High resolution melting assay for genotyping of IFNL4 associated dinucleotide variant rs368234815.

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High resolution melting assay for genotyping of IFNL4 associated dinucleotide variant rs368234815.

Clin Microbiol Infect. 2014 Apr 11;

Authors: Galmozzi E, Facchetti F, Perbellini R, Aghemo A

Abstract
Genome-wide association studies (GWAS) showed that single nucleotide polymorphism (SNP) rs12979860 near to interleukin-28B gene (IL28B) was the most important genetic marker of spontaneous and interferon-induced clearance of hepatitis C virus (HCV) [1-4]. However, whether rs12979860 exerts biological effects or whether it is in linkage disequilibrium (LD) with other functional polymorphisms was still unknown. Recently, two publications have described the identification of a novel dinucleotide variant rs368234815 TT/-G (previously designated as ss469415590) that is in strong LD with the rs12979860 polymorphism and likely has a functional mechanism. In the first study Prokunina-Olsson et al. This article is protected by copyright. All rights reserved.

PMID: 24724563 [PubMed - as supplied by publisher]

A MEMS-Based Approach to Single Nucleotide Polymorphism Genotyping.

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A MEMS-Based Approach to Single Nucleotide Polymorphism Genotyping.

Sens Actuators A Phys. 2013 Jun 1;195:175-182

Authors: Zhu J, Palla M, Ronca S, Warpner R, Ju J, Lin Q

Abstract
Genotyping of single nucleotide polymorphisms (SNPs) allows diagnosis of human genetic disorders associated with single base mutations. Conventional SNP genotyping methods are capable of providing either accurate or high-throughput detection, but are still labor-, time-, and resource-intensive. Microfluidics has been applied to SNP detection to provide fast, low-cost, and automated alternatives, although these applications are still limited by either accuracy or throughput issues. To address this challenge, we present a MEMS-based SNP genotyping approach that uses solid-phase-based reactions in a single microchamber on a temperature control chip. Polymerase chain reaction (PCR), allele specific single base extension (SBE), and desalting on microbeads are performed in the microchamber, which is coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the SBE product. Experimental results from genotyping of the SNP on exon 1 of the HBB gene, which causes sickle cell anemia, demonstrate the potential of the device for rapid, accurate, multiplexed and high-throughput detection of SNPs.

PMID: 24729659 [PubMed - as supplied by publisher]

A hybrid qPCR/SNP array approach allows cost efficient assessment of KIR gene copy numbers in large samples.

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A hybrid qPCR/SNP array approach allows cost efficient assessment of KIR gene copy numbers in large samples.

BMC Genomics. 2014 Apr 11;15(1):274

Authors: Pontikos N, Smyth DJ, Schuilenburg H, Howson JM, Walker NM, Burren OS, Guo H, Onengut-Gumuscu S, Chen WM, Concannon P, Rich SS, Jayaraman J, Jiang W, Traherne JA, Trowsdale J, Todd JA, Wallace C

Abstract
BACKGROUND: Killer Immunoglobulin-like Receptors (KIRs) are surface receptors of natural killer cells that bind to their corresponding Human Leukocyte Antigen (HLA) class I ligands, making them interesting candidate genes for HLA-associated autoimmune diseases, including type 1 diabetes (T1D). However, allelic and copy number variation in the KIR region effectively mask it from standard genome-wide association studies: single nucleotide polymorphism (SNP) probes targeting the region are often discarded by standard genotype callers since they exhibit variable cluster numbers. Quantitative Polymerase Chain Reaction (qPCR) assays address this issue. However, their cost is prohibitive at the sample sizes required for detecting effects typically observed in complex genetic diseases.
RESULTS: We propose a more powerful and cost-effective alternative, which combines signals from SNPs with more than three clusters found in existing datasets, with qPCR on a subset of samples. First, we showed that noise and batch effects in multiplexed qPCR assays are addressed through normalisation and simultaneous copy number calling of multiple genes. Then, we used supervised classification to impute copy numbers of specific KIR genes from SNP signals. We applied this method to assess copy number variation in two KIR genes, \textit{KIR3DL1} and \textit{KIR3DS1}, which are suitable candidates for T1D susceptibility since they encode the only KIR molecules known to bind with HLA-Bw4 epitopes. We find no association between \textit{KIR3DL1/3DS1} copy number and T1D in 6744 cases and 5362 controls; a sample size twenty-fold larger than in any previous KIR association study. Due to our sample size, we can exclude odds ratios larger than 1.1 for the common \textit{KIR3DL1/3DS1} copy number groups at the 5% significance level.
CONCLUSION: We found no evidence of association of \textit{KIR3DL1/3DS1} copy number with T1D, either overall or dependent on HLA-Bw4 epitope. Five other KIR genes, \textit{KIR2DS4}, \textit{KIR2DL3}, \textit{KIR2DL5}, \textit{KIR2DS5} and \textit{KIR2DS1}, in high linkage disequilibrium with \textit{KIR3DL1} and \textit{KIR3DS1}, are also unlikely to be significantly associated. Our approach could potentially be applied to other KIR genes to allow cost effective assaying of gene copy number in large samples.

PMID: 24720548 [PubMed - as supplied by publisher]

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

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Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

BMC Bioinformatics. 2014 Apr 10;15(1):102

Authors: Guo X, Meng Y, Yu N, Pan Y

Abstract
Backgroud: Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger.
RESULTS: In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions.
CONCLUSIONS: Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

PMID: 24717145 [PubMed - as supplied by publisher]

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