Potential for Genetic Improvement of the Main Slaughter Yields in Common Carp With in vivo Morphological Predictors
|Author(s)||Prchal Martin1, Bugeon Jerome2, Vandeputte Marc3, 4, Kause Antti5, Vergnet Alain4, Zhao Jinfeng1, Gela David1, Genestout Lucie6, Bestin Anastasia7, Haffray Pierrick7, Kocour Martin1|
|Affiliation(s)||1 : Univ South Bohemia Ceske Budejovice, Fac Fisheries & Protect Waters, South Bohemian Res Ctr Aquaculture & Biodivers Hy, Vodnany, Czech Republic.
2 : INRA, LPGP, Rennes, France.
3 : Univ Paris Saclay, AgroParisTech, INRA, GABI, Jouy En Josas, France.
4 : IFREMER, Palavas Les Flots, France.
5 : Nat Resources Inst Finland Luke, Biometr Genet, Jokioinen, Finland.
6 : LABOGENA DNA, Jouy En Josas, France.
7 : SYSAAF Sect Aquacole, Rennes, France.
|Source||Frontiers In Genetics (1664-8021) (Frontiers Media Sa), 2018-07 , Vol. 9 , N. 283 , P. 13p.|
|WOS© Times Cited||4|
|Keyword(s)||heritability estimates, genetic correlations, indirect selection, morphological landmarks, slaughter yields, ultrasound imagery|
Common carp is a major aquaculture species worldwide, commonly sold alive but also as processed headless carcass or filets. However, recording of processing yields is impossible on live breeding candidates, and alternatives for genetic improvement are either sib selection based on slaughtered fish, or indirect selection on correlated traits recorded in vivo. Morphological predictors that can be measured on live fish and that correlate with real slaughter yields hence remain a possible alternative. To quantify the power of morphological predictors for genetic improvement of yields, we estimated genetic parameters of slaughter yields and various predictors in 3-year-old common carp reared communally under semi-intensive pond conditions. The experimental stock was established by a partial factorial design of 20 dams and 40 sires, and 1553 progenies were assigned to their parents using 12 microsatellites. Slaughter yields were highly heritable (h2 = 0.46 for headless carcass yield, 0.50 for filet yield) and strongly genetically correlated with each other (rg = 0.96). To create morphological predictors, external (phenotypes, 2D digitization) and internal measurements (ultrasound imagery) were recorded and combined by multiple linear regression to predict slaughter yields. The accuracy of the phenotypic prediction was high for headless carcass yield (R2 = 0.63) and intermediate for filet yield (R2 = 0.49). Interestingly, heritability of predicted slaughter yields (0.48–0.63) was higher than that of the real yields to predict, and had high genetic correlations with the real yields (rg = 0.84–0.88). In addition, both predicted yields were highly phenotypically and genetically correlated with each other (0.95 for both), suggesting that using predicted headless carcass yield in a breeding program would be a good way to also improve filet yield. Besides, two individual predictors (P1 and P2) included in the prediction models and two simple internal measurements (E4 and E23) exhibited intermediate to high heritability estimates (h2 = 0.34 – 0.72) and significant genetic correlations to the slaughter yields (rg = |0.39 – 0.83|). The results show that there is a solid potential for genetic improvement of slaughter yields by selecting for predictor traits recorded on live breeding candidates of common carp.