Collaborative Research: Can Hundreds of Unlinked Loci Really Resolve Recent, Rapid Radiations of Plant Species?

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Milkweeds (Asclepias) are common and ecologically important perennial plants of North American grassland and forest ecosystems. They are the only host plants of the monarch butterfly, a species of significant conservation concern. Because milkweed species diversified over a short evolutionary time span, reconstructing their relationships is exceedingly difficult and requires examination of a large amount of data from across their genomes and powerful computational techniques. This research will contribute to the development of new methods for more accurately determining evolutionary relationships when many species have been formed in rapid succession. The results will have implications for better understanding the coevolution between milkweeds and monarch butterflies and the evolution of plant defense, as well as provide a robust evolutionary context for understanding the results of other scientific studies exploring aspects of plant reproduction, genome evolution, and other areas using milkweeds. The project will train postdoctoral fellows and graduate student in the latest phylogenetic and bioinformatics methods thereby training the next generation of phylogenetic biologists.This research will demonstrate the feasibility of solving difficult phylogenetic problems at the species level in plants by employing improvements in next-generation sequencing techniques. The work combines methods for targeted sequencing of hundreds of specific regions of the nuclear genome applied to unusually large within-species sampling. The project applies nuclear gene probes developed directly from Asclepias genome and transcriptome sequences to effectively target 768 genes and substantial amounts of their non-coding flanking regions. Phylogenetically useful off-target sequences, (e.g., complete chloroplast genomes) are also obtained. By sampling 20 individuals per species, the approach will distinguish common causes of gene tree discordance: incomplete lineage sorting and introgression. An analytic workflow will be applied that incorporates simulation of incomplete lineage sorting and a combination of species tree inference methods that are effective even when introgression has occurred. Because current species tree approaches are constrained by a computational tradeoff between the number of loci and number of alleles that can simultaneously analyzed, the project will evaluate the strengths and weaknesses of alternative methods. The large sample of loci will also validate the recognition of species not currently accepted in Asclepias. Undergraduate and graduate student training in genomics, bioinformatics, and phylogenetics will target participants from underrepresented groups. Project outcomes will reach the broader scientific community and the general public through workshops held at scientific meetings, K-12 education modules focused on milkweed ecology and evolution, and demonstration exhibits at a public botanic garden.