Data from: The predictability of genomic changes underlying a recent host shift in Melissa blue butterflies

Despite accumulating evidence that evolution can be predictable, studies
quantifying the predictability of evolution remain rare. Here, we measured
the predictability of genome-wide evolutionary changes associated with a
recent host shift in the Melissa blue butterfly (Lycaeides melissa). We
asked whether and to what extent genome-wide patterns of evolutionary
change in nature could be predicted (1) by comparisons among instances of
repeated evolution, and (2) from SNP $\times$ performance associations in
a lab experiment. We delineated the genetic loci (SNPs) most strongly
associated with host use in two L. melissa lineages that colonized
alfalfa. Whereas most SNPs were strongly associated with host use in none
or one of these lineages, we detected a ~two-fold excess of SNPs
associated with host use in both lineages. Similarly, we found that
host-associated SNPs in nature could also be partially predicted from SNP
$\times$ performance (survival and weight) associations in a lab rearing
experiment. But the extent of overlap, and thus degree of predictability,
was somewhat reduced. Although we were able to predict (to a modest
extent) the SNPs most strongly associated with host use in nature (in
terms of parallelism and from the experiment), we had little to no ability
to predict the direction of evolutionary change during the colonization of
alfalfa. Our results show that different aspects of evolution associated
with recent adaptation can be more or less predictable, and highlight how
stochastic and deterministic processes interact to drive patterns of
genome-wide evolutionary change