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.

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