R-Gada: a fast and flexible pipeline for copy number analysis in association studies

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) using Copy Number Variation (CNV) are becoming a central focus of genetic research. CNVs have successfully provided target genome regions for some disease conditions where simple genetic variation (i.e., SNPs) has previously failed to provide a clear association.</p> <p>Results</p> <p>Here we present a new R package, that integrates: (i) data import from most common formats of Affymetrix, Illumina and aCGH arrays; (ii) a fast and accurate segmentation algorithm to call CNVs based on Genome Alteration Detection Analysis (GADA); and (iii) functions for displaying and exporting the Copy Number calls, identification of recurrent CNVs, multivariate analysis of population structure, and tools for performing association studies. Using a large dataset containing 270 HapMap individuals (Affymetrix Human SNP Array 6.0 Sample Dataset) we demonstrate a flexible pipeline implemented with the package. It requires less than one minute per sample (3 million probe arrays) on a single core computer, and provides a flexible parallelization for very large datasets. Case-control data were generated from the HapMap dataset to demonstrate a GWAS analysis.</p> <p>Conclusions</p> <p>The package provides the tools for creating a complete integrated pipeline from data normalization to statistical association. It can effciently handle a massive volume of data consisting of millions of genetic markers and hundreds or thousands of samples with very accurate results.</p

Luminally expressed gastrointestinal biomarkers

Introduction: A biomarker is a measurable indicator of normal biologic processes, pathogenic processes or pharmacological responses. The identification of a useful biomarker is challenging, with several hurdles to overcome before clinical adoption. This review gives a general overview of a range of biomarkers associated with inflammatory bowel disease or colorectal cancer along the gastrointestinal tract. Areas covered: These markers include those that are already clinically accepted, such as inflammatory markers such as faecal calprotectin, S100A12 (Calgranulin C), Fatty Acid Binding Proteins (FABP), malignancy markers such as Faecal Occult Blood, Mucins, Stool DNA, Faecal microRNA (miRNA), other markers such as Faecal Elastase, Faecal alpha-1-antitrypsin, Alpha2-macroglobulin and possible future markers such as microbiota, volatile organic compounds and pH. Expert commentary: There are currently a few biomarkers that have been sufficiently validated for routine clinical use at present such as FC. However, many of these biomarkers continue to be limited in sensitivity and specificity for various GI diseases. Emerging biomarkers have the potential to improve diagnosis and monitoring but further study is required to determine efficacy and validate clinical utility

The Effect of Algorithms on Copy Number Variant Detection

BACKGROUND: The detection of copy number variants (CNVs) and the results of CNV-disease association studies rely on how CNVs are defined, and because array-based technologies can only infer CNVs, CNV-calling algorithms can produce vastly different findings. Several authors have noted the large-scale variability between CNV-detection methods, as well as the substantial false positive and false negative rates associated with those methods. In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery. METHODOLOGY AND PRINCIPAL FINDINGS: We used a 56 K Illumina genotyping array enriched for CNV regions to generate hybridization intensities and allele frequencies for 48 Caucasian schizophrenia cases and 48 age-, ethnicity-, and gender-matched control subjects. No algorithm found a difference in CNV burden between the two groups. However, the total number of CNVs called ranged from 102 to 3,765 across algorithms. The mean CNV size ranged from 46 kb to 787 kb, and the average number of CNVs per subject ranged from 1 to 39. The number of novel CNVs not previously reported in normal subjects ranged from 0 to 212. CONCLUSIONS AND SIGNIFICANCE: Motivated by the availability of multiple publicly available genome-wide SNP arrays, investigators are conducting numerous analyses to identify putative additional CNVs in complex genetic disorders. However, the number of CNVs identified in array-based studies, and whether these CNVs are novel or valid, will depend on the algorithm(s) used. Thus, given the variety of methods used, there will be many false positives and false negatives. Both guidelines for the identification of CNVs inferred from high-density arrays and the establishment of a gold standard for validation of CNVs are needed

Genotyping with a 198 Mutation Arrayed Primer Extension Array for Hereditary Hearing Loss: Assessment of Its Diagnostic Value for Medical Practice

Molecular diagnostic testing of individuals with congenital sensorineural hearing loss typically begins with DNA sequencing of the GJB2 gene. If the cause of the hearing loss is not identified in GJB2, additional testing can be ordered. However, the step-wise analysis of several genes often results in a protracted diagnostic process. The more comprehensive Hereditary Hearing Loss Arrayed Primer Extension microarray enables analysis of 198 mutations across eight genes (GJB2, GJB6, GJB3, GJA1, SLC26A4, SLC26A5, MTRNR1 and MTTS1) in a single test. To evaluate the added diagnostic value of this microarray for our ethnically diverse patient population, we tested 144 individuals with congenital sensorineural hearing loss who were negative for biallelic GJB2 or GJB6 mutations. The array successfully detected all GJB2 changes previously identified in the study group, confirming excellent assay performance. Additional mutations were identified in the SLC26A4, SLC26A5 and MTRNR1 genes of 12/144 individuals (8.3%), four of whom (2.8%) had genotypes consistent with pathogenicity. These results suggest that the current format of this microarray falls short of adding diagnostic value beyond the customary testing of GJB2, perhaps reflecting the array's limitations on the number of mutations included for each gene, but more likely resulting from unknown genetic contributors to this phenotype. We conclude that mutations in other hearing loss associated genes should be incorporated in the array as knowledge of the etiology of hearing loss evolves. Such future modification of the flexible configuration of the Hereditary Hearing Loss Arrayed Primer Extension microarray would improve its impact as a diagnostic tool

Alteration of Blood–Brain Barrier Integrity by Retroviral Infection

The blood–brain barrier (BBB), which forms the interface between the blood and the cerebral parenchyma, has been shown to be disrupted during retroviral-associated neuromyelopathies. Human T Lymphotropic Virus (HTLV-1) Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP) is a slowly progressive neurodegenerative disease associated with BBB breakdown. The BBB is composed of three cell types: endothelial cells, pericytes and astrocytes. Although astrocytes have been shown to be infected by HTLV-1, until now, little was known about the susceptibility of BBB endothelial cells to HTLV-1 infection and the impact of such an infection on BBB function. We first demonstrated that human cerebral endothelial cells express the receptors for HTLV-1 (GLUT-1, Neuropilin-1 and heparan sulfate proteoglycans), both in vitro, in a human cerebral endothelial cell line, and ex vivo, on spinal cord autopsy sections from HAM/TSP and non-infected control cases. In situ hybridization revealed HTLV-1 transcripts associated with the vasculature in HAM/TSP. We were able to confirm that the endothelial cells could be productively infected in vitro by HTLV-1 and that blocking of either HSPGs, Neuropilin 1 or Glut1 inhibits this process. The expression of the tight-junction proteins within the HTLV-1 infected endothelial cells was altered. These cells were no longer able to form a functional barrier, since BBB permeability and lymphocyte passage through the monolayer of endothelial cells were increased. This work constitutes the first report of susceptibility of human cerebral endothelial cells to HTLV-1 infection, with implications for HTLV-1 passage through the BBB and subsequent deregulation of the central nervous system homeostasis. We propose that the susceptibility of cerebral endothelial cells to retroviral infection and subsequent BBB dysfunction is an important aspect of HAM/TSP pathogenesis and should be considered in the design of future therapeutics strategies

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

Parsimonious Higher-Order Hidden Markov Models for Improved Array-CGH Analysis with Applications to Arabidopsis thaliana

Array-based comparative genomic hybridization (Array-CGH) is an important technology in molecular biology for the detection of DNA copy number polymorphisms between closely related genomes. Hidden Markov Models (HMMs) are popular tools for the analysis of Array-CGH data, but current methods are only based on first-order HMMs having constrained abilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. Here, we develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling spatial dependencies. We apply parsimonious higher-order HMMs to the analysis of Array-CGH data of the accessions C24 and Col-0 of the model plant Arabidopsis thaliana. We compare these models against first-order HMMs and other existing methods using a reference of known deletions and sequence deviations. We find that parsimonious higher-order HMMs clearly improve the identification of these polymorphisms. Moreover, we perform a functional analysis of identified polymorphisms revealing novel details of genomic differences between C24 and Col-0. Additional model evaluations are done on widely considered Array-CGH data of human cell lines indicating that parsimonious HMMs are also well-suited for the analysis of non-plant specific data. All these results indicate that parsimonious higher-order HMMs are useful for Array-CGH analyses. An implementation of parsimonious higher-order HMMs is available as part of the open source Java library Jstacs (www.jstacs.de/index.php/PHHMM)

Retroviral matrix and lipids, the intimate interaction

Retroviruses are enveloped viruses that assemble on the inner leaflet of cellular membranes. Improving biophysical techniques has recently unveiled many molecular aspects of the interaction between the retroviral structural protein Gag and the cellular membrane lipids. This interaction is driven by the N-terminal matrix domain of the protein, which probably undergoes important structural modifications during this process, and could induce membrane lipid distribution changes as well. This review aims at describing the molecular events occurring during MA-membrane interaction, and pointing out their consequences in terms of viral assembly. The striking conservation of the matrix membrane binding mode among retroviruses indicates that this particular step is most probably a relevant target for antiviral research

HTLV-1-induced leukotriene B4 secretion by T cells promotes T cell recruitment and virus propagation.

The human T-lymphotropic virus type 1 (HTLV-1) is efficiently transmitted through cellular contacts. While the molecular mechanisms of viral cell-to-cell propagation have been extensively studied in vitro, those facilitating the encounter between infected and target cells remain unknown. In this study, we demonstrate that HTLV-1-infected CD4 T cells secrete a potent chemoattractant, leukotriene B4 (LTB4). LTB4 secretion is dependent on Tax-induced transactivation of the pla2g4c gene, which encodes the cytosolic phospholipase A2 gamma. Inhibition of LTB4 secretion or LTB4 receptor knockdown on target cells reduces T-cell recruitment, cellular contact formation and virus propagation in vitro. Finally, blocking the synthesis of LTB4 in a humanized mouse model of HTLV-1 infection significantly reduces proviral load. This results from a decrease in the number of infected clones while their expansion is not impaired. This study shows the critical role of LTB4 secretion in HTLV-1 transmission both in vitro and in vivo

Characterising chromosome rearrangements: recent technical advances in molecular cytogenetics

Genomic rearrangements can result in losses, amplifications, translocations and inversions of DNA fragments thereby modifying genome architecture, and potentially having clinical consequences. Many genomic disorders caused by structural variation have initially been uncovered by early cytogenetic methods. The last decade has seen significant progression in molecular cytogenetic techniques, allowing rapid and precise detection of structural rearrangements on a whole-genome scale. The high resolution attainable with these recently developed techniques has also uncovered the role of structural variants in normal genetic variation alongside single-nucleotide polymorphisms (SNPs). We describe how array-based comparative genomic hybridisation, SNP arrays, array painting and next-generation sequencing analytical methods (read depth, read pair and split read) allow the extensive characterisation of chromosome rearrangements in human genomes