Quantifying the Predictability of Evolution at the Genomic Level in Lycaeides Butterflies

Stephen Jay Gould, a great scientist and evolutionary biologists, suggested that if we could replay the tape of life, we would not have observed similar course of events because evolution is stochastic and if affected by several events. Since then, the possibility that evolution is repeatable or predictable has been debated. Studies using large-scale evolution experiments, long-term data for individual populations, and controlled experiments in nature, have demonstrated phenotypic and genetic convergence in several taxa. These studies suggest that despite some randomness, predictable evolutionary patterns can emerge on a large temporal and spatial scale. However, a few cases also exist where evolution is unpredictable and stochastic. One way to understand evolutionary predictability better can be to have quantitative estimates of predictability at different heirarchical levels (mutations, genetic, phenotypic). This can help better understand if evolution is predictable and the extent to which it is predictable. My dissertation uses Lycaeides butterflies to identify and quantify evolutionary predictability in different contexts such as on a geographic scale, temporal scale and genomic scale. I accomplished this by sequencing and annotating the genomes of these butterflies across a vast geographic range and on a temporal scale and by comparing natural and experimental populations. My results show that different mechanisms can assist evolution of organisms to adapt to novel environmental challenges, and that the evolutionary changes can be somewhat predictable. Through this work I demonstrate three main findings: first, quantitative estimates of evolutionary predictability indicate that degree of predictability is variable and is highly context-dependent. Second, we can predict evolutionary patterns on a spatial as well as temporal scale, and can predict patterns in nature by controlled laboratory experiments. Additionally, genomic changes underlying repeatability vary across the genome. Lastly, the approach of quantifying predictability can help us better understand the mechanisms which drive evolution and how organisms will evolve in response to similar environmental pressures. These results suggest that evolution can be constrained and if we actually replay the tape of life, we could see a considerably similar outcome in biodiversity compared to what Gould predicted

Recent Hybrids Recapitulate Ancient Hybrid Outcomes

Genomic outcomes of hybridization depend on selection and recombination in hybrids. Whether these processes have similar effects on hybrid genome composition in contemporary hybrid zones versus ancient hybrid lineages is unknown. Here we show that patterns of introgression in a contemporary hybrid zone in Lycaeides butterflies predict patterns of ancestry in geographically adjacent, older hybrid populations. We find a particularly striking lack of ancestry from one of the hybridizing taxa, Lycaeides melissa, on the Z chromosome in both the old and contemporary hybrids. The same pattern of reduced L. melissa ancestry on the Z chromosome is seen in two other ancient hybrid lineages. More generally, we find that patterns of ancestry in old or ancient hybrids are remarkably predictable from contemporary hybrids, which suggests selection and recombination affect hybrid genomes in a similar way across disparate time scales and during distinct stages of speciation and species breakdown

Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus

Genomic insights on the recent evolution of novel host use in the Melissa blue butterfly

The factors that shape the evolution of animal diets remain poorly known. For herbivorous insects, the expectation has been that trade­offs exist, such that adaptation to one host plant reduces success on other potential hosts. We investigated the genomic basis of alternative host plant use in Melissa blue butterflies (Lycaeides melissa) by analyzing genetic variation in natural and experimental butterfly populations. We showed that distinct Melissa blue butterfly populations have independently colonized alfalfa since the 1800s when this plant was introduced, and that these populations have adapted to this novel resource. We documented segregating polygenic variation within and among butterfly populations for performance on alfalfa, and showed that different instances of adaptation to alfalfa have occurred via selection on a mixture of the same and different genes. Genetic variants in transposable elements might be particularly important for host adaptation. We documented very few loci with genetic trade­offs that would inherently constrain diet breadth by preventing the optimization of performance across hosts. Instead most genetic variants that affected performance on one host had little to no effect on the other host

Predicting SNP-host use association from an experiment

This compressed directory contains multiple R scripts and text files to implement the tests for overlap and sign coincidence between SNP-host use association in nature and SNP-performance association from a larval rearing experiment. A readme.txt file is included with additional details about each file

Treemix analysis

This compressed directory contains the files we used to conduct the treemix analysis. This includes scripts and infiles. A readme.txt file is included providing additional details

Ancestral reconstruction of host use

The files in this compressed directory are for the ancestral reconstruction of host use, including determining posterior probabilities for number of transitions from native feeding to Medicago sativa feeding. The R script also specifies the plotting of the ancestral state reconstruction tree

Variant calling

These are scripts we used for SNP variant calling. The locuslist provides a list of specific SNPs which were called for this analysis. We used samtools for variant calling