Within the past decade, the study of biology has been revolutionized by a flood of sequencing data. This wealth of raw data has led not just to answers about questions on the nature of evolution and its specific impact on organisms, but also to new questions. The technology developed to sequence the human genome has since spread into the other taxa, resulting in the whole genome sequences of multiple species as being freely available, both for individuals and for populations. Here, this sequence information is used to answer fundamental questions about the nature of evolution within plants, and how it impacts high-value phenotypic traits. By identifying the regions of genome sequence that are conserved between flowering plants (angiosperms), we can learn which genes are more likely to be essential. Using Arabidopsis thaliana as a reference, we scored genome-wide conservation, and identified a large set of previously-uncharacterized conserved regions. The set of conserved regions allowed for evolutionarily-informed RNA-folding prediction, as well as analysis of element specific conservation. To learn more about how evolution shapes plant defense, we investigated a total of 130 genes related to jasmonic acid elicitation, synthesis, hormone response, and secondary metabolite production. To infer selection within this defense pathway, we leveraged both whole-genome and population data. The overlapping tests of selection revealed two clusters of genes under positive selection, which were significant compared to signatures of selection detected in control set of fifty genes that were randomly selected from the A. thaliana genome. Panicum virgatum, commonly know as switchgrass, has become the focus of plant breeding efforts centered on biomass production. In order to better identify genes involved in biomass accumulation, we studied the transcriptomes of two cultivars of switchgrass (Panicum virgatum): Alamo and Dacotah, which manifest drastically different biomass phenotypes. By using both a reference genome and a de novo transcriptome, we identify differentially-expressed genes between the two cultivars, and highlight three genes that were found to be significant even after correction for false discovery.