régulation.<p><p>Premièrement, l’observation des données d’expression utilisées nous a conduits à approfondir l’étude des phénomènes survenant lors des changements de stades de développement de la drosophile. Dans ce but, deux méthodes de détection automatique de ces changements ont été développées et appliquées aux données temporelles disponibles sur le développement d’eucaryotes supérieurs. Elles ont également été appliquées à des données temporelles relatives à des perturbations externes de bactéries. Cette étude à montré qu’une formulation mathématique simple permettait de retrouver les instants expérimentaux où une perturbation ou un changement de stade de développement est observé, à partir uniquement des profils d’expression. Par ailleurs, la réponse à une perturbation externe s’avère non distinguable d’une succession de stades de développement, sur la base des seuls profils temporels d’expression.<p><p>Deuxièmement, en raison des dimensions du problème constitué par les données d’expression de plusieurs milliers de gènes et de l’impossibilité de distinguer le rôle dans la régulation des gènes qui présentent des profils d’expression similaires, il s’est avéré nécessaire de classifier les gènes selon leurs profils d’expression. En nous basant sur les résultats obtenus lors de la détection des stades de développement, la démarche suivie est de regrouper les gènes qui présentent des profils temporels d’expression aux comportements similaires non seulement au cours de la série temporelle complète, mais également dans chacun des stades de développement. Dans cette optique, trois distances ont été proposées et utilisées dans une classification hiérarchique des données d’expression de la drosophile.<p><p>Troisièmement, des structures de modèles linéaires et non linéaires ainsi que des méthodes d’estimation et de réduction paramétriques ont été développées et utilisées pour reproduire les données d’expression du développement de la drosophile. Les résultats de ce travail ont montré qu’avec une structure de modèle linéaire simple, la reproduction des profils expérimentaux était excellente et que, dans ce cas, le réseau de régulation génique de la drosophile pouvait se contenter d’une faible connectivité (en moyenne 3 connexions par classe de gènes) et ce, sans hypothèse a priori. Toutefois, les modèles linéaires ont ensuite sérieusement été remis en question par des analyses de robustesse aux perturbations paramétriques et de stabilité des profils après extrapolation dans le temps. Dès lors, quatre structures de modèles non linéaires et cinq méthodes de réduction paramétrique ont été proposées et utilisées pour concilier les critères de reproduction des données, de robustesse et de stabilité des réseaux identifiés. En outre, ces méthodes de modélisation ont été appliquées à un sous-ensemble de 20 gènes impliqués dans le développement musculaire de la drosophile et pour lesquels 36 interactions ont été validées expérimentalement, ainsi qu’à des profils synthétiques bruités. Nous avons pu constater que plus de la moitié des connexions et non-connexions sont retrouvées par trois modèles non linéaires. Les résultats de cette étude ont permis d’éliminer certaines structures de modèle et méthodes de réduction et ont mis en lumière plusieurs directions futures à suivre dans la démarche de modélisation des réseaux de régulation génique. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished