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

  • Animal Genetics • Original Paper
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Abstract

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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Acknowledgements

This study was funded by Special Scientific Research Funds for Central Non-profit Institutes, Chinese Academy of Fishery Sciences (2014B004 and 2014A04XK01) and the National Natural Science Foundation of China (31201989).

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Correspondence to Runqing Yang.

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The authors declared that they had no competing interests.

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Communicated by: Maciej Szydlowski

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He, J., Zhao, Y., Zhao, J. et al. Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus). J Appl Genetics 59, 99–107 (2018). https://doi.org/10.1007/s13353-018-0428-7

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  • DOI: https://doi.org/10.1007/s13353-018-0428-7

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