Literature DB >> 29667329

Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples.

Iliana Bista1,2, Gary R Carvalho1, Min Tang3, Kerry Walsh4, Xin Zhou3, Mehrdad Hajibabaei5, Shadi Shokralla5, Mathew Seymour1, David Bradley6, Shanlin Liu7,8, Martin Christmas4, Simon Creer1.   

Abstract

New applications of DNA and RNA sequencing are expanding the field of biodiversity discovery and ecological monitoring, yet questions remain regarding precision and efficiency. Due to primer bias, the ability of metabarcoding to accurately depict biomass of different taxa from bulk communities remains unclear, while PCR-free whole mitochondrial genome (mitogenome) sequencing may provide a more reliable alternative. Here, we used a set of documented mock communities comprising 13 species of freshwater macroinvertebrates of estimated individual biomass, to compare the detection efficiency of COI metabarcoding (three different amplicons) and shotgun mitogenome sequencing. Additionally, we used individual COI barcoding and de novo mitochondrial genome sequencing, to provide reference sequences for OTU assignment and metagenome mapping (mitogenome skimming), respectively. We found that, even though both methods occasionally failed to recover very low abundance species, metabarcoding was less consistent, by failing to recover some species with higher abundances, probably due to primer bias. Shotgun sequencing results provided highly significant correlations between read number and biomass in all but one species. Conversely, the read-biomass relationships obtained from metabarcoding varied across amplicons. Specifically, we found significant relationships for eight of 13 (amplicons B1FR-450 bp, FF130R-130 bp) or four of 13 (amplicon FFFR, 658 bp) species. Combining the results of all three COI amplicons (multiamplicon approach) improved the read-biomass correlations for some of the species. Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding. However, for large-scale ecological studies, metabarcoding currently remains the most commonly used approach for diversity assessment.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  biodiversity; biomass; genome skimming; invertebrates; metabarcoding; metagenomics

Year:  2018        PMID: 29667329     DOI: 10.1111/1755-0998.12888

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  20 in total

1.  Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods.

Authors:  Paula Arribas; Carmelo Andújar; Kristine Bohmann; Jeremy R deWaard; Evan P Economo; Vasco Elbrecht; Stefan Geisen; Marta Goberna; Henrik Krehenwinkel; Vojtech Novotny; Lucie Zinger; Thomas J Creedy; Emmanouil Meramveliotakis; Víctor Noguerales; Isaac Overcast; Hélène Morlon; Anna Papadopoulou; Alfried P Vogler; Brent C Emerson
Journal:  Gigascience       Date:  2022-07-19       Impact factor: 7.658

2.  Improved high throughput protocol for targeting eukaryotic symbionts in metazoan and eDNA samples.

Authors:  Diana Minardi; David Ryder; Javier Del Campo; Vera Garcia Fonseca; Rose Kerr; Stein Mortensen; Alberto Pallavicini; David Bass
Journal:  Mol Ecol Resour       Date:  2021-10-01       Impact factor: 8.678

3.  Comparison of traditional and DNA metabarcoding samples for monitoring tropical soil arthropods (Formicidae, Collembola and Isoptera).

Authors:  Yves Basset; Mehrdad Hajibabaei; Michael T G Wright; Anakena M Castillo; David A Donoso; Simon T Segar; Daniel Souto-Vilarós; Dina Y Soliman; Tomas Roslin; M Alex Smith; Greg P A Lamarre; Luis F De León; Thibaud Decaëns; José G Palacios-Vargas; Gabriela Castaño-Meneses; Rudolf H Scheffrahn; Marleny Rivera; Filonila Perez; Ricardo Bobadilla; Yacksecari Lopez; José Alejandro Ramirez Silva; Maira Montejo Cruz; Angela Arango Galván; Héctor Barrios
Journal:  Sci Rep       Date:  2022-06-24       Impact factor: 4.996

4.  Detection and quantification of Anopheles gambiae sensu lato mosquito larvae in experimental aquatic habitats using environmental DNA (eDNA).

Authors:  Joel Odero; Bruno Gomes; Ulrike Fillinger; David Weetman
Journal:  Wellcome Open Res       Date:  2018-03-08

5.  Food Tracking Perspective: DNA Metabarcoding to Identify Plant Composition in Complex and Processed Food Products.

Authors:  Antonia Bruno; Anna Sandionigi; Giulia Agostinetto; Lorenzo Bernabovi; Jessica Frigerio; Maurizio Casiraghi; Massimo Labra
Journal:  Genes (Basel)       Date:  2019-03-25       Impact factor: 4.096

6.  Uncovering bacterial and functional diversity in macroinvertebrate mitochondrial-metagenomic datasets by differential centrifugation.

Authors:  Jan-Niklas Macher; Arjen Speksnijder; Le Qin Choo; Berry van der Hoorn; Willem Renema
Journal:  Sci Rep       Date:  2019-07-16       Impact factor: 4.379

7.  Increased performance of DNA metabarcoding of macroinvertebrates by taxonomic sorting.

Authors:  Kevin K Beentjes; Arjen G C L Speksnijder; Menno Schilthuizen; Marten Hoogeveen; Rob Pastoor; Berry B van der Hoorn
Journal:  PLoS One       Date:  2019-12-16       Impact factor: 3.240

8.  Genome-skimming provides accurate quantification for pollen mixtures.

Authors:  Dandan Lang; Min Tang; Jiahui Hu; Xin Zhou
Journal:  Mol Ecol Resour       Date:  2019-09-18       Impact factor: 7.090

9.  Establishing arthropod community composition using metabarcoding: Surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches.

Authors:  Daniel Marquina; Rodrigo Esparza-Salas; Tomas Roslin; Fredrik Ronquist
Journal:  Mol Ecol Resour       Date:  2019-09-18       Impact factor: 7.090

10.  Analysis of 13,312 benthic invertebrate samples from German streams reveals minor deviations in ecological status class between abundance and presence/absence data.

Authors:  Dominik Buchner; Arne J Beermann; Alex Laini; Peter Rolauffs; Simon Vitecek; Daniel Hering; Florian Leese
Journal:  PLoS One       Date:  2019-12-23       Impact factor: 3.240

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