Biodiv Sci ›› 2018, Vol. 26 ›› Issue (5): 445-456.  DOI: 10.17520/biods.2018058

Special Issue: 传粉生物学 物种形成与系统进化 昆虫多样性与生态功能

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Qualitative and quantitative molecular construction of plant-pollinator network: Application and prospective

Dandan Lang1,2, Min Tang1,3, Xin Zhou1,3,*()   

  1. 1 Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100193
    2 College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083
    3 College of Plant Protection, China Agricultural University, Beijing 100193
  • Received:2018-02-15 Accepted:2018-05-11 Online:2018-05-20 Published:2018-09-11
  • Contact: Zhou Xin
  • About author:

    # Co-first authors


Pollinators serve key ecological functions, ensuring stable ecosystems and high agricultural yields. Hence, assessing ecosystem health and effects of agricultural management would benefit from understanding and monitoring pollination networks, which involves identifications of pollinators and pollinated plants. Classic approaches of morphology-based identification of plants and pollinators can be time-consuming, labor-intensive and costly, and require highly specialized taxonomic expertise. In comparison, DNA barcoding and high-throughput sequencing technologies can provide efficient and accurate identifications of plants and their pollinators, which may facilitate construction of pollination networks. Here we propose using sequencing technologies with a PCR-free genome-skimming work frame, using "super DNA barcode" as a new method to assess plant-pollinator networks. We expect this technique to improve resolution and accuracy of taxonomic identification to help gain quantitative information for bulk samples of pollinators or pollens. Although there are technical challenges to be resolved, the robustness of the new methodology has been validated in relevant biodiversity studies, suggesting promise in constructing pollination networks.

Key words: mitochondria, chloroplast, pollen, metabarcoding, metagenome, PCR-free, quantify