Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus)

被引:0
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作者
Jie He
Yunfeng Zhao
Jingli Zhao
Jin Gao
Pao Xu
Runqing Yang
机构
[1] Chinese Academy of Fishery Sciences,Freshwater Fisheries Research Center
[2] Chinese Academy of Fishery Sciences,Key Laboratory of Aquatic Genomics, Ministry of Agriculture, Research Centre for Aquatic Biotechnology
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关键词
Random regression model; Body weight; Morphological trait; GIFT tilapia;
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学科分类号
摘要
To genetically analyse growth traits in genetically improved farmed tilapia (GIFT), the body weight (BWE) and main morphological traits, including body length (BL), body depth (BD), body width (BWI), head length (HL) and length of the caudal peduncle (CPL), were measured six times in growth duration on 1451 fish from 45 mixed families of full and half sibs. A random regression model (RRM) was used to model genetic changes of the growth traits with days of age and estimate the heritability for any growth point and genetic correlations between pairwise growth points. Using the covariance function based on optimal RRMs, the heritabilities were estimated to be from 0.102 to 0.662 for BWE, 0.157 to 0.591 for BL, 0.047 to 0.621 for BD, 0.018 to 0.577 for BWI, 0.075 to 0.597 for HL and 0.032 to 0.610 for CPL between 60 and 140 days of age. All genetic correlations exceeded 0.5 between pairwise growth points. Moreover, the traits at initial days of age showed less correlation with those at later days of age. With phenotypes observed repeatedly, the model choice showed that the optimal RRMs could more precisely predict breeding values at a specific growth time than repeatability models or multiple trait animal models, which enhanced the efficiency of selection for the BWE and main morphological traits.
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页码:99 / 107
页数:8
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