Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Plant Protection, China Agricultural University, Beijing, China.
Mol Ecol Resour. 2019 Nov;19(6):1433-1446. doi: 10.1111/1755-0998.13061. Epub 2019 Sep 18.
Studies on foraging partitioning in pollinators can provide critical information to the understanding of food-web niche and pollination functions, thus aiding conservation. Metabarcoding based on PCR amplification and high-throughput sequencing has seen increasing applications in characterizing pollen loads carried by pollinators. However, amplification bias across taxa could lead to unpredictable artefacts in estimation of pollen compositions. We examined the efficacy of a genome-skimming method based on direct shotgun sequencing in quantifying mixed pollen, using mock samples (five and 14 mocks of flower and bee pollen, respectively). The results demonstrated a high level of repeatability and accuracy in identifying pollen from mixtures of varied species ratios. All pollen species were detected in all mocks, and pollen frequencies estimated from the number of sequence reads of each species were significantly correlated with pollen count proportions (linear model, R = 86.7%, p = 2.2e-16). For >97% of the mixed taxa, pollen proportion could be quantified by sequencing to the correct order of magnitude, even for species which constituted only 0.2% of the total pollen. In addition, DNA extracted from pollen grains equivalent to those collected from a single honeybee corbicula was sufficient for genome-skimming. We conclude that genome-skimming is a feasible approach to identifying and quantifying mixed pollen samples. By providing reliable and sensitive taxon identification and relative abundance, this method is expected to improve our understanding in studies that involve plant-pollinator interactions, such as pollen preference in corbiculate bees, pollen diet analyses and identification of landscape pollen resource use from beehives.
对传粉者觅食分区的研究可以为了解食物网生态位和传粉功能提供关键信息，从而有助于保护。基于聚合酶链反应（PCR）扩增和高通量测序的代谢组学分析越来越多地应用于描述传粉者携带的花粉负荷。然而，跨分类群的扩增偏差可能导致花粉组成估计中出现不可预测的人为假象。我们通过模拟样本（分别为 5 个和 14 个花和蜜蜂花粉模拟样本）检验了基于直接鸟枪法测序的基因组扫描方法在量化混合花粉方面的功效。结果表明，该方法在识别不同物种比例混合花粉方面具有高度的可重复性和准确性。所有模拟样本中都检测到了所有花粉物种，并且从每个物种的序列读数数量估计的花粉频率与花粉计数比例显著相关（线性模型，R = 86.7%，p = 2.2e-16）。对于 >97%的混合类群，即使对于构成总花粉的 0.2%的物种，也可以通过测序来正确地量化花粉比例。此外，从单个蜜蜂附肢采集的花粉粒中提取的 DNA 足以进行基因组扫描。我们得出结论，基因组扫描是一种可行的方法，可用于识别和量化混合花粉样本。通过提供可靠和敏感的分类群鉴定和相对丰度，该方法有望提高我们对涉及植物-传粉者相互作用的研究的理解，例如附肢蜜蜂的花粉偏好、花粉饮食分析以及从蜂箱中识别景观花粉资源利用。
