Molecular Characterization of Pediatric Restrictive Cardiomyopathy from Integrative Genomics

Pediatric restrictive cardiomyopathy (RCM) is a genetically heterogeneous heart disease with limited therapeutic options. RCM cases are largely idiopathic; however, even within families with a known genetic cause for cardiomyopathy, there is striking variability in disease severity. Although accumulating evidence implicates both gene expression and alternative splicing in development of dilated cardiomyopathy (DCM), there have been no detailed molecular characterizations of underlying pathways dysregulated in RCM. RNA-Seq on a cohort of pediatric RCM patients compared to other forms of adult cardiomyopathy and controls identified transcriptional differences highly common to the cardiomyopathies, as well as those unique to RCM. Transcripts selectively induced in RCM include many known and novel G-protein coupled receptors linked to calcium handling and contractile regulation. In-depth comparisons of alternative splicing revealed splicing events shared among cardiomyopathy subtypes, as well as those linked solely to RCM. Genes identified with altered alternative splicing implicate RBM20, a DCM splicing factor, as a potential mediator of alternative splicing in RCM. We present the first comprehensive report on molecular pathways dysregulated in pediatric RCM including unique/shared pathways identified compared to other cardiomyopathy subtypes and demonstrate that disruption of alternative splicing patterns in pediatric RCM occurs in the inverse direction as DCM

Mosaic: making biological sense of complex networks

Summary: We present a Cytoscape plugin called Mosaic to support interactive network annotation, partitioning, layout and coloring based on gene ontology or other relevant annotations

Use of GenMAPP and MAPPFinder to analyse pathways involved in chickens infected with the protozoan parasite Eimeria

<p>Abstract</p> <p>Background</p> <p>Microarrays allow genome-wide assays of gene expression. There is a need for user-friendly software to visualise and analyse these data. Analysing microarray data in the context of biological pathways is now common, and several tools exist.</p> <p>Results</p> <p>We describe the use of MAPPFinder, a component of GenMAPP to characterise the biological pathways affected in chickens infected with the protozoan parasite <it>Eimeria. </it>Several pathways were significantly affected based on the unadjusted p-value, including several immune-system pathways.</p> <p>Conclusion</p> <p>GenMAPP/MAPPFinder provides a means to rapidly visualise pathways affected in microarray studies. However, it relies on good genome annotation and having genes reliably linked to pathway objects. We show that GenMAPP/MAPPFinder can produce useful results, and as the annotation of the chicken genome improves, so will the level of information gained.</p

MADNet: microarray database network web server

MADNet is a user-friendly data mining and visualization tool for rapid analysis of diverse high-throughput biological data such as microarray, phage display or even metagenome experiments. It presents biological information in the context of metabolic and signalling pathways, transcription factors and drug targets through minimal user input, consisting only of the file with the experimental data. These data are integrated with information stored in various biological databases such as NCBI nucleotide and protein databases, metabolic and signalling pathway databases (KEGG), transcription regulation (TRANSFAC©) and drug target database (DrugBank). MADNet is freely available for academic use at http://www.bioinfo.hr/madnet

hiPathDB: a human-integrated pathway database with facile visualization

One of the biggest challenges in the study of biological regulatory networks is the systematic organization and integration of complex interactions taking place within various biological pathways. Currently, the information of the biological pathways is dispersed in multiple databases in various formats. hiPathDB is an integrated pathway database that combines the curated human pathway data of NCI-Nature PID, Reactome, BioCarta and KEGG. In total, it includes 1661 pathways consisting of 8976 distinct physical entities. hiPathDB provides two different types of integration. The pathway-level integration, conceptually a simple collection of individual pathways, was achieved by devising an elaborate model that takes distinct features of four databases into account and subsequently reformatting all pathways in accordance with our model. The entity-level integration creates a single unified pathway that encompasses all pathways by merging common components. Even though the detailed molecular-level information such as complex formation or post-translational modifications tends to be lost, such integration makes it possible to investigate signaling network over the entire pathways and allows identification of pathway cross-talks. Another strong merit of hiPathDB is the built-in pathway visualization module that supports explorative studies of complex networks in an interactive fashion. The layout algorithm is optimized for virtually automatic visualization of the pathways. hiPathDB is available at http://hiPathDB.kobic.re.kr

The kSORT Assay to Detect Renal Transplant Patients at High Risk for Acute Rejection: Results of the Multicenter AART Study

Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR. We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set—the Kidney Solid Organ Response Test (kSORT)—was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91–0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88–1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86–0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials. The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants

PathExpress update: the enzyme neighbourhood method of associating gene-expression data with metabolic pathways

The post-genomic era presents us with the challenge of linking the vast amount of raw data obtained with transcriptomic and proteomic techniques to relevant biological pathways. We present an update of PathExpress, a web-based tool to interpret gene-expression data and explore the metabolic network without being restricted to predefined pathways. We define the Enzyme Neighbourhood (EN) as a sub-network of linked enzymes with a limited path length to identify the most relevant sub-networks affected in gene-expression experiments. PathExpress is freely available at: http://bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/

Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consor tium

The rigorous characterization of distinct induced pluripotent stem cells (iPSC) derived from multiple reprogramming technologies, somatic sources, and donors is required to understand potential sources of variability and downstream potential. To achieve this goal, the Progenitor Cell Biology Consortium performed comprehensive experimental and genomic analyses of 58 iPSC from ten laboratories generated using a variety of reprogramming genes, vectors, and cells. Associated global molecular characterization studies identified functionally informative correlations in gene expression, DNA methylation, and/or copy-number variation among key developmental and oncogenic regulators as a result of donor, sex, line stability, reprogramming technology, and cell of origin. Furthermore, X-chromosome inactivation in PSC produced highly correlated differences in teratoma-lineage staining and regulator expression upon differentiation. All experimental results, and raw, processed, and metadata from these analyses, including powerful tools, are interactively accessible from a new online portal at https://www.synapse.org to serve as a reusable resource for the stem cell community

Consistency, comprehensiveness, and compatibility of pathway databases

<p>Abstract</p> <p>Background</p> <p>It is necessary to analyze microarray experiments together with biological information to make better biological inferences. We investigate the adequacy of current biological databases to address this need.</p> <p>Description</p> <p>Our results show a low level of consistency, comprehensiveness and compatibility among three popular pathway databases (KEGG, Ingenuity and Wikipathways). The level of consistency for genes in similar pathways across databases ranges from 0% to 88%. The corresponding level of consistency for interacting genes pairs is 0%-61%. These three original sources can be assumed to be reliable in the sense that the interacting gene pairs reported in them are correct because they are curated. However, the lack of concordance between these databases suggests each source has missed out many genes and interacting gene pairs.</p> <p>Conclusions</p> <p>Researchers will hence find it challenging to obtain consistent pathway information out of these diverse data sources. It is therefore critical to enable them to access these sources via a consistent, comprehensive and unified pathway API. We accumulated sufficient data to create such an aggregated resource with the convenience of an API to access its information. This unified resource can be accessed at <url>http://www.pathwayapi.com</url>.</p

The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services

BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org