A Multi-Gene Region Targeted Capture Approach to Detect Plant DNA in Environmental Samples: A Case Study From Coastal Environments

Nicole R. Foster, Kor Jent van Dijk, Ed Biffin, Jennifer M. Young, Vicki A. Thomson, Bronwyn M. Gillanders, Alice R. Jones, Michelle Waycott

Research output: Contribution to journalArticlepeer-review

Abstract

Metabarcoding of plant DNA recovered from environmental samples, termed environmental DNA (eDNA), has been used to detect invasive species, track biodiversity changes, and reconstruct past ecosystems. The P6 loop of the trnL intron is the most widely utilised gene region for metabarcoding plants due to the short fragment length and subsequent ease of recovery from degraded DNA, which is characteristic of environmental samples. However, the taxonomic resolution for this gene region is limited, often precluding species level identification. Additionally, targeting gene regions using universal primers can bias results as some taxa will amplify more effectively than others. To increase the ability of DNA metabarcoding to better resolve flowering plant species (angiosperms) within environmental samples, and reduce bias in amplification, we developed a multi-gene targeted capture method that simultaneously targets 20 chloroplast gene regions in a single assay across all flowering plant species. Using this approach, we effectively recovered multiple chloroplast gene regions for three species within artificial DNA mixtures down to 0.001 ng/μL of DNA. We tested the detection level of this approach, successfully recovering target genes for 10 flowering plant species. Finally, we applied this approach to sediment samples containing unknown compositions of eDNA and confidently detected plant species that were later verified with observation data. Targeting multiple chloroplast gene regions in environmental samples, enabled species-level information to be recovered from complex DNA mixtures. Thus, the method developed here, confers an improved level of data on community composition, which can be used to better understand flowering plant assemblages in environmental samples.

Original languageEnglish
Article number735744
Pages (from-to)1-12
Number of pages12
JournalFrontiers in Ecology and Evolution
Volume9
DOIs
Publication statusPublished - 25 Oct 2021
Externally publishedYes

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