Assessment of oocyte and trochophore quality in Pacific oyster, Crassostrea gigas

• Published in: Aquaculture
• Main Authors: Boulais, Myrina, Corporeau, Charlotte, Huvet, Arnaud, Bernard, Ismael, Quere, Claudie, Quillien, Virgile, Fabioux, Caroline, Suquet, Marc
• Format: Text
• Language: English
• Published: Elsevier Science Bv 2015
• Subjects: envir; socio; Pacific; Crassostrea gigas; Pacific oyster
• Online Access: https://doi.org/10.1016/j.aquaculture.2014.11.025; https://archimer.ifremer.fr/doc/00239/35010/33544.pdf; https://archimer.ifremer.fr/doc/00239/35010/

Pacific oyster hatchery production remains highly variable, partially due to inconsistent gamete quality. However, little attention has been paid to oocyte quality in Pacific oyster compared to important vertebrate aquaculture species such as fishes. The aims of the present study were to identify criteria of oocyte and trochophore quality used as predictive tools for embryo developmental success at the D-larval stage. Twenty-six potential proxies of oocyte and trochophore quality were studied on 25 mature females, as determined using histology. Some morphological and biochemical characteristics of mature oocytes were described. Protein appeared to be the main constituent of fully mature Pacific oyster oocytes. Neutral lipids accounted for 61% of the total lipids and triglycerides for 85% of the neutral lipids. Oocyte fertilization capacity was assessed by determining the D-larval yield. High inter-individual variation of D-larval yield was observed (ranging from 1 to 58%). D-larval yield was positively correlated with the percentage of motile trochophores (R2 = 0.237) and with trochophore Velocity of the Average Path (VAP; R2 = 0.255) and negatively correlated with oocyte total steryl esters (R2 = 0.244). The use of a multivariate model, including D-larval yield, trochophore VAP and total steryl esters, led to a higher coefficient of determination (R2 = 0.352), highlighting that the prediction of embryo development in molluscs is a complex process requiring sophisticated multi-factor models.