Using metabarcoding to reveal and quantify plant-pollinator interactions

被引：0
作者：
André Pornon
Nathalie Escaravage
Monique Burrus
Hélène Holota
Aurélie Khimoun
Jérome Mariette
Charlène Pellizzari
Amaia Iribar
Roselyne Etienne
Pierre Taberlet
Marie Vidal
Peter Winterton
Lucie Zinger
Christophe Andalo
机构：
[1] Laboratoire Evolution and Diversité Biologique EDB,Département de Langues et Gestion
[2] Université Toulouse III Paul Sabatier,undefined
[3] CNRS,undefined
[4] EDB,undefined
[5] UMR 5174,undefined
[6] Laboratoire Biogeosciences,undefined
[7] Université de Bourgogne 6 bld Gabriel,undefined
[8] Plate-forme Bio-informatique Genotoul,undefined
[9] Mathématiques et Informatique Appliqués INRA,undefined
[10] UR875 Toulouse,undefined
[11] Laboratoire d’Ecologie Alpine,undefined
[12] CNRS UMR 5553,undefined
[13] Université Joseph Fourier,undefined
[14] BP 43,undefined
[15] GeT-PlaGe,undefined
[16] Genotoul,undefined
[17] INRA UAR1209,undefined
[18] Université Paul Sabatier,undefined
来源：
Scientific Reports | / 6卷
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摘要：
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.
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