Quantitative assessment of fish larvae community composition in spawning areas using metabarcoding of bulk samples

Abstract

Accurate assessment of larval community composition in spawning areas is essential for fisheries management and conservation but is often hampered by the cryptic nature of many larvae, which renders them difficult to identify morphologically. Metabarcoding is a rapid and cost-effective method to monitor early life stages for management and environmental impact assessment purposes but its quantitative capability is under discussion. We compared metabarcoding with traditional morphological identification to evaluate taxonomic precision and reliability of abundance estimates, using 332 fish larvae from multinet hauls (0-50 m depth) collected at 14 offshore sampling sites in the Irish and Celtic seas. To improve quantification accuracy (relative abundance estimates), the amount of tissue for each specimen was standardized and mitochondrial primers (12S gene) with conserved binding sites were used. Relative family abundance estimated from metabarcoding reads and morphological assessment were positively correlated, as well as taxon richness (R S = 0.81, P = 0.007) and diversity (R S = 0.90, P = 0.002). Spatial patterns of community composition did not differ significantly between metabarcoding and morphological assessments. Our results show that DNA metabarcoding of bulk tissue samples can be used to monitor changes in fish larvae abundance and community composition. This represents a feasible, efficient, and faster alternative to morphological methods that can be applied to terrestrial and aquatic habitats.

Ichthyoplankton DNA metabarcoding: Challenges and perspectives

“…Constraints affecting the quantitative performance of metabarcoding are due to bias introduced during the four main stages of its workflow: (1) sample collection and processing; (2) choice of target gene; (3) HTS DNA sequencing; and (4) bioinformatics (Figure 1). Numerous approaches have been implemented to mitigate bias during each stage in order to avoid constraints that hinder accurate quali‐quantitative DNA metabarcoding analysis (Deagle et al, 2018; Ratcliffe et al, 2021; Thomas et al, 2016).…”

“…Also, the authors were able to size fractionated specimens and extract DNA from individuals of similar size to minimize bias due to different initial amounts of DNA from each larva. Similarly, Ratcliffe et al (2021) used a standardized amount of tissue for each species to improve quantification accuracy. Instead, they used PCR and conserved primer binding sites to amplify the mitochondrial 12S gene and avoid bias due to differential amplification rates.…”

“…biomonitoring 2.0, DNA barcode, environmental genomics, high-throughput DNA sequencing, neotropical fish to mitigate bias during each stage in order to avoid constraints that hinder accurate quali-quantitative DNA metabarcoding analysis (Deagle et al, 2018;Ratcliffe et al, 2021;Thomas et al, 2016). Mariac et al (2021) addresses well the bias that may arise from ichthyoplankton sampling and the unequal body size of fish larvae that may lead to differences in cell and DNA quantity from each species/specimen per bulk sample.…”

Ichthyoplankton DNA metabarcoding: challenges and perspectives

“…Constraints affecting the quantitative performance of metabarcoding are due to bias introduced during the four main stages of its workflow: (1) sample collection and processing, (2) choice of target gene, (3) HTS DNA sequencing and (4) bioinformatics (Figure 1). Numerous approaches have been implemented to mitigate bias during each stage in order to avoid constraints that hinder accurate quali-quantitative DNA metabarcoding analysis (Thomas et al 2016, Deagle et al 2018Ratcliffe et al 2021). Mariac et al (2021) addresses well the bias that may arise from ichthyoplankton sampling and the unequal body size of fish larvae that may lead to differences in cell and DNA quantity from each species/specimen per bulk sample.…”

“…Also, the authors were able to size fractionated specimens and extract DNA from individuals of similar size to minimize bias due to different initial amounts of DNA from each larva. Similarly, Ratcliffe et al (2021) used a standardized amount of tissue for each species to improve quantification accuracy. But instead, they used PCR and conserved primer binding sites to amplify the mitochondrial 12S gene and avoid bias due to differential amplification rates.…”