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Abstract Detail

Population Genetics/Genomics

Hale, Haley [1], Pokorny, Lisa [2], Gardner, Elliot [3], Johnson, Matthew [4].

Developing a cost-effective workflow for targeted sequencing of herbarium specimens using Angiosperms353.

The reduced cost of high-throughput targeted sequencing, along with new “universal” probe sets like Angiosperms353, means genomic-scale data is no longer limited to heavily funded laboratories. However, the feasibility of targeted sequencing for conservation genomics has not been fully explored. Here, we look at the costs and challenges of producing target-capture datasets from herbarium specimens to answer within-species questions in a variety of flowering plants. We describe best practices for choosing methods for DNA extraction, use of enzymatic fragmentation, high-throughput library preparation, and sequencing platform using the Angiosperms353 probe set for enrichment of hundreds of nuclear genes. Our dataset includes herbarium specimens from 24 species collected during a survey of Guadelupe Mountains National Park between 1971 and 1974. The variety and age of the specimens brings their own challenges to large scale processing, especially DNA extraction due to the presence of different foliar or floral compounds as well as the diverse tissue composition used. By optimizing and generating a detailed protocol and cost calculator for sample processing, we offer a strategy for wide adoption of target capture sequencing for both phylogenetics and conservation genomics.

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1 - Texas Tech University, Biological Sciences, 2901 Main Street, Lubbock, TX, 79409, USA
2 - Royal Botanic Gardens, Kew, Jodrell Laboratory, Jodrell Laboratory, Richmond, SRY, TW9 3DS, United Kingdom
3 - 4449 Groveland Rd, University Heights, OH, 44118, United States
4 - Texas Tech University, Biological Sciences, 2901 Main Street, Ms3131, Lubbock, TX, 79409, United States

Conservation Genomics
Sequence Capture

Presentation Type: Oral Paper
Session: POPGEN2, Population Genetics/Genomics II
Location: Tucson H/Starr Pass
Date: Wednesday, July 31st, 2019
Time: 4:15 PM
Number: POPGEN2011
Abstract ID:826
Candidate for Awards:None

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