Literature DB >> 26602877

Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material.

Austen C Thomas1,2, Bruce E Deagle3, J Paige Eveson4, Corie H Harsch1, Andrew W Trites1.   

Abstract

DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high-throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co-occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field-collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population-level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives.
© 2015 John Wiley & Sons Ltd.

Entities:  

Keywords:  DNA barcoding; diet analysis; environmental DNA; predator prey interactions

Mesh:

Year:  2015        PMID: 26602877     DOI: 10.1111/1755-0998.12490

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


  35 in total

1.  Message in a Bottle-Metabarcoding enables biodiversity comparisons across ecoregions.

Authors:  D Steinke; S L deWaard; J E Sones; N V Ivanova; S W J Prosser; K Perez; T W A Braukmann; M Milton; E V Zakharov; J R deWaard; S Ratnasingham; P D N Hebert
Journal:  Gigascience       Date:  2022-04-28       Impact factor: 7.658

2.  Consistent and correctable bias in metagenomic sequencing experiments.

Authors:  Michael R McLaren; Amy D Willis; Benjamin J Callahan
Journal:  Elife       Date:  2019-09-10       Impact factor: 8.140

3.  DNA metabarcoding uncovers the diet of subterranean rodents in China.

Authors:  Xuxin Zhang; Yao Zou; Xuan Zou; Zhenggang Xu; Xiaoning Nan; Chongxuan Han
Journal:  PLoS One       Date:  2022-04-28       Impact factor: 3.240

4.  DNA in a bottle-Rapid metabarcoding survey for early alerts of invasive species in ports.

Authors:  Yaisel J Borrell; Laura Miralles; Hoang Do Huu; Khaled Mohammed-Geba; Eva Garcia-Vazquez
Journal:  PLoS One       Date:  2017-09-05       Impact factor: 3.240

5.  Are we ready to detect nematode diversity by next generation sequencing?

Authors:  Thomas Peham; Florian M Steiner; Birgit C Schlick-Steiner; Wolfgang Arthofer
Journal:  Ecol Evol       Date:  2017-04-27       Impact factor: 2.912

6.  Diet analysis in piscivorous birds: What can the addition of molecular tools offer?

Authors:  Johannes Oehm; Bettina Thalinger; Stephanie Eisenkölbl; Michael Traugott
Journal:  Ecol Evol       Date:  2017-02-23       Impact factor: 2.912

7.  Zooplankton Community Profiling in a Eutrophic Freshwater Ecosystem-Lake Tai Basin by DNA Metabarcoding.

Authors:  Jianghua Yang; Xiaowei Zhang; Yuwei Xie; Chao Song; Yong Zhang; Hongxia Yu; G Allen Burton
Journal:  Sci Rep       Date:  2017-05-11       Impact factor: 4.379

8.  Tackling critical parameters in metazoan meta-barcoding experiments: a preliminary study based on coxI DNA barcode.

Authors:  Bachir Balech; Anna Sandionigi; Caterina Manzari; Emiliano Trucchi; Apollonia Tullo; Flavio Licciulli; Giorgio Grillo; Elisabetta Sbisà; Stefano De Felici; Cecilia Saccone; Anna Maria D'Erchia; Donatella Cesaroni; Maurizio Casiraghi; Saverio Vicario
Journal:  PeerJ       Date:  2018-06-13       Impact factor: 2.984

9.  Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding.

Authors:  Henrik Krehenwinkel; Madeline Wolf; Jun Ying Lim; Andrew J Rominger; Warren B Simison; Rosemary G Gillespie
Journal:  Sci Rep       Date:  2017-12-15       Impact factor: 4.379

10.  Combined Metabarcoding and Multi-locus approach for Genetic characterization of Colletotrichum species associated with common walnut (Juglans regia) anthracnose in France.

Authors:  Daniele Da Lio; José F Cobo-Díaz; Cyrielle Masson; Morgane Chalopin; Djiby Kebe; Michel Giraud; Agnes Verhaeghe; Patrice Nodet; Sabrina Sarrocco; Gaetan Le Floch; Riccardo Baroncelli
Journal:  Sci Rep       Date:  2018-07-17       Impact factor: 4.379

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