Genetic variability in residual feed intake in rainbow trout clones and testing of indirect selection criteria (Open Access publication)

Genetics Selection Evolution

Muriel Mambrini²  Béatrice Chatain¹  Christèle Robert-Granié³  Thierry Boujard²  Edwige Quillet²  Laure Grima¹ 

[1] Ifremer, Station d'aquaculture expérimentale, chemin de Maguelone, 34250 Palavas-les-Flots, France;INRA, UR 544 Génétique des poissons, Domaine de Vilvert, 78350 Jouy-en-Josas, France;INRA, UR 631 Station d'amélioration génétique des animaux, BP 52627, 31320 Castanet-Tolosan, France

关键词: selection;    indirect criteria;    residual feed intake;    clone;    rainbow trout;   

Others  :  1093808
DOI  :  10.1186/1297-9686-40-6-607

 received in 2008-01-10, accepted in 2008-07-01,  发布年份 2008

【 摘 要 】

Little is known about the genetic basis of residual feed intake (RFI) variation in fish, since this trait is highly sensitive to environmental influences, and feed intake of individuals is difficult to measure accurately. The purpose of this work was (i) to assess the genetic variability of RFI estimated by an X-ray technique and (ii) to develop predictive criteria for RFI. Two predictive criteria were tested: loss of body weight during feed deprivation and compensatory growth during re-feeding. Ten heterozygous rainbow trout clones were used. Individual intake and body weight were measured three times at threeweek intervals. Then, individual body weight was recorded after two cycles of a three-week feed deprivation followed by a three-week re-feeding. The ratio of the genetic variance to the phenotypic variance was found high to moderate for growth, feed intake, and RFI (VG/VP = 0.63 ± 0.11, 0.29 ± 0.11, 0.29 ± 0.09, respectively). The index that integrates performances achieved during deprivation and re-feeding periods explained 59% of RFI variations. These results provide a basis for further studies on the origin of RFI differences and show that indirect criteria are good candidates for future selective breeding programs.

【 授权许可】

   
2008 INRA, EDP Sciences