Biology subjects

Nussbaumer, T.

Publications and source records attributed to Nussbaumer, T..

3 recordsLinked to original sources

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↗