Abstract
The nucleotide variation in the cytochrome c oxidase subunit I (COI) gene makes it ideal for assigning sequences to species. However, this variability also makes it difficult to design truly universal primers. Here, we present the forward primer “Sauron‐S878,” specifically designed to facilitate library preparation for metabarcoding. This primer is modified to improve the coverage of terrestrial species compared to the primer mCOIintF, optimized for aquatic systems, which raised the in silico coverage from 74.4% to 98.3% of available NCBI sequences (perfect match in 3′ region, up to three mismatches in remaining primer). When paired with the reverse primer “jgHCO2198” (fragment length ~313 bp), these primers amplified 98.4% of 255 tested DNA extracts from various taxa, which are better than many other common COI barcoding primers. Furthermore, a single‐tube protocol was developed, wherein these primers amplify the target gene, and attach MIDs and Illumina sequencing adapters in one reaction. This eliminates the need for re‐amplification or enzymatic ligation during library preparation while keeping the flexibility to modularly combine primers and MIDs. Using the single‐tube approach, three replicates of three mock samples were sequenced on a MiSeq platform with no adverse effects compared to commercial Nextera indexing kits. From this run, 75% of all included taxa could be recovered, with no considerable bias among taxonomic groups. Despite the fact that 98.4% of the extracts were confirmed to amplify in vitro, this number was lower than expected. A reason for this discrepancy was a clear link between the relative concentration of a specific DNA type in the template and the number of returned reads for this DNA. We would argue that such a bias may be especially problematic in metabarcoding where samples usually contain trace DNA in unknown amounts. However, how this affects the completeness of metabarcoding results has yet been poorly investigated.
Highlights
Metabarcoding is an easy to use and powerful method that increasingly is being employed to detect the presence of species in applications ranging from the analysis of community bulk samples (Ji et al, 2013; Yu et al, 2012) to biodiversity assessments from environmental DNA (Bohmann et al, 2014; Taberlet, Coissac, Hajibabaei, & Rieseberg, 2012; Thomsen & Willerslev, 2015) and studies of trophic interactions (De Barba et al, 2014; Deagle, Kirkwood, & Jarman, 2009; Pompanon et al, 2012; Valentini et al 2009)
The main reason for this is that, even though other genes have been shown to work better to identify plants, fungi (ITS; Schoch et al, 2012) and bacteria (16S; Tringe & Hugenholtz, 2008), c oxidase subunit one (COI) has usually been suitable in identifying most animals to species level (Hebert, Cywinska, & Ball, 2003)
It was selected as the target gene for the barcode of life initiative (BOLD), and so far, the number of animal species sequenced for this gene fragment (~2.3 million sequences from ~280,000 species in GenBank) is much greater than for other common barcoding genes such as 16S (~380,000 sequences from ~90,000 species) or 18S (~170,000 sequences from ~70,000 species)
Summary
Metabarcoding is an easy to use and powerful method that increasingly is being employed to detect the presence of species in applications ranging from the analysis of community bulk samples (Ji et al, 2013; Yu et al, 2012) to biodiversity assessments from environmental DNA (Bohmann et al, 2014; Taberlet, Coissac, Hajibabaei, & Rieseberg, 2012; Thomsen & Willerslev, 2015) and studies of trophic interactions (De Barba et al, 2014; Deagle, Kirkwood, & Jarman, 2009; Pompanon et al, 2012; Valentini et al 2009). As even though alternative barcoding regions may be more suited for primer design, these will restrict scientists to treating individual taxa as observed operational taxonomic units (OTUs; Ji et al, 2013) This can have negative effects on the quality of results, especially when reference sequences are not available or when species cannot be distinguished based on the delivered sequence information (e.g., 18S). This will hamper species identification and make important characteristics such as species traits difficult or impossible to assign
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