EDGAR: A software framework for the comparative analysis of prokaryotic genomes

Blom J, Albaum S, Doppmeier D, et al. EDGAR: a software framework for the comparative analysis of prokaryotic genomes. BMC Bioinformatics. 2009;10(1): 154.Background:The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons. Results: To support these studies EDGAR – ''Efficient Database framework for comparative Genome Analyses using BLAST score Ratios'' – was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy. Conclusion: EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface http://edgar.cebitec.uni-bielefeld.de webcite, where the precomputed data sets can be browsed

Using the GUS Reporter Gene for Quantitative Studies of Promotor Activity in A.thaliana Seedlings

Doppmeier D, Stracke R, Lutter P, Goesmann A, Niehaus K, Weisshaar B. Using the GUS Reporter Gene for Quantitative Studies of Promotor Activity in A.thaliana Seedlings. Presented at the ICSB 2011 Heidelberg/Mannheim, Heidelberg/Mannheim, Germany

EDGAR: A software framework for the comparative analysis of prokaryotic genomes

Abstract Background The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons. Results To support these studies EDGAR – "Efficient Database framework for comparative Genome Analyses using BLAST score Ratios" – was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy. Conclusion EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface http://edgar.cebitec.uni-bielefeld.de, where the precomputed data sets can be browsed.</p

ReadXplorer - Visualization and Analysis of Mapped Sequences

Hilker R, Stadermann KB, Doppmeier D, et al. ReadXplorer - Visualization and Analysis of Mapped Sequences. Bioinformatics. 2014;30(16):2247-2254.MOTIVATION: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data. RESULTS: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion-insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets. AVAILABILITY AND IMPLEMENTATION: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. The Author 2014. Published by Oxford University Press

Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming

Blom J, Jakobi T, Doppmeier D, et al. Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming. Bioinformatics. 2011;27(10):1351-1358.Motivation: The introduction of next-generation sequencing techniques and especially the high-throughput systems Solexa (Illumina Inc.) and SOLiD (ABI) made the mapping of short reads to reference sequences a standard application in modern bioinformatics. Short-read alignment is needed for reference based re-sequencing of complete genomes as well as for gene expression analysis based on transcriptome sequencing. Several approaches were developed during the last years allowing for a fast alignment of short sequences to a given template. Methods available to date use heuristic techniques to gain a speedup of the alignments, thereby missing possible alignment positions. Furthermore, most approaches return only one best hit for every query sequence, thus losing the potentially valuable information of alternative alignment positions with identical scores. Results: We developed SARUMAN (Semiglobal Alignment of short Reads Using CUDA and NeedleMAN-Wunsch), a mapping approach that returns all possible alignment positions of a read in a reference sequence under a given error threshold, together with one optimal alignment for each of these positions. Alignments are computed in parallel on graphics hardware, facilitating an considerable speedup of this normally time-consuming step. Combining our filter algorithm with CUDA-accelerated alignments, we were able to align reads to microbial genomes in time comparable or even faster than all published approaches, while still providing an exact, complete and optimal result. At the same time, SARUMAN runs on every standard Linux PC with a CUDA-compatible graphics accelerator

Next-generation sequencing of the Chinese hamster ovary microRNA transcriptome: Identification, annotation and profiling of microRNAs as targets for cellular engineering

Hackl M, Jakobi T, Blom J, et al. Next-generation sequencing of the Chinese hamster ovary microRNA transcriptome: Identification, annotation and profiling of microRNAs as targets for cellular engineering. Journal of Biotechnology. 2011;153(1-2):62-75.Chinese hamster ovary (CHO) cells are the predominant cell factory for the production of recombinant therapeutic proteins. Nevertheless, the lack in publicly available sequence information is severely limiting advances in CHO cell biology, including the exploration of microRNAs (miRNA) as tools for CHO cell characterization and engineering. In an effort to identify and annotate both conserved and novel CHO miRNAs in the absence of a Chinese hamster genome, we deep-sequenced small RNA fractions of 6 biotechnologically relevant cell lines and mapped the resulting reads to an artificial reference sequence consisting of all known miRNA hairpins. Read alignment patterns and read count ratios of 5' and 3' mature miRNAs were obtained and used for an independent classification into miR/miR* and 5p/3p miRNA pairs and discrimination of miRNAs from other non-coding RNAs, resulting in the annotation of 387 mature CHO miRNAs. The quantitative content of next-generation sequencing data was analyzed and confirmed using qPCR, to find that miRNAs are markers of cell status. Finally, cDNA sequencing of 26 validated targets of miR-17-92 suggests conserved functions for miRNAs in CHO cells, which together with the now publicly available sequence information sets the stage for developing novel RNAi tools for CHO cell engineering