Biology subjects

Nussbaumer, T.

Publications and source records attributed to Nussbaumer, T..

8 recordsLinked to original sources

bioRxiv2020

Gexplora - user interface that highlights and explores the density of genomic elements along a chromosomal sequence

The density of genomic elements such as genes or transposable elements along its consecutive sequence can provide an overview of a genomic sequence while in the detailed analysis of candidate genes it may depict enriched chromosomal hotspots harbouring genes that explain a certain trait. The herein presented python-based graphical user interface Gexplora allows to obtain more information about a genome by considering sequence-intrinsic information from external databases such as Ensembl, OMA and STRING database using REST API calls to retrieve sequence-intrinsic information, protein-protein datasets and orthologous groups. Gexplora is available under https://github.com/nthomasCUBE/Gexplora.

genomics↗

bioRxiv2020

COMPOSITUM 1 (COM1) contributes to the architectural simplification of barley inflorescence via cell wall-mediated and meristem identity signals

Grasses have varying inflorescence shapes; however, little is known about the genetic mechanisms specifying such shapes among tribes. We identified the grass-specific TCP transcription factor COMPOSITUM 1 (COM1) expressed in inflorescence meristematic boundaries of different grasses. COM1 specifies branch-inhibition in Triticeae (barley) versus branch-formation in non-Triticeae grasses. Analyses of cell size, cell walls and transcripts revealed barley COM1 regulates cell growth, affecting cell wall properties and signaling specifically in meristematic boundaries to establish identity of adjacent meristems. COM1 acts upstream of the boundary gene Liguleless1 and confers meristem identity partially independent of the COM2 pathway. Furthermore, COM1 is subject to purifying natural selection, thereby contributing to specification of the spike inflorescence shape. This meristem identity pathway has conceptual implications for both inflorescence evolution and molecular breeding in Triticeae.

plant biology↗

bioRxiv2019

MicrobComp - graphical user interface enables an in-silico comparison of taxonomic differences between two amplicon datasets

The experimental and computational analysis of microbes is in the focus of basic and applied research for several decades already and has massively extended our knowledge of role and impact of microbes during that time.\n\nAmplicon sequencing is still widely adapted and standard procedure to determine key species in a biological sample and despite a high number of different datasets being steadily generated and fed into current data archives, there is a shortcoming in data interpretation. Furthermore, more computational tools are still required to guide the researcher towards an in-depth understanding of an experiment in a more systematic way. Towards that aim, MicrobComp was created as a graphical user interface which allows to compare two separate species frequency tables that contain the relative or absolute abundance of microbial species in an experiment. Therefore, this tool can be of great help when studying different amplicon experiments where studies were originally performed in different experimental labs.

bioinformatics↗

bioRxiv2019

TraitCorr - correlating gene expression measurements with phenotypic data

Today, transcriptomes and microarrays can be generated and analysed in high quantity. In addition, experiments often include descriptive information about each sample which needs to be compared to the gene expression profiles. The understanding of the relationships between gene expression and phenotype is introduced as new challenge in system biology. Combining expression (RNA-seq and microarray) and phenotype data could reveal the role or effects of each gene on traits. To address all these needs, the user-interface TraitCorr was developed which allows to determine genes that are significantly correlating with a selected trait. Furthermore, it allows to determine significantly correlated genes among different traits and provides visualisation and analysis possibilities.

bioinformatics↗

bioRxiv2019

Host_microbe_PPI - R package to analyse intra-species and inter-species protein-protein interactions in the model plant Arabidopsis thaliana

Intra-species protein-protein interactions (PPI) provide valuable information about the systemic response of a model species when facing either abiotic and biotic stress conditions. Inter-species PPI can otherwise offer insights into how microbes interact with its host and can provide clues how early infection mechanism takes place. To understand these processes in a more comprehensive way and to compare it with experimental outcomes from omics studies, we require additional methods to analyse and visualize PPI data. We demonstrate the user-interface host_microbe_PPI that is implemented in R Shiny. It allows for interactively analysing inter-species and intra-species datasets from various published Arabidopsis thaliana datasets. It enables among other features comparisons of the centrality measurements (degree, betweenness and closeness) and analysis the existence of orthologous proteins in closely related genomes, e.g. when gene loss in host and non-host plants is compared. Arabidopsis was used even so the tool can be also applied in other host-microbe systems.

bioinformatics↗

bioRxiv2018

Stage-specific transcriptomes and DNA methylomes indicate an early and transient loss of transposon control in Arabidopsis shoot stem cells

In contrast to animals, postembryonic development in plants is modular, and aerial organs originate from stem cells in the center of the shoot apical meristem (SAM) throughout life. Descendants of SAM stem cells in the subepidermal layer (L2) give also rise to male and female gametes (reviewed in 1) and are therefore considered primordial germ cells. In these cells, transmission of somatic mutations including virus and TE insertions must be avoided. Despite their essential role for plant development and intergenerational continuity, no comprehensive molecular analysis of SAM stem cells exists, due to their low number, deep embedding among non-stem cells, and difficult isolation. Here we present a comprehensive analysis of stage-specific gene expression and DNA methylation dynamics in Arabidopsis SAM stem cells. Stem cell expression signatures are mostly defined by development, but we also identified a core set of differentially expressed stemness genes. Surprisingly, vegetative SAM stem cells showed increased expression of transposable elements (TEs) relative to surrounding cells, despite high expression of genes connected to epigenetic silencing. We also find increasing methylation at CHG and a drop in CHH methylation at TEs before stem cells enter the reproductive lineage, indicating an onset of epigenetic reprogramming at an early stage. Transiently elevated TE expression is reminiscent of that in animal primordial germ cells (PGCs) 2 and demonstrates commonality of transposon biology. Our results connect SAM stem cells with germline development and transposon evolution and will allow future experiments to determine the degree of epigenetic heritability between generations.

developmental biology↗

bioRxiv2017

Host_microbe_mapper allows to analyse and interpret the expression of dual RNA-seq measurements and reveals potential microbial contaminations in the data

Next-generation sequencing technologies provide a wealth of sequencing data. To handle these data amounts, various tools were developed over the last years for mapping, normalisation and functional analyses. To support researchers in the interpretation of expression measurements originating from dual RNA-seq studies and from host-microbe systems in particular, the computational pipeline host_microbe_mapper can be applied to quantify and interpret dual RNA-seq datasets in host-microbe experiments. The pipeline with all the required scripts is stored at the Github repository (https://github.com/nthomasCUBE/hostmicrobemapper).

bioinformatics↗

bioRxiv2017

BioSankey: Visualizing microbial communities and gene expression data over time

Metagenomics, RNA-seq, WGS (Whole Genome Sequencing) and other types of next-generation sequencing techniques provide quantitative measurements for single strains and genes over time. To obtain a global overview of the experiment and to explore the full potential of a given dataset, intuitive and interactive visualization tools are needed. Therefore, we established BioSankey, which allows to visualize microbial species in microbiome studies and gene expression over time as a Sankey diagram. These diagrams are embedded into a project-specific HTML page, that contains all information as provided during the installation process. BioSankey can be easily applied to analyse bacterial communities in time-series datasets. Furthermore, it can be used to analyse the fluctuations of differentially expressed genes (DEG). The output of BioSankey is a project-specific HTML page, which depends only on JavaScript to enable searches of interesting species or genes of interest without requiring a web server or connection to a database to exchange results among collaboration partners. BioSankey is a tool to visualize different data elements from single and dual RNA-seq datasets as well as from metagenomes studies.

bioinformatics↗