Objectives: In Europe, 27% of the population are sensitised to grass pollen leading to extensive negative health outcomes (e.g. allergic rhinitis and allergic asthma). However, grass pollen from different species cannot be discriminated using traditional observational methods. Currently, there is no way of detecting, modelling or forecasting the aerial dispersion of taxon-specific pollen from the extensive biodiversity of UK grasses. Primary objectives here include:
To develop a taxonomically resolved, grass pollen assessment framework throughout the UK.
Establish if there are phenological or geographical trends exhibited in pollen deposition, or whether the summer pollen load is admixed?
Method: We analysed aerial environmental DNA (eDNA) from up to 13 sites across the UK during the 2016–2017 grass flowering seasons. Two plant molecular taxonomy markers, ITS2 and rbcL, were used for eDNA “metabarcoding”, complemented by taxon-specific quantitative PCR to detect which species or genera of grass pollen are present in space and time during the summer months across the UK. Our aim was to quantify trends exhibited in pollen deposition of key known allergenic grasses, including Dactylis glomerata, Lolium perenne and Phleum pratense.

Results: Metabarcoding demonstrated that the species composition of aerial grass pollen communities varies significantly both temporally and spatially across the grass flowering season. Quantitative PCR data also confirmed significant quantitative spatio-temporal variation in pollen deposition.

Conclusions: The results confirm that pollen deposition throughout the grass flowering season is heterogeneous, showing quantitative differences in taxon composition throughout the summer months. The data demonstrate that seasonal exposure to different types of grass pollen is not static, but features shifting abundances of different species of pollen that can be linked to allergy. The empirical findings will be discussed in relation to coincidental health outcomes in addition to providing a broader perspective of the PollerGEN program, that integrates species vegetation mapping, advanced aerobiological modelling, environmental genomics, and human epidemiology.