Semi-quantitative characterisation of mixed pollen samples using MinION sequencing and Reverse Metagenomics (RevMet)
N. Peel, L. Dicks, M. D. Clark, D. Heavens, L. Percival-Alwyn, C. Cooper, R. G. Davies, R. M. Leggett, D. W. Yu
Abstract
1. The ability to identify and quantify the constituent plant species that make up a mixed-species sample of pollen has important applications in ecology, conservation, and agriculture. Recently, metabarcoding protocols have been developed for pollen that can identify constituent plant species, but there are strong reasons to doubt that metabarcoding can accurately quantify their relative abundances. A PCR-free, shotgun metagenomics approach has greater potential for accurately quantifying species relative abundances, but applying metagenomics to eukaryotes is challenging due to low numbers of reference genomes. 2. We have developed a pipeline, RevMet (Reverse Metagenomics), that allows reliable and semi-quantitative characterization of the species composition of mixed-species eukaryote samples, such as bee-collected pollen, without requiring reference genomes. Instead, reference species are represented only by genome skims: low-cost, low-coverage, short-read sequence datasets. The skims are mapped to individual long reads sequenced from mixed-species samples using the MinION, a portable nanopore sequencing device, and each long read is uniquely assigned to a plant species. 3. We genome-skimmed 49 wild UK plant species, validated our pipeline with mock DNA mixtures of known composition, and then applied RevMet to pollen loads collected from wild bees. We demonstrate that RevMet can identify plant species present in mixed-species samples at proportions of DNA [≥]1%, with few false positives and false negatives, and reliably differentiate species represented by high versus low amounts of DNA in a sample. 4. The RevMet pipeline could readily be adapted to generate semi-quantitative datasets for a wide range of mixed eukaryote samples, which could include characterising diets, quantifying allergenic pollen from air samples, quantifying soil fauna, and identifying the compositions of algal and diatom communities. Our per-sample costs were {pound}90 per genome skim and {pound}60 per pollen sample, and new versions of sequencers available now will further reduce these costs.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genome-skimming provides accurate quantification for pollen mixtures
- Taxonomic identification of airborne pollen from complex environmental samples by DNA metabarcoding: a methodological study for optimizing protocols
C. Leontidou, C. Vernesi, … A. Cristofori·bioRxiv·Jan 10, 2017
- Efficient Multiplexing of Pollinator Metabarcodes Using Oxford Nanopore MinION Sequencing: Insights for Meadow Management from Floral Environmental DNA
Stephen E. Harris, Amelia Whitehurst, … Christopher M. Nagy·bioRxiv·Dec 15, 2023
- Primed and ready: Nanopore metabarcoding can now recover highly accurate consensus barcodes that are generally indel-free
J. J. M. Chang, Y. C. A. Ip, … D. Huang·bioRxiv·Aug 4, 2023
- PIMENTA: PIpeline for MEtabarcoding through Nanopore Technology used for Authentication
Valerie van der Vorst, Marijke Thijssen, … R.G. Jak·bioRxiv·Feb 14, 2024
- City life: airborne DNA metagenomic biodiversity monitoring reveals dynamic changes across time and space
Ned Peel, Piotr Cuber, … Matthew D. Clark·bioRxiv·Sep 3, 2026