311 research outputs found

    Comparative study of sequence-dependent hybridization kinetics in solution and on microspheres

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    Hybridization kinetics of DNA sequences with known secondary structures and random sequences designed with similar melting temperatures were studied in solution and when one strand was bound to 5 μm silica microspheres. The rates of hybridization followed second-order kinetics and were measured spectrophotometrically in solution and fluorometrically in the solid phase. In solution, the rate constants for the model sequences varied by almost two orders of magnitude, with a decrease in the rate constant with increasing amounts of secondary structure in the target sequence. The random sequences also showed over an order of magnitude difference in the rate constant. In contrast, the hybridization experiments in the solid phase with the same model sequences showed almost no change in the rate constant. Solid phase rate constants were approximately three orders of magnitude lower compared with the solution phase constants for sequences with little or no single-stranded structure. Sequences with a known secondary structure yielded solution phase rate constants as low as 3 × 10(3) M(−1) s(−1) with solid phase rate constants for the same sequences measured at 2.5 × 10(2) M(−1) s(−1). The results from these experiments indicate that (i) solid phase hybridization occurs three orders of magnitude slower than solution phase, (ii) trends observed in structure-dependent kinetics of solution phase hybridization may not be applicable to solid phase hybridization and (iii) model probes with known secondary structure decrease reaction rates; however, even random sequences with no known internal single-stranded structure can yield a broad range of reaction rates

    DDoS defense by offense

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    This article presents the design, implementation, analysis, and experimental evaluation of speak-up, a defense against application-level distributed denial-of-service (DDoS), in which attackers cripple a server by sending legitimate-looking requests that consume computational resources (e.g., CPU cycles, disk). With speak-up, a victimized server encourages all clients, resources permitting, to automatically send higher volumes of traffic. We suppose that attackers are already using most of their upload bandwidth so cannot react to the encouragement. Good clients, however, have spare upload bandwidth so can react to the encouragement with drastically higher volumes of traffic. The intended outcome of this traffic inflation is that the good clients crowd out the bad ones, thereby capturing a much larger fraction of the server's resources than before. We experiment under various conditions and find that speak-up causes the server to spend resources on a group of clients in rough proportion to their aggregate upload bandwidths, which is the intended result.National Science Foundation (U.S.) (NSF grant CNS-0225660)National Science Foundation (U.S.) (NSF grant CNS-0520241)United States. Dept. of Defense (National Security Science and Engineering Faculty Fellowship

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    Burden of Rare Sarcomere Gene Variants in the Framingham and Jackson Heart Study Cohorts

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    Rare sarcomere protein variants cause dominant hypertrophic and dilated cardiomyopathies. To evaluate whether allelic variants in eight sarcomere genes are associated with cardiac morphology and function in the community, we sequenced 3,600 individuals from the Framingham Heart Study (FHS) and Jackson Heart Study (JHS) cohorts. Out of the total, 11.2% of individuals had one or more rare nonsynonymous sarcomere variants. The prevalence of likely pathogenic sarcomere variants was 0.6%, twice the previous estimates; however, only four of the 22 individuals had clinical manifestations of hypertrophic cardiomyopathy. Rare sarcomere variants were associated with an increased risk for adverse cardiovascular events (hazard ratio: 2.3) in the FHS cohort, suggesting that cardiovascular risk assessment in the general population can benefit from rare variant analysis

    Multi-Ethnic Analysis of Lipid-Associated Loci: The NHLBI CARe Project

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    Background: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities. Methodology/Principal Findings: We tested a set of \sim50,000 polymorphisms from \sim2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed. Conclusions/Significance: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans

    Association of Exome Sequences With Cardiovascular Traits among Blacks in the Jackson Heart Study

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    The correlation of null alleles with human phenotypes can provide insight into gene function in humans. In individuals of African ancestry, we set out to identify null and damaging missense variants, and test these variants for association with a range of cardiovascular phenotypes

    Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

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    Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior–posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = −0.02, SE = 0.004, P-value = 2.10 × 10(−8)). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10(−4)). In exome-array single-variant analysis (P-value threshold = 9 × 10(−7)), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10(−5)). In the gene-based analysis (P-value threshold = 1.85 × 10(−6)), PCSK5 showed an association with AAD (P-value = 8.03 × 10(−7)). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = −0.003, P-value = 0.02), triglycerides (beta = −0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases
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