Adaptation by improbable changes can identify the phenotypic targets of selection

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Objective. My lab will develop, test, and apply statistical methods to identify which phenotypic changes were targets of selection during molecular adaptation. Rationale. Adaptations are traits that evolved because selection improved an aspect of their function, and determining the functional effects of mutations is one primary goal of modern biological research. However, even detailed knowledge of function is not sufficient to demonstrate adaptation. It is difficult to determine which evolutionary changes are adaptations because mutations often, or perhaps always, influence more than one trait. So, even if a trait evolves by mutations that change some measured function, the real target of selection could be the effects of these same mutations on a correlated trait. Approach. Many features of organisms are manifestly improbable. Complex or finely-optimized traits invite adaptive explanations because selection is the only mechanism that can drive systems consistently toward unlikely states. Based on this understanding, my research program's long-term goal is to develop methods to identify adaptations not by their function but by the improbability of their occurrence. I propose two short-term aims to support this long-term goal. Aim 1. We will test proposed adaptations of whale myoglobin by predicting biophysical protein phenotypes. Diving mammals hold oxygen in muscle myoglobin. We will test two competing adaptive stories of how myoglobin evolved to tolerate high muscle concentrations without precipitating: increases in charge or stability. Did either trait evolve in an improbable direction? Both traits can be predicted from the biophysical properties of myoglobin. So we can generate phenotypes for all single mutations of an allele, and estimate the probability that a phenotype will change in one direction or the other by chance. These fully-resolved phenotype spaces also offer exciting projects that explore the theoretical basis of adaptation. Aim 2. We will test a classic example of luminescent colour adaptation by large-scale empirical measurement of mutant phenotypes. Click-beetle luciferase glow has evolved repeatedly from green to orange. Is this change common or rare? We will evaluate the phenotype space for luciferase by expressing artificial mutants, sorting alleles into pools based on their colour, and sequencing. Deep-sequenced pools of alleles, each pool a different phenotype, may also be useful for training machine-learning algorithms for phenotype prediction. Importance. Adaptation is the center of biology, but we need to know which traits selection acts on to understand the causes of evolution. The applications of a rigorous statistical test of molecular adaptation span all of biology. From tracing the origin of adaptive functions (in crops or changing environments) or maladaptive functions (in the pleiotropic causes of disease) to understanding how conflicts drive novelty (in immune recognition or species formation).