Genome-Wide Analysis of the Circulating miRNome After Cerebral Ischemia Reveals a Reperfusion-Induced MicroRNA Cluster.

BACKGROUND AND PURPOSE: Circulating microRNAs (miRNAs) are emerging biomarkers for stroke because of their high stability in the bloodstream and association with pathophysiologic conditions. However, the circulating whole-genome miRNAs (miRNome) has not been characterized comprehensively in the acute phase of stroke. METHODS: We profiled the circulating miRNome in mouse models of acute ischemic and hemorrhagic stroke by next-generation sequencing. Stroke models were compared with sham-operated and naive mice to identify deregulated circulating miRNAs. Top-ranked miRNAs were validated and further characterized by quantitative reverse transcription polymerase chain reaction. RESULTS: We discovered 24 circulating miRNAs with an altered abundance in the circulation 3 hours after ischemia, whereas the circulating miRNome was not altered after intracerebral hemorrhage compared with sham-operated mice. Among the upregulated miRNAs in ischemia, the top-listed miR-1264/1298/448 cluster was strongly dependent on reperfusion in different ischemia models. A time course experiment revealed that the miR-1264/1298/448 cluster peaked in the circulation around 3 hours after reperfusion and gradually decreased thereafter. CONCLUSIONS: Alteration of the miRNome in the circulation is associated with cerebral ischemia/reperfusion, but not hemorrhage, suggesting a potential to serve as biomarkers for reperfusion in the acute phase. The pathophysiological role of reperfusion-inducible miR-1264/1298/448 cluster, which is located on chromosome X within the introns of the serotonin receptor HTR2C, requires further investigation.

SplicingCompass: differential splicing detection using RNA-seq data.

MOTIVATION: Alternative splicing is central for cellular processes and substantially increases transcriptome and proteome diversity. Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types. The emergence of next-generation RNA sequencing (RNA-seq) provides an exciting new technology to analyse alternative splicing on a large scale. However, algorithms that enable the analysis of alternative splicing from short-read sequencing are not fully established yet and there are still no standard solutions available for a variety of data analysis tasks. RESULTS: We present a new method and software to predict genes that are differentially spliced between two different conditions using RNA-seq data. Our method uses geometric angles between the high dimensional vectors of exon read counts. With this, differential splicing can be detected even if the splicing events are composed of higher complexity and involve previously unknown splicing patterns. We applied our approach to two case studies including neuroblastoma tumour data with favourable and unfavourable clinical courses. We show the validity of our predictions as well as the applicability of our method in the context of patient clustering. We verified our predictions by several methods including simulated experiments and complementary in silico analyses. We found a significant number of exons with specific regulatory splicing factor motifs for predicted genes and a substantial number of publications linking those genes to alternative splicing. Furthermore, we could successfully exploit splicing information to cluster tissues and patients. Finally, we found additional evidence of splicing diversity for many predicted genes in normalized read coverage plots and in reads that span exon-exon junctions. AVAILABILITY: SplicingCompass is licensed under the GNU GPL and freely available as a package in the statistical language R at http://www.ichip.de/software/SplicingCompass.html

Spatial localization of genes determined by intranuclear DNA fragmentation with the fusion proteins lamin KRED and histone KRED und visible light.

The highly organized DNA architecture inside of the nuclei of cells is accepted in the scientific world. In the human genome about 3 billion nucleotides are organized as chromatin in the cell nucleus. In general, they are involved in gene regulation and transcription by histone modification. Small chromosomes are localized in a central nuclear position whereas the large chromosomes are peripherally positioned. In our experiments we inserted fusion proteins consisting of a component of the nuclear lamina (lamin B1) and also histone H2A, both combined with the light inducible fluorescence protein KillerRed (KRED). After activation, KRED generates reactive oxygen species (ROS) producing toxic effects and may cause cell death. We analyzed the spatial damage distribution in the chromatin after illumination of the cells with visible light. The extent of DNA damage was strongly dependent on its localization inside of nuclei. The ROS activity allowed to gain information about the location of genes and their functions via sequencing and data base analysis of the double strand breaks of the isolated DNA. A connection between the damaged gene sequences and some diseases was found.

Genome-wide prediction of splice-modifying SNPs in human genes using a new analysis pipeline called AASsites.

BACKGROUND: Some single nucleotide polymorphisms (SNPs) are known to modify the risk of developing certain diseases or the reaction to drugs. Due to next generation sequencing methods the number of known human SNPs has grown. Not all SNPs lead to a modified protein, which may be the origin of a disease. Therefore, the recognition of functional SNPs is needed. Because most SNP annotation tools look for SNPs which lead to an amino acid exchange or a premature stop, we designed a new tool called AASsites which searches for SNPs which modify splicing. RESULTS: AASsites uses several gene prediction programs and open reading frame prediction to compare the wild type (wt) and the variant gene sequence. The results of the comparison are combined by a handmade rule system to classify a change in splicing as "likely, probable, unlikely". Having received good results from tests with SNPs known for changing the splicing pattern we checked 80,000 SNPs from the human genome which are located near splice sites for their ability to change the splicing pattern of the gene and hereby result in a different protein. We identified 301 "likely" and 985 "probable" classified SNPs with such characteristics. Within this set 33 SNPs are described in the ssSNP Target database to cause modified splicing. CONCLUSIONS: With AASsites single SNPs can be checked for those causing splice modifications. Screening 80,000 known human SNPs we detected about 1,200 SNPs which probably modify splicing. AASsites is available at http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar using any web browser.

New miRNAs cloned from neuroblastoma.

BACKGROUND: MicroRNAs (miRNAs) are a novel class of gene expression regulators implicated in cancer biology. Neuroblastoma (NB) is an embryonal tumour consisting of neural crest-derived undifferentiated cells and is characterised by variable clinical courses ranging from spontaneous regression to therapy-resistant progression. Recent advances identified a subset of miRNAs with putative function in NB biology. However, the full repertoire of miRNAs expressed in NBs is not available. RESULTS: We describe miRNA profiles of 13 NB specimens and 2 NB cell lines as determined by miRNA cloning. A total of 3153 sequences were sequenced and analysed by a miRNA prediction tool (miRpredict). Our library covered 27% miRNAs known to date. 39 reads corresponding to 25 individual sequences were classified as novel miRNAs, including miRNA* species of 10 known miRNAs. Expression of 5 new miRNA* forms and 8 individual sequences was supported by Northern blotting. Most of the novel miRNA genes are not related to each other and do not share homology with the annotated sequences in the public miRNA database, but they are conserved within mammals or have close homologues in primates genomes. CONCLUSION: We provide evidence for 29 new miRNA and miRNA-like sequences (24 novel sequences and 5 miRNAs discovered initially in other species). Some of these newly identified sequences reside within frequently altered chromosomal regions in NB tumours and may play a role in NB biology.

The LIFEdb database in 2006.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

GOPET: a tool for automated predictions of Gene Ontology terms.

BACKGROUND: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. DESCRIPTION: We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar CONCLUSION: Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

CAFTAN: a tool for fast mapping, and quality assessment of cDNAs.

BACKGROUND: The German cDNA Consortium has been cloning full length cDNAs and continued with their exploitation in protein localization experiments and cellular assays. However, the efficient use of large cDNA resources requires the development of strategies that are capable of a speedy selection of truly useful cDNAs from biological and experimental noise. To this end we have developed a new high-throughput analysis tool, CAFTAN, which simplifies these efforts and thus fills the gap between large-scale cDNA collections and their systematic annotation and application in functional genomics. RESULTS: CAFTAN is built around the mapping of cDNAs to the genome assembly, and the subsequent analysis of their genomic context. It uses sequence features like the presence and type of PolyA signals, inner and flanking repeats, the GC-content, splice site types, etc. All these features are evaluated in individual tests and classify cDNAs according to their sequence quality and likelihood to have been generated from fully processed mRNAs. Additionally, CAFTAN compares the coordinates of mapped cDNAs with the genomic coordinates of reference sets from public available resources (e.g., VEGA, ENSEMBL). This provides detailed information about overlapping exons and the structural classification of cDNAs with respect to the reference set of splice variants. The evaluation of CAFTAN showed that is able to correctly classify more than 85% of 5950 selected "known protein-coding" VEGA cDNAs as high quality multi- or single-exon. It identified as good 80.6 % of the single exon cDNAs and 85 % of the multiple exon cDNAs. The program is written in Perl and in a modular way, allowing the adoption of this strategy to other tasks like EST-annotation, or to extend it by adding new classification rules and new organism databases as they become available. We think that it is a very useful program for the annotation and research of unfinished genomes. CONCLUSION: CAFTAN is a high-throughput sequence analysis tool, which performs a fast and reliable quality prediction of cDNAs. Several thousands of cDNAs can be analyzed in a short time, giving the curator/scientist a first quick overview about the quality and the already existing annotation of a set of cDNAs. It supports the rejection of low quality cDNAs and helps in the selection of likely novel splice variants, and/or completely novel transcripts for new experiments.

LIFEdb: a database for functional genomics experiments integrating information from external sources, and serving as a sample tracking system.

We have implemented LIFEdb (http://www.dkfz.de/LIFEdb) to link information regarding novel human full-length cDNAs generated and sequenced by the German cDNA Consortium with functional information on the encoded proteins produced in functional genomics and proteomics approaches. The database also serves as a sample-tracking system to manage the process from cDNA to experimental read-out and data interpretation. A web interface enables the scientific community to explore and visualize features of the annotated cDNAs and ORFs combined with experimental results, and thus helps to unravel new features of proteins with as yet unknown functions.

ESTAnnotator: A tool for high throughput EST annotation.

In high throughput sequence analysis, it is often necessary to combine the results of contemporary bioinformatics tools, because no individual tool alone computes all the requested information. ESTAnnotator is a tool for the high throughput annotation of expressed sequence tags (ESTs) by automatically running a collection of bioinformatics applications. In the first step, a quality check is performed and repeats, vector parts and low quality sequences are masked. Then successive steps of database searching and EST clustering are performed. Already known transcripts present within mRNA and genomic DNA reference databases are identified. Subsequently, tools for the clustering of anonymous ESTs, and for further database searches at the protein level, are applied. Finally, the outputs of each individual tool are gathered and the relevant results presented in a descriptive summary. ESTAnnotator was already successfully applied for the systematic identification and characterisation of novel human genes involved in cartilage/bone formation, growth, differentiation and homeostasis. ESTAnnotator is available at http://genome.dkfz-heidelberg.de, contact: genome@dkfz.de.

High-throughput protein analysis integrating bioinformatics and experimental assays.

The wealth of transcript information that has been made publicly available in recent years requires the development of high-throughput functional genomics and proteomics approaches for its analysis. Such approaches need suitable data integration procedures and a high level of automation in order to gain maximum benefit from the results generated. We have designed an automatic pipeline to analyse annotated open reading frames (ORFs) stemming from full-length cDNAs produced mainly by the German cDNA Consortium. The ORFs are cloned into expression vectors for use in large-scale assays such as the determination of subcellular protein localization or kinase reaction specificity. Additionally, all identified ORFs undergo exhaustive bioinformatic analysis such as similarity searches, protein domain architecture determination and prediction of physicochemical characteristics and secondary structure, using a wide variety of bioinformatic methods in combination with the most up-to-date public databases (e.g. PRINTS, BLOCKS, INTERPRO, PROSITE SWISSPROT). Data from experimental results and from the bioinformatic analysis are integrated and stored in a relational database (MS SQL-Server), which makes it possible for researchers to find answers to biological questions easily, thereby speeding up the selection of targets for further analysis. The designed pipeline constitutes a new automatic approach to obtaining and administrating relevant biological data from high-throughput investigations of cDNAs in order to systematically identify and characterize novel genes, as well as to comprehensively describe the function of the encoded proteins.

cDNA2Genome: a tool for mapping and annotating cDNAs.

BACKGROUND: In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process. RESULTS: cDNA2Genome is an application for the automatic high-throughput mapping and characterization of cDNAs. It utilizes current annotation data and the most up to date databases, especially in the case of ESTs and mRNAs in conjunction with a vast number of approaches to gene prediction in order to perform a comprehensive assessment of the cDNA exon-intron structure. The final result of cDNA2Genome is an XML file containing all relevant information obtained in the process. This XML output can easily be used for further analysis such us program pipelines, or the integration of results into databases. The web interface to cDNA2Genome also presents this data in HTML, where the annotation is additionally shown in a graphical form. cDNA2Genome has been implemented under the W3H task framework which allows the combination of bioinformatics tools in tailor-made analysis task flows as well as the sequential or parallel computation of many sequences for large-scale analysis. CONCLUSIONS: cDNA2Genome represents a new versatile and easily extensible approach to the automated mapping and annotation of human cDNAs. The underlying approach allows sequential or parallel computation of sequences for high-throughput analysis of cDNAs.

Applying Support Vector Machines for Gene Ontology based gene function prediction.

BACKGROUND: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions. RESULTS: We have developed a large-scale annotation system that tackles all of these shortcomings. In our approach, annotation was provided through Gene Ontology terms by applying multiple Support Vector Machines (SVM) for the classification of correct and false predictions. The general performance of the system was benchmarked with a large dataset. An organism-wise cross-validation was performed to define confidence estimates, resulting in an average precision of 80% for 74% of all test sequences. The validation results show that the prediction performance was organism-independent and could reproduce the annotation of other automated systems as well as high-quality manual annotations. We applied our trained classification system to Xenopus laevis sequences, yielding functional annotation for more than half of the known expressed genome. Compared to the currently available annotation, we provided more than twice the number of contigs with good quality annotation, and additionally we assigned a confidence value to each predicted GO term. CONCLUSIONS: We present a complete automated annotation system that overcomes many of the usual problems by applying a controlled vocabulary of Gene Ontology and an established classification method on large and well-described sequence data sets. In a case study, the function for Xenopus laevis contig sequences was predicted and the results are publicly available at ftp://genome.dkfz-heidelberg.de/pub/agd/gene_association.agd_Xenopus.

The transcriptome of the colonial marine hydroid Hydractinia echinata.

An increasing amount of expressed sequence tag (EST) and genomic data, predominantly for the cnidarians Acropora, Hydra and Nematostella, reveals that cnidarians have a high genomic complexity, despite being one of the morphologically simplest multicellular animals. Considering the diversity of cnidarians, we performed an EST project on the hydroid Hydractinia echinata, to contribute towards a broader coverage of this phylum. After random sequencing of almost 9000 clones, EST characterization revealed a broad diversity in gene content. Corroborating observations in other cnidarians, Hydractinia sequences exhibited a higher sequence similarity to vertebrates than to ecdysozoan invertebrates. A significant number of sequences were hitherto undescribed in metazoans, suggesting that these may be either cnidarian innovations or ancient genes lost in the bilaterian genomes analysed so far. However, we cannot rule out some degree of contamination from commensal bacteria. The identification of unique Hydractinia sequences emphasizes that the acquired genomic information generated so far is not large enough to be representative of the highly diverse cnidarian phylum. Finally, a database was created to store all the acquired information (http://www.mchips.org/hydractinia_echinata.html).

Global expression analysis of the brown alga Ectocarpus siliculosus (Phaeophyceae) reveals large-scale reprogramming of the transcriptome in response to abiotic stress.

BACKGROUND: Brown algae (Phaeophyceae) are phylogenetically distant from red and green algae and an important component of the coastal ecosystem. They have developed unique mechanisms that allow them to inhabit the intertidal zone, an environment with high levels of abiotic stress. Ectocarpus siliculosus is being established as a genetic and genomic model for the brown algal lineage, but little is known about its response to abiotic stress. RESULTS: Here we examine the transcriptomic changes that occur during the short-term acclimation of E. siliculosus to three different abiotic stress conditions (hyposaline, hypersaline and oxidative stress). Our results show that almost 70% of the expressed genes are regulated in response to at least one of these stressors. Although there are several common elements with terrestrial plants, such as repression of growth-related genes, switching from primary production to protein and nutrient recycling processes, and induction of genes involved in vesicular trafficking, many of the stress-regulated genes are either not known to respond to stress in other organisms or are have been found exclusively in E. siliculosus. CONCLUSIONS: This first large-scale transcriptomic study of a brown alga demonstrates that, unlike terrestrial plants, E. siliculosus undergoes extensive reprogramming of its transcriptome during the acclimation to mild abiotic stress. We identify several new genes and pathways with a putative function in the stress response and thus pave the way for more detailed investigations of the mechanisms underlying the stress tolerance of brown algae.

A task framework for the web interface W2H.

SUMMARY: The W3H task framework allows the execution of compound jobs utilizing the description of work and data flows in a heterogeneous bioinformatics environment using meta-data information. By means of these descriptions, the task system can schedule the necessary execution of applications available in the environment, depending on rules specified in the meta-data. By integrating this task framework into the publicly available web interface W2H, similarly based on meta-data, web access and data management are immediately available for each task description. Authors of task descriptions can base their work on the underlying classes and objects to be able to describe dependency rules between previously independent applications. The result of a compound task is given as XML data that is translated according to XSLT data into web pages or plain text to report the result of the task to the user. AVAILABILITY: Within the HUSAR environment at DKFZ http://genome.dkfz-heidelberg.de/

PATH: a task for the inference of phylogenies.

UNLABELLED: Phylogenetic Analysis Task in Husar (PATH) is a task for the inference of phylogenies. It executes three phylogenetic methods and automatically chooses the evolutionary model for each set of data. The output of the tasks shows the consensus trees together with full results obtained from all executed methods. AVAILABILITY: PATH is available at the German EMBnet node after registration via www at http://genome.dkfz-heidelberg.de