• Our aim is to advance our understanding of biological systems,

    ranging from single species to multi-species systems and ecosystems,

    based on data from large-scale bioanalytical methods.

  • We develop, improve and apply

    computational methods

    for the interpretation of molecular information in biology.

  • We establish and analyse

    quantitative mathematical models.

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Latest publications

scikit-hubness: Hubness Reduction and Approximate Neighbor Search

scikit-hubness is a Python package for efficient nearest neighbor search in high-dimensional spaces. Hubness is an aspect of the curse of dimensionality in nearest neighbor graphs. Specifically, it describes the increasing occurrence of hubs and antihubs with growing data dimensionality: Hubs are objects, that appear unexpectedly often among the nearest neighbors of others objects, while antihubs are never retrieved as neighbors. As a consequence, hubs may propagate their information (for example, class labels) too widely within the neighbor graph, while information from antihubs is depleted. These semantically distorted graphs can reduce learning performance in various tasks, such as classification, clustering, or visualization. Hubness is known to affect a variety of applied learning systems, or improper transport mode detection.

Currently, there is a lack of fully-featured, up-to-date, user-friendly software dealing with hubness. Available packages miss critical features and have not been updated in years, or are not particularly user-friendly. In this paper we describe scikit-hubness, which provides powerful, readily available, and easy-to-use hubness-related methods.

Feldbauer R, Rattei T, Flexer A
2020 - The Journal of Open Source Software, 5: 1957

Exploring Actinobacteria Associated With Rhizosphere and Endosphere of the Native Alpine Medicinal Plant Subspecies .

The rhizosphere of plants is enriched in nutrients facilitating growth of microorganisms, some of which are recruited as endophytes. Endophytes, especially Actinobacteria, are known to produce a plethora of bioactive compounds. We hypothesized that subsp. (Edelweiss), a rare alpine medicinal plant, may serve as yet untapped source for uncommon Actinobacteria associated with this plant. Rhizosphere soil of native Alpine plants was used, after physical and chemical pre-treatments, for isolating Actinobacteria. Isolates were selected based on morphology and identified by 16S rRNA gene-based barcoding. Resulting 77 Actinobacteria isolates represented the genera , , , , , , , and . In parallel, Edelweiss plants from the same location were surface-sterilized, separated into leaves, roots, rhizomes, and inflorescence and pooled within tissues before genomic DNA extraction. Metagenomic 16S rRNA gene amplicons confirmed large numbers of actinobacterial operational taxonomic units (OTUs) descending in diversity from roots to rhizomes, leaves and inflorescences. These metagenomic data, when queried with isolate sequences, revealed an overlap between the two datasets, suggesting recruitment of soil bacteria by the plant. Moreover, this study uncovered a profound diversity of uncultured Actinobacteria from Rubrobacteridae, Thermoleophilales, Acidimicrobiales and unclassified Actinobacteria specifically in belowground tissues, which may be exploited by a targeted isolation approach in the future.

Oberhofer M, Hess J, Leutgeb M, Gössnitzer F, Rattei T, Wawrosch C, Zotchev SB
2019 - Front Microbiol, 2531

Hybrid de novo transcriptome assembly of poinsettia (Euphorbia pulcherrima Willd. Ex Klotsch) bracts.

Poinsettia is a popular and important ornamental crop, mostly during the Christmas season. Its bract coloration ranges from pink/red to creamy/white shades. Despite its ornamental value, there is a lack of knowledge about the genetics and molecular biology of poinsettia, especially on the mechanisms of color formation. We performed an RNA-Seq analysis in order to shed light on the transcriptome of poinsettia bracts. Moreover, we analyzed the transcriptome differences of red- and white-bracted poinsettia varieties during bract development and coloration. For the assembly of a bract transcriptome, two paired-end cDNA libraries from a red and white poinsettia pair were sequenced with the Illumina technology, and one library from a red-bracted variety was used for PacBio sequencing. Both short and long reads were assembled using a hybrid de novo strategy. Samples of red- and white-bracted poinsettias were sequenced and comparatively analyzed in three color developmental stages in order to understand the mechanisms of color formation and accumulation in the species.
The final transcriptome contains 288,524 contigs, with 33% showing confident protein annotation against the TAIR10 database. The BUSCO pipeline, which is based on near-universal orthologous gene groups, was applied to assess the transcriptome completeness. From a total of 1440 BUSCO groups searched, 77% were categorized as complete (41% as single-copy and 36% as duplicated), 10% as fragmented and 13% as missing BUSCOs. The gene expression comparison between red and white varieties of poinsettia showed a differential regulation of the flavonoid biosynthesis pathway only at particular stages of bract development. An initial impairment of the flavonoid pathway early in the color accumulation process for the white poinsettia variety was observed, but these differences were no longer present in the subsequent stages of bract development. Nonetheless, GSTF11 and UGT79B10 showed a lower expression in the last stage of bract development for the white variety and, therefore, are potential candidates for further studies on poinsettia coloration.
In summary, this transcriptome analysis provides a valuable foundation for further studies on poinsettia, such as plant breeding and genetics, and highlights crucial information on the molecular mechanism of color formation.

Vilperte V, Lucaciu CR, Halbwirth H, Boehm R, Rattei T, Debener T
2019 - BMC genomics, 1: 900