节肢动物传粉媒介多样性的元条形码分析:来自花和来自大量昆虫样本的eDNA的方法学比较。

IF 3.9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Kara S. Jones, David S. Pilliod, Aaron W. Aunins
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引用次数: 0

摘要

传统昆虫取样方法的局限性促使了能够量化不同节肢动物群落的新型非致死方法的发展和优化。利用节肢动物特异性引物的环境DNA (eDNA)元条形码作为一种利用植物表面沉积的DNA来表征节肢动物群落的新方法,最近得到了研究。这种抽样方法已经被证明是成功的,但是传粉媒介——尤其是蜜蜂——在这些研究中被奇怪地低估了。为了评估这种不一致性,我们研究了蜜蜂和其他传粉媒介的eDNA元条形码的局限性。我们使用三种元条形码引物比较了从花中提取的eDNA和从放置在同一地点的叶片诱捕器收集的昆虫粉样中提取的DNA的传粉媒介多样性,其中两种引物主要针对节肢动物(COI-Jusino和16S-Marquina),另一种引物针对大黄蜂(Bombus spp., COI-Milam)。共检测到9目77科昆虫。与16S-Marquina和COI-Milam相比,COI-Jusino扩增的分类多样性最高。从叶片诱捕器中获得的扩增子序列变异(asv)(蓝色:1357个,黄色:1542个)多于花(245个),但在不同的方法中,只有23%的科和13%的属是相同的,这表明花和蓝色和黄色叶片诱捕器可能分别采集了节肢动物群落的不同部分。在已知有蜜蜂来访的29个花样本中,只有10个样本的eDNA检测到蜜蜂,不完整的参考数据库阻碍了物种的分配。尽管我们的研究为eDNA元条形码对表征节肢动物群落的有用性提供了额外的证据,但在使用eDNA元条形码方法识别和量化传粉媒介群落,特别是蜜蜂时,仍然存在重大挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metabarcoding Analysis of Arthropod Pollinator Diversity: A Methodological Comparison of eDNA Derived From Flowers and DNA Derived From Bulk Samples of Insects

Limitations of traditional insect sampling methods have motivated the development and optimisation of new non-lethal methods capable of quantifying diverse arthropod communities. Environmental DNA (eDNA) metabarcoding using arthropod-specific primers has recently been investigated as a novel way to characterise arthropod communities from the DNA they deposit on the surface of plants. This sampling method has had demonstrated success, but pollinators—especially bees—are oddly underrepresented in these studies. To evaluate this inconsistency, we investigated the limitations of eDNA metabarcoding for bees and other pollinators. We compared pollinator diversity derived from eDNA extracted from flowers and DNA extracted from pulverised bulk samples of insects collected from vane traps deployed at the same sites using three metabarcoding primers, two of which target arthropods generally (COI-Jusino and 16S-Marquina) and one that targets bumblebees (Bombus spp., COI-Milam). Across methods, we detected 77 insect families from 9 orders. The COI-Jusino marker amplified the highest taxonomic diversity compared to 16S-Marquina and COI-Milam. More amplicon sequence variants (ASVs) were recovered from vane traps (blue: 1357, yellow: 1542) than flowers (245), but only 23% of families and 13% of genera were shared among methods, indicating that flowers and blue and yellow vane traps may each sample different parts of the available arthropod community. Of 29 flower samples with known bee visitations, only 10 samples had bee detections from eDNA, and incomplete reference databases hindered assignment to species. Although our study provides additional evidence for the usefulness of eDNA metabarcoding for characterising arthropod communities, significant challenges remain when using eDNA metabarcoding methods to identify and quantify pollinator communities, especially bees.

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来源期刊
Molecular Ecology
Molecular Ecology 生物-进化生物学
CiteScore
8.40
自引率
10.20%
发文量
472
审稿时长
1 months
期刊介绍: Molecular Ecology publishes papers that utilize molecular genetic techniques to address consequential questions in ecology, evolution, behaviour and conservation. Studies may employ neutral markers for inference about ecological and evolutionary processes or examine ecologically important genes and their products directly. We discourage papers that are primarily descriptive and are relevant only to the taxon being studied. Papers reporting on molecular marker development, molecular diagnostics, barcoding, or DNA taxonomy, or technical methods should be re-directed to our sister journal, Molecular Ecology Resources. Likewise, papers with a strongly applied focus should be submitted to Evolutionary Applications. Research areas of interest to Molecular Ecology include: * population structure and phylogeography * reproductive strategies * relatedness and kin selection * sex allocation * population genetic theory * analytical methods development * conservation genetics * speciation genetics * microbial biodiversity * evolutionary dynamics of QTLs * ecological interactions * molecular adaptation and environmental genomics * impact of genetically modified organisms
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