Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach

Area of Science:

• Molecular Palynology
• Bioinformatics
• Ecology

Background:

• Microscopic pollen identification presents challenges for large-scale ecological studies.
• Metabarcoding offers a potential solution to streamline pollen analysis.
• Quantitative accuracy of metabarcoding requires further investigation.

Purpose of the Study:

• To evaluate the quantitative capacity of different plant metabarcode regions (ITS2, matK, rbcL) and primer sets.
• To compare metabarcoding results with traditional light microscopy for pollen analysis.
• To determine the reliability of single-locus versus multilocus metabarcoding for pollen assemblages.

Main Methods:

• Applied metabarcoding targeting ITS2, matK, and rbcL loci on honey bee pollen samples.
• Analyzed six pollen samples using both metabarcoding and light microscopy.
• Assessed rank-based associations between pollen type abundances from both methods.

Main Results:

• Significant rank-based associations were found between metabarcoding and light microscopy data.
• Metabarcoding data from plastid loci (matK, rbcL) showed higher reliability for quantitative pollen characterization.
• Multilocus metabarcoding demonstrated greater reliability than single-locus analyses.

Conclusions:

• Plastid metabarcode regions are more suitable for quantitative pollen analysis than ribosomal regions.
• Multilocus metabarcoding enhances the reliability of pollen assemblage characterization.
• Further research is needed to discover and optimize novel barcodes for molecular palynology.