Premium
Estimation of genetic parameters for early growth trait of turbot ( Scophthalmus maximus L.) using molecular relatedness
Author(s) -
Guan Jiantao,
Wang Weiji,
Luan Sheng,
Ma Yu,
Hu Yulong,
Xu Liyong,
Kong Jie
Publication year - 2016
Publication title -
aquaculture research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.646
H-Index - 89
eISSN - 1365-2109
pISSN - 1355-557X
DOI - 10.1111/are.12673
Subject(s) - biology , heritability , scophthalmus , akaike information criterion , restricted maximum likelihood , statistics , trait , genetic correlation , maximum likelihood , mating design , bayesian information criterion , turbot , genetics , genetic variation , mathematics , fish <actinopterygii> , heterosis , fishery , botany , hybrid , computer science , gene , programming language
In this study, a data set of 1140 progenies from 19 families that were composed of 13 half‐sib and six full‐sib families was used in the estimation of the genetic parameters of weight for juvenile turbot at 100 days post hatch. Sixty progenies were randomly selected from each family, and 20 of these individuals were genotyped at 12 microsatellite loci. Two sorts of relatedness, including pedigree relatedness ( PR ) from a complete pedigree and average molecular relatedness ( AMR ) from molecular markers, were compared to explore the feasibility of AMR in selective breeding when only parents were known. Two different animal models, Model 1 and Model 2 which were without and with the addition of maternal and common environmental effects, respectively, were used to estimate the variance component and breeding values for weight using restricted maximum likelihood ( REML ) method. Thereafter, cross‐validation was applied to investigate predictive ability of model and accuracy of breeding values. Pearson correlation analysis showed that AMR was highly correlated (0.91) with PR . According to conditional Akaike Information Criterion, the best models for AMR and PR methods were Model 2 and Model 1 respectively. Heritability estimates from AMR and PR methods based on their best models were 0.19 (±0.06) and 0.66 (±0.17). Cross‐validation showed that AMR was comparable to PR in terms of predictive abilities and accuracies of breeding values based on the same model. This study therefore suggests that the AMR can be applied as alternative of PR when only parents were known.