Validating a multi-locus metabarcoding approach for characterizing mixed-pollen samples.

Melissopalynology Metabarcoding Metagenetic Palynology Pollen Pollination

Journal

Plant methods
ISSN: 1746-4811
Titre abrégé: Plant Methods
Pays: England
ID NLM: 101245798

Informations de publication

Date de publication:
04 Nov 2023
Historique:
received: 16 12 2022
accepted: 21 10 2023
medline: 5 11 2023
pubmed: 5 11 2023
entrez: 5 11 2023
Statut: epublish

Résumé

The mutualistic interaction between entomophilous plants and pollinators is fundamental to the structure of most terrestrial ecosystems. The sensitive nature of this relationship has been disrupted by anthropogenic modifications to natural landscapes, warranting development of new methods for exploring this trophic interaction. Characterizing the composition of pollen collected by pollinators, e.g. Apis mellifera, is a common means of exploring this relationship, but traditional methods of microscopic pollen assessment are laborious and limited in their scope. The development of pollen metabarcoding as a method of rapidly characterizing the abundance and diversity of pollen within mixed samples presents a new frontier for this type of work, but metabarcoding may have limitations, and validation is warranted before any suite of primers can be confidently used in a research program. We set out to evaluate the utility of an integrative approach, using a set of established primers (ITS2 and rbcL) versus melissopalynological analysis for characterizing 27 mixed-pollen samples from agricultural sites across Canada. Both individual markers performed well relative to melissopalynology at the family level with decreases in the strength of correlation and linear model fits at the genus level. Integrating data from both markers together via a multi-locus approach provided the best rank-based correlation between metagenetic and melissopalynological data at both the genus (ρ = 0.659; p < 0.001) and family level (ρ = 0.830; p < 0.001). Species accumulation curves indicated that, after controlling for sampling effort, melissopalynological characterization provides similar or higher species richness estimates than either marker. The higher number of plant species discovered via the metabarcoding approach simply reflects the vastly greater sampling effort in comparison to melissopalynology. Pollen metabarcoding performed well at characterizing the composition of mixed pollen samples relative to a traditional melissopalynological approach. Limitations to the quantitative application of this method can be addressed by adopting a multi-locus approach that integrates information from multiple markers.

Sections du résumé

BACKGROUND BACKGROUND
The mutualistic interaction between entomophilous plants and pollinators is fundamental to the structure of most terrestrial ecosystems. The sensitive nature of this relationship has been disrupted by anthropogenic modifications to natural landscapes, warranting development of new methods for exploring this trophic interaction. Characterizing the composition of pollen collected by pollinators, e.g. Apis mellifera, is a common means of exploring this relationship, but traditional methods of microscopic pollen assessment are laborious and limited in their scope. The development of pollen metabarcoding as a method of rapidly characterizing the abundance and diversity of pollen within mixed samples presents a new frontier for this type of work, but metabarcoding may have limitations, and validation is warranted before any suite of primers can be confidently used in a research program. We set out to evaluate the utility of an integrative approach, using a set of established primers (ITS2 and rbcL) versus melissopalynological analysis for characterizing 27 mixed-pollen samples from agricultural sites across Canada.
RESULTS RESULTS
Both individual markers performed well relative to melissopalynology at the family level with decreases in the strength of correlation and linear model fits at the genus level. Integrating data from both markers together via a multi-locus approach provided the best rank-based correlation between metagenetic and melissopalynological data at both the genus (ρ = 0.659; p < 0.001) and family level (ρ = 0.830; p < 0.001). Species accumulation curves indicated that, after controlling for sampling effort, melissopalynological characterization provides similar or higher species richness estimates than either marker. The higher number of plant species discovered via the metabarcoding approach simply reflects the vastly greater sampling effort in comparison to melissopalynology.
CONCLUSIONS CONCLUSIONS
Pollen metabarcoding performed well at characterizing the composition of mixed pollen samples relative to a traditional melissopalynological approach. Limitations to the quantitative application of this method can be addressed by adopting a multi-locus approach that integrates information from multiple markers.

Identifiants

pubmed: 37925401
doi: 10.1186/s13007-023-01097-9
pii: 10.1186/s13007-023-01097-9
pmc: PMC10625703
doi:

Types de publication

Journal Article

Langues

eng

Pagination

120

Subventions

Organisme : Ontario Genomics Institute
ID : OGI-185
Organisme : Genome Canada
ID : LSARP #16420
Organisme : Ontario Research Fund
ID : LSARP #16420

Informations de copyright

© 2023. The Author(s).

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Auteurs

Sydney B Wizenberg (SB)

Department of Biology, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.

Laura R Newburn (LR)

Department of Biology, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.

Mateus Pepinelli (M)

Department of Biology, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.

Ida M Conflitti (IM)

Department of Biology, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.

Rodney T Richardson (RT)

Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, 21613, USA.

Shelley E R Hoover (SER)

Department of Biological Sciences, University of Lethbridge, 4401 University Drive W, Lethbridge, AB, T1K3M4, Canada.

Robert W Currie (RW)

Department of Entomology, University of Manitoba, 12 Dafoe Road, Winnipeg, MB, R3T2N2, Canada.

Pierre Giovenazzo (P)

Département de Biologie, Université Laval, 2325 Rue de l'Université, Québec City, Québec, G1V0A6, Canada.

Amro Zayed (A)

Department of Biology, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada. zayed@yorku.ca.

Classifications MeSH