| Abstract Detail
Conference Wide Cai, Liming [1], Davis, Charles [2]. Herbariomics-based biodiversity research: from specimen to phylogeny. Herbarium specimens provide the most reliable links between taxonomy, phenotypic traits, genetic information, and species distributions. The application of whole genome sequencing to herbarium specimens (herbariomics) and mounting efforts in digitization provide unparalleled opportunities to investigate phylogenetic diversity in a spatio-temporal context. However, applying herbariomics across large clades can still be challenging due to technical and financial bottlenecks. In this half-day workshop, we will provide hands-on instructions for the design and application of genome skimming technique to herbarium specimens. Participants will be introduced to techniques that enable efficient and economic genomic sequencing across hundreds to thousands of specimens. We will also provide step-by-step instructions to curate and analyze high throughput sequence data with an emphasis on phylogenetic studies using our newly developed software PhyloHerb. Participants will learn to assemble and annotate sequences from the plastid, mitochondrial, and nuclear ITS regions. Following assembly, we will use PhyloHerb to extract orthologous sequences from genic and intergenic regions for phylogenetic analysis. Participants will learn to reconstruct alignments and phylogenetic trees for large data set containing thousands of species. For advanced users, we will also introduce strategies to identify and verify structural changes in the plastid genomes by visualizing the assembly graphs produced by GetOrganelle. Prepared datasets will be provided, but attendees may bring their own data. Participants will need to bring a laptop (either Mac or Windows) with a UNIX-compatible operating system such as OS-X or Linux.
1 - University of Texas, Austin
2 - Harvard University, 22 Divinity Avenue, 26 Oxford St., MCZ Room 109a, CAMBRIDGE, MA, 02138, United States
Keywords:
none specified
Presentation Type: Workshop
Number: W19001
Abstract ID:16
Candidate for Awards:None |
