The concept of a fitness landscape is a powerful metaphor that offers 10 insight into various aspects of evolutionary processes and guidance for the study of 11 evolution. Until recently, empirical evidence on the ruggedness of these landscapes 12 was lacking, but since it became feasible to construct all possible genotypes containing 13 combinations of a limited set of mutations, the number of studies has grown to a 14 point where a classification of landscapes becomes possible. The aim of this review 15 is to identify measures of epistasis that allow a meaningful comparison of fitness 16 landscapes and then apply them to the empirical landscapes to discern factors that 17 affect ruggedness. The various measures of epistasis that have been proposed in the 18 literature appear to be equivalent. Our comparison shows that the ruggedness of 19 the empirical landscape is affected by whether the included mutations are beneficial 20 or deleterious and by whether intra-or intergenic epistasis is involved. Finally, the 21 empirical landscapes are compared to landscapes generated with the Rough Mt. Fuji 22 model. Despite the simplicity of this model, it captures the features of the experimental 23 landscapes remarkably well.

Functional effects of different mutations are known to combine to the total effect in highly nontrivial ways. For the trait under evolutionary selection (‘fitness’), measured values over all possible combinations of a set of mutations yield a fitness landscape that determines which mutational states can be reached from a given initial genotype. Understanding the accessibility properties of fitness landscapes is conceptually important in answering questions about the predictability and repeatability of evolutionary adaptation. Here we theoretically investigate accessibility of the globally optimal state on a wide variety of model landscapes, including landscapes with tunable ruggedness as well as neutral ‘holey’ landscapes. We define a mutational pathway to be accessible if it contains the minimal number of mutations required to reach the target genotype, and if fitness increases in each mutational step. Under this definition accessibility is high, in the sense that at least one accessible pathway exists with a substantial probability that approaches unity as the dimensionality of the fitness landscape (set by the number of mutational loci) becomes large. At the same time the number of alternative accessible pathways grows without bounds. We test the model predictions against an empirical 8-locus fitness landscape obtained for the filamentous fungus Aspergillus niger. By analyzing subgraphs of the full landscape containing different subsets of mutations, we are able to probe the mutational distance scale in the empirical data. The predicted effect of high accessibility is supported by the empirical data and is very robust, which we argue reflects the generic topology of sequence spaces. Together with the restrictive assumptions that lie in our definition of accessibility, this implies that the globally optimal configuration should be accessible to genome wide evolution, but the repeatability of evolutionary trajectories is limited owing to the presence of a large number of alternative mutational pathways.

To gauge the relative importance of contingency and determinism in evolution is a fundamental problem that continues to motivate much theoretical and empirical research. In recent evolution experiments with microbes, this question has been explored by monitoring the repeatability of adaptive changes in replicate populations. Here, we present the results of an extensive computational study of evolutionary predictability based on an experimentally measured eight-locus fitness landscape for the filamentous fungus Aspergillus niger. To quantify predictability, we define entropy measures on observed mutational trajectories and endpoints. In contrast to the common expectation of increasingly deterministic evolution in large populations, we find that these entropies display an initial decrease and a subsequent increase with population size N, governed, respectively, by the scales Nμ and Nμ 2 , corresponding to the supply rates of single and double mutations, where μ denotes the mutation rate. The amplitude of this pattern is determined by μ. We show that these observations are generic by comparing our findings for the experimental fitness landscape to simulations on simple model landscapes.clonal interference | epistasis | experimental evolution E volutionary adaptations arise from an intricate interplay of deterministic selective forces and random reproductive or mutational events, and the relative roles of these two types of influences on the outcome of evolution has been subject to longstanding controversy with significant philosophical implications (1, 2). Although the vision of "replaying the tape of life" on Earth or on some extrasolar planet remains confined to the realm of imagination (3, 4), evolution experiments with microbial populations have begun to address predictability of adaptation on a microevolutionary scale (5-9). In particular, strong signatures of parallel evolution have been observed in the context of the evolution of antibiotic resistance in pathogens, a finding that is of direct relevance to strategies of drug design and deployment (10-14). As lack of knowledge of crucial parameters (e.g., the frequency of beneficial mutations) in such experiments prevents forward predictions, predictability is used in a weaker, a posteriori sense implying repeatability of evolutionary trajectories in replicate populations. For this reason, the two terms will often be used interchangeably in the following (15).The repeatability of adaptive trajectories is expected to depend on the genetic constraints imposed by epistatic interactions as well as on parameters such as population size N, mutation rate μ, and the typical scale s of selection coefficients (16-18). To be specific, consider a population evolving in the regime of strong selection and weak mutation (SSWM), where mutations are so rare that normally not more than one mutant is present simultaneously and the population can be represented as a single entity that performs an adaptive walk in the space of genotypes (19)(20)(21). Such walks are constrained to ...

Abstract. We consider records and sequences of records drawn from discrete time series of the form X n = Y n + cn, where the Y n are independent and identically distributed random variables and c is a constant drift. For very small and very large drift velocities, we investigate the asymptotic behavior of the probability p n (c) of a record occurring in the nth step and the probability P N (c) that all N entries are records, i.e. that X 1 < X 2 < ... < X N . Our work is motivated by the analysis of temperature time series in climatology, and by the study of mutational pathways in evolutionary biology.Records and sequences of records from random variables with a linear trend 2

The statistics of records in sequences of independent, identically distributed random variables is a classic subject of study. One of the earliest results concerns the stochastic independence of record events. Recently, records statistics beyond the case of i.i.d. random variables have received much attention, but the question of independence of record events has not been addressed systematically. In this paper, we study this question in detail for the case of independent, non-identically distributed random variables, specifically, for random variables with a linearly moving mean. We find a rich pattern of positive and negative correlations, and show how their asymptotics is determined by the universality classes of extreme value statistics.