Omanische Heilpflanze im Fokus der Phytochemie IPB-Wissenschaftler und Partner aus Dhofar haben jüngst die omanische Heilpflanze Terminalia dhofarica unter die phytochemische Lupe genommen. Die Pflanze ist reich an…
Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
The historic developmental hourglass concept depicts the convergence of animal embryos to a common form during the phylotypic period. Recently, it has been shown that a transcriptomic hourglass is associated with this morphological pattern, consistent with the idea of underlying selective constraints due to intense molecular interactions during body plan establishment. Although plants do not exhibit a morphological hourglass during embryogenesis, a transcriptomic hourglass has nevertheless been identified in the model plant Arabidopsis thaliana. Here, we investigated whether plant hourglass patterns are also found post-embryonically. We found that the two main phase changes during the life cycle of Arabidopsis, from embryonic to vegetative and from vegetative to reproductive development, are associated with transcriptomic hourglass patterns. In contrast, flower development, a process dominated by organ formation, is not. This suggests that plant hourglass patterns are decoupled from organogenesis and body plan establishment. Instead, they may reflect general transitions through organizational checkpoints.
Publikation
Drost, H.-G.; Gabel, A.; Grosse, I.; Quint, M.;Evidence for Active Maintenance of Phylotranscriptomic Hourglass Patterns in Animal and Plant EmbryogenesisMol. Biol. Evol.321221-1231(2015)DOI: 10.1093/molbev/msv012
The developmental hourglass model has been used to describe the morphological transitions of related species throughout embryogenesis. Recently, quantifiable approaches combining transcriptomic and evolutionary information provided novel evidence for the presence of a phylotranscriptomic hourglass pattern across kingdoms. As its biological function is unknown it remains speculative whether this pattern is functional or merely represents a nonfunctional evolutionary relic. The latter would seriously hamper future experimental approaches designed to test hypotheses regarding its function. Here, we address this question by generating transcriptome divergence index (TDI) profiles across embryogenesis of Danio rerio, Drosophila melanogaster, and Arabidopsis thaliana. To enable meaningful evaluation of the resulting patterns, we develop a statistical test that specifically assesses potential hourglass patterns. Based on this objective measure we find that two of these profiles follow a statistically significant hourglass pattern with the most conserved transcriptomes in the phylotypic periods. As the TDI considers only recent evolutionary signals, this indicates that the phylotranscriptomic hourglass pattern is not a rudiment but possibly actively maintained, implicating the existence of some linked biological function associated with embryogenesis in extant species.
Publikation
Nettling, M.; Treutler, H.; Grau, J.; Keilwagen, J.; Posch, S.; Grosse, I.;DiffLogo: a comparative visualization of sequence motifsBMC Bioinformatics16387(2015)DOI: 10.1186/s12859-015-0767-x
BackgroundFor three decades, sequence logos are the de facto standard for the visualization of sequence motifs in biology and bioinformatics. Reasons for this success story are their simplicity and clarity. The number of inferred and published motifs grows with the number of data sets and motif extraction algorithms. Hence, it becomes more and more important to perceive differences between motifs. However, motif differences are hard to detect from individual sequence logos in case of multiple motifs for one transcription factor, highly similar binding motifs of different transcription factors, or multiple motifs for one protein domain.ResultsHere, we present DiffLogo, a freely available, extensible, and user-friendly R package for visualizing motif differences. DiffLogo is capable of showing differences between DNA motifs as well as protein motifs in a pair-wise manner resulting in publication-ready figures. In case of more than two motifs, DiffLogo is capable of visualizing pair-wise differences in a tabular form. Here, the motifs are ordered by similarity, and the difference logos are colored for clarity. We demonstrate the benefit of DiffLogo on CTCF motifs from different human cell lines, on E-box motifs of three basic helix-loop-helix transcription factors as examples for comparison of DNA motifs, and on F-box domains from three different families as example for comparison of protein motifs.ConclusionsDiffLogo provides an intuitive visualization of motif differences. It enables the illustration and investigation of differences between highly similar motifs such as binding patterns of transcription factors for different cell types, treatments, and algorithmic approaches.
Publikation
Moreno, P.; Beisken, S.; Harsha, B.; Muthukrishnan, V.; Tudose, I.; Dekker, A.; Dornfeldt, S.; Taruttis, F.; Grosse, I.; Hastings, J.; Neumann, S.; Steinbeck, C.;BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontologyBMC Bioinformatics1656(2015)DOI: 10.1186/s12859-015-0486-3
BackgroundOntology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis.ResultsWe describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology.ConclusionsBiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.