AGenDA: gene prediction by comparative sequence analysis

Comparative sequence analysis is a powerful approach to identify functional elements in genomic sequences. Herein, we describe AGenDA (Alignment-based GENe Detection Algorithm), a novel method for gene prediction that is based on long-range alignment of syntenic regions in eukaryotic genome sequences. Local sequence homologies identified by the DIALIGN program are searched for conserved splice signals to define potential protein-coding exons; these candidate exons are then used to assemble complete gene structures. The performance of our method was tested on a set of 105 human-mouse sequence pairs. These test runs showed that sensitivity and specificity of AGenDA are comparable with the best gene- prediction program that is currently available. However, since our method is based on a completely different type of input information, it can detect genes that are not detectable by standard methods and vice versa. Thus, our approach seems to be a useful addition to existing gene-prediction programs. Availability: DIALIGN is available through the Bielefeld Bioinformatics Server (BiBiServ) at http://bibiserv.techfak.uni-bielefeld.de/dialign/ The gene-prediction program AGenDA described in this paper will be available through the BiBiServ or MIPS web server at http://mips.gsf.de.     

The PEDANT genome database

The PEDANT genome database (http://pedant.gsf.de) provides exhaustive automatic analysis of genomic sequences by a large variety of established bioinformatics tools through a comprehensive Web-based user interface. One hundred and seventy seven completely sequenced and unfinished genomes have been processed so far, including large eukaryotic genomes (mouse, human) published recently. In this contribution, we describe the current status of the PEDANT database and novel analytical features added to the PEDANT server in 2002. Those include: (i) integration with the BioRS data retrieval system which allows fast text queries, (ii) pre-computed sequence clusters in each complete genome, (iii) a comprehensive set of tools for genome comparison, including genome comparison tables and protein function prediction based on genomic context, and (iv) computation and visualization of protein-protein interaction (PPI) networks based on experimental data. The availability of functional and structural predictions for 650 000 genomic proteins in well organized form makes PEDANT a useful resource for both functional and structural genomics.     

CRONOS: the cross-reference navigation server

Summary: Cross-mapping of gene and protein identifiers betweendifferent databases is a tedious and time-consuming task. Toovercome this, we developed CRONOS, a cross-reference serverthat contains entries from five mammalian organisms presentedby major gene and protein information resources. Sequence similarityanalysis of the mapped entries shows that the cross-referencesare highly accurate. In total, up to 18 different identifiertypes can be used for identification of cross-references. Thequality of the mapping could be improved substantially by exclusionof ambiguous gene and protein names which were manually validated.Organism-specific lists of ambiguous terms, which are valuablefor a variety of bioinformatics applications like text miningare available for download. Availability: CRONOS is freely available to non-commercial usersat http://mips.gsf.de/genre/proj/cronos/index.html, web servicesare available at http://mips.gsf.de/CronosWSService/CronosWS?wsdl. Contact: brigitte.waegele{at}helmholtz-muenchen.de Supplementary information: Supplementary data are availableat Bioinformatics online. The online Supplementary Materialcontains all figures and tables referenced by this article. Associate Editor: Martin Bishop     

CREDO: a web-based tool for computational detection of conserved sequence motifs in noncoding sequences

SUMMARY: CREDO is a user-friendly, web-based tool that integrates the analysis and results of different algorithms widely used for the computational detection of conserved sequence motifs in noncoding sequences. It enables easy comparison of the individual results. CREDO offers intuitive interfaces for easy and rapid configuration of the applied algorithms and convenient views on the results in graphical and tabular formats. AVAILABILITY: http://mips.gsf.de/proj/regulomips/credo.htm.     

Plotting haplotype-specific linkage disequilibrium patterns by extended haplotype homozygosity

Association studies may request more details of a specific haplotype. Haplotype-specific decay of linkage disequilibrium is such a crucial and versatile characteristic. It may be used, e.g. to search for signals of natural selection in a risk haplotype. Here, we present a web-based tool to explore the relationship between population frequency and extended linkage disequilibrium measured as haplotype homozygosity of observed haplotypes within a specified candidate region. AVAILABILITY: The web-tool is available at http://ihg.gsf.de/cgi-bin/mueller/webehh.pl     

Gepard: a rapid and sensitive tool for creating dotplots on genome scale

Gepard provides a user-friendly, interactive application for the quick creation of dotplots. It utilizes suffix arrays to reduce the time complexity of dotplot calculation to Theta(m*log n). A client-server mode, which is a novel feature for dotplot creation software, allows the user to calculate dotplots and color them by functional annotation without any prior downloading of sequence or annotation data. AVAILABILITY: Both source codes and executable binaries are available at http://mips.gsf.de/services/analysis/gepard     

OrderedList--a bioconductor package for detecting similarity in ordered gene lists

SUMMARY: OrderedList is a Bioconductor compliant package for meta-analysis based on ordered gene lists like those resulting from differential gene expression analysis. Our package quantifies the similarity between gene lists. The significance of the similarity score is estimated from random scores computed on perturbed data. OrderedList illustrates list similarity in intuitive plots and determines the score-driving genes for further analysis. AVAILABILITY: http://www.bioconductor.org CONTACT: claudio.lottaz@molgen.mpg.de SUPPLEMENTARY INFORMATION: Please visit our webpage on http://compdiag.molgen.mpg.de/software.     

水稻条纹病毒胁迫下的水稻全基因组表达谱

水稻条纹叶枯病由水稻条纹病毒(Rice stripe virus, RSV)引起,对我国水稻生产危害严重.为了明确RSV侵染对水稻基因表达谱的影响,采用Affymetrix水稻全基因组芯片对RSV接种后出现条纹症状第7天的武育粳3号水稻病叶和相应的健康叶片进行了全基因组表达谱分析,得到3 517个差异基因,其中2 002个表达上调,1 515个表达下调.根据TIGR数据库注释(http://www.tigr.org/tdb/e2k1/osa1/)和MIPS基因功能分类标准(http://mips.gsf.de/projects/funcat)将差异基因归类为15个功能类别,多数差异基因与植物防御、信号传导及蛋白质、碳水化合物的代谢相关,一些转录因子的表达也发生了明显的变化.代谢途径分析表明,RSV侵染后磷酸戊糖途径、类黄酮合成途径和芸苔素合成途径的相关基因表达明显增强,赤霉素合成途径相关基因的表达受到了抑制.     

Separation of sequences from host-pathogen interface using triplet nucleotide frequencies

The identification of genes involved in host-pathogen interactions is important for the elucidation of mechanisms of disease resistance and host susceptibility. A traditional way to classify the origin of genes sampled from a pool of mixed cDNA is through sequence similarity to known genes from either the pathogen or host organism or other closely related species. This approach does not work when the identified sequence has no close homologues in the sequence databases. In our previous studies, we classified genes using their codon frequencies. This method, however, explicitly required the prediction of CDS regions and thus could not be applied to sequences composed from the non-coding regions of genes. In this study, we show that the use of sliding-window triplet frequencies extends the application of the algorithm to both coding and non-coding sequences and also increases the prediction accuracy of a Support Vector Machine classifier from 95.6+/-0.3 to 96.5+/-0.2. Thus the use of the triplet frequencies increased the prediction accuracy of the new method by more than 20% compared to our previous approach. A functional analysis of sequences detected gene families having significantly higher or lower probability to be correctly classified compared to the average accuracy of the method is described. The server to perform classification of EST sequences using triplet frequencies is available at (URL: http://mips.gsf.de/proj/est3).     

REGANOR

With >1,000 prokaryotic genome sequencing projects ongoing or already finished, comprehensive comparative analysis of the gene content of these genomes has become viable. To allow for a meaningful comparative analysis, gene prediction of the various genomes should be as accurate as possible. It is clear that improving the state of genome annotation requires automated gene identification methods to cope with the influence of artifacts, such as genomic GC content. There is currently still room for improvement in the state of annotations. We present a web server and a database of high-quality gene predictions. The web server is a resource for gene identification in prokaryote genome sequences. It implements our previously described, accurate gene finding method REGANOR. We also provide novel gene predictions for 241 complete, or almost complete, prokaryotic genomes. We demonstrate how this resource can easily be utilised to identify promising candidates for currently missing genes from genome annotations with several examples. All data sets are available online. AVAILABILITY: The gene finding server is accessible via https://www.cebitec.uni-bielefeld.de/groups/brf/software/reganor/cgi-bin/reganor_upload.cgi. The server software is available with the GenDB genome annotation system (version 2.2.1 onwards) under the GNU general public license. The software can be downloaded from https://sourceforge.net/projects/gendb/. More information on installing GenDB and REGANOR and the system requirements can be found on the GenDB project page http://www.cebitec.uni-bielefeld.de/groups/brf/software/wiki/GenDBWiki/AdministratorDocumentation/GenDBInstallation     

BLAST2GENE: a comprehensive conversion of BLAST output into independent genes and gene fragments

SUMMARY: BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region. AVAILABILITY: The program is available upon request from the authors. A web server of BLAST2GENE is maintained at http://www.bork.embl.de/blast2gene     

GEPIS--quantitative gene expression profiling in normal and cancer tissues

MOTIVATION: Expression profiling in diverse tissues is fundamental to understanding gene function as well as therapeutic target identification. The vast collection of expressed sequence tags (ESTs) and the associated tissue source information provides an attractive opportunity for studying gene expression. RESULTS: To facilitate EST-based expression analysis, we developed GEPIS (gene expression profiling in silico), a tool that integrates EST and tissue source information to compute gene expression patterns in a large panel of normal and tumor samples. We found EST-based expression patterns to be consistent with published papers as well as our own experimental results. We also built a GEPIS Regional Atlas that depicts expression characteristics of all genes in a selected genomic region. This program can be adapted for large-scale screening for genes with desirable expression patterns, as illustrated by our large-scale mining for tissue- and tumor-specific genes. AVAILABILITY: The email server version of the GEPIS application is freely available at http://share.gene.com/share/gepis. An interactive version of GEPIS will soon be freely available at http://www.cgl.ucsf.edu/Research/genentech/gepis/. The source code, modules, data and gene lists can be downloaded at http://share.gene.com/share/gepis.     

GEPAS: A web-based resource for microarray gene expression data analysis

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).     

EXP-PAC: providing comparative analysis and storage of next generation gene expression data

Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html).     

Apple gene function and gene family database: an integrated bioinformatics database for apple research

The apple (Malus domestica) is one of the most economically important fruit crops in the world, due its importance to human nutrition and health. To analyze the function and evolution of different apple genes, we developed apple gene function and gene family database (AppleGFDB) for collecting, storing, arranging, and integrating functional genomics information of the apple. The AppleGFDB provides several layers of information about the apple genes, including nucleotide and protein sequences, chromosomal locations, gene structures, and any publications related to these annotations. To further analyze the functional genomics data of apple genes, the AppleGFDB was designed to enable users to easily retrieve information through a suite of interfaces, including gene ontology, protein domain and InterPro. In addition, the database provides tools for analyzing the expression profiles and microRNAs of the apple. Moreover, all of the analyzed and collected data can be downloaded from the database. The database can also be accessed using a convenient web server that supports a full-text search, a BLAST sequence search, and database browsing. Furthermore, to facilitate cooperation among apple researchers, AppleGFDB is presented in a user-interactive platform, which provides users with the opportunity to modify apple gene annotations and submit publication information for related genes. AppleGFDB is available at http://www.applegene.org or http://gfdb.sdau.edu.cn/.     

SLAM web server for comparative gene finding and alignment

SLAM is a program that simultaneously aligns and annotates pairs of homologous sequences. The SLAM web server integrates SLAM with repeat masking tools and the AVID alignment program to allow for rapid alignment and gene prediction in user submitted sequences. Along with annotations and alignments for the submitted sequences, users obtain a list of predicted conserved non-coding sequences (and their associated alignments). The web site also links to whole genome annotations of the human, mouse and rat genomes produced with the SLAM program. The server can be accessed at http://bio.math.berkeley.edu/slam.     

HuGeMap: a distributed and integrated Human Genome Map database.

The HuGeMap database stores the major genetic and physical maps of the human genome. It is also interconnected with the gene radiation hybrid mapping database RHdb. HuGeMap is accessible through a Web server for interactive browsing at URL http://www.infobiogen. fr/services/Hugemap , as well as through a CORBA server for effective programming. HuGeMap is intended as an attempt to build open, interconnected databases, that is databases that distribute their objects worldwide in compliance with a recognized standard of distribution. Maps can be displayed and compared with a java applet (http://babbage.infobiogen.fr:15000/Mappet/Show. html ) that queries the HuGeMap ORB server as well as the RHdb ORB server at the EBI.     

GSDS: 基因结构显示系统

构建了一个用于绘制基因结构示意图的网站系统(http://gsds.cbi.pku.edu.cn/)。用户可提交核酸序列、NCBI核酸序列号或基因外显子位置信息, 得到基因结构示意图; 并可指定在基因结构图上标注某些特定区域。系统允许用户同时输入多个基因, 并指定输出次序和标注区域。结果可用位图和矢量图两种图形格式显示。点击位图格式结果, 可以查看相应序列。系统提供中英文两种用户界面。     

CRCView: a web server for analyzing and visualizing microarray gene expression data using model-based clustering

CRCView is a user-friendly point-and-click web server for analyzing and visualizing microarray gene expression data using a Dirichlet process mixture model-based clustering algorithm. CRCView is designed to clustering genes based on their expression profiles. It allows flexible input data format, rich graphical illustration as well as integrated GO term based annotation/interpretation of clustering results. Availability: http://helab.bioinformatics.med.umich.edu/crcview/.