918 resultados para Genome-wide Search


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A genome-wide search for markers associated with BSE incidence was performed by using Transmission-Disequilibrium Tests (TDTs). Significant segregation distortion, i.e., unequal transmission probabilities of alleles within a locus, was found for three marker loci on Chromosomes (Chrs) 5, 10, and 20. Although TDTs are robust to false associations owing to hidden population substructures, it cannot distinguish segregation distortion caused by a true association between a marker and bovine spongiform encephalopathy (BSE) from a population-wide distortion. An interaction test and a segregation distortion analysis in half-sib controls were used to disentangle these two alternative hypotheses. None of the markers showed any significant interaction between allele transmission rates and disease status, and only the marker on Chr 10 showed a significant segregation distortion in control individuals. Nevertheless, the control group may have been a mixture of resistant and susceptible but unchallenged individuals. When new genotypes were generated in the vicinity of these three markers, evidence for an association with BSE was confirmed for the locus on Chr 5.

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The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

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Les habitudes de consommation de substances psychoactives, le stress, l’obésité et les traits cardiovasculaires associés seraient en partie reliés aux mêmes facteurs génétiques. Afin d’explorer cette hypothèse, nous avons effectué, chez 119 familles multi-générationnelles québécoises de la région du Saguenay-Lac-St-Jean, des études d’association et de liaison pangénomiques pour les composantes génétiques : de la consommation usuelle d’alcool, de tabac et de café, de la réponse au stress physique et psychologique, des traits anthropométriques reliés à l’obésité, ainsi que des mesures du rythme cardiaque (RC) et de la pression artérielle (PA). 58000 SNPs et 437 marqueurs microsatellites ont été utilisés et l’annotation fonctionnelle des gènes candidats identifiés a ensuite été réalisée. Nous avons détecté des corrélations phénotypiques significatives entre les substances psychoactives, le stress, l’obésité et les traits hémodynamiques. Par exemple, les consommateurs d’alcool et de tabac ont montré un RC significativement diminué en réponse au stress psychologique. De plus, les consommateurs de tabac avaient des PA plus basses que les non-consommateurs. Aussi, les hypertendus présentaient des RC et PA systoliques accrus en réponse au stress psychologique et un indice de masse corporelle (IMC) élevé, comparativement aux normotendus. D’autre part, l’utilisation de tabac augmenterait les taux corporels d’épinéphrine, et des niveaux élevés d’épinéphrine ont été associés à des IMC diminués. Ainsi, en accord avec les corrélations inter-phénotypiques, nous avons identifié plusieurs gènes associés/liés à la consommation de substances psychoactives, à la réponse au stress physique et psychologique, aux traits reliés à l’obésité et aux traits hémodynamiques incluant CAMK4, CNTN4, DLG2, DAG1, FHIT, GRID2, ITPR2, NOVA1, NRG3 et PRKCE. Ces gènes codent pour des protéines constituant un réseau d’interactions, impliquées dans la plasticité synaptique, et hautement exprimées dans le cerveau et ses tissus associés. De plus, l’analyse des sentiers de signalisation pour les gènes identifiés (P = 0,03) a révélé une induction de mécanismes de Potentialisation à Long Terme. Les variations des traits étudiés seraient en grande partie liées au sexe et au statut d’hypertension. Pour la consommation de tabac, nous avons noté que le degré et le sens des corrélations avec l’obésité, les traits hémodynamiques et le stress sont spécifiques au sexe et à la pression artérielle. Par exemple, si des variations ont été détectées entre les hommes fumeurs et non-fumeurs (anciens et jamais), aucune différence n’a été observée chez les femmes. Nous avons aussi identifié de nombreux traits reliés à l’obésité dont la corrélation avec la consommation de tabac apparaît essentiellement plus liée à des facteurs génétiques qu’au fait de fumer en lui-même. Pour le sexe et l’hypertension, des différences dans l’héritabilité de nombreux traits ont également été observées. En effet, des analyses génétiques sur des sous-groupes spécifiques ont révélé des gènes additionnels partageant des fonctions synaptiques : CAMK4, CNTN5, DNM3, KCNAB1 (spécifique à l’hypertension), CNTN4, DNM3, FHIT, ITPR1 and NRXN3 (spécifique au sexe). Ces gènes codent pour des protéines interagissant avec les protéines de gènes détectés dans l’analyse générale. De plus, pour les gènes des sous-groupes, les résultats des analyses des sentiers de signalisation et des profils d’expression des gènes ont montré des caractéristiques similaires à celles de l’analyse générale. La convergence substantielle entre les déterminants génétiques des substances psychoactives, du stress, de l’obésité et des traits hémodynamiques soutiennent la notion selon laquelle les variations génétiques des voies de plasticité synaptique constitueraient une interface commune avec les différences génétiques liées au sexe et à l’hypertension. Nous pensons, également, que la plasticité synaptique interviendrait dans de nombreux phénotypes complexes influencés par le mode de vie. En définitive, ces résultats indiquent que des approches basées sur des sous-groupes et des réseaux amélioreraient la compréhension de la nature polygénique des phénotypes complexes, et des processus moléculaires communs qui les définissent.

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A genome-wide scan was performed to detect quantitative trait loci (QTLs) for osteochondrosis (OC) and osteochondrosis dissecans (OCD) in horses. The marker set comprised 260 microsatellites. We collected data from 211 Hanoverian warmblood horses consisting of 14 paternal half-sib families. Traits used were OC (fetlock and/or hock joints affected), OCD (fetlock and/or hock joints affected), fetlock OC, fetlock OCD, hock OC, and hock OCD. The first genome scan included 172 microsatellite markers. In a second step 88 additional markers were chosen to refine putative QTLs found in the first scan. Genome-wide significant QTLs were located on equine chromosomes 2, 4, 5, and 16. QTLs for fetlock OC and hock OC partly overlapped on the same chromosomes, indicating that these traits may be genetically related. QTLs reached the chromosome-wide significance level on eight different equine chromosomes: 2, 3, 4, 5, 15, 16, 19, and 21. This whole-genome scan was a first step toward the identification of candidate genome regions harboring genes responsible for equine OC. Further investigations are necessary to refine the map positions of the QTLs already identified for OC.

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Systemic lupus erythematosus (SLE) is an autoimmune multisystem inflammatory disease characterized by the production of pathogenic autoantibodies. Previous genetic studies have suggested associations with HLA Class II alleles, complement gene deficiencies, and Fc receptor polymorphisms; however, it is likely that other genes contribute to SLE susceptibility and pathogenesis. Here, we report the results of a genome-wide microsatellite marker screen in 105 SLE sib-pair families. By using multipoint nonparametric methods, the strongest evidence for linkage was found near the HLA locus (6p11-p21) [D6S257, logarithm of odds (lod) = 3.90, P = 0.000011] and at three additional regions: 16q13 (D16S415, lod = 3.64, P = 0.000022), 14q21–23 (D14S276, lod = 2.81, P = 0.00016), and 20p12 (D20S186, lod = 2.62, P = 0.00025). Another nine regions (1p36, 1p13, 1q42, 2p15, 2q21–33, 3cent-q11, 4q28, 11p15, and 15q26) were identified with lod scores ≥1.00. These data support the hypothesis that multiple genes, including one in the HLA region, influence susceptibility to human SLE.

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Bipolar affective disorder (BPAD; manic-depressive illness) is characterized by episodes of mania and/or hypomania interspersed with periods of depression. Compelling evidence supports a significant genetic component in the susceptibility to develop BPAD. To date, however, linkage studies have attempted only to identify chromosomal loci that cause or increase the risk of developing BPAD. To determine whether there could be protective alleles that prevent or reduce the risk of developing BPAD, similar to what is observed in other genetic disorders, we used mental health wellness (absence of any psychiatric disorder) as the phenotype in our genome-wide linkage scan of several large multigeneration Old Order Amish pedigrees exhibiting an extremely high incidence of BPAD. We have found strong evidence for a locus on chromosome 4p at D4S2949 (maximum genehunter-plus nonparametric linkage score = 4.05, P = 5.22 × 10−4; sibpal Pempirical value <3 × 10−5) and suggestive evidence for a locus on chromosome 4q at D4S397 (maximum genehunter-plus nonparametric linkage score = 3.29, P = 2.57 × 10−3; sibpal Pempirical value <1 × 10−3) that are linked to mental health wellness. These findings are consistent with the hypothesis that certain alleles could prevent or modify the clinical manifestations of BPAD and perhaps other related affective disorders.

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The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

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Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

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BACKGROUND: The tendency to conceive dizygotic (DZ) twins is a complex trait influenced by genetic and environmental factors. To search for new candidate loci for twinning, we conducted a genome-wide linkage scan in 525 families using microsatellite and single nucleotide polymorphism marker panels. METHODS AND RESULTS: Non-parametric linkage analyses, including 523 families containing a total of 1115 mothers of DZ twins (MODZT) from Australia and New Zealand (ANZ) and The Netherlands (NL), produced four linkage peaks above the threshold for suggestive linkage, including a highly suggestive peak at the extreme telomeric end of chromosome 6 with an exponential logarithm of odds \[(exp)LOD] score of 2.813 (P = 0.0002). Since the DZ twinning rate increases steeply with maternal age independent of genetic effects, we also investigated linkage including only families where at least one MODZT gave birth to her first set of twins before the age of 30. These analyses produced a maximum expLOD score of 2.718 (P = 0.0002), largely due to linkage signal from the ANZ cohort, however, ordered subset analyses indicated this result is most likely a chance finding in the combined dataset. Linkage analyses were also performed for two large DZ twinning families from the USA, one of which produced a peak on chromosome 2 in the region of two potential candidate genes. Sequencing of FSHR and FIGLA, along with INHBB in MODZTs from two large NL families with family specific linkage peaks directly over this gene, revealed a potentially functional variant in the 5' untranslated region of FSHR that segregated with the DZ twinning phenotype in the Utah family. CONCLUSION: Our data provide further evidence for complex inheritance of familial DZ twinning.

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There is great interindividual variability in HIV-1 viral setpoint after seroconversion, some of which is known to be due to genetic differences among infected individuals. Here, our focus is on determining, genome-wide, the contribution of variable gene expression to viral control, and to relate it to genomic DNA polymorphism. RNA was extracted from purified CD4+ T-cells from 137 HIV-1 seroconverters, 16 elite controllers, and 3 healthy blood donors. Expression levels of more than 48,000 mRNA transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina). Genome-wide SNP data was generated from genomic DNA using the HumanHap550 Genotyping BeadChip (Illumina). We observed two distinct profiles with 260 genes differentially expressed depending on HIV-1 viral load. There was significant upregulation of expression of interferon stimulated genes with increasing viral load, including genes of the intrinsic antiretroviral defense. Upon successful antiretroviral treatment, the transcriptome profile of previously viremic individuals reverted to a pattern comparable to that of elite controllers and of uninfected individuals. Genome-wide evaluation of cis-acting SNPs identified genetic variants modulating expression of 190 genes. Those were compared to the genes whose expression was found associated with viral load: expression of one interferon stimulated gene, OAS1, was found to be regulated by a SNP (rs3177979, p = 4.9E-12); however, we could not detect an independent association of the SNP with viral setpoint. Thus, this study represents an attempt to integrate genome-wide SNP signals with genome-wide expression profiles in the search for biological correlates of HIV-1 control. It underscores the paradox of the association between increasing levels of viral load and greater expression of antiviral defense pathways. It also shows that elite controllers do not have a fully distinctive mRNA expression pattern in CD4+ T cells. Overall, changes in global RNA expression reflect responses to viral replication rather than a mechanism that might explain viral control.

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Before the advent of genome-wide association studies (GWASs), hundreds of candidate genes for obesity-susceptibility had been identified through a variety of approaches. We examined whether those obesity candidate genes are enriched for associations with body mass index (BMI) compared with non-candidate genes by using data from a large-scale GWAS. A thorough literature search identified 547 candidate genes for obesity-susceptibility based on evidence from animal studies, Mendelian syndromes, linkage studies, genetic association studies and expression studies. Genomic regions were defined to include the genes ±10 kb of flanking sequence around candidate and non-candidate genes. We used summary statistics publicly available from the discovery stage of the genome-wide meta-analysis for BMI performed by the genetic investigation of anthropometric traits consortium in 123 564 individuals. Hypergeometric, rank tail-strength and gene-set enrichment analysis tests were used to test for the enrichment of association in candidate compared with non-candidate genes. The hypergeometric test of enrichment was not significant at the 5% P-value quantile (P = 0.35), but was nominally significant at the 25% quantile (P = 0.015). The rank tail-strength and gene-set enrichment tests were nominally significant for the full set of genes and borderline significant for the subset without SNPs at P < 10(-7). Taken together, the observed evidence for enrichment suggests that the candidate gene approach retains some value. However, the degree of enrichment is small despite the extensive number of candidate genes and the large sample size. Studies that focus on candidate genes have only slightly increased chances of detecting associations, and are likely to miss many true effects in non-candidate genes, at least for obesity-related traits.

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Human genetic variation contributes to differences in susceptibility to HIV-1 infection. To search for novel host resistance factors, we performed a genome-wide association study (GWAS) in hemophilia patients highly exposed to potentially contaminated factor VIII infusions. Individuals with hemophilia A and a documented history of factor VIII infusions before the introduction of viral inactivation procedures (1979-1984) were recruited from 36 hemophilia treatment centers (HTCs), and their genome-wide genetic variants were compared with those from matched HIV-infected individuals. Homozygous carriers of known CCR5 resistance mutations were excluded. Single nucleotide polymorphisms (SNPs) and inferred copy number variants (CNVs) were tested using logistic regression. In addition, we performed a pathway enrichment analysis, a heritability analysis, and a search for epistatic interactions with CCR5 Δ32 heterozygosity. A total of 560 HIV-uninfected cases were recruited: 36 (6.4%) were homozygous for CCR5 Δ32 or m303. After quality control and SNP imputation, we tested 1 081 435 SNPs and 3686 CNVs for association with HIV-1 serostatus in 431 cases and 765 HIV-infected controls. No SNP or CNV reached genome-wide significance. The additional analyses did not reveal any strong genetic effect. Highly exposed, yet uninfected hemophiliacs form an ideal study group to investigate host resistance factors. Using a genome-wide approach, we did not detect any significant associations between SNPs and HIV-1 susceptibility, indicating that common genetic variants of major effect are unlikely to explain the observed resistance phenotype in this population.

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In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

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Nuclear Factor Y (NF-Y) is a trimeric complex that binds to the CCAAT box, a ubiquitous eukaryotic promoter element. The three subunits NF-YA, NF-YB and NF-YC are represented by single genes in yeast and mammals. However, in model plant species (Arabidopsis and rice) multiple genes encode each subunit providing the impetus for the investigation of the NF-Y transcription factor family in wheat. A total of 37 NF-Y and Dr1 genes (10 NF-YA, 11 NF-YB, 14 NF-YC and 2 Dr1) in Triticum aestivum were identified in the global DNA databases by computational analysis in this study. Each of the wheat NF-Y subunit families could be further divided into 4-5 clades based on their conserved core region sequences. Several conserved motifs outside of the NF-Y core regions were also identified by comparison of NF-Y members from wheat, rice and Arabidopsis. Quantitative RT-PCR analysis revealed that some of the wheat NF-Y genes were expressed ubiquitously, while others were expressed in an organ-specific manner. In particular, each TaNF-Y subunit family had members that were expressed predominantly in the endosperm. The expression of nine NF-Y and two Dr1 genes in wheat leaves appeared to be responsive to drought stress. Three of these genes were up-regulated under drought conditions, indicating that these members of the NF-Y and Dr1 families are potentially involved in plant drought adaptation. The combined expression and phylogenetic analyses revealed that members within the same phylogenetic clade generally shared a similar expression profile. Organ-specific expression and differential response to drought indicate a plant-specific biological role for various members of this transcription factor family.