983 resultados para SNP- polymorphisme
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Presenta algunas estimaciones sobre la abundancia de los peces demersales y analiza las condiciones biológicas de diferentes especies de peces demersales relacionadas con las condiciones del ambiente.
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Presenta información sobre la alteración oceanográfica del verano pasado, provocada por la invasión de aguas tropicales superficiales que cubrieron la costa norte. El estudio se realizó entre el 25 de abril y el 3 de mayo 1972 a lo largo de la costa sur del Perú.
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Se registra la biomasa de diez especies palágicas: anchoveta, sardina, jurel, caballa, samasa, falso volador, bagre, vinciguerria, múnida y pota
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El crucero realizado entre el 23 de noviembre y el 15 de diciembre de 1999, se observó la distribución de diez especies pelágicas.
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Se observaron los cambios en la distribución, estructura poblacional y biomasa de los principales recursos pelágicos.
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Predominaron huevos y larvas de anchoveta, seguidos por el pez luminoso Vinciguerria lucetia.
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Se registró el predominio de las Aguas costeras Frías al norte de los 10°S y al sur de los 13° S.
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Se analizaron las variaciones espaciales en la dieta de la anchoveta, en 1412 ejemplares de 8 y 18 cm. de longitud.
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El crucero se efectuó del 18 de enro al 29 de febrero del 2000, mostró que las redes de arrastre pelágicas tuvieron una buena eficiencia y comportamiento en los 299 lances de comprobación.
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Establecer las normas administrativas de organización y funcionamiento de los BIC’s Humboldt, José Olaya Balandra y Snp-2 en bahía y durante la ejecución de los cruceros y prospecciones de investigación científica y tecnológica.
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BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.
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BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.
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There are many known examples of multiple semi-independent associations at individual loci; such associations might arise either because of true allelic heterogeneity or because of imperfect tagging of an unobserved causal variant. This phenomenon is of great importance in monogenic traits but has not yet been systematically investigated and quantified in complex-trait genome-wide association studies (GWASs). Here, we describe a multi-SNP association method that estimates the effect of loci harboring multiple association signals by using GWAS summary statistics. Applying the method to a large anthropometric GWAS meta-analysis (from the Genetic Investigation of Anthropometric Traits consortium study), we show that for height, body mass index (BMI), and waist-to-hip ratio (WHR), 3%, 2%, and 1%, respectively, of additional phenotypic variance can be explained on top of the previously reported 10% (height), 1.5% (BMI), and 1% (WHR). The method also permitted a substantial increase (by up to 50%) in the number of loci that replicate in a discovery-validation design. Specifically, we identified 74 loci at which the multi-SNP, a linear combination of SNPs, explains significantly more variance than does the best individual SNP. A detailed analysis of multi-SNPs shows that most of the additional variability explained is derived from SNPs that are not in linkage disequilibrium with the lead SNP, suggesting a major contribution of allelic heterogeneity to the missing heritability.
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The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.
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O objetivo deste trabalho foi validar a associação de marcadores moleculares do tipo "single nucleotide polymorphism" (SNP) para os genes FAD3A, FAD3B e FAD3C com o conteúdo de ácido linolênico (18:3) em sementes de soja e analisar a influência dos parâmetros genéticos destes marcadores nesta característica. Foram genotipadas 185 progênies F2 derivadas do cruzamento entre A29 (mutante para os três genes FAD3, 1% de 18:3) e Tucunaré (genótipo selvagem, 11% de 18:3). Os marcadores moleculares para os genes FAD3A, FAD3B e FAD3C explicaram a variação do conteúdo de 18:3 nas populações segregantes F2 e F2:3. Além disso, as substituições alélicas no loco FAD3A proporcionam maiores variações no conteúdo de 18:3 que as substituições nos outros dois locos.