TY - JOUR

T1 - Improving quantification of bivalve larvae in mixed plankton samples using qPCR: A case study on Mytilus edulis

AU - Alexander, Jenna

AU - Malham, Shelagh

AU - Smyth, David

AU - Webb, Julie

AU - Fidler, David

AU - Bayford, Philippa

AU - McDonald, James

AU - Le Vay, Lewis

PY - 2021/2/15

Y1 - 2021/2/15

N2 - Problems sourcing spat from naturally occurring seed beds for relay has been the main underlying limiting factor in mussel aquaculture over recent years. Attempts to address this issue require a better understanding of mussel larval patterns during the initial planktonic phase prior to settlement. A crucial step in progressing the detection and prediction of larval travel is the accurate identification of mussel larvae within environmental samples in conjunction with hydrodynamic patterns. This requires unambiguous, high throughput methods for the discrimination between larvae of morphologically-similar bivalve species. Presently methodologies require direct microscopic observation with accuracy based on taxonomic skills, techniques which are impractical for large-scale larval movement studies. Species-specific polymerase chain-reaction (PCR) presents a powerful alternative method for species detection. In addition, the technique allows for the collection of quantitative real-time PCR data which can be used for inter sample comparisons of relative larval abundance.In this study Blue mussel Mytilus edulis D-stage larvae were used to compare and optimise DNA extraction methods and to examine the quantitative potential of species-specific qPCR targeting the polyphenolic adhesive protein involved in byssal thread production. Molecular data were used to create a predictive model which could be employed to determine larval numbers from real-time data. Assays were then used to estimate M. edulis abundance in vertical–tow plankton samples collected from a trial aquaculture site off the North Wales coast.This method offers a more effective means of temporal and spatial larval pattern analysis which will improve the tracking and predictive capabilities of seed supply hydrodynamic models used for dispersal and population connectivity predictions.

AB - Problems sourcing spat from naturally occurring seed beds for relay has been the main underlying limiting factor in mussel aquaculture over recent years. Attempts to address this issue require a better understanding of mussel larval patterns during the initial planktonic phase prior to settlement. A crucial step in progressing the detection and prediction of larval travel is the accurate identification of mussel larvae within environmental samples in conjunction with hydrodynamic patterns. This requires unambiguous, high throughput methods for the discrimination between larvae of morphologically-similar bivalve species. Presently methodologies require direct microscopic observation with accuracy based on taxonomic skills, techniques which are impractical for large-scale larval movement studies. Species-specific polymerase chain-reaction (PCR) presents a powerful alternative method for species detection. In addition, the technique allows for the collection of quantitative real-time PCR data which can be used for inter sample comparisons of relative larval abundance.In this study Blue mussel Mytilus edulis D-stage larvae were used to compare and optimise DNA extraction methods and to examine the quantitative potential of species-specific qPCR targeting the polyphenolic adhesive protein involved in byssal thread production. Molecular data were used to create a predictive model which could be employed to determine larval numbers from real-time data. Assays were then used to estimate M. edulis abundance in vertical–tow plankton samples collected from a trial aquaculture site off the North Wales coast.This method offers a more effective means of temporal and spatial larval pattern analysis which will improve the tracking and predictive capabilities of seed supply hydrodynamic models used for dispersal and population connectivity predictions.

U2 - 10.1016/j.aquaculture.2020.736003

DO - 10.1016/j.aquaculture.2020.736003

M3 - Article

VL - 532

JO - Aquaculture

JF - Aquaculture

SN - 0044-8486

M1 - 736003

ER -