What we do

Our research revolves around the bioinformatic integration and analysis of datasets from state-of-the-art omics technologies, which we obtain through close collaboration with experimental biologists. These datasets include genome sequences, gene and protein expression, as well as metabolomics data.
One focus is to exploit the unique advantages of proteomics data, including strategies to identify all proteins encoded in a genome (proteogenomics). Another focus is to study the role of microbiomes - e.g. for plant protection - by applying metagenomic, comparative genomic and transcriptomic approaches and integration of the resulting datasets.

Highlights 2018

One highlight was the de novo assembly of a prokaryote with a highly complex genome harboring near identical repeats of 70 kb in length, which contained genes that may confer a fitness advantage. Such highly complex genomes represented about 10% of all prokaryotic genomes. Very long reads allow to assemble such genomes without the need for labor-intense manual steps like optical mapping, primer walking, etc. We released the repeat complexity assessment for almost 10'000 prokaryotic genomes.

We also applied our expertise in genome assembly and comparative genomics on a project studying cheese starter cultures.

Finally, we applied our integrative proteogenomics strategy to identify missed protein-coding genes in prokaryotes on additional model organisms. A public web server allows researchers to create such integrated proteogenomics search databases (iPtgxDBs), as well as GFF files that integrate different annotations, transparently capturing overlap and differences.

Find out more about the Group’s activities

Main publications 2018

  • Schmid M et al.
    Pushing the limits of de novo genome assembly for complex prokaryotic genomes harboring very long, near identical repeats.
    Nucl Acid Res, https://doi.org/10.1093/nar/gky726
  • Schmid M et al.
    Comparative genomics of completely sequencedl Lactobacillus helveticus genomes provides insights into strain-specific genes and resolves metagenomics data down to the strain level.
    Front Microbiol, doi: 10.3389/fmicb.2018.00063




Zurich university waedenswil

Christian Ahrens
Bioinformatics and Proteogenomics Group
Agroscope, Wädenswil
Group Webpage

Domain(s) of activity:

  • Proteins and proteomes
  • Comparative genomics
  • Data mining
  • Drug resistance
  • Functional genomics
  • Metagenomics
  • Microbiology
  • Next generation sequencing
  • Proteomics
  • Software engineering
  • Transcriptomics

Domain(s) of application:

  • Agriculture
  • Basic research