TY - JOUR

T1 - How quantitative is metabarcoding

T2 - a meta-analytical approach

AU - Lamb, Philip D

AU - Hunter, Ewan

AU - Pinnegar, John K

AU - Creer, Simon

AU - Taylor, Martin I

AU - Davies, Richard G.

N1 - © 2018 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

PY - 2019/1

Y1 - 2019/1

N2 - Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis, and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding we conducted a structured review and meta-analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ±0.34, p<0.01), albeit it with a large degree of uncertainty. None of the tested moderators: sequencing platform type, the number of species used in a trial, or the source of DNA were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilised for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study. This article is protected by copyright. All rights reserved.

AB - Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis, and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding we conducted a structured review and meta-analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ±0.34, p<0.01), albeit it with a large degree of uncertainty. None of the tested moderators: sequencing platform type, the number of species used in a trial, or the source of DNA were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilised for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study. This article is protected by copyright. All rights reserved.

KW - Biomass

KW - High-throughout sequencing

KW - Meta-analysis

KW - Metabarcoding

KW - next generation sequencing

U2 - 10.1111/mec.14920

DO - 10.1111/mec.14920

M3 - Article

C2 - 30408260

VL - 28

SP - 420

EP - 430

JO - Molecular Ecology

JF - Molecular Ecology

SN - 1365-294X

IS - 2

ER -