Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches
Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to differen...
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doaj-8f46a50151644fe79c4dad833e7cf43b2021-09-25T23:59:59ZengMDPI AGDiversity1424-28182021-09-011343743710.3390/d13090437Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering ApproachesNicola Tommasi0Andrea Ferrari1Massimo Labra2Andrea Galimberti3Paolo Biella4ZooplantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milano, ItalyZooplantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milano, ItalyZooplantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milano, ItalyZooplantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milano, ItalyZooplantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milano, ItalyAlthough DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.https://www.mdpi.com/1424-2818/13/9/437bioinformaticscut-off thresholdshigh throughput sequencingrare taxafalse positivesmolecular ecological network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nicola Tommasi Andrea Ferrari Massimo Labra Andrea Galimberti Paolo Biella |
spellingShingle |
Nicola Tommasi Andrea Ferrari Massimo Labra Andrea Galimberti Paolo Biella Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches Diversity bioinformatics cut-off thresholds high throughput sequencing rare taxa false positives molecular ecological network |
author_facet |
Nicola Tommasi Andrea Ferrari Massimo Labra Andrea Galimberti Paolo Biella |
author_sort |
Nicola Tommasi |
title |
Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches |
title_short |
Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches |
title_full |
Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches |
title_fullStr |
Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches |
title_full_unstemmed |
Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches |
title_sort |
harnessing the power of metabarcoding in the ecological interpretation of plant-pollinator dna data: strategies and consequences of filtering approaches |
publisher |
MDPI AG |
series |
Diversity |
issn |
1424-2818 |
publishDate |
2021-09-01 |
description |
Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable. |
topic |
bioinformatics cut-off thresholds high throughput sequencing rare taxa false positives molecular ecological network |
url |
https://www.mdpi.com/1424-2818/13/9/437 |
work_keys_str_mv |
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