Epistasis and the structure of fitness landscapes: are experimental fitness landscapes compatible with Fisher’s geometric model?

The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes.

The origin of genes through spontaneous symmetry breaking

The heredity of the modern cell is provided by a small number of non-catalytic template molecules—the gene. This basic feature of modern-type heredity, however, is believed to have been absent at the earliest stages of evolution. The RNA world hypothesis posits that the heredity of the first, primitive cell (protocell, for short) was provided by a population of dual-functional molecules serving as both templates and catalysts. How could genes originate in protocells? Here, I will discuss the possibility that gene-like molecules emerge in protocells through spontaneous symmetry breaking between the complementary strands of replicating molecules. Our model assumes a population of primitive cells, each containing a population of replicating molecules. Protocells are selected towards maximizing the catalytic activity of internal molecules, whereas molecules tend to evolve towards minimizing it. This conflicting evolutionary tendencies at different levels induce symmetry breaking, whereby one strand of replicating molecules maintains catalytic activity and increases its copy number, whereas the other completely loses catalytic activity and decreases its copy number—like genes. The evolution of these gene-like molecules increases the equilibrium fitness of protocells. Our results implicate conflicting multilevel evolution as a key cause of the evolution of genetic complexity.

Evolution of Evolvable Systems

I shall survey experimental and theoretical results from an ERC Advanced project with that name (https://www.parmenides-foundation.org/research/projects/evoevo/). I shall focus on three issues:

• Experimental approach to infrabiological systems,
• Major transitions theory 2.0 (especially the filial transitions),
• Learning in evolution versus Evolution in learning.