967 resultados para WIDE ASSOCIATION


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Objective: To investigate whether submicroscopic copy number variants (CNVs) on the X chromosome can be identified in women with primary ovarian insufficiency (POI), defined as spontaneous secondary amenorrhea before 40 years of age accompanied by follicle-stimulating hormone levels above 40 IU/L on at least two occasions. Design: Analysis of intensity data of single nucleotide polymorphism (SNP) probes generated by genomewide Illumina 370k CNV BeadChips, followed by the validation of identified loci using a custom designed ultra-high-density comparative genomic hybridization array containing 48,325 probes evenly distributed over the X chromosome. Setting: Multicenter genetic cohort study in the Netherlands. Patient(s): 108 Dutch Caucasian women with POI, 97 of whom passed quality control, who had a normal karyogram and absent fragile X premutation, and 235 healthy Dutch Caucasian women as controls. Intervention(s): None. Main Outcome Measure(s): Amount and locus of X chromosomal microdeletions or duplications. Result(s): Intensity differences between SNP probes identify microdeletions and duplications. The initial analysis identified an overrepresentation of deletions in POI patients. Moreover, CNVs in two genes on the Xq21.3 locus (i.e., PCDH11X and TGIF2LX) were statistically significantly associated with the POI phenotype. Mean size of identified CNVs was 262 kb. However, in the validation study the identified putative Xq21.3 deletions samples did not show deviations in intensities in consecutive probes. Conclusion(s): X chromosomal submicroscopic CNVs do not play a major role in Caucasian POI patients. We provide guidelines on how submicroscopic cytogenetic POI research should be conducted. (Fertil Steril (R) 2011;95:1584-8. (C) 2011 by American Society for Reproductive Medicine.)

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We investigated whether variants in major candidate genes for food intake and body weight regulation contribute to obesity-related traits under a multilocus perspective. We studied 375 Brazilian subjects from partially isolated African-derived populations (quilombos). Seven variants displaying conflicting results in previous reports and supposedly implicated in the susceptibility of obesity-related phenotypes were investigated: beta(2)-adrenergic receptor (ADRB2) (Arg16Gly), insulin induced gene 2 (INSIG2) (rs7566605), leptin (LEP) (A19G), LEP receptor (LEPR) (Gln223Arg), perilipin (PLIN) (6209T > C), peroxisome proliferator-activated receptor-gamma (PPARG) (Pro12Ala), and resistin (RETN) (-420C > G). Regression models as well as generalized multifactor dimensionality reduction (GMDR) were employed to test the contribution of individual effects and higher-order interactions to BMI and waist-hip ratio (WHR) variation and risk of overweight/obesity. The best multilocus association signal identified in the quilombos was further examined in an independent sample of 334 Brazilian subjects of European ancestry. In quilombos, only the PPARG polymorphism displayed significant individual effects (WHR variation, P = 0.028). No association was observed either with the risk of overweight/obesity (BMI >= 25 kg/m(2)), risk of obesity alone (BMI >= 30 kg/m(2)) or BMI variation. However, GMDR analyses revealed an interaction between the LEPR and ADRB2 polymorphisms (P = 0.009) as well as a third-order effect involving the latter two variants plus INSIG2 (P = 0.034) with overweight/obesity. Assessment of the LEPR-ADRB2 interaction in the second sample indicated a marginally significant association (P = 0.0724), which was further verified to be limited to men (P = 0.0118). Together, our findings suggest evidence for a two-locus interaction between the LEPR Gln223Arg and ADRB2 Arg16Gly variants in the risk of overweight/obesity, and highlight further the importance of multilocus effects in the genetic component of obesity.

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This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in upto 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 x 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for similar to 2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous systemin obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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Preeclampsia is a spectral disease, with different clinical forms which can evolve with severe multisystemic complications. This present study aimed to determine the risk factors associated with preeclampsia (PE); to validate the existence of aggregation of hypertensive disease in families of women with preeclampsia and verify the existence of association between polymorphisms in the VEGF gene and level of VEGF and its soluble receptor (sFlt1). A case-control study was performed (n = 851). Genotyping of VEGF was performed and serum levels of VEGF and sFlt1 were measured by ELISA. It was observed that 38% of mothers (173, 455) of a case of preeclampsia and 30.8% (78 of 361) of controls had history of hypertension (p <0.0001). Similarly, when examining the history of maternal preeclampsia, we observed that 14.6% (48 of 328) of mothers of women with preeclampsia and 9.6% (12 of 294) of mothers of controls had a history of preeclampsia (p = 0.0001). As for maternal history of preeclampsia, we found that 5.1% (15 of 295) of cases and 3.6% (7 of 314) of controls had a history of preeclampsia (p = 0.0568). Sisters of women with preeclampsia also had a history of hypertensive disease in 9% (41 of 455) versus 6.6% (13 of 361), p = 0.002. Similarly when examining the history of preeclampsia in sisters, it was observed that 22.7% (57 of 251) of a sister of case versus 11.4% (26 of 228) of controls had a history of preeclampsia (P = 0.0011). We observed a decrease in free VEGF in the serum of patients (P <0.05) and increased soluble VEGF receptor. There was no association between polymorphisms in the VEGF gene and preeclampsia. The data obtained in this work validate that hypertensive disease in mothers and sisters with preeclampsia are risk factors for preeclampsia. The risk of illness in the family is higher according to disease severity. High incidence of preeclampsia can be assumed by the high incidence of this disease among the controls. Significant differences between the frequency of preeclampsia in mothers of cases and controls indicate familial factors. Work is being conducted with the to eventually perform genome wide association studies to identify susceptibility loci

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Background: New challenges are rising in the animal protein market, and one of the main world challenges is to produce more in shorter time, with better quality and in a sustainable way. Brazil is the largest beef exporter in volume hence the factors affecting the beef meat chain are of major concern in countrýs economy. An emerging class of biotechnological approaches, the molecular markers, is bringing new perspectives to face these challenges, particularly after the publication of the first complete livestock genome (bovine), which has triggered a massive initiative to put in practice the benefits of the so called the Post-Genomic Era. Review: This article aimed at showing the directions and insights in the application of molecular markers on livestock genetic improvement and reproduction as well at organizing the progress so far, pointing some perspectives of these emerging technologies in Brazilian ruminant production context. An overview on the nature of the main molecular markers explored in ruminant production is provided, which describes the molecular bases and detection approaches available for microsatellites (STR) and single nucleotide polymorphisms (SNP). A topic is dedicated to review the history of association studies between markers and important trait variation in livestock, showing the timeline starting on quantitative trait loci (QTL) identification using STR markers and ending in high resolution SNP panels to proceed whole genome scans for phenotype/genotype association. Also the article organizes this information to reveal how QTL prospection using STR could open ground to the feasibility of marker-assisted selection and why this approach is quickly being replaced by studies involving the application of genome-wide association using SNP research in a new concept called genomic selection. Conclusion: The world's scientific community is dedicating effort and resources to apply SNP information in livestock selection through the development of high density panels for genomic association studies, connecting molecular genetic data with phenotypes of economic interest. Once generated, this information can be used to take decisions in genetic improvement programs by selecting animals with the assistance of molecular markers.

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Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

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This review paper presents the three main approaches currently used in livestock genomic sciences where the bioinfomatics plays a critical role. They are named as Genomic Selection (GS), Genome Wide Association Study (GWAS) and Signatures of Selection (SS). The subsides for the construction of this article were generated in a current project (started in 2011), so called Zebu Genome Consortium (ZGC), which joins researchers from different institutions and countries, aiming to scientifically explore genomic information of Bos taurus indicus cattle breeds and deliver useful information to breeders and academic community, specially from the tropical regions of the world. © 2012 Springer-Verlag.

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To investigate morphological and genomic differences between cutting and racing lines of Quarter Horses, 120 racing and 68 cutting animals of both sexes, registered at the Brazilian Association of Quarter Horse Breeders, were used. Blood samples were collected, and the following physical traits were measured: weight; height at withers; body length; length of the shank, pastern, rump, head, and neck; and chest, shank, and hoof circumference. For analysis of genomic differences, 54,602 single-nucleotide polymorphisms (SNPs) were genotyped using the Equine SNP50 BeadChip, and the quality of individual and SNP genotype data were evaluated. The fixation index, FST, was used to identify genome regions that were altered in the lines by selection. The results showed significant differences between the lines in all physical traits. Quality control led to the exclusion of four cutting animals with a call rate of <0.95. After filtering, 12,544, 13,815, and 13,370 SNPs were excluded for the whole population (n = 184), the 120 racing animals, and the 64 cutting animals, respectively. The number of informative polymorphisms detected in each line and in the whole population indicated that the Equine SNP50 BeadChip can be used in genetic studies of Quarter Horses. The fixation index, FST, identified 2,558 genome regions that may have been modified by divergent selection. © 2013 Elsevier Inc.

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)