Welcome

We are always looking for motivated students to join the group. We have many projects and ideas for assistants and bachlor/master theses in areas such as:

  • de novo transcriptome assembly
  • prokaryotic annotation pipelining
  • high-throughput data visualization
  • virus bioinformatics
  • long-read analysis

Some examples are given here, please contact me directly for more details.

Analysis of host/virus sequencing data: differential alternative splicing during viral infections

Alternative splicing plays crucial roles during many biological processes. Especially, when a host system is challenged by a viral infection, the splicing machinery seems to be disturbed. However, it is not understood on a large scale how viral infections affect the splicing machinery and result in differential expressed isoforms. We want to use transcriptomic (RNA-Seq) datasets publicly available from databases as the NCBI SRA to screen for differential alternative splicing events (such as intron retention, exon skipping, …) and to identify genes, that are generally affected during viral infections.

Pan-genome pipeline: calculation of bacterial core gene sets (or “dudes”)

Defining the core gene set, so the genes that are common among many species (or bacterial strains), is still a challenging task. Although computational tools already exist (Roary, BPGA, panX, …), an easy-to-use pipeline that starts with bacterial genomes as input and automizes all steps from the annotation, clustering, visualization of the results and the downstream analyses (such as phylogeny) is needed. In a pilot project, we already showed that combining sequence homology output and ILPs to resolve gene clusters can outperform current workflows. Here, you can help to test and extend our preliminary pipeline called RIBAP (written in python).

Differential isoform expression analysis by combining short- and long-read data

Long-read sequencing, as provided by Oxford Nanopore Technologies (ONT), is not only revolutionizing genomics but also the way we are able to analyze transcriptomes nowadays. With nanopores, we can for the first time directly sequence native RNA and therefore transcripts in their entirety. Especially for non-model organisms with no available genome sequence, sequencing the transcriptome can directly help to tackle various biological questions. We want to combine short- (Illumina) and long-read (ONT) transcriptomic data to characterize and quantify isoforms de novo.

Identification and annotation of plasmids

Plasmids are most commonly found as small circular, double-stranded DNA molecules in bacteria. In nature, they often carry genes that may benefit the survival of an organism, for example, antibiotic resistance. We want to evaluate current computational tools for plasmid annotation and aim to establish a pipeline for the automatic identification and annotation of plasmids, that should be inspired by the Mitos web service for the specific annotation of mitochondrial genomes. An easy-to-use workflow and a comprehensive visualization of the annotations will be crucial parts.

News

08. May 2021

Many laboratories have ramped up nanopore sequencing for SARS-CoV-2 surveillance, but are in dire need of bioinformatics support. Here we present poreCov, a high-throughput software pipeline for reliable genotyping and reference-based genome reconstruction of SARS-CoV-2 samples based on nanopore tiled amplicon sequencing focused around the ARTIC protocol. On GitHub! Big kudos @CaSe Group Jena!

11. April 2021

Our chromosome-level hybrid genome assembly with RNA-Seq-improved annotation of the oleaginous yeast Rhodotorula toruloides is out as a preprint! Great collaboration w/ the Swedish University of Agricultural Sciences, Uppsala (SLU)!

05. April 2021

Finally! Together with great colleagues from ANSES in France (among others) we describe a new genus Chlamydiifrater gen. nov. inside the family Chlamydiaceae isolated from flamingo! The bioinformatics part actually started with Fabien visiting us in 2016 and 2017 to learn about assembly and finally found its successful conclusion with the analysis of nanopore data and high-quality genomes.

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