Insect metabarcoding has been mainly based on PCR amplification of short fragments within the "barcoding region" of the gene cytochrome oxidase I (COI). However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches (ecoprimers and degeprime) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein-coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon-based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today.
Keywords: DNA barcoding; Hexapoda; in silico PCR; primer bias; taxonomic resolution.
© 2018 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.