Introduction/Background: Guidelines from the World Health Organization currently recommend targeting a body mass index (BMI) between 18.5 and 24.9 kg/m2 based on the lowest risk of mortality observed in epidemiological studies. However, these recommendations are based on population observations and do not take into account potential inter-individual differences. We hypothesized that genetic and non-genetic differences in adiposity, anthropometric, and metabolic measures result in inter-individual variation in the optimal BMI. Methods: Genetic variants associated with BMI as well as related adiposity, anthropometric, and metabolic phenotypes (e.g. triglyceride (TG)) were combined into polygenic risk scores (PRS), cumulative risk scores derived from the weighted contributions of each variant. 387,692 participants in the UK Biobank were split by quantiles of PRS or clinical biomarkers such as C-reactive protein (CRP), and alanine aminotransferase (ALT). The BMI linked with the lowest risk of all-cause and cause-specific mortality outcomes (“nadir value”) was then compared across quantiles (“Cox meta-regression model”). Our results were replicated using the non-linear mendelian randomization (NLMR) model to assess causality. Results: The nadir value for the BMI–all-cause mortality relationship differed across percentiles of BMI PRS, suggesting inter-individual variation in optimal BMI based on genetics (p = 0.005). There was a difference of 1.90 kg/m2 in predicted optimal BMI between individuals in the top and bottom 5th BMI PRS percentile. Individuals having above and below median TG (p = 1.29×10-4), CRP (p = 7.92 × 10-5), and ALT (p = 2.70 × 10-8) levels differed in nadir for this relationship. There was no difference in the computed nadir between the Cox meta-regression or NLMR models (p = 0.102). Conclusions: The impact of BMI on mortality is heterogenous due to individual genetic and clinical biomarker level differences. Although we cannot confirm that are results are causal, genetics and clinical biomarkers have potential use for making more tailored BMI recommendations for patients. / Thesis / Master of Science (MSc) / The World Health Organization (WHO) recommends targeting a body mass index (BMI) between 18.5 - 24.9 kg/m2 for optimal health. However, this recommendation does not take into account individual differences in genetics or biology. Our project aimed to determine whether the optimal BMI, or the BMI associated with the lowest risk of mortality, varies due to genetic or biological variation. Analyses were conducted across 387,692 individuals. We divided participants into groups according to genetic risk for obesity or clinical biomarker profile. Our results show that the optimal BMI varies according to genetic or biomarker profile. WHO recommendations do not account for this variation, as the optimal BMI can fall under the normal 18.5 - 24.9 kg/m2 or overweight 25.0 – 29.0 kg/m2 WHO BMI categories depending on individual genetic or biomarker profile. Thus, there is potential for using genetic and/or biomarker profiles to make more precise BMI recommendations for patients.

No description available.

Bermudagrass (Cynodon spp.) breeding and cultivar development is hampered by limited information regarding its genetic and phenotypic diversity. A germplasm collection of 206 bermudagrass accessions from 29 countries was genotyped with high-throughput genotyping-by-sequencing technique. Genomic diversity in this diverse germplasm panel was assessed with multifaceted approaches including population structure, phylogenetic analysis, principal component analysis, and genetic diversity parameters. This study revealed substantial genetic variation in the Cynodon accessions, demonstrating the potential of this germplasm panel for further genetic studies and cultivar development in breeding programs. Another critical issue in turfgrass breeding is the lack of information regarding the genetic architecture of traits. Four agronomic traits leaf length, leaf width, internode distance and stem diameter were evaluated in a germplasm panel of common bermudagrass accessions. Then genome-wide association study was performed to dissect the genetic basis of the traits.

Flax (Linum usitatissimum L.) is a self-pollinated crop widely cultivated for fiber and oil production. Flaxseed is renowned for its health attributes but the presence of compounds, such as the heavy metal cadmium (Cd), is undesirable. Genomic studies in flax have produced large amounts of data in the last 15 years, providing useful resources to improve the genetic of this crop using genomics-based technologies and strategies. The goal of this thesis is therefore to capitalize on these advances to address the Cd problem and to propose solutions to improve breeding efficiencies. To find genomic-based solutions to Cd content, to the currently low breeding efficiency and to abiotic stress resistance in flax, this study utilized four major strategies: (1) genomic cross prediction, (2) gene family identification, (3) genome-wide association study (GWAS) and (4) genomic selection (GS). Characterization of the ATP-binding cassette (ABC) transporter and heavy metal associated (HMA) gene families was performed using the flax genome sequence. A total of 198 ABC transporter and 12 HMA genes were identified in the flax genome, of which nine were orthologous to Cd-associated genes in Arabidopsis, rice and maize. A transcriptomic analysis of eight tissues provided some support towards the functional annotation of these genes and confirmed the expression of these ABC transporter and HMA genes in flax seeds and other tissues. A diversity panel of 168 flax accessions was grown in the field at multiple locations and years and the seed content of 24 heavy metals (HMs) was measured. The panel was also sequenced and a single nucleotide polymorphism (SNP) dataset of nearly 43,000 SNPs was defined. A GWAS was conducted using these genotypic and phenotypic data and a total of 355 non-redundant quantitative trait nucleotides (QTNs) were identified for ten of the 24 metal contents. Overall, a total of 24 major and 331 minor effect QTNs were detected, including 11 that were pleiotropic. After allelic tests, 108 non-redundant QTNs were retained for eight of the ten metals and ranging from one for copper (Cu) to 70 for strontium (Sr). A total of 20 candidate genes for HM accumulation were identified at 12 of the 24 major QTN loci, of which five belonged to the ABC transporter family. Many of the metal contents, including Cd, appeared to be controlled by many genes of small effects; hence, GS is better suited than marker-assisted selection for application in breeding. To test this, predictive ability using ten GS statistical models was evaluated using trait-specific QTN and the random genome-wide 43K SNP datasets. Significantly higher predictive abilities were observed from the GS models built with the dataset made of QTNs associated with metal contents (70-80%) compared to that of the 43K dataset (10-25%). This study showed the feasibility of using GS to improve the predictive ability of polygenic traits such as metal content in seeds. GS can be applied in early generation selection to accelerate the improvement of abiotic stress resistance and either select low-Cd lines or discard high-Cd lines. These findings validate the use of a QTL-based strategy as a highly effective method for improving the efficiency of predictive ability of GS for highly complex traits such as resistance or tolerance to HM accumulation. Identification of both large and minor effect QTNs and/or pleiotropic effects hold potential for flax breeding improvement. Candidate gene functional validation can be performed using methods such as genome editing or targeting induced local lesions in genomes (TILLING).

La drépanocytose est une maladie causée par une seule mutation dans le gène de la bêta-globine. Les complications liées à la maladie se manifestent sur le plan génétique, épigénique, transcriptionnel, et métabolique. Les approches intégratives des technologies de séquençage à haut-débit permettent de comprendre le mécanisme pathologique et de découvrir des thérapies en lien avec la maladie. Dans cette thèse, j’intègre divers jeux de données omiques et j’applique des méthodes statistiques pour élaborer de nouvelles hypothèses et analyser les données. Dans les deux premières études, je combine les résultats des études d'association pangénomique d'hémoglobine fœtale (HbF) et des globules rouges denses déshydratés (DRBC) avec l'expression génique, l'interaction chromatinienne, les bases de données relatives aux maladies et les cibles médicamenteuses sélectionnées par des experts. Cette approche intégrative a révélé trois nouveaux loci sur le chromosome 10 (BICC1), le chromosome 19 (KLF1) et le chromosome 22 (CECR2) comme régulateurs de l'HbF. Pour l’étude sur la densité de globules rouges, quatre cibles médicamenteuses (BCL6, LRRC32, KNCJ14 et LETM1) ont été identifiées comme des modulateurs potentiels de la sévérité. Dans la troisième étude, j’intégre la métabolomique à la génomique pour établir une relation causale entre la L-glutamine et les crises douleurs en utilisant la randomisation mendélienne. En outre, nous avons identifié 66 biomarqueurs pour 6 complications liées à la drépanocytose et le débit de filtration glomérulaire estimé (DFGe). Enfin, dans la dernière étude j’ai appliqué une approche de clustering aux métabolites que j’ai ensuite combiné aux données de génotype. J’ai découvert des changements métabolomiques mettant en évidence des familles de métabolites impliqués dans les dysfonctionnements rénaux et hépatiques, en plus de confirmer le rôle d'une classe d'acides gras dans la formation en faucille des globules rouges. Ce travail met en évidence l'importance des approches multi-omiques pour découvrir de nouveaux mécanismes biologiques et étudier les maladies humaines. / Sickle cell disease is a monogenic disorder caused by a point mutation in the beta-globin gene. The complications related to the disease are characterized by a broad spectrum of distinct genetic, epigenetic, transcriptional, and metabolomic states. Integrative high-throughput technologies approaches to sickle cell disease pathophysiology are crucial to understanding complications mechanisms and uncovering therapeutic interventions. In this thesis, I integrate various omics datasets and apply statistical methods to derive new hypotheses and analyze data. I combine genome-wide association studies results of fetal hemoglobin (HbF) and dehydrated dense red blood cells (DRBC) with gene expression, chromatin interaction, disease-relevant databases, and expert-curated drug targets. This integrative approach revealed three novel loci on chromosome 10 (BICC1), chromosome 19 (KLF1) and chromosome 22 (CECR2) as key modulators of HbF. For DRBC, four drug targets (BCL6, LRRC32, KNCJ14, and LETM1) were identified as potential severity modifiers. Using mendelian randomization, I integrated metabolomics with genomics in the third study to establish a potential causal relationship between L-glutamine and painful crisis. Additionally, we identified 66 biomarkers for 6 SCD-related complications and estimated glomerular filtration rate (eGFR). Finally, the last study applied a clustering framework to metabolites which I then combined with genotypes. I found specific metabolomics changes highlighting families of metabolites involved in renal and liver dysfunction and confirming the role of a class of fatty acids in red blood cell sickling. This work highlights the importance of multi-omics approaches to unearth new biology and study human diseases.

No description available.

No description available.

To leverage the extreme parallelism of emerging architectures, so that scientific applications can fulfill their high fidelity and multi-physics potential while sustaining high efficiency relative to the limiting resource, numerical algorithms must be redesigned. Algorithmic redesign is capable of shifting the limiting resource, for example from memory or communication to arithmetic capacity. The benefit of algorithmic redesign expands greatly when introducing a tunable tradeoff between accuracy and resources. Scientific applications from diverse sources rely on dense matrix operations. These operations arise in: Schur complements, integral equations, covariances in spatial statistics, ridge regression, radial basis functions from unstructured meshes, and kernel matrices from machine learning, among others. This thesis demonstrates how to extend the problem sizes that may be treated and to reduce their execution time. Two “universes” of algorithmic innovations have emerged to improve computations by orders of magnitude in capacity and runtime. Each introduces a hierarchy, of rank or precision. Tile Low-Rank approximation replaces blocks of dense operator with those of low rank. Mixed precision approximation, increasingly well supported by contemporary hardware, replaces blocks of high with low precision. Herein, we design new high-performance direct solvers based on the synergism of TLR and mixed precision. Since adapting to data sparsity leads to heterogeneous workloads, we rely on task-based runtime systems to orchestrate the scheduling of fine-grained kernels onto computational resources. We first demonstrate how TLR permits to accelerate acoustic scattering and mesh deformation simulations. Our solvers outperform the state-of-art libraries by up to an order of magnitude. Then, we demonstrate the impact of enabling mixed precision in bioinformatics context. Mixed precision enhances the performance up to three-fold speedup. To facilitate the adoption of task-based runtime systems, we introduce the AL4SAN library to provide a common API for the expression and queueing of tasks across multiple dynamic runtime systems. This library handles a variety of workloads at a low overhead, while increasing user productivity. AL4SAN enables interoperability by switching runtimes at runtime, which permits to achieve a twofold speedup on a task-based generalized symmetric eigenvalue solver.

Yes / Bone morphogenetic proteins (BMPs) play essential roles in the control of skin development, postnatal tissue remodelling and tumorigenesis. To explore whether some of the effects of BMP signalling are mediated by microRNAs, we performed genome-wide microRNA (miRNA) screening in primary mouse keratinocytes after BMP4 treatment. Microarray analysis revealed substantial BMP4-dependent changes in the expression of distinct miRNAs, including miR-21. Real-time PCR confirmed that BMP4 dramatically inhibits miR-21 expression in the keratinocytes. Consistently, significantly increased levels of miR-21 were observed in transgenic mice overexpressing the BMP antagonist noggin under control of the K14 promoter (K14-noggin). By in situ hybridization, miR-21 expression was observed in the epidermis and hair follicle epithelium in normal mouse skin. In K14-noggin skin, miR-21 was prominently expressed in the epidermis, as well as in the peripheral portion of trichofolliculoma-like hair follicle-derived tumours that contain proliferating and poorly differentiated cells. By transfecting keratinocytes with a miR-21 mimic, we identified the existence of two groups of the BMP target genes, which are differentially regulated by miR-21. These included selected BMP-dependent tumour-suppressor genes (Pten, Pdcd4, Timp3 and Tpm1) negatively regulated by miR-21, as well as miR-21-independent Id1, Id2, Id3 and Msx2 that predominantly mediate the effects of BMPs on cell differentiation. In primary keratinocytes and HaCaT cells, miR-21 prevented the inhibitory effects of BMP4 on cell proliferation and migration. Thus, our study establishes a novel mechanism for the regulation of BMP-induced effects in the skin and suggests miRNAs are important modulators of the effects of growth factor signalling pathways on skin development and tumorigenesis.

La scoliose idiopathique est une déformation tridimensionnelle de la colonne vertébrale dont la pathogenèse reste obscure. Cette maladie affecte 2-4% des adolescents de 10-18 ans parmi les garçons et les filles. Il est à noter que les filles sont plus sévèrement affectées et ce en plus grand nombre que les garçons. Les études de jumeaux ont montré que les facteurs génétiques jouent un rôle important dans la scoliose idiopathique de l'adolescent (SIA). Depuis 2010, les études d'association pan génomiques ont été multipliées dans les recherches, visant à trouver des gènes candidats impliqués dans la SIA à travers des examens des polymorphismes nucléotidiques (SNPs). Un test génétique nommé "ScoliScore" a été publié pour essayer de prédire la progression de courbure dans la population caucasienne. Cependant, l'association n'a pas été reproduite dans une grande étude japonaise, soulignant l'importance d'une étude de réplication dans une population caucasienne indépendante. Dans ce contexte, mon projet de maîtrise a permis de génotyper plus de 1,4 millions de SNPs dans une cohorte canadienne-française dans le but: 1) de valider l'association de ScoliScoreTM; et 2) d’identifier les variants génomiques associées à la SIA dans la population québécoise. Notre étude a montré qu’aucun des variants constituant le test ScoliScoreTM n’était associé à la SIA. Ceci suggère que l'absence d'association dans une cohorte japonaise n'est pas due à l'appartenance ethnique. Aussi, nous avons identifié des variants génomiques associés significativement à l’initiation et/ou la progression de SIA dans la population québécoise, suggérant des gènes candidats impliqués dans la pathogenèse de SIA. / Idiopathic scoliosis is a common spinal deformation occurring without clear reason. This disease affects 2-4% adolescents aging from 10-18 years old in both genders. Of note, girls are more affected in number and severity than boys. Twin studies demonstrated that genetic factors play an important role in adolescent idiopathic scoliosis (AIS). Since 2010, Genome-wide association studies (GWAS) have been multiplied in AIS researches, aiming to find out candidate genes involved in the disease by an examination of single nucleotide polymorphisms (SNPs) throughout the entire genome. A genetic test named “ScoliScore” was released for the prediction of curvature progression in Caucasian AIS population using 53 SNPs. However, such association was not replicated in a larger Japanese-population study. Such a discrepancy could be explained by ethnicity, raising the importance of a replication study in an independent Caucasian population of European descent. In that context, we genotyped over 1.4 million SNPs in a French-Canadian cohort: 1) to validate the association in ScoliScoreTM test; and 2) to identify genomic variants associated with AIS in the population of Quebec. As a result, the association of ScoliScoreTM genomic markers could not be reproduced in French-Canadian AIS patients, suggesting that the lack of association of these SNPs in a Japanese cohort is not due to ethnicity. Meanwhile, we identified genome-wide significant variants associated with spinal curve initiation and/or progression in French-Canadian population, suggesting candidate genes involved in AIS pathogenesis.