Environmental DNA metabarcoding as a tool for fish diversity assessment in Varna Bay

Abstract

Fish diversity is widely recognized as a key indicator of aquatic ecosystem health and integrity but is increasingly threatened by anthropogenic pressures and biological invasions. Consequently, reliable and efficient methods for monitoring fish communities are essential for biodiversity conservation and ecosystem-based management. This pilot study represents the first application of environmental DNA (eDNA) metabarcoding to assess the taxonomic diversity of coastal fish assemblages in Varna Bay during the summer season. Information on coastal fish diversity along the Bulgarian Black Sea coast remains limited, as shallow coastal habitats are difficult to sample effectively using conventional fishing gears. In June 2025, water samples were collected from five coastal sites in Varna Bay. MiFish universal primers targeting the mitochondrial 12S rRNA gene region and the Illumina MiSeq platform were used. Raw demultiplexed sequencing reads were subjected to quality assessment using FastQC v0.12.1, and primers were removed using Cutadapt v4.0. Amplicon sequence variants (ASVs) were inferred using the DADA2 pipeline v1.32.0 in the R environment. Raw paired-end reads were quality filtered using filterAndTrim, discarding reads containing ambiguous bases (maxN=0) and reads with expected errors greater than two (maxEE=2). Reads were truncated at 160 bp (truncLen=c(160,160)) and additionally truncated when quality scores dropped below Q2 (truncQ=2); PhiX sequences were removed. Error rates were estimated from the data and ASVs were inferred using the DADA2 error-modeling algorithm. Forward and reverse reads were merged requiring a minimum overlap of 12 bp and no mismatches (minOverlap=12, maxMismatch=0). Chimeric sequences were removed using the consensus method implemented in removeBimeraDenovo. The resulting non-chimeric ASVs were used for downstream analyses. Taxonomic assignment was conducted using the BLAST+ tool (blastn, v2.16.0) with a top-hit approach against the MitoFish v2026.02 database. Sequences assigned to fish species were further verified using the NCBI BLAST web interface. A similarity threshold of ≥97% was used for taxonomic assignment. A total of 18 fish species were identified, whereas only a single species was reported in commercial catches by the Executive Agency for Fisheries and Aquaculture (EAFA) from the same area and sampling period. The detected fish assemblage included commercially important species that use the area as feeding and spawning grounds, such as European anchovy, horse mackerel, mullets, spiny dogfish, big-scale sand smelt, flathead grey mullet, golden grey mullet, and gobies. It also included non-commercial species of high ecological importance that are rarely detected by conventional monitoring methods, including blennies, pipefishes, Atlantic stargazer, and wrasses, as well as relatively rare species such as Mediterranean sand smelt and Atlantic horse mackerel. These findings underscore the need for comprehensive biodiversity baselines and long-term monitoring of coastal fish assemblages in the region. Despite its potential, several challenges (e.g., biases related to sampling, DNA extraction, amplification primers and conditions, bioinformatic analyses, reference databases, and the lack of standardization) require further improvement. However, the study demonstrate that environmental DNA (eDNA) metabarcoding is a sensitive and effective tool for assessing fish biodiversity in coastal marine ecosystems, highlighting its strong potential to support biodiversity monitoring, conservation planning, and evidence-based marine resource management.