Climate change, pollution or planned mining activities have and will have impacts on ocean ecosystems and thus, on the distribution of functions and metabolisms bolstered by their microbial denizens. For example, mechanisms of chemolithoautotrophy in mineral deposits are poorly understood yet functional gene markers exist to quantify their potential and notably in regions where their removal is likely. Similarly, markers of gene and plasmid exchange or of resource utilization also exist, allowing for their quantification in relation to temperature change or other drivers, at global scale.
Shotgun metagenomics is an environmental DNA sequencing approach that offers deep insights into such functional potentials at the levels of genomes or even strains. Today, metagenomics can address new, function-centered questions by leveraging the unprecedented statistical power of large, global, and public ocean genomics datasets. We invite highly motivated master students interested by metagenomic and microbiome data analysis, bioinformatics, and biostatistics to join our team. We will explore the spatial distribution, differential abundance, and phylogenetic context of specific microbial functions across marine provinces representing climatic regimes predicted to experience change.
The candidate will start with exploring the scientific literature related to the fertile topic of marine microbiology and environmental DNA sequencing. This will clarify thinking to elaborate a precise and testable research question focused on key microbial gene functions. Relevant open-access data and metadata from selected studies will be collected and tidied for analysis. The candidate may establish professional communications with peers to ask for missing information, when necessary (often). The candidate will be trained to use and contribute to the code of a python, class-oriented software pipeline tailored for supercomputers, as well as working from scratch on such infrastructures. The pipeline outputs will be explored using state-of-the-art biostatistics and innovative data visualization techniques, to fuel insightful discussions as the project progress and opportunities to present results arise. We expect the candidate to be able to demonstrate creative and critical thinking when interpreting retrospective, publicly available data, which will be key for the production of at least one scientific article.
Desired skills:
- Previous exposure to the Unix environment
- Basics in python programming (I/O, importing, data structures)
- Curiosity, motivation, and open-science philosophy
Expected gain:
- Mastery in python applied to running start-to-end shotgun metagenomics pipelines
- Ability to reprocess large public datasets and publish meta-analysis results
- Learning code development in team and testing (unit-testing and best practices)
Supervisors: Main PhD Franck Lejzerowicz and co-supervisor: Prof. Alexander Eiler, Department of Biosciences, Section for Aquatic Biology and Toxicology