WAVELET-BASED GENETIC ASSOCIATION ANALYSIS OF FUNCTIONAL PHENOTYPES ARISING FROM HIGH-THROUGHPUT SEQUENCING ASSAYS.
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ABSTRACT:
SUBMITTER: Shim H
PROVIDER: S-EPMC5795621 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe ongoing global efforts to control influenza epidemics and pandemics require high-throughput technologies to detect, quantify, and functionally characterize viral isolates. The 2009 influenza pandemic as well as the recent in-vitro selection of highly transmissible H5N1 variants have only increased existing concerns about emerging influenza strains with significantly enhanced human-to-human transmissibility. High-affinity binding of the virus hemagglutinin to human receptor glycans is a highly sensitive and stringent indicator of host adaptation and virus transmissibility. The surveillance of receptor-binding characteristics can therefore provide a strong additional indicator for the relative hazard imposed by circulating and newly emerging influenza strains.ResultsStreptavidin-coated microspheres were coated with selected biotinylated glycans to mimic either human or avian influenza host-cell receptors. Such glycospheres were used to selectively capture influenza virus of diverse subtypes from a variety of samples. Bound virus was then detected by fluorescently labelled antibodies and analyzed by quantitative flow cytometry. Recombinant hemagglutinin, inactivated virus, and influenza virions were captured and analyzed with regards to receptor specificity over a wide range of analyte concentration. High-throughput analyses of influenza virus produced dose-response curves that allow for functional assessment of relative receptor affinity and thus transmissibility.ConclusionsModular glycosphere assays for high-throughput functional characterization of influenza viruses introduce an important tool to augment the surveillance of clinical and veterinarian influenza isolates with regards to receptor specificity, host adaptation, and virus transmissibility.
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Project description:MotivationHigh-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA.ResultsWe describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters.Availability and implementationThe software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:BACKGROUND: Over 100 genes have been implicated in the aetiology of amyotrophic lateral sclerosis (ALS). A detailed understanding of their independent and cumulative contributions to disease burden may help guide various clinical and research efforts. METHODS: Using targeted high-throughput sequencing, we characterised the variation of 10 Mendelian and 23 low penetrance/tentative ALS genes within a population-based cohort of 444 Irish ALS cases (50 fALS, 394 sALS) and 311 age-matched and geographically matched controls. RESULTS: Known or potential high-penetrance ALS variants were identified within 17.1% of patients (38% of fALS, 14.5% of sALS). 12.8% carried variants of Mendelian disease genes (C9orf72 8.78%; SETX 2.48%; ALS2 1.58%; FUS 0.45%; TARDBP 0.45%; OPTN 0.23%; VCP 0.23%. ANG, SOD1, VAPB 0%), 4.7% carried variants of low penetrance/tentative ALS genes and 9.7% (30% of fALS, 7.1% of sALS) carried previously described ALS variants (C9orf72 8.78%; FUS 0.45%; TARDBP 0.45%). 1.6% of patients carried multiple known/potential disease variants, including all identified carriers of an established ALS variant (p<0.01); TARDBP:c.859G>A(p.[G287S]) (n=2/2 sALS). Comparison of our results with those from studies of other European populations revealed significant differences in the spectrum of disease variation (p=1.7×10(-4)). CONCLUSIONS: Up to 17% of Irish ALS cases may carry high-penetrance variants within the investigated genes. However, the precise nature of genetic susceptibility differs significantly from that reported within other European populations. Certain variants may not cause disease in isolation and concomitant analysis of disease genes may prove highly important.
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Project description:BACKGROUND:Clinical interpretation of the large number of rare variants identified by high throughput sequencing (HTS) technologies is challenging. The aim of this study was to explore the clinical implications of a HTS strategy for patients with hypertrophic cardiomyopathy (HCM) using a targeted HTS methodology and workflow developed for patients with a range of inherited cardiovascular diseases. By comparing the sequencing results with published findings and with sequence data from a large-scale exome sequencing screen of UK individuals, we sought to quantify the strength of the evidence supporting causality for detected candidate variants. METHODS AND RESULTS:223 unrelated patients with HCM (46±15 years at diagnosis, 74% males) were studied. In order to analyse coding, intronic and regulatory regions of 41 cardiovascular genes, we used solution-based sequence capture followed by massive parallel resequencing on Illumina GAIIx. Average read-depth in the 2.1 Mb target region was 120. Rare (frequency<0.5%) non-synonymous, loss-of-function and splice-site variants were defined as candidates. Excluding titin, we identified 152 distinct candidate variants in sarcomeric or associated genes (89 novel) in 143 patients (64%). Four sarcomeric genes (MYH7, MYBPC3, TNNI3, TNNT2) showed an excess of rare single non-synonymous single-nucleotide polymorphisms (nsSNPs) in cases compared to controls. The estimated probability that a nsSNP in these genes is pathogenic varied between 57% and near certainty depending on the location. We detected an additional 94 candidate variants (73 novel) in desmosomal, and ion-channel genes in 96 patients (43%). CONCLUSIONS:This study provides the first large-scale quantitative analysis of the prevalence of sarcomere protein gene variants in patients with HCM using HTS technology. Inclusion of other genes implicated in inherited cardiac disease identifies a large number of non-synonymous rare variants of unknown clinical significance.
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