Microbial Genomics

Course description
Microbes (bacteria, archaea and microbial eukaryotes, including fungi) are key members of our biosphere and are highly relevant for human life as mutualists and pathogens and as crucial drivers of nutrient cycling, agriculture, and many other aspects of our daily lives. The genomes of microbes provide a wealth of information on the processes and mechanisms that these organisms use in their environment. For instance, on mechanisms that pathogens use to overcome host immunity or antibiotics, or enzymes that fungi use to produce interesting metabolites that can be used in medicine or agriculture. Furthermore, microbes are commonly used as model systems to research molecules and molecular processes and to uncover how organisms function, develop, and interact with their environment.

In this course you will learn how to analyse genome data of individual microbes, but also of microbial communities (metagenomics). The first part of the course will be focused on basic bioinformatic skills (linux, bash, and command line tools) and the analysis of bacterial genomes. The second part will be focused on the analyses of eukaryotic microbes with a focus on fungal genomes, such as comparative approaches and gene expression analysis. The course will includetheoretical lectures, but will mainly consist of hands-on bioinformatic practicals. Therefore, interest to work with a computer is required (and desirable!).

Learning Objectives
At the end of the course, students are expected to be able to…

1. … understand the importance of (meta)genomics in microbial biology.
2. … know and explain differences in prokaryotic and eukaryotic genome structure.
3. … explain the power and usefulness of comparative genome analyses.
4. … navigate a computer file system using the command line.
5. … design automated workflows with a series of sequential commands and examine the results.
6. … identify, visualize, and interpret between and within species diversity.
7. … evaluate the quality of genome sequencing data.
8. … explain the impact of genome sequencing and assembly strategies as well as the genome structure on the quality of prokaryotic and eukaryotic genome sequences.
9. … develop a suitable workflow to analyse (re-)sequencing data and interpret the results.
10. … perform gene predictions from a genome sequence and understand its challenges and limitations.
11. … map transcriptome data, determine gene expression values, and perform differential gene expression analysis.
12. … perform functional annotation of predicted protein sequences and interpret the results.
13. … design and execute comparative genomics analyses and interpret the results.
14. … hypothesize on the causes of phenotypes associated with the different genomic datasets.

Knowledge about genome biologyand genome sequencing