TiArA: A Virtual Appliance for the Analysis of Tiling Array Data

Background

Genomic tiling arrays have been described in the scientific literature since 2003, yet there is a shortage of user-friendly applications available for their analysis.

Methodology/Principal Findings

Tiling Array Analyzer (TiArA) is a software program that provides a user-friendly graphical interface for the background subtraction, normalization, and summarization of data acquired through the Affymetrix tiling array platform. The background signal is empirically measured using a group of nonspecific probes with varying levels of GC content and normalization is performed to enforce a common dynamic range.

Conclusions/Significance

TiArA is implemented as a standalone program for Linux systems and is available as a cross-platform virtual machine that will run under most modern operating systems using virtualization software such as Sun VirtualBox or VMware. The software is available as a Debian package or a virtual appliance at http://purl.org/NET/tiara.     

Intra-Species Diversity between Seven Bifidobacterium adolescentis Strains Identified by Genome-Wide Tiling Array Analysis

Six Bifidobacterium adolescentis strains, JCM1275, JCM1251, JCM7044, JCM7045, JCM7046, and 9-124, were analyzed using a tiling array designed according to the full genome sequence of ATCC15703. The results demonstrated deletion clusters along with single-gene mutations and deletions. Most deletions concerned genes involved in polysaccharide and cell-surface biogenesis. A dendrogram illustrating the deletions and mutations is presented and the evolution of B. adolescentis is discussed.     

CINPER: An Interactive Web System for Pathway Prediction for Prokaryotes

We present a web-based network-construction system, CINPER (CSBL INteractive Pathway BuildER), to assist a user to build a user-specified gene network for a prokaryotic organism in an intuitive manner. CINPER builds a network model based on different types of information provided by the user and stored in the system. CINPER’s prediction process has four steps: (i) collection of template networks based on (partially) known pathways of related organism(s) from the SEED or BioCyc database and the published literature; (ii) construction of an initial network model based on the template networks using the P-Map program; (iii) expansion of the initial model, based on the association information derived from operons, protein-protein interactions, co-expression modules and phylogenetic profiles; and (iv) computational validation of the predicted models based on gene expression data. To facilitate easy applications, CINPER provides an interactive visualization environment for a user to enter, search and edit relevant data and for the system to display (partial) results and prompt for additional data. Evaluation of CINPER on 17 well-studied pathways in the MetaCyc database shows that the program achieves an average recall rate of 76% and an average precision rate of 90% on the initial models; and a higher average recall rate at 87% and an average precision rate at 28% on the final models. The reduced precision rate in the final models versus the initial models reflects the reality that the final models have large numbers of novel genes that have no experimental evidences and hence are not yet collected in the MetaCyc database. To demonstrate the usefulness of this server, we have predicted an iron homeostasis gene network of Synechocystis sp. PCC6803 using the server. The predicted models along with the server can be accessed at http://csbl.bmb.uga.edu/cinper/.     

Evolution of Prokaryotes: A Kuhnian Scientific Revolution

The conviction, due to previous failures, that bacteriology and darwinism were incompatible, has postponed the application of molecular phylogenesis to bacteria. But once introduced, this new field has led to a profound revolution of this science. A stable classification of the bacteria is at last possible; a new domain, the Archae, as distant from the Bacteria as from the Eukarya, has been discovered; noncultivable new species can be identified from the environment. It may even be possible to unravel the pathway of early evolution after the common ancestor. However, controversies on this subject are already disregarded by the new paradigm. This revised version was published online in June 2006 with corrections to the Cover Date.     

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.     

IMonitor: A Robust Pipeline for TCR and BCR Repertoire Analysis

The advance of next generation sequencing (NGS) techniques provides an unprecedented opportunity to probe the enormous diversity of the immune repertoire by deep sequencing T-cell receptors (TCRs) and B-cell receptors (BCRs). However, an efficient and accurate analytical tool is still on demand to process the huge amount of data. We have developed a high-resolution analytical pipeline, Immune Monitor (“IMonitor”) to tackle this task. This method utilizes realignment to identify V(D)J genes and alleles after common local alignment. We compare IMonitor with other published tools by simulated and public rearranged sequences, and it demonstrates its superior performance in most aspects. Together with this, a methodology is developed to correct the PCR and sequencing errors and to minimize the PCR bias among various rearranged sequences with different V and J gene families. IMonitor provides general adaptation for sequences from all receptor chains of different species and outputs useful statistics and visualizations. In the final part of this article, we demonstrate its application on minimal residual disease detection in patients with B-cell acute lymphoblastic leukemia. In summary, this package would be of widespread usage for immune repertoire analysis.     

Restriction Site Tiling Analysis: accurate discovery and quantitative genotyping of genome-wide polymorphisms using nucleotide arrays

High-throughput genotype data can be used to identify genes important for local adaptation in wild populations, phenotypes in lab stocks, or disease-related traits in human medicine. Here we advance microarray-based genotyping for population genomics with Restriction Site Tiling Analysis. The approach simultaneously discovers polymorphisms and provides quantitative genotype data at 10,000s of loci. It is highly accurate and free from ascertainment bias. We apply the approach to uncover genomic differentiation in the purple sea urchin.     

Energy Coupling Factor-Type ABC Transporters for Vitamin Uptake in Prokaryotes

Energy coupling factor (ECF) transporters are a subgroup of ATP-binding cassette (ABC) transporters involved in the uptake of vitamins and micronutrients in prokaryotes. In contrast to classical ABC importers, ECF transporters do not make use of water-soluble substrate binding proteins or domains but instead employ integral membrane proteins for substrate binding (named S-components). S-components form active translocation complexes with the ECF module, an assembly of two nucleotide-binding domains (NBDs, or EcfA) and a second transmembrane protein. In some cases, the ECF module is dedicated to a single S-component, but in many cases, the ECF module can interact with several different S-components that are unrelated in sequence and bind diverse substrates. The modular organization with exchangeable S-components on a single ECF module allows the transport of chemically different substrates via a common route. The recent determination of the crystal structures of the S-components that recognize thiamin and riboflavin has provided a first clue about the mechanism of S-component exchange. This review describes recent advances and the current views of the mechanism of transport by ECF transporters.     

Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data

Background  

Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression.