Open thesis topics

Metatranscriptome assembly (M.Sc.)

Background

Advances in sequencing technologies have enabled the study of microbial communities, their composition and their genetic potential. In a culture-independent approach known as metagenomics, DNA is obtained directly from the environment and the resulting sequence data is analyzed in order to derive taxonomic community profiles as well as metabolic potential. In a similar manner, translated mRNA of bacterial communities is sequenced (environmental ``RNA-Seq'' or metatranscriptomics) and processed, thereby allowing to identify transcribed genes and perform differential gene expression analysis.

For the management, storage and analysis of such datasets, we have developed and operate the MGX platform, a client-server framework enabling scientists to conveniently process sequence data obtained from microbial communities. MGX offers a wide range of different analysis workflows for taxonomic and functional profiling of metagenome datasets based on unassembled sequence data. Recently, MGX was also extended with a pipeline based on the Common Workflow Language (CWL) supporting metagenome assembly, gene prediction, quantification and taxonomic binning.
Within the scope of de.NBI, the German network for bioinformatics infrastructure, MGX is provided as one the flagship services by the Bielefeld-Giessen Center for microbial bioinformatics.

Thesis aims

• Design and implementation of a bioinformatics pipeline for the de novo assembly, quantification, and binning of metatranscriptome datasets based on CWL,
• performance evaluation of the pipeline with regard to choice of transcriptome
  assembler software (e.g. Trinity, rnaSPAdes) , and
• exemplary analysis of a sample metatranscriptome dataset.

Prerequisites

• In-depth knowledge of the Linux command line
• Prior experience with workflow systems, preferably Common Workflow Language (CWL)
• Ability to work independently
• Methodical way of working

Contact: Sebastian Jaenicke

Bacterial promoter annotation assistant (M.Sc.)

Background

The ability to withstand environmental changes makes bacteria omnipresent in the entire world. The act of change responses relies on the capability to precisely target genes for transcription. One key regulatory element is the gene's promoter, where the -35 and -10 regions are recognized by sigma factors, which lead the RNA polymerase to the transcription start site. In general, bacteria encode for several various sigma factors, which also target different promoters, and therefore, establish specific responses for numerous stress-conditions. Consequently, promoter and co-transcribed gene analysis are essential to understand and manipulate an organism's transcriptome. Until now, there are several tools, which predict promoters and regulons, based on manually curated promoter sequences. Unfortunately, there are only a few databases for promoter regions, which rely on manually curated data; and if they are available, most of them are outdated.
Therefore, to ensure quality for annotated promoter regions, a small web service has to be established to help scientists annotate promoters in a way where machines and humans can interact efficiently and reproducible (see FAIR principles).

Thesis Aims

• Design and implementation for a web service/database to annotate, store and retrieve promoters of several bacterial organisms
• Evaluate the usability of the newly developed platform

Prerequisites

• Knowledge of
• web development frameworks including testing, preferably Ruby on Rails with Rspec and Cucumber
• JavaScript frameworks, preferably vue.js
• containerization software, preferably docker, docker-compose, k8s
• CI/CD
• Ability to work independently
• Methodical way of working
• Excellent command in spoken and written English

Contact: Raphael Müller

Also, additional thesis topics are offered by the group for Algorithmic Bioinfomatics of Prof. Stefan Janssen; a comprehensive list of open theses is available.