José Rojas-Echenique

Epistasis can markedly affect evolutionary trajectories. In recent decades, protein-level fitness landscapes have revealed extensive idiosyncratic epistasis among specific mutations. By contrast, other work has found ubiquitous and apparently nonspecific patterns of global diminishing-returns and increasing-costs epistasis among mutations across the genome. Here, we used a hierarchical CRISPR gene drive system to construct all combinations of 10 missense mutations from across the genome in budding yeast and measured their fitness in six environments. We show that the resulting fitness landscapes exhibit global fitness-correlated trends but that these trends emerge from specific idiosyncratic interactions. We thus provide experimental validation of recent theoretical work arguing that fitness-correlated trends can emerge as the generic consequence of idiosyncratic epistasis.

Screens for epistatic interactions have long been used to characterize functional relationships corresponding to protein complexes, metabolic pathways, and other functional modules. Although epistasis between adaptive mutations is also common in laboratory evolution experiments, the functional basis for these interactions is less well characterized. Here, we quantify the extent to which gene function (as determined by a genome-wide screen for epistasis among deletion mutants) influences the rate and genetic basis of compensatory adaptation in a set of 37 gene deletion mutants nested within 16 functional modules. We find that functional module has predictive power: mutants with deletions in the same module tend to adapt more similarly, on average, than those with deletions in different modules. At the same time, initial fitness also plays a role: independent of the specific functional modules involved, adaptive mutations tend to be systematically more beneficial in less-fit genetic backgrounds, consistent with a general pattern of diminishing returns epistasis. We measured epistatic interactions between initial gene deletion mutations and the mutations that accumulate during compensatory adaptation and found a general trend towards positive epistasis (i.e. mutations tend to be more beneficial in the background in which they arose). In two functional modules, epistatic interactions between the initial gene deletions and the mutations in their descendant lines caused evolutionary entrenchment, indicating an intimate functional relationship. Our results suggest that genotypes with similar epistatic interactions with gene deletion mutations will also have similar epistatic interactions with adaptive mutations, meaning that genome scale maps of epistasis between gene deletion mutations can be predictive of evolutionary dynamics.

Software to manage automated laboratories, when interfaced with hardware instruments, gives users a way to specify experimental protocols and schedule activities to avoid hardware conflicts. In addition to these basics, modern laboratories need software that can run multiple different protocols in parallel and that can be easily extended to interface with a constantly growing diversity of techniques and instruments. We present Clarity, a laboratory automation manager that is hardware agnostic, portable, extensible, and open source. Clarity provides critical features including remote monitoring, robust error reporting by phone or email, and full state recovery in the event of a system crash. We discuss the basic organization of Clarity, demonstrate an example of its implementation for the automated analysis of bacterial growth, and describe how the program can be extended to manage new hardware. Clarity is mature, well documented, actively developed, written in C# for the Common Language Infrastructure, and is free and open-source software. These advantages set Clarity apart from currently available laboratory automation programs. The source code and documentation for Clarity is available at http://code.google.com/p/osla/.

Intransitive communities, those in which species' abilities cannot be ranked in a hierarchy, have been the focus of theoretical and empirical research, as intransitivity could help explain the maintenance of biodiversity. Here we show that models for intransitive competition embedding slightly different interaction rules can produce opposite patterns. In particular, we find that interactions in which an individual can be outcompeted by its neighbors, but cannot outcompete its neighbors, produce negative frequency dependence that, in turn, promotes coexistence. Whenever the interaction rule is modified toward symmetry (the individual and the neighbors can outcompete each other) the negative frequency dependence vanishes, producing different coexistence levels. Macroscopically, we find that asymmetric interactions yield highest biodiversity if species compete globally, while symmetric interactions favor highest biodiversity if competition takes place locally.