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

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.

Diet and trophic interactions of a circumglobally significant gelatinous marine zooplankter,Dolioletta gegenbauri(Uljanin, 1884)

“…Increasingly, these methods are also being used to quantify prey consumption although quantification can be considerably more challenging (Frischer et al, ; Nejstgaard et al, ). Results from NGS studies are particularly prone to systematic bias associated with library preparation, sequencing and bioinformatics procedures, and thus, it is recommended that NGS data be interpreted qualitatively unless appropriate controls or complimentary orthogonal methods are also applied (Bista et al, ; Hardwick, Deveson, & Mercer, ). In this study, NGS data were interpreted semi‐quantitatively and, in the case of diatoms, the results confirmed independently by real‐time qPCR.…”

The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative

“…Universal primers do not perfectly match the DNA of all species, and so there is a variable number of template-primer mismatches across species. In consequence, some species are better amplified than others and the proportions in the final mixture do not reflect the original proportion of each species (Bista et al, 2018;Elbrecht & Leese, 2015;Leray et al, 2013). There are other complications in the PCR step that produce more biases; for instance, the use of indexed PCR primers (used to minimize the per sample cost of sequencing by allowing the sequencing of many samples in a single run) might induce further biases (Leray & Knowlton, 2017;O'Donnell, Kelly, Lowell, & Port, 2016).…”

“…There are other complications in the PCR step that produce more biases; for instance, the use of indexed PCR primers (used to minimize the per sample cost of sequencing by allowing the sequencing of many samples in a single run) might induce further biases (Leray & Knowlton, 2017;O'Donnell, Kelly, Lowell, & Port, 2016). The avoidance of the PCR step (shotgun metagenomics) would in theory render a faithful list of R i (Bista et al, 2018), and this is what is mostly used in microbial metabarcoding nowadays (Jovel et al, 2016). However, in eukaryotes, the scarcity of assembled genomes, and the vast amount of sequencing depth needed, makes shotgun metabarcoding still unsuitable in most circumstances (Gómez-Rodríguez, Crampton-Platt, Timmermans, Baselga, & Vogler, 2015;Zhou et al, 2013).…”

Testing clustering strategies for metabarcoding‐based investigation of community–environment interactions

“…Metabarcoding generates enormous biodiversity information of zooplankton with high sensitivity, including species at any stages, and cryptic species and organisms that are either too fragile, small or rare to be identified by traditional methods (Abad et al, 2016;Lindeque, Parry, Harmer, Somerfield, & Atkinson, 2013;Zhan et al, 2013). Thus, metabarcoding can comprehensively characterize taxa composition and estimate relative abundance of taxa in a semiquantitative way (Abad et al, 2016;Bista et al, 2018). As a result, metabarcoding-based methods have been popularly utilized in many ecological studies.…”