Environmental DNA metabarcoding primers for freshwater fish detection and quantification: In silico and in tanks

Abstract

Abstract Environmental DNA (eDNA) techniques refer to utilizing the organisms’ DNA extracted from environment samples to genetically identify target species without capturing actual organisms. eDNA metabarcoding via high‐throughput sequencing can simultaneously detect multiple fish species from a single water sample, which is a powerful tool for the qualitative detection and quantitative estimates of multiple fish species. However, sequence counts obtained from eDNA metabarcoding may be influenced by many factors, of which primer bias is one of the foremost causes of methodological error. The performance of 18 primer pairs for COI, cytb, 12S rRNA, and 16S rRNA mitochondrial genes, which are all frequently used in fish eDNA metabarcoding, were evaluated in the current study. The ribosomal gene markers performed better than the protein‐coding gene markers during in silico screening, resulting in higher taxonomic coverage and appropriate barcode lengths. Four primer pairs—AcMDB07, MiFish‐U, Ve16S1, and Ve16S3—designed for various regions of the 12S and 16S rRNA genes were screened for tank metabarcoding in a case study targeting six freshwater fish species. The four primer pairs were able to accurately detect all six species in different tanks, while only MiFish‐U, Ve16S1, and Ve16S3 revealed a significant positive relationship between species biomass and read count for the pooled tank data. The positive relationship could not be found in all species within the tanks. Additionally, primer efficiency differed depending on the species while primer preferential species varied in different fish assemblages. This case study supports the potential for eDNA metabarcoding to assess species diversity in natural ecosystems and provides an alternative strategy to evaluate the performance of candidate primers before application of eDNA metabarcoding in natural ecosystems.

Keywords

• environmental DNA
• in silico
• metabarcoding
• primer selection
• tank