Population genomics

The population genomics team studies how ecological and evolutionary processes interactively culminate in disease outbreaks, using a combination of bioinformatics, experimental evolution and in silico modelling.

Crops are very successful species: cared for by dedicated farmers and grown in acres of genetically similar individuals. However, this also makes them an irresistible target for pathogens. New diseases caused by microbial pathogens emerge continuously, and known pathogens are able to rapidly adapt to resistant crop varieties.

Our methods

In the Population Genomics team, we use comparative genomics to reconstruct and compare evolutionary histories of microbial plant pathogens and closely related, more benign microbes. We delineate which ecological and evolutionary processes collectively contributed to the emergence of new diseases so that we better understand how we can prevent new diseases to arise and spread. 

In many species, genes that are important for infection are clustered in genomic islands, or on specific plasmids or chromosomes. Horizontal transfer of these gene clusters may result in the recipient individuals obtaining certain abilities. The ‘functional modules’ encoded by these gene clusters thus function as semi-autonomous evolutionary entities that can be mixed and matched in different genomic backgrounds. This is likely to contribute considerably to the speed of pathogen adaptation. Moreover, these gene clusters are often enriched with transposable elements, or “jumping genes”. These are often viewed as genomic parasites, yet could also aid in fast adaptation by increasing rates of mutations associated with transposition.   

Our focus

How does genome organization emerge and why do different species have different types of genome organization? 

To answer this question, we reconstruct where genes that are collocated in clusters or on specialized plasmids or chromosomes come from – do they mainly arrive via horizontal transfer, or are they duplicated from more conserved regions on the genome, or both? We do this for different species that have different lifestyles and different types of genome organization. We study clusters of genes that are associated with infection, but also genes that are important for microbe-microbe interactions. We complement this comparative research in natural isolates with in silico models. In these models, we can for example jumble genes and disrupt genome organization and compare the adaptability of digital organisms that can organize their genomes with those that are jumbled.   

What is the distribution of genetic diversity in the field? Do pathogens and non-pathogens coexist and regularly exchange genes? 

To answer this question, we extensively sample isolates of the same or different species in a field to determine how well individuals with different genotypes (e.g., that have or don’t have additional chromosomes or plasmids) are mixed. We assume that well-mixed populations have easy access to each other’s mobile gene pool, while populations in which individuals coexist in patches of identical genotypes probably only interact and exchange genes at the boundaries of these patches. We can compare fields that differ in terms of tilling, crop rotation.