La maladie d’Alzheimer est une maladie neurodégénérative, elle représente 70% des formes de démences et affecte près de 860 000 personnes en France. Cette maladie est caractérisée par deux lésions neuropathologiques : les Dégénérescences neurofibrillaires et les Plaques séniles. Ces dernières sont principalement constituées de peptides amyloïdes (A&#946;) résultant du clivage d’une protéine membranaire appelée Précurseur du peptide amyloïde (APP). L’étude des formes familiales monogéniques a montré que des mutations des gènes de l’APP et des Présénilines 1 et 2 conduisaient systématiquement à une augmentation de la production d’A&#946;. Cette observation a permis l’élaboration de la cascade amyloïde plaçant le métabolisme de l’APP au centre du processus physiopathologique. Même si aujourd’hui ce métabolisme commence à être relativement bien connu, plusieurs zones d’ombres subsistent encore. Dans l’optique de caractériser de nouveaux acteurs intervenant dans ce métabolisme, nous avons émis une hypothèse qui repose sur deux constatations : (i) les protéines impliquées dans l’étiologie de la maladie sont différentiellement exprimées entre les cerveaux des patients et ceux des témoins (ii) dans le cerveau, de nombreuses métalloprotéases participent aux même mécanismes que l’APP (adhésion cellulaire, neuroinflammation, plasticité neuronale...), certaines sont aussi directement actrices du métabolisme de l’APP en tant qu’&#945;-sécrétase (ADAM9, ADAM10 et ADAM17) ou en dégradant l’A&#946; (NEP, IDE, MMP2, MMP3 et MMP9). Nous avons donc supposé que les métalloprotéases présentant une différence d’expression entre le tissu cérébral des malades et celui des témoins soient des candidates intéressantes pour moduler le métabolisme et le trafic de l’APP. Une première analyse transcriptomique par biopuce, à partir d’ARN totaux issus des cerveaux de 12 malades et de 12 témoins, nous a permis d’identifier quatre métalloprotéases présentant une différence d’expression significative (p<10-5) : ADAMTS16, ADAM17, ADAM30 et ADAM33. Nous avons cherché à confirmer ce résultat par une autre technologie sur un plus grand nombre d’échantillons (malades n=52 et témoins n=42). Seules ADAM30 et ADAM33 ont pu être validées. Nous avons également pu observer que l’expression d’ADAM30 dans le tissu cérébral des malades est inversement proportionnelle à la quantité d’A&#946;42 déposée dans la parenchyme (A&#946;42 la forme d’A&#946; la plus neurotoxique). De plus, au niveau cérébral, l’expression d’ADAM30 est restreinte aux neurones, cellules sièges du métabolisme de l’APP. Nous avons donc sélectionné ADAM30 comme intervenante potentielle dans le métabolisme de l’APP. Pour tester notre hypothèse, nous avons sous- et sur-exprimé ADAM30 dans deux modèles cellulaires différents. Nous avons mis en évidence que la sur-expression d’ADAM30 entraîne une diminution de l’ensemble des produits du métabolisme de l’APP. En mutant le site catalytique de cette protéase, nous avons remarqué que cette action sur le métabolisme de l’APP est dépendante de cette activité catalytique. De manière cohérente, une sous-expression d’ADAM30 entraîne une augmentation de l’ensemble des produits du métabolisme de l’APP. En utilisant les inhibiteurs alcalisant, nous avons démontré que l’effet d’ADAM30 sur le métabolisme de l’APP met en jeu la dégradation par le lysosome. Des expériences d’immunofluorescence ont attesté qu’ADAM30 est localisée dans le réticulum endoplasmique et l’appareil de Golgi et qu’elle co-localise fortement avec l’APP dans ces organites. Au vu des résultats obtenus durant ces quatre années, nous pensons qu’ADAM30 pourrait être une protéine clé de la régulation de l’APP en inhibant son acheminement jusqu’à la membrane plasmique et en favorisant sa dégradation par le lysosome. [...] / Alzheimer’s disease (AD) is the most common neurodegenerative disorder of the old age, characterized by the presence of two major neuropathological features : neurofibrillary tangles and senile plaques. These plaques are composed of the A&#946; peptides cleavage product of the amyloid precursor protein (APP). Proteolytic processing of APP is modulated by the action of enzymes &#945;-, &#946;- and &#947;-secretases with the latter two mediating the amyloidogenic pathway. Suggesting that processing of APP is a key step in the pathology of AD. However, even if extensively studied, this APP metabolism is still not fully characterized. With this background, we postulate that the characterization of new actors of the APP metabolism might help for a more subtle understanding of this APP metabolism and trafficking. We focused on the ADAMs and related proteins with the hypothesis that ADAMs and related proteins, under- or over-expressed in the brain of AD cases compared with the one of controls, may be of particular interest. Beyond the obvious implication of several ADAMs as &#945;-secretases, this hypothesis was also driven by several observations : (i) ADAMs have been involved in numerous biological processes including brain development, plasticity and repair as APP; (ii) several metalloproteases (MMP-2, -3 and -9) have been described to degrade A&#946; peptides. Using microarray to screen the expression of 117 ADAMs and MMPs was analyzed using total RNA extracted from cerebral tissue of 12 AD cases and 12 controls. We observed that 4 ADAMs were differentially expressed. We first confirmed that the ADAM30 expression was decreased in AD brains and we observed that ADAM30 under-expression was correlated with an increase in A&#946;42 deposition in AD brains. Consistently, over-expression of ADAM30 led to decrease APP metabolism and as a consequence, A&#946; secretion in two different cell lines (Moreover, under-expressed ADAM30 increases APP processing and A&#946; generation). This modification of the APP metabolism was directly linked to the ADAM30 catalytic properties. Our data suggest that catalytic activity of ADAM30 takes an important place in APP processing in a lysosome dependent manner and AD pathophysiological process.

<p>Linkage in the 2q37 region was evaluated using microsatellite markers in multi-case families from Sweden, Iceland and Norway. Both the two-point and the multipoint linkage analysis show highly significant LOD scores (Z=4.51 and 6.03, respectively). Linkage disequilibrium mapping indicates that some association exists in this region. The <i>PDCD1</i> gene was suggested as a candidate gene within the 2q37 locus due to its importance in immune regulation. Indeed, one haplotype, described by the presence of allele A of the PD1.3 SNP located within intron 4 of this gene, shows linkage to SLE in the Nordic families. The PD1.3A allele is also found to be strongly associated in familiar and sporadic cases of SLE in Europeans and Mexicans. Functional studies further support PD1.3A to be a susceptibility allele for SLE.</p><p>The 1q23 region, containing the genes for the low affinity Fcγ receptors, was fine mapped using single- and multi- case families of various origins. Genetic variants of those genes were analysed and association is found to both the risk alleles of <i>Fc</i>γ<i>RIIA</i> and <i>Fc</i>γ<i>RIIIA</i> in all families. In these families, a single haplotype carrying both risk alleles is predominantly transmitted to patients with SLE, suggesting a presence of linkage disequilibrium between those two genes. <i>Fc</i>γ<i>RIIA</i> and <i>Fc</i>γ<i>RIIIA</i> are also found to be associated to SLE and lupus nephritis in a case-control cohort from Sweden. In the same cohort, the PD1.3A allele shows strong association to lupus nephritis. We suggest that there may be an additive effect between <i>Fc</i>γ<i>RIIA</i> and <i>PDCD1</i>, since having the disease-associated genotypes at both loci gives an increased risk for developing lupus nephritis.</p><p>Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disorder with a complex multifactorial aetiology. Genetic studies suggest that several genes are involved in disease pathogenesis and that extended genetic heterogeneity is present.</p>

<p>The aim of this thesis has been to identify genes and gene regions underlying four different disorders. In papers I-IV, positional cloning methods, such as linkage, association and haplotype analysis have been used for the identification of genomic regions associated with the ichthyosis prematurity syndrome (IPS), adult-onset autosomal dominant leukodystrophy (ADLD) and Kostmann disease. </p><p>IPS is a rare autosomal recessive skin disorder, which includes a premature birth of the affected child. We mapped the IPS locus to a region on chromosome 9q34, and within this region a haplotype is shared by IPS patients, which suggests a strong founder effect. The haplotype spans 76 kb, which includes four known genes. No sequence or mRNA expression alterations could be detected for the four genes in IPS patients. </p><p>A candidate region for an adult-onset leukodystrophy (ADLD) on chromosome 5 was investigated in a large Swedish family with ADLD. A significant multipoint LOD score of 9.45 was obtained for markers in the chromosome 5 region and fine-mapping of recombination events restricts a candidate gene region to 1.5 Mb. </p><p>Kostmann disease is an autosomal recessive form of severe congenital neutropenia. We have identified a 1.2 Mb region on chromosome 1q22 associated with the disease in the original Kostmann family. The region contains 37 genes.</p><p>In paper V, cDNA microarrays were used to asses the mRNA levels of 7,700 genes in lymphoblastoid cell lines derived from autistic and control samples. The <i>SEMA5A</i> gene, which is involved in axonal guidance, was found downregulated in the cells derived from autistic individuals, and this was confirmed by quantitative PCR. </p><p>In summary, candidate genes or gene regions have been identified for all four disorders and further studies are needed to confirm their roles in the pathogenesis of the disorders. </p>

Linkage in the 2q37 region was evaluated using microsatellite markers in multi-case families from Sweden, Iceland and Norway. Both the two-point and the multipoint linkage analysis show highly significant LOD scores (Z=4.51 and 6.03, respectively). Linkage disequilibrium mapping indicates that some association exists in this region. The PDCD1 gene was suggested as a candidate gene within the 2q37 locus due to its importance in immune regulation. Indeed, one haplotype, described by the presence of allele A of the PD1.3 SNP located within intron 4 of this gene, shows linkage to SLE in the Nordic families. The PD1.3A allele is also found to be strongly associated in familiar and sporadic cases of SLE in Europeans and Mexicans. Functional studies further support PD1.3A to be a susceptibility allele for SLE. The 1q23 region, containing the genes for the low affinity Fcγ receptors, was fine mapped using single- and multi- case families of various origins. Genetic variants of those genes were analysed and association is found to both the risk alleles of FcγRIIA and FcγRIIIA in all families. In these families, a single haplotype carrying both risk alleles is predominantly transmitted to patients with SLE, suggesting a presence of linkage disequilibrium between those two genes. FcγRIIA and FcγRIIIA are also found to be associated to SLE and lupus nephritis in a case-control cohort from Sweden. In the same cohort, the PD1.3A allele shows strong association to lupus nephritis. We suggest that there may be an additive effect between FcγRIIA and PDCD1, since having the disease-associated genotypes at both loci gives an increased risk for developing lupus nephritis. Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disorder with a complex multifactorial aetiology. Genetic studies suggest that several genes are involved in disease pathogenesis and that extended genetic heterogeneity is present.

The aim of this thesis has been to identify genes and gene regions underlying four different disorders. In papers I-IV, positional cloning methods, such as linkage, association and haplotype analysis have been used for the identification of genomic regions associated with the ichthyosis prematurity syndrome (IPS), adult-onset autosomal dominant leukodystrophy (ADLD) and Kostmann disease. IPS is a rare autosomal recessive skin disorder, which includes a premature birth of the affected child. We mapped the IPS locus to a region on chromosome 9q34, and within this region a haplotype is shared by IPS patients, which suggests a strong founder effect. The haplotype spans 76 kb, which includes four known genes. No sequence or mRNA expression alterations could be detected for the four genes in IPS patients. A candidate region for an adult-onset leukodystrophy (ADLD) on chromosome 5 was investigated in a large Swedish family with ADLD. A significant multipoint LOD score of 9.45 was obtained for markers in the chromosome 5 region and fine-mapping of recombination events restricts a candidate gene region to 1.5 Mb. Kostmann disease is an autosomal recessive form of severe congenital neutropenia. We have identified a 1.2 Mb region on chromosome 1q22 associated with the disease in the original Kostmann family. The region contains 37 genes. In paper V, cDNA microarrays were used to asses the mRNA levels of 7,700 genes in lymphoblastoid cell lines derived from autistic and control samples. The SEMA5A gene, which is involved in axonal guidance, was found downregulated in the cells derived from autistic individuals, and this was confirmed by quantitative PCR. In summary, candidate genes or gene regions have been identified for all four disorders and further studies are needed to confirm their roles in the pathogenesis of the disorders.

Choosing with whom to mate is one of the most important decisions a female makes in her lifetime and inter-individual variation of these preferences can have important evolutionary consequences. In order to get a complete understanding of why and how females choose a mate, we must identify factors that can contribute to variation of female mate choice. Many decades of research sought to understand ultimate mechanisms of female mate choice with proximate mechanisms receiving a lot more attention in recent years. For my thesis, I identify intrinsic and extrinsic factors that correlate with individual variation of female Xiphophorus nigrensis mate preference. I provide evidence that a female’s size (e.g. age and sexual experience) as well as male behavioral displays can predict female mate preference. Using genes associated with female mate preference (neuroserpin, neurologin-3), I identify four brain regions (Dl, Dm, HV, POA) that show significant differences in gene expression between females exhibiting high preference for males relative to females displaying little mate preference. Neuroserpin and neuroligin-3 gene expression within these brain regions are also positively correlated with female mate preference behavior. Two of these brain regions (Dm and Dl) integrate multisensory information and are found in the putative teleost mesolimbic reward circuitry; the other two regions (HV and POA) are involved in sexual behaviors. With the implication of the reward circuitry, I assess whether there are changes in dopamine synthesis (via tyrosine hydroxylase, TH) in dopaminergic brain regions associated with the degree of mate preference. I do not find evidence of rapid changes (within 30 minutes) of TH expression (i.e. dopamine synthesis) in dopaminergic brain regions related to variation in female mate preference. Collectively my results suggest that mate preference behavior in the brain may be coordinated not just through regions associated with sexual response but also through forebrain areas that may integrate primary sensory information, with no associated changes of a proxy for dopamine synthesis in dopaminergic brain regions. / text

The cost of feed remains an important factor affecting the profitability of beef production, and the difficulty of recording feed intake is a major limitation in an industry-wide selection program. Novel genomics approaches offer opportunities to select for efficient cattle. Therefore, the main objective of this work was to identify genetic markers responsible for genetic variation in feed efficiency traits as well as to understand the molecular basis of feed efficiency traits. The candidate gene approach revealed new single nucleotide polymorphisms (SNPs) in the Cholecystokinin B receptor (CCKBR) and pancreatic anionic trypsinogen (TRYP8) genes that showed strong evidence of association with feed efficiency traits. An in silico approach was proposed as a cost-effective method for SNP discovery. SNPs within genes Pyruvate carboxylase, ATPaseH+, UBQEI, UCP2, and PTI showed evidence of association with carcass traits without negatively affecting feed efficiency traits. The polymorphisms within genes CCKBR and TRYP8 were associated with pancreas mass and pancreatic exocrine secretion. A fine-mapping study on 1,879 SNPs revealed 807 SNPs with significant associations corresponding to 1,012 genes. These 807 SNPs represented a genomic heritability of 0.32 and 89% of the genetic variance of residual feed intake (RFI). Genomic breeding values estimated from the SNP set (807) were highly correlated (0.96) to the breeding values estimated from a mixed animal model. The 10 most influential SNPs were located in chromosomes 16, 17, 9, 11, 12, 20, 15, and 19. Enrichment analysis for the identified genes (1,012) suggested 110 biological processes and 141 pathways contributed to variation in RFI. The 339 newly identified SNPs corresponding to 180 genes identified by fine-mapping were tested for association with feed efficiency, growth, and carcass traits. Strong evidence of associations for RFI was located on chromosomes 8, 15, 16, 18, 19, 21, and 28. Combing validated SNPs from fine-mapping and the candidate gene approach may help develop a DNA test panel for commercial use and increase our understanding of the biological basis of feed efficiency in beef cattle. / The Ministry of Higher Education of Egypt

No description available.

A candidate gene approach was used to identify single nucleotide polymorphisms (SNPs) and their associations with body fat deposition and carcass merit traits in beef cattle. In total, 37 SNPs from 9 candidate genes have been genotyped on 463 hybrid, 206 Angus and 187 Charolais steers for association analyses with 10 different fat deposition and carcass merit traits. In single SNP analyses, 28 SNPs of 9 genes have been found significantly (P<0.05) associated with different traits in the cattle populations. Gene-specific linkage disequilibrium assessment of SNPs revealed the existence of haplotype blocks within 4 genes. Haplotype analyses have identified 31 haplotypes of 6 genes having significant associations (P<0.05) with different fat deposition and carcass merit traits in the cattle populations. These findings will provide insight into the genetic mechanism regulating body fat deposition in beef cattle and will assist the beef industry to improve beef quality through marker assisted selection. / Animal Science

Physicians frequently face challenges in predicting which bacterial subpopulations are likely to cause severe infections. A more accurate prediction of virulence would improve diagnostics and limit the extent of antibiotic resistance. Nowadays, bacterial pathogens can be typed with high accuracy with advanced genotyping technologies. However, effective translation of bacterial genotyping data into assessments of clinical risk remains largely unexplored. The discovery of unknown virulence genes is another key determinant of successful prediction of infectious disease outcomes. The trial-and-error method for virulence gene discovery is time-consuming and resource-intensive. Selecting candidate genes with higher precision can thus reduce the number of futile trials. Several in silico candidate gene prioritisation (CGP) methods have been proposed to aid the search for genes responsible for inherited diseases in human. It remains uninvestigated as to how the CGP concept can assist with virulence gene discovery in bacterial pathogens. The main contribution of this thesis is to demonstrate the value of translational bioinformatics methods to address challenges in virulence prediction and virulence gene discovery. This thesis studied an important perinatal bacterial pathogen, group B streptococcus (GBS), the leading cause of neonatal sepsis and meningitis in developed countries. While several antibiotic prophylactic programs have successfully reduced the number of early-onset neonatal diseases (infections that occur within 7 days of life), the prevalence of late-onset infections (infections that occur between 7??30 days of life) remained constant. In addition, the widespread use of intrapartum prophylactic antibiotics may introduce undue risk of penicillin allergy and may trigger the development of antibiotic-resistant microorganisms. To minimising such potential harm, a more targeted approach of antibiotic use is required. Distinguish virulent GBS strains from colonising counterparts thus lays the cornerstone of achieving the goal of tailored therapy. There are three aims of this thesis: 1. Prediction of virulence by analysis of bacterial genotype data: To identify markers that may be associated with GBS virulence, statistical analysis was performed on GBS genotype data consisting of 780 invasive and 132 colonising S. agalactiae isolates. From a panel of 18 molecular markers studied, only alp3 gene (which encodes a surface protein antigen commonly associated with serotype V) showed an increased association with invasive diseases (OR=2.93, p=0.0003, Fisher??s exact test). Molecular serotype II (OR=10.0, p=0.0007) was found to have a significant association with early-onset neonatal disease when compared with late-onset diseases. To investigate whether clinical outcomes can be predicted by the panel of genotype markers, logistic regression and machine learning algorithms were applied to distinguish invasive isolates from colonising isolates. Nevertheless, the predictive analysis only yielded weak predictive power (area under ROC curve, AUC: 0.56??0.71, stratified 10-fold cross-validation). It was concluded that a definitive predictive relationship between the molecular markers and clinical outcomes may be lacking, and more discriminative markers of GBS virulence are needed to be investigated. 2. Development of two computational CGP methods to assist with functional discovery of prokaryotic genes: Two in silico CGP methods were developed based on comparative genomics: statistical CGP exploits the differences in gene frequency against phenotypic groups, while inductive CGP applies supervised machine learning to identify genes with similar occurrence patterns across a range of bacterial genomes. Three rediscovery experiments were carried out to evaluate the CGP methods: a) Rediscovery of peptidoglycan genes was attempted with 417 published bacterial genome sequences. Both CGP methods achieved their best AUC >0.911 in Escherichia coli K-12 and >0.978 Streptococcus agalactiae 2603 (SA-2603) genomes, with an average improvement in precision of >3.2-fold and a maximum of >27-fold using statistical CGP. A median AUC of >0.95 could still be achieved with as few as 10 genome examples in each group in the rediscovery of the peptidoglycan metabolism genes. b) A maximum of 109-fold improvement in precision was achieved in the rediscovery of anaerobic fermentation genes. c) In the rediscovery experiment with genes of 31 metabolic pathways in SA-2603, 14 pathways achieved an AUC >0.9 and 28 pathways achieved AUC >0.8 with the best inductive CGP algorithms. The results from the rediscovery experiments demonstrated that the two CGP methods can assist with the study of functionally uncategorised genomic regions and the discovery of bacterial gene-function relationships. 3. Application of the CGP methods to discover GBS virulence genes: Both statistical and inductive CGP were applied to assist with the discovery of unknown GBS virulence factors. Among a list of hypothetical protein genes, several highly-ranked genes were plausibly involved in molecular mechanisms in GBS pathogenesis, including several genes encoding family 8 glycosyltransferase, family 1 and family 2 glycosyltransferase, multiple adhesins, streptococcal neuraminidase, staphylokinase, and other factors that may have roles in contributing to GBS virulence. Such genes may be candidates for further biological validation. In addition, the co-occurrence of these genes with currently known virulence factors suggested that the virulence mechanisms of GBS in causing perinatal diseases are multifactorial. The procedure demonstrated in this prioritisation task should assist with the discovery of virulence genes in other pathogenic bacteria.