Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

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.

Identification of GPx8 as a novel cellular substrate of the hepatitis C virus NS3-4A protease

Background: The hepatitis C virus (HCV) NS3-4A protease is not only an essential component of the viral replication complex and a prime target for a ntiviral intervention but also a key player i n the persistence and pathogenesis of HCV. It cleaves and thereby inactivates two crucial adaptor proteins in viral RNA sensing and innate immunity (MAVS and TRIF) as well as a phosphatase involved in growth factor signaling (TCPTP). T he aim of this study was to identify novel cellular substrates o f the N S3-4A protease and to investigate their role in the replication and pathogenesis of HCV. Methods: Cell lines inducibly expressing t he NS3-4A protease were analyzed in basal as well as interferon-α-stimulated states by stable isotopic l abeling using amino acids in cell culture (SILAC) coupled with protein separation and mass spectrometry. Candidates fulfilling stringent criteria for potential substrates or products of the NS3-4A protease were further i nvestigated in different experimental systems as well a s in liver biopsies from patients with chronic hepatitis C. Results: SILAC coupled with protein separation and mass spectrometry yielded > 5000 proteins of which 18 candidates were selected for further analyses. These allowed us to identify GPx8, a membrane-associated peroxidase involved in disulfide bond formation in the endoplasmic reticulum, as a n ovel cellular substrate of the H CV NS3-4A protease. Cleavage occurs at cysteine in position 11, removing the cytosolic tip of GPx8, and was observed in different experimental systems as well as in liver biopsies from patients with chronic hepatitis C. Further functional studies, involving overexpression and RNA silencing, revealed that GPx8 is a p roviral factor involved in viral particle production but not in HCV entry or HCV RNA replication. Conclusions: GPx8 is a proviral host factor cleaved by the HCV NS3-4A protease. Studies investigating the consequences of GPx8 cleavage for protein function are underway. The identification of novel cellular substrates o f the HCV N S3-4A protease should yield new insights i nto the HCV life cycle and the pathogenesis of hepatitis C and may reveal novel targets for antiviral intervention.

Improving the Accuracy and Usability of Iowa Falling Weight Deflectometer Data, May 2013

This study aims to improve the accuracy and usability of Iowa Falling Weight Deflectometer (FWD) data by incorporating significant enhancements into the fully-automated software system for rapid processing of the FWD data. These enhancements include: (1) refined prediction of backcalculated pavement layer modulus through deflection basin matching/optimization, (2) temperature correction of backcalculated Hot-Mix Asphalt (HMA) layer modulus, (3) computation of 1993 AASHTO design guide related effective SN (SNeff) and effective k-value (keff ), (4) computation of Iowa DOT asphalt concrete (AC) overlay design related Structural Rating (SR) and kvalue (k), and (5) enhancement of user-friendliness of input and output from the software tool. A high-quality, easy-to-use backcalculation software package, referred to as, I-BACK: the Iowa Pavement Backcalculation Software, was developed to achieve the project goals and requirements. This report presents theoretical background behind the incorporated enhancements as well as guidance on the use of I-BACK developed in this study. The developed tool, I-BACK, provides more fine-tuned ANN pavement backcalculation results by implementation of deflection basin matching optimizer for conventional flexible, full-depth, rigid, and composite pavements. Implementation of this tool within Iowa DOT will facilitate accurate pavement structural evaluation and rehabilitation designs for pavement/asset management purposes. This research has also set the framework for the development of a simplified FWD deflection based HMA overlay design procedure which is one of the recommended areas for future research.