Introduction
Interest in the preservation of the environment has been heightened by environmental disruptions. Investigating biodiversity, population size, and time-course changes associated with environmental change is important for the conservation of biodiversity. Traditionally, monitoring of species has been carried out by counting individuals using distinct morphological characters. Although the direct monitoring of species is a reliable approach, it is laborious and relies on intense monitoring and sampling efforts. Moreover, certain species, such as nocturnal species, are difficult to investigate. Furthermore, direct monitoring is sometimes invasive to the environment and individual organisms.
Environmental DNA (eDNA) is a mixture of DNA released to the environment from many different species in the form of mucus, saliva, faeces, urine, gametes, and skin (Barnes and Turner, 2016; Thomsen and Willerslev, 2015; Deiner et al., 2017). By monitoring eDNA, we can monitor species in the environment without the need for sampling efforts or visual identification expertise. In the past decade, eDNA has been used to investigate the biodiversity of various species such as fish, plants, fungi, birds, and mammals (Tsuji, Takahara, Doi, Shibata, and Yamanaka, 2019). eDNA analysis is not only applied to the present environment, but also to studies of past biodiversity in ice cores and sediments (Parducci et al, 2017; Willerslev et al., 2007).
For ecological community analysis, DNA fragments (e.g., mtDNA and nuclear rRNA genes) used for phylogenetic identification are amplified by PCR followed by high-throughput sequencing (HTS). Species abundances in the community are often determined according to the obtained number of sequences or relative abundance of the sequences of each taxon in a sequence library. However, these methods are not quantitative because efficiencies of PCR amplification vary depending on several factors, such as amplified DNA sequences (e.g. GC content or the base adjacent to primers) and primer sequences when degenerate primers are used (Ben‐Dov, Shapiro, and Kushmaro, 2012; Ruijter et al., 2009; Salipante et al., 2014; Sipos et al., 2007).
Quantitative eDNA data from each taxon is useful for estimating species biomass/abundance and determining the effects of environmental disruption. DNA quantification has been conventionally performed by quantitative PCR (qPCR) (Takahara, Minamoto, Yamanaka Doi, and Kawabata, 2012; Doi et al., 2017) and more recently by digital PCR (dPCR), which is more accurate than the former because of tolerance to PCR inhibitory substances (Hoshino and Inagaki, 2012). For quantification by qPCR or dPCR, establishing an assay for each target is needed, including the design of PCR primers, preparation of standards (if qPCR is used), and optimization of PCR conditions. Therefore, the simultaneous quantification of many species is not straightforward.
Quantitative sequencing (qSeq), which has been recently developed (Hoshino and Inagaki, 2012; Hoshino and Hamada, 2017), enables simultaneous sequencing and quantification of many species in a single HTS run. In qSeq analysis, a random sequence tag is added to the 5′ end of the target sequence during single primer extension prior to PCR amplification to prepare the sequence library. If the variety of random tag sequences is sufficiently large relative to the number of targeting DNA molecules, the distribution of the random tag to DNA molecules follows the Poisson statistic. Therefore, after high-throughput sequencing, the number of DNA molecules in a sample can be estimated by counting the variety of random tags at the 5′ end of the targeted sequence without being affected by PCR bias.
In this study, we applied qSeq to eDNA analysis of five species of fish in aquaria and compared the results with dPCR and relative quantification using conventional HTS.