Using metabarcoding to reveal and quantify plant-pollinator interactions.

André Pornon (1) , Nathalie Escaravage (1) , Monique Burrus (1) , Hélène Holota (1) , Aurélie Khimoun (2) , Jérôme J. Mariette (3) , Charlène Pellizzari (1) , Amaia Iribar (1) , Roselyne Etienne (1) , Pierre Taberlet (4) , Marie Vidal (5) , Peter Winterton (6) , Lucie Zinger (1) , Christophe Andalo (1)

1 EDB - Evolution et Diversité Biologique
2 BGS - Biogéosciences [UMR 6282]
3 MIAT INRA - Unité de Mathématiques et Informatique Appliquées de Toulouse
4 LECA - Laboratoire d'Ecologie Alpine
5 GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique
6 UT3 - Université Toulouse III - Paul Sabatier

Given the ongoing decline of both pollinators and plants, it is crucial to implement effective methods to describe complex pollination networks across time and space in a comprehensive and high-throughput way. Here we tested if metabarcoding may circumvent the limits of conventional methodologies in detecting and quantifying plant-pollinator interactions. Metabarcoding experiments on pollen DNA mixtures described a positive relationship between the amounts of DNA from focal species and the number of trnL and ITS1 sequences yielded. The study of pollen loads of insects captured in plant communities revealed that as compared to the observation of visits, metabarcoding revealed 2.5 times more plant species involved in plant-pollinator interactions. We further observed a tight positive relationship between the pollen-carrying capacities of insect taxa and the number of trnL and ITS1 sequences. The number of visits received per plant species also positively correlated to the number of their ITS1 and trnL sequences in insect pollen loads. By revealing interactions hard to observe otherwise, metabarcoding significantly enlarges the spatiotemporal observation window of pollination interactions. By providing new qualitative and quantitative information, metabarcoding holds great promise for investigating diverse facets of interactions and will provide a new perception of pollination networks as a whole.

Domaines: Biodiversité et Ecologie; Interactions entre organismes; Génétique

André Pornon, Nathalie Escaravage, Monique Burrus, Hélène Holota, Aurélie Khimoun, et al.. Using metabarcoding to reveal and quantify plant-pollinator interactions.. Scientific Reports, 2016, 6, pp.27282. ⟨10.1038/srep27282⟩. ⟨hal-01333538⟩