Literature DB >> 33476342

Floral hosts of leaf-cutter bees (Megachilidae) in a biodiversity hotspot revealed by pollen DNA metabarcoding of historic specimens.

Annemarie Gous1,2, Connal D Eardley2, Steven D Johnson2, Dirk Z H Swanevelder1, Sandi Willows-Munro2.   

Abstract

South Africa is a megadiverse country with three globally recognised biodiversity hotspots within its borders. Bees in particular show high diversity and endemism in the western part of the country. Not much is currently known about the floral host preferences of indigenous bees in South Africa, with data only available from observational studies. Pollen metabarcoding provides provenance information by utilising DNA analyses instead of floral visitation and traditional microscopic identification to identify pollinator food plants, which can be time consuming and imprecise. In this study, we sampled pollen from leaf-cutter bees (Megachilidae) specimens maintained in a historic insect collection (National Collection of Insects, South Africa) that were originally collected from two florally important areas in South Africa (Succulent Karoo and Savanna) and used metabarcoding to determine pollen provenance. We also sampled pollen from leafcutter bee species with wider distributions, that extend across many different biomes, to determine if these 'generalist' species show relaxed floral host specificity in some biomes. Metabarcoding involved sequencing of the nuclear internal transcribed spacer 2 (ITS2) region. Amplicons were compared to a sequence reference database to assign taxonomic classifications to family level. Sequence reads were also clustered to OTUs based on 97% sequence similarity to estimate numbers of plant species visited. We found no significant difference in the mean number of plant taxa visited in the Succulent Karoo and Savanna regions, but the widespread group visited significantly more floral hosts. Bees from the widespread group were also characterised by a significantly different composition in pollen assemblage. The time since specimens were collected did not have an effect on the mean number of taxa visited by any of the bee species studied. This study highlights national history collections as valuable sources of temporal and spatial biodiversity data.

Entities:  

Year:  2021        PMID: 33476342      PMCID: PMC7819603          DOI: 10.1371/journal.pone.0244973

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  21 in total

1.  Taxonomic revival.

Authors:  E Pennisi
Journal:  Science       Date:  2000-09-29       Impact factor: 47.728

2.  Search and clustering orders of magnitude faster than BLAST.

Authors:  Robert C Edgar
Journal:  Bioinformatics       Date:  2010-08-12       Impact factor: 6.937

3.  Floral syndromes accurately predict pollination by a specialized oil-collecting bee (Rediviva peringueyi, Melittidae) in a guild of South African orchids (Coryciinae).

Authors:  Anton Pauw
Journal:  Am J Bot       Date:  2006-06       Impact factor: 3.844

4.  Evaluating multiplexed next-generation sequencing as a method in palynology for mixed pollen samples.

Authors:  A Keller; N Danner; G Grimmer; M Ankenbrand; K von der Ohe; W von der Ohe; S Rost; S Härtel; I Steffan-Dewenter
Journal:  Plant Biol (Stuttg)       Date:  2014-09-30       Impact factor: 3.081

Review 5.  Pollen DNA barcoding: current applications and future prospects.

Authors:  Karen L Bell; Natasha de Vere; Alexander Keller; Rodney T Richardson; Annemarie Gous; Kevin S Burgess; Berry J Brosi
Journal:  Genome       Date:  2016-04-13       Impact factor: 2.166

6.  A taxonomic revision of the southern African leaf-cutter bees, Megachile Latreille sensu stricto and Heriadopsis Cockerell (Hymenoptera: Apoidea: Megachilidae).

Authors:  Connal Eardley
Journal:  Zootaxa       Date:  2013-01-11       Impact factor: 1.091

7.  Pollen metabarcoding reveals broad and species-specific resource use by urban bees.

Authors:  Caitlin Potter; Natasha de Vere; Laura E Jones; Col R Ford; Matthew J Hegarty; Kathy H Hodder; Anita Diaz; Elizabeth L Franklin
Journal:  PeerJ       Date:  2019-02-19       Impact factor: 2.984

8.  Plant-pollinator interactions over time: Pollen metabarcoding from bees in a historic collection.

Authors:  Annemarie Gous; Dirk Z H Swanevelder; Connal D Eardley; Sandi Willows-Munro
Journal:  Evol Appl       Date:  2018-11-13       Impact factor: 5.183

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

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

Authors:  Rodney T Richardson; Chia-Hua Lin; Juan O Quijia; Natalia S Riusech; Karen Goodell; Reed M Johnson
Journal:  Appl Plant Sci       Date:  2015-10-30       Impact factor: 1.936

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  2 in total

1.  DNA metabarcoding identifies urban foraging patterns of oligolectic and polylectic cavity-nesting bees.

Authors:  Kristen Fernandes; Kit Prendergast; Philip W Bateman; Benjamin J Saunders; Mark Gibberd; Michael Bunce; Paul Nevill
Journal:  Oecologia       Date:  2022-09-13       Impact factor: 3.298

2.  DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring.

Authors:  Marcel Polling; Melati Sin; Letty A de Weger; Arjen G C L Speksnijder; Mieke J F Koenders; Hugo de Boer; Barbara Gravendeel
Journal:  Sci Total Environ       Date:  2021-09-21       Impact factor: 7.963

  2 in total

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