Semi-quantitative characterisation of mixed pollen samples using MinION sequencing and Reverse Metagenomics (RevMet)

Abstract

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. 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. 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. RevMet could readily be adapted to generate semi‐quantitative datasets for a wide range of mixed eukaryote samples. Our per‐sample costs were £90 per genome skim and £60 per pollen sample, and new versions of sequencers available now will further reduce these costs.

Using ITS2 metabarcoding and microscopy to analyse shifts in pollen diets of honey bees and bumble bees along a mass‐flowering crop gradient

“…New developments in microscopic pollen detection using deep learning techniques (Gallardo‐Caballero et al., 2019) or in full‐length amplicon or genome sequencing with, for example, nanopore sequencing techniques (Lang et al . 2019; Leidenfrost et al., 2020; Peel et al., 2019) could improve the weaknesses of both approaches (e.g., time expenditure in microscopy or quantification accuracy in molecular methods). However, studies are needed to compare and evaluate the accuracy of those new developments.…”

“…However, metabarcoding is restricted in its applicability in pollen quantification. Several factors may affect the quantification results obtained by next‐generation sequencing (NGS)‐based amplicon sequencing, such as DNA extraction, PCR (polymerase chain reaction) amplification or barcode copy number (Peel et al., 2019), which can lead to over‐ or underestimation of actual pollen counts (Baksay et al., 2020; Pornon et al., 2016; Richardson et al., 2015). The number of metabarcoding reads may be more likely to be positively related to microscopy‐based counts for commonly occurring taxa than for rare pollen taxa in the samples (Smart et al., 2017).…”

“…Larger colonies were expected to collect greater pollen richness while smaller colonies should collect greater proportions of crop pollen close to the hive. Due to several factors that influence outcomes of pollen quantification based on metabarcoding (Bell et al., 2019; Peel et al., 2019), we hypothesized a positive and pollen type‐specific relationship between the number of metabarcoding reads and microscopic pollen counts for the two target crop species, namely strawberry and OSR.…”

Pollen availability for the Horned mason bee (Osmia cornuta) in regions of different land use and landscape structures

“…However, we cannot exclude the existence of PCR biases caused by preferential annealing of the primers in some taxa. This limitation could be overcome, using PCR‐free approaches such as genome skimming (Taberlet et al ., ; Lang et al ., ; Peel et al ., ) or multiple marker sets with different affinities for the different taxa studied (Fazekas et al ., ). Some of the species named due to a match in a molecular reference database are not recorded from Austria, e.g.…”

msGBS: A new high‐throughput approach to quantify the relative species abundance in root samples of multispecies plant communities

“…Peel et al. (2019) described RevMet; 49 wild reference species were represented by genome skims which were mapped to individual long Minion sequence reads derived from mixed species pollen samples. Each read was assigned to a plant species and species proportions calculated from the collection of identified reads.…”