| 基于Gibbs抽样的贝叶斯方法估计大菱鲆生长和耐高温性状的遗传参数 |
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| 引用本文： | 马爱军,王新安,黄智慧,刘志峰,崔文晓,曲江波.基于Gibbs抽样的贝叶斯方法估计大菱鲆生长和耐高温性状的遗传参数[J].海洋学报(英文版),2018,37(6):40-46. |
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| 作者姓名： | 马爱军 王新安 黄智慧 刘志峰 崔文晓 曲江波 |
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| 作者单位： | 中国水产科学研究院黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 青岛市海水鱼类种子工程与生物技术重点实验室, 山东 青岛 266071;青岛海洋科学与技术国家实验室, 海洋生物学与生物技术功能实验室, 山东 青岛 266071,中国水产科学研究院黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 青岛市海水鱼类种子工程与生物技术重点实验室, 山东 青岛 266071;青岛海洋科学与技术国家实验室, 海洋生物学与生物技术功能实验室, 山东 青岛 266071,中国水产科学研究院黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 青岛市海水鱼类种子工程与生物技术重点实验室, 山东 青岛 266071;青岛海洋科学与技术国家实验室, 海洋生物学与生物技术功能实验室, 山东 青岛 266071,中国水产科学研究院黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 青岛市海水鱼类种子工程与生物技术重点实验室, 山东 青岛 266071;青岛海洋科学与技术国家实验室, 海洋生物学与生物技术功能实验室, 山东 青岛 266071,中国水产科学研究院黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 青岛市海水鱼类种子工程与生物技术重点实验室, 山东 青岛 266071;青岛海洋科学与技术国家实验室, 海洋生物学与生物技术功能实验室, 山东 青岛 266071,烟台天源水产有限公司, 山东 烟台 264003 |
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| 基金项目： | The Earmarked Fund for Modern Agro-Industry Technology Research System under contract No. CARS-47-G01; the AoShan Talents Cultivation Program supported by Qingdao National Laboratory for Marine Science and Technology under contract No. 2017ASTCP-OS04; the Key Research and Development Plan of Shandong under contract No. 2016GSF115019; the Agricultural Fine Breed Project of Shandong under contract No. 2016LZGC031; Chinese Acdemy of Fishery Sciences Basal Research Fund under contract No. 2016HY-JC0301; the Special Financial Grant from the China Postdoctoral Science Foundation under contract No. 2016T90661. |
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| 摘 要： | 为了开展大菱鲆耐高温选育工作,对其进行耐高温性状及其相关生长性状的遗传评估是非常必要的。以来源于英国、法国、丹麦和挪威4个国家的不同群体构建大菱鲆选育家系,利用F1的20个和F2的22个耐高温选育家系进行耐高温实验,统计耐高温评估指标（UTT）和相应的实验鱼体重（每个家系选取40-50尾实验鱼）。基于Gibbs抽样的贝叶斯方法,采用包含母性效应和不包含母性效应的两种动物模型,对大菱鲆耐高温（UTT）和生长性状的遗传力以及这两个性状间的遗传相关和表型相关进行分析。结果表明,基于不包含母性效应的动物模型估计的体重和耐高温性状的遗传力以及这两个性状之间的表型相关和遗传相关分别为0.239±0.141,0.111±0.080,0.075±0.026和-0.019±0.011。基于包含母性效应的动物模型估计的这4个值分别为0.203±0.115,0.055±0.026,0.047±0.034和-0.024±0.028,体重和耐高温性状的母性效应分别为0.050±0.017和0.013±0.004。母性效应对这两个性状的遗传评估有一定的影响。本文的研究结论为制订合理的大菱鲆耐高温育种规划提供了理论依据。
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| 关 键 词： | 遗传力 遗传相关 耐高温 体重 大菱鲆 贝叶斯推断 |
| 收稿时间： | 2017/8/9 0:00:00 |
| 修稿时间： | 2017/12/12 0:00:00 |
Estimation of genetic parameters for upper thermal tolerance and growth-related traits in turbot Scophthalmus maximus using the Bayesian method based on Gibbs sampling |
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| MA Aijun,WANG Xin''an,HUANG Zhihui,LIU Zhifeng,CUI Wenxiao and QU Jiangbo.Estimation of genetic parameters for upper thermal tolerance and growth-related traits in turbot Scophthalmus maximus using the Bayesian method based on Gibbs sampling[J].Acta Oceanologica Sinica,2018,37(6):40-46. |
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| Authors: | MA Aijun WANG Xin'an HUANG Zhihui LIU Zhifeng CUI Wenxiao and QU Jiangbo |
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| Institution: | 1.Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences;Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture;Qingdao Key Laboratory for Marine Fish Breeding and Biotechnology, Qingdao 266071, China;Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China2.Yantai Tianyuan Aquatic Limited Corporation, Yantai 264003, China |
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| Abstract: | In order to carry out the genetic improvement of turbot upper thermal tolerance, it is necessary to estimate the genetic parameters of UTT (upper thermal tolerance) and growth-related traits. The objective of this study was to estimate genetic parameters for BW (body weight) and UTT in a two-generational turbot (Scophthalmus maximus L.) pedigree derived from four imported turbot stocks (England, France, Denmark and Norway). A total of 42 families including 20 families from G1 generation and 22 families from G2 generation were used to test upper thermal tolerance (40–50 animals per family) in this study and the body weight of individuals were measured. The heritability of BW and UTT and the correlation between these two traits were estimated based on an individual animal model using Bayesian method based on two types of animal models with and without maternal effects. These results showed that the heritabilities for BW and UTT and phenotypic and genetic correlations between the two traits estimated from model without maternal effects were 0.239±0.141, 0.111±0.080, 0.075±0.026 and–0.019±0.011, respectively. The corresponding values from model with maternal effects were 0.203±0.115, 0.055±0.026, 0.047±0.034 and–0.024±0.028, respectively. The maternal effects of BW and UTT were 0.050±0.017 and 0.013±0.004, respectively. The maternal effects had a certain influence on the genetic evaluation of the two traits. The findings of this paper provided the necessary background to determine the best selection strategy to be adopted in the genetic improvement program. |
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| Keywords: | heritability genetic correlation thermotolerance body weight Turbot Bayesian inference |
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