Experimental evolution


At present, our knowledge about polyploidy and its consequences is largely based on the signature of WGDs in present-day plant genomes. Although retrospective approaches can have substantial power if patterns arise when comparing a large number of lineages, they do not really allow to establish a direct causal link between pattern and process. Experimental evolution, on the other hand, is an assumption-free method to establish such a causal link. Consequently, ideally, a combination of retrospective comparative studies and prospective empirical studies is needed to fully understand the mechanisms and consequences of established polyploidy. Therefore, to gain further insights into the mechanistic underlying of the short and long-term establishment and effects of polyploidy, we want to initiate several long-term evolutionary experiments wherein both conditions for initial establishment and long(er)-term evolution of polyploid genome characteristics can be studied.

Although a few long(er)-term studies on polyploidization have recently been conducted on yeast and experimental studies using resynthesized yeast polyploids have yielded some understanding into the short-term effects of polyploidisation on both adaptation and genome structure, no similar experiments have yet been conducted for the green lineage (green algae plus plants). In particular, the long generation time of plants has hindered the experimental study of long(er)-term polyploid evolution. Also, although the studies on yeast cited above yielded some insights regarding adaptations of polyploids, it remains to be seen to what extent yeast is a good model system to study the effects and consequences of polyploidy for plant and crop evolution and adaptation. Therefore, we are using the green alga Chlamydomonas for the study of WGD in plants. A so-called Evolve and Resequence (E&R) approach will be applied. E&R approaches use a starting population that is subjected to multiple generations of selection. At specific times, these generations will be subjected to pooled genome sequencing (Pool-Seq, whole genome sequencing of pools of individuals), which is increasingly used in population genomics applications. It has been shown that Pool-Seq is particularly well-suited to study the impact of ecological factors on the partitioning of genomic variation in natural populations, because it can be applied to analyses comprising populations adapted to different environments. Furthermore, the caveats of both E&R approaches as well as Pool-Seq are well-known.

Specifically, through such E&R experiments we hope to learn more about the 'dynamics' of adaptation following WGD and polyploidy. Is adaptation a gradual accumulation of small adaptive changes? Do tetraploids indeed adapt faster than diploids under stressful environments? Is adaptation mainly due to increased mutational robustness? Is adaptation due to positive selection on particular genes? Is adaptation due to a clear increase in the frequency of beneficial alleles? Are polyploids adapting in different ways to different stressors, or is there a more general way in how polyploids adapt, i.e. are there different routes of adaptation following polyploidy, etc.?

In addition, we want to apply computational approaches that model the short and long(er)-term adaptation of polyploids, and simulate the evolution of populations of digital organisms (DOs) running on artificial gene regulatory networks in changing environments to evaluate theoretically how polyploidy might potentially enhance the adaptive potential of organisms. The results obtained will be cross-referenced with those from the evolutionary experiments with real organisms.