| Abstract Detail
Recent Topics Posters Lockwood, Emily [1], Burleigh, Gordon [2], Carey, Sarah [2], Endara, Lorena [2], Lehnert, Marcus [4], Pryer, Kathleen M. [5], Rothfels, Carl [6]. A species-level phylogeny of the genus Equisetum. Equisetum is the sole extant genus of the entire Equisetopsida class, a unique and ancient group of seedless vascular plants commonly referred to as horsetails. Equisetum is a small and morphologically distinct group with a rich fossil record dating back to the Devonian Period. Historically, this group was extremely diverse, with many large plants dominating the understory of late Paleozoic forests. Today, there are only fifteen accepted extant Equisetum species. These plants hybridize easily, and several Equisetum hybrids are recognized. Although molecular data has provided many insights into the relationships among Equisetum species, new next generation sequencing approaches provide unprecedented opportunities to elucidate the evolutionary history of Equietum. For this study, we extracted DNA from 122 Equisetum plants, including several individuals from each Equisetum species, putative hybrids, subspecies, and geographic variants. We used a targeted sequence capture approach, developed as part of the NSF-funded Genealogy of Flagellate Plants project to generate sequence data from over 400 exons from low-copy nuclear genes, as well as their flanking intron regions. Here we present preliminary analyses of species-level phylogeny of the genus Equisetum from a large-scale nuclear dataset.
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1 - University of Florida, Biology, Gainesville, FL, 32611, USA
2 - University of Florida, Department of Biology, Gainesville, FL, 32611, USA
3 - University of Florida, Department of Biology, Gainesville, FL, 32611, USA
4 - University of Bonn
5 - Duke University, Biology
6 - University of California-Berkeley, Department of Integrated Biology
Keywords:
none specified
Presentation Type: Recent Topics Poster
Session: P, Recent Topics Posters
Location: Grand Ballroom - Exhibit Hall/Mayo Civic Center
Date: Monday, July 23rd, 2018
Time: 5:30 PM
Number: PRT024
Abstract ID:1319
Candidate for Awards:None |
