Classes Alléliques d’Haplotypes et Sélection Positive dans le Génome Humain

L'identification de régions génomiques cibles de la sélection naturelle positive permet de mieux comprendre notre passé évolutif et de trouver des variants génétiques fonctionnels importants. Puisque la fréquence des allèles sélectionnés augmente dans la population, la sélection laisse des traces sur les séquences d'ADN et ces empreintes sont détectées lorsque la variabilité génétique d'une région est différente de celle attendue sous neutralité sélective. On propose une nouvelle approche pour analyser les données de polymorphismes : le calcul des classes alléliques d’haplotypes (HAC), permettant d'évaluer la diversité globale des haplotypes en étudiant leur composition allélique. L'idée de l'approche est de déterminer si un site est sous sélection positive récente en comparant les distributions des HAC obtenues pour les deux allèles de ce site. Grâce à l'utilisation de données simulées, nous avons étudié ces distributions sous neutralité et sous sélection en testant l'effet de différents paramètres populationnels. Pour tester notre approche empiriquement, nous avons analysé la variation génétique au niveau du gène de lactase dans les trois populations inclues dans le projet HapMap.Natural selection eliminates detrimental and favors advantageous phenotypes. This process leaves characteristic signatures in the underlying genomic segments that can be recognized through deviations in the allelic or in haplotypic frequency spectra. We introduce a new way of looking at the genomic single nucleotide polymorphisms : the haplotype allelic classes (HAC). The model combine segregating sites and haplotypic informations in order to reveal useful characteristics of the data, providing an identifiable signature of recent positive selection that can be detected by comparison with the background distribution. We compare the HAC distribution's partition between the haplotypes carrying the selected allele and the remaining ones. Coalescence simulations are used to study the distributions under standard population models assuming neutrality, demographic scenarios and selection models. To test, in practice, the performance of HAC and the derived statistic in capturing deviation from neutrality due to selection, we analyzed the genetic variation in the locus of lactase persistence in the three HapMap populations

Genomic variation in recombination patterns : implications for disease and cancer

Durant la méiose, il se produit des échanges réciproques entre fragments de chromosomes homologues par recombinaison génétique. Les chromosomes parentaux ainsi modifiés donnent naissance à des gamètes uniques. En redistribuant les mutations génétiques pour générer de nouvelles combinaisons, ce processus est à l’origine de la diversité haplotypique dans la population. Dans cette thèse, je présente des résultats décrivant l’implication de la recombinaison méiotique dans les maladies chez l’humain. Premièrement, l'analyse statistique de données de génotypage de familles québécoises démontre une importante hétérogénéité individuelle et sexe-spécifique des taux de recombinaisons. Pour la première fois chez l’humain, nous avons observé que le taux de recombinaison maternel diminue avec l'âge de la mère, un phénomène potentiellement impliqué dans la régulation du taux d’aneuploïdie associé à l’âge maternel. Ensuite, grâce à l’analyse de données de séquençage d’exomes de patients atteints de leucémie et de ceux de leurs parents, nous avons découvert une localisation anormale des évènements de recombinaison chez les enfants leucémiques. Le gène PRDM9, principal déterminant de la localisation des recombinaisons chez l’humain, présente des formes alléliques rares dans ces familles. Finalement, en utilisant un large spectre de variants génétiques identifiés dans les transcriptomes d’individus Canadiens Français, nous avons étudié et comparé le fardeau génétique présent dans les régions génomiques à haut et à faible taux de recombinaison. Le fardeau génétique est substantiellement plus élevé dans les régions à faible taux de recombinaison et nous démontrons qu’au niveau individuel, ce fardeau varie selon la population humaine. Grâce à l’utilisation de données génomiques de pointe pour étudier la recombinaison dans des cohortes populationnelles et médicales, ce travail démontre de quelle façon la recombinaison peut affecter la santé des individus.The intergenerational mixing of DNA through meiotic recombination of homologous chromosomes is, along with mutation, a major mechanism generating diversity and driving the evolution of genomes. In this thesis, I use bioinformatics and statistical approaches to analyse modern genomic data in order to study the implication of meiotic recombination in human disease. First, using high-density genotyping data from French-Canadian families, we studied sex- and age-specific effects on recombination patterns. These analyses lead to the first observation of a significant decrease in recombination rates with advancing maternal age in humans, with potential implications for understanding trisomic conceptions. Second, using next-generation sequencing of exomes from families of children with leukemia, we discovered unusual distributions of recombination breakpoints in some leukemia patients, which implicates PRDM9, a protein involved in defining the location of recombination breakpoints, in leukemogenesis. Third, using single nucleotide polymorphisms (SNPs) called from RNA sequencing data, we present a detailed comparison of the mutational burden between high and low recombining regions in the human genome. We further show that the mutational load in regions of low recombination at the individual level varies among human populations. In analysing genomic data to study recombination in population and disease cohorts, this work improves our understanding of how recombination impacts human health. Furthermore, these results provide insights on how variation in recombination modulates the expression of phenotypes in humans

A family-based probabilistic method for capturing de novo mutations from high-throughput short-read sequencing data

Recent advances in high-throughput DNA sequencing technologies and associated statistical analyses have enabled in-depth analysis of whole-genome sequences. As this technology is applied to a growing number of individual human genomes, entire families are now being sequenced. Information contained within the pedigree of a sequenced family can be leveraged when inferring the donors' genotypes. The presence of a de novo mutation within the pedigree is indicated by a violation of Mendelian inheritance laws. Here, we present a method for probabilistically inferring genotypes across a pedigree using high-throughput sequencing data and producing the posterior probability of de novo mutation at each genomic site examined. This framework can be used to disentangle the effects of germline and somatic mutational processes and to simultaneously estimate the effect of sequencing error and the initial genetic variation in the population from which the founders of the pedigree arise. This approach is examined in detail through simulations and areas for method improvement are noted. By applying this method to data from members of a well-defined nuclear family with accurate pedigree information, the stage is set to make the most direct estimates of the human mutation rate to date

Anti-hyperglycemic effects of aqueous Lenzites betulina extracts from the Philippines on the blood glucose levels of the ICR mice (Mus musculus)

AbstractObjectiveTo examine the anti-hyperglycemic effects of aqueous Lenzites betulina (L. betulina) extracts on normoglycemic glucose-loaded mice.MethodsDifferent doses of aqueous extract from L. betulina were administered to 45 ICR mice (Mus musculus) to determine whether there was an effect of L. betulina extracts on the blood glucose level of the ICR mice. Aqueous extracts of L. betulina were orally gavaged to mice using oral glucose tolerance test. A total of five groups were used to determine the effect of the fungi on blood glucose of the mice. Group A (positive control) was given 16.7 μg/kg glimepiride; Group B (negative control) was given distilled water; Group C (low dosage) was given 200 mg/kg aqueous extract; Group D (mid dosage) was given 400 mg/kg aqueous extract and Group E (high dosage) was given 800 mg/kg aqueous extract. Baseline blood glucose value was firstly acquired before induction of hyperglycemia through d-glucose, after which another check on blood glucose was made after 0.5 h. Immediately, after the acquisition of hyperglycemic blood glucose level, the individual administration of treatments were done. After that, three blood collections were done spanning 3 h with 1 h interval.ResultsThe low dose (200 mg/kg) and the mid dose (400 mg/kg) of L. betulina extracts were significantly different (P < 0.05) from their respective baseline values throughout the whole experiment with the latter surpassing its baseline value during the 3rd hour. On the other hand, the high dose (800 mg/kg) during the 1st hour after administration was not significantly different (P > 0.05) from its corresponding baseline value, acting faster than the positive control (glimepiride), which only became significantly different (P < 0.05) at the 2nd hour.ConclusionsAqueous L. betulina extract is able to produce hypoglycemic effects on the mice with all doses, which are able to normalize blood glucose levels at varying times

Insights into Platypus Population Structure and History from Whole-Genome Sequencing

The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly improved reference genome, we called over 6.7 M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative among other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0 × 10−9/bp/generation (95% CI 4.1 × 10−9–1.2 × 10−8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.We thank the High-Throughput Genomics Group at the Wellcome Centre for Human Genetics (funded by Wellcome Trust grant reference 090532/Z/09/Z) for the generation of sequencing data. This work was supported by a Wellcome Trust Core Award (090532/Z/09/Z) to P.D. and by a University of Sydney StartUp Research grant to J.G

Multicohort analysis of the maternal age effect on recombination

Several studies have reported that the number of crossovers increases with maternal age in humans, but others have found the opposite. Resolving the true effect has implications for understanding the maternal age effect on aneuploidies. Here, we revisit this question in the largest sample to date using single nucleotide polymorphism (SNP)-chip data, comprising over 6,000 meioses from nine cohorts. We develop and fit a hierarchical model to allow for differences between cohorts and between mothers. We estimate that over 10 years, the expected number of maternal crossovers increases by 2.1% (95% credible interval (0.98%, 3.3%)). Our results are not consistent with the larger positive and negative effects previously reported in smaller cohorts. We see heterogeneity between cohorts that is likely due to chance effects in smaller samples, or possibly to confounders, emphasizing that care should be taken when interpreting results from any specific cohort about the effect of maternal age on recombination

A Population Genetic Approach to Mapping Neurological Disorder Genes Using Deep Resequencing

Deep resequencing of functional regions in human genomes is key to identifying potentially causal rare variants for complex disorders. Here, we present the results from a large-sample resequencing (n = 285 patients) study of candidate genes coupled with population genetics and statistical methods to identify rare variants associated with Autism Spectrum Disorder and Schizophrenia. Three genes, MAP1A, GRIN2B, and CACNA1F, were consistently identified by different methods as having significant excess of rare missense mutations in either one or both disease cohorts. In a broader context, we also found that the overall site frequency spectrum of variation in these cases is best explained by population models of both selection and complex demography rather than neutral models or models accounting for complex demography alone. Mutations in the three disease-associated genes explained much of the difference in the overall site frequency spectrum among the cases versus controls. This study demonstrates that genes associated with complex disorders can be mapped using resequencing and analytical methods with sample sizes far smaller than those required by genome-wide association studies. Additionally, our findings support the hypothesis that rare mutations account for a proportion of the phenotypic variance of these complex disorders

Age-dependent recombination rates in human pedigrees.

In humans, chromosome-number abnormalities have been associated with altered recombination and increased maternal age. Therefore, age-related effects on recombination are of major importance, especially in relation to the mechanisms involved in human trisomies. Here, we examine the relationship between maternal age and recombination rate in humans. We localized crossovers at high resolution by using over 600,000 markers genotyped in a panel of 69 French-Canadian pedigrees, revealing recombination events in 195 maternal meioses. Overall, we observed the general patterns of variation in fine-scale recombination rates previously reported in humans. However, we make the first observation of a significant decrease in recombination rates with advancing maternal age in humans, likely driven by chromosome-specific effects. The effect appears to be localized in the middle section of chromosomal arms and near subtelomeric regions. We postulate that, for some chromosomes, protection against non-disjunction provided by recombination becomes less efficient with advancing maternal age, which can be partly responsible for the higher rates of aneuploidy in older women. We propose a model that reconciles our findings with reported associations between maternal age and recombination in cases of trisomies