After spending my graduate career using genetic data to reconstruct historical demographic events, one of the things that excite me the most about my postdoc work is the opportunity to use experimental methods to make evolution happen (insert mad scientist laugh here). Manipulative experiments on organisms with short generation times are a great way to study how populations and their genomes adapt in response to mutation, selection, and/or environmental change (for a review see Barrick and Lenski 2013).
One view of adaptive evolution is that it proceeds via the accumulation of beneficial mutations. However, deleterious mutations are maintained at low levels in natural populations and they generate strong selective pressure for improved fitness through compensatory mutation, which may be a mechanism of population divergence. For example, the figure below (adapted from Szamecz et al. 2014) shows a fitness landscape where all possible genotypes occupy a space on the surface. The higher the peak on which the genotype sits, the higher the fitness of that genotype. Here WT represents a wild-type genotype with high fitness. If a deleterious mutation occurs, the new genotype (referred to in the figure as KO for ‘knock out’) will have lower fitness than the original wild-type genotype. We may expect subsequent compensatory mutations in the knock out individuals to restore, or at least improve, fitness (referred to in the figure as EV1 and EV2 for ‘evolved’ genotypes). If compensatory mutations occur through different evolutionary routes, as depicted in the figure, then these mutations will drive population divergence.
In their recent PLoS Biology paper, Szamecz et al. (2014) performed a series of elegant experiments to test how yeast populations evolved to compensate for a deleterious mutation. The authors knocked out a different gene in each of 180 identical haploid yeast strains. The resulting mutant strains had low fitness (i.e. slow, but non-zero growth) compared to wild type strains. The mutant strains were propagated for 400 generations, as were 22 wild type strains used to control for potential non-compensatory evolution. The authors measured growth in the initial (i.e. unevolved) and final (i.e. evolved) mutant and wild-type strains and collected whole genome sequences for a subset of mutant and wild type strains before and after they evolved.
Here are some of the important findings from the study:
i) 68% of mutated strains returned to near wild-type fitness while evolving wild-type control strains showed minimal improvements in fitness.
ii) The lower the initial fitness of the mutant strain, the more likely it was to evolve a compensatory mutation.
iii) compensatory evolution preferentially affected genes that were functionally related to the gene that was knocked out.
iv) compensatory mutations did not improve fitness when they were experimentally inserted into a wild-type genetic background, showing the mutation was only beneficial when the target gene was knocked-out.
The results I found most interesting were those from an experiment that measured gene expression changes among the wild-type, unevolved mutant, and evolved mutant strains. The results indicated that although near wild-type fitness was achieved in the evolved mutant lines, wild-type gene expression was not restored, indicating that the compensatory mutations drove the strains to novel genomic expression states. You can see this clearly in the figure below.
The figure on the left shows gene expression changes among strains. In the unevolved mutant strain (referred to here as the ancestor), the rsc2 gene has been knocked out. The rows represent gene expression differences among strains, each vertical line represents a gene, and the colors represents up (yellow) or down (blue) regulation of gene expression. So in the rsc2 knock-out strain, across the top row, expression for genes towards the left side of the figure are down-regulated compared to the wild-type strain and genes towards the right are up-regulated compared to the wild-type strain. If gene expression was restored by compensatory mutation, we would expect to see all black for the evolved vs wild-type comparison, indicating no differences in gene regulation between those two strains. Instead we see differences in gene regulation in the evolved compared to the wild-type strain.
The figure on the right shows that the different strains occupy different parts of “gene expression space,” to put it simply. Here, if gene expression had been restored to a wild-type state, we would expect the evolved mutant strain (“evo”) overlap with the wild-type strain (“WT”). What we see, however, is that each strain (ancestral (“anc”), evolved, and wild type) occupies its own place in gene expression space.
Taken together, the results of this paper suggest that genomes undergo major changes not only in response to external conditions but also to compensate for accumulated deleterious mutation.
Szamecz, B., Boross, G., Kalapis, D., Kovács, K., Fekete, G., Farkas, Z., … & Pál, C. (2014). The genomic landscape of compensatory evolution. PLoS Biology, 12(8), e1001935. DOI:10.1371/journal.pbio.1001935