Does adaptation to different diets result in assortative mating? Ambiguous results from experiments on Drosophila.

The emergence of behavioural isolation between populations under divergent selection can be crucial for ecological speciation, but the mechanisms underlying such isolation are poorly understood. Several experimental evolution studies have shown that positive assortative mating (preference for similar mates) can arise rapidly in Drosophila laboratory populations reared in different stressful conditions, while other studies failed to confirm this effect. Here, we present the results of an evolution experiment in which outbred lines of Drosophila melanogaster were reared for 1-2 years on one of the three different diets (standard, starch based or high salt). We show that nonrandom mating arose in some, but not all lines, and that the manifestations and possible interpretations of this nonrandomness depend strongly on the type of tests used to assess mating preferences. More specifically, multiple-choice four-fly tests revealed positive assortative mating (prevalence of homogamic matings) in some starch-adapted and salt-adapted lines when paired with a control line reared on the standard diet, but competitive three-fly tests rather revealed competitive advantage of control males and females over the flies reared on stressful diets. The results imply that divergent adaptation can result in differences in mating propensity or competitive ability, which, in turn, may either facilitate or hamper speciation depending on the relative frequency of high- vs. low-competition settings in natural habitats of the diverging populations. The results also emphasize the importance of using diverse tests for assessing mating structure in natural and laboratory populations.

Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation.

Motivation: Computational prediction of the effect of mutations on protein stability is used by researchers in many fields. The utility of the prediction methods is affected by their accuracy and bias. Bias, a systematic shift of the predicted change of stability, has been noted as an issue for several methods, but has not been investigated systematically. Presence of the bias may lead to misleading results especially when exploring the effects of combination of different mutations. Results: Here we use a protocol to measure the bias as a function of the number of introduced mutations. It is based on a self-consistency test of the reciprocity the effect of a mutation. An advantage of the used approach is that it relies solely on crystal structures without experimentally measured stability values. We applied the protocol to four popular algorithms predicting change of protein stability upon mutation, FoldX, Eris, Rosetta and I-Mutant, and found an inherent bias. For one program, FoldX, we manage to substantially reduce the bias using additional relaxation by Modeller. Authors using algorithms for predicting effects of mutations should be aware of the bias described here. Availability and implementation: All calculations were implemented by in-house PERL scripts. Supplementary information: Supplementary data are available at Bioinformatics online. Note: The article 10.1093/bioinformatics/bty348, published alongside this paper, also addresses the problem of biases in protein stability change predictions.