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基于家系水平的凡纳滨对虾(Litopenaeus vannamei)保种群体出肉率与表型性状的相关性分析
柴 展,栾 生,罗 坤,孔 杰,许圣钰
1.大连海洋大学水产与生命学院 大连 116023;2.农业部海洋渔业可持续发展重点实验室 中国水产科学研究院黄海水产研究所 青岛 266071;3.青岛海壬水产种业科技有限公司 青岛 266071
摘要:
本研究从家系水平上比较凡纳滨对虾(Litopenaeus vannamei)保种群体出肉率的差异,评估出肉率性状的选择潜力,寻找替代出肉率的间接选择性状,可为出肉率性状的遗传改良提供技术参数。2012年,保种群体养殖350 d后,测定42个家系(2094尾凡纳滨对虾)的8个表型性状(净肉重、体重、头胸甲长、腹节长、头胸甲-腹节长、体长、全长、肥满度),然后将虾杀死,剖取虾肉,计算出肉率;利用单因素方差分析方法,比较不同家系间出肉率的差异;计算各表型性状与出肉率之间的相关系数,利用逐步回归方法构建表型性状对出肉率的多元线性回归方程。结果显示,凡纳滨对虾家系出肉率的均值为(53.59±3.26)%,分布范围为50.25%−59.51%,变异系数为6.08%,家系间差异达到极显著水平(P<0.01);在8个表型性状中,与出肉率的相关性最高的3个性状分别为净肉重(r=0.478)、头胸甲-腹节长(r=0.376)和腹节长(r=0.370);在表型性状对出肉率的多元线性回归方程中,包括头胸甲-腹节长、体重和头胸甲-腹节长/全长3个性状,预测方程的决定系数为0.172。本研究首次在家系水平上表明,凡纳滨对虾保种群体家系间出肉率差异显著,但遗传变异度较低,为提高遗传进展,需进一步持续收集外部种质资源群体,并对出肉率进行家系间和家系内选择,以便获得期望的遗传进展。已测定表型性状与出肉率均处于中低度线性相关水平,初步获得与出肉率中度相关的间接选择性状;已构建的多元线性回归方程预测出肉率的准确度较低,因此,应进一步采用新的技术如超声波、核磁共振等,测定肌肉横截面积、腹节周长等新的性状,提高预测出肉率的准确性。
关键词:  凡纳滨对虾  家系  出肉率  相关
DOI:10.11758/yykxjz.20150610
分类号:
基金项目:国家“863”项目“基于全基因组信息的对虾遗传选育”(2012AA10A404)和农业部948项目“基于高通量SNP信息的凡纳滨对虾分子辅助遗传评估技术引进”(2015-Z17)以及青岛市科技成果转化引导计划(青年专项)(14-2-4-52-jch)共同资助
Correlation Analysis of Fillet Yield with Phenotypic Traits for Families from Conservation Population of Litopenaeus vannamei
CHAI Zhan1,2, LUAN Sheng3, LUO Kun3, KONG Jie3, XU Shengyu4
1.College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023;2..Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071;3.Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071;4.Qingdao Higene Aquabreeding Technology CO., LTD, Qingdao 266071
Abstract:
The objective of this study on Pacific white shrimp (Litopenaeus vannamei) was to evaluate the fillet yield performance of different families in the conservation population. A multivariate linear regression equation of fillet yield was established to find alternative indirect traits of fillet yield. A total of 2094 shrimps from 42 full-sib families were randomly sampled for measuring phenotypic traits and fillet yield in the conservation population after rearing 350 days. These traits were measured for each shrimp: fillet weight(FW), body weight(BW), carapace length(CL), segment length(SL), the length from the base of eye stalk to the 6th segment(ESL), body length(BL), total length(TL) and condition factor(CF). Fillet yield was obtained after anatomizing the shrimp and taking the meat. Differences of fillet yield between different families were analyzed using the ANOVA method. The component of variance and heritability of fillet yield trait were estimated using REML method and an individual animal model. Correlation coefficients between the phenotypic traits and fillet yield were calculated, and the prediction equations for fillet yield were established using step-wise regression analysis method. The results showed that the average fillet yield was 53.59% in L. vannamei. The mean of fillet yield between families ranged from 50.25% to 59.51%. The variation coefficient of fillet yield was 6.08% and there were significant differences between families (P<0.01). Three traits having strong correlation with fillet yield were FW (r=0.478), ESL (r=0.376) and SL(r=0.370). The multivariate linear regression equation for fillet yield was composed of ESL, BW and ESL/TL, and the coefficient of determination of the equation was 0.172. This study first implied that difference between families for fillet yield was significant. Although genetic variation for fillet yield was poor at the family level in the conservation population of L. vannamei, improved strains or populations will be introduced to increase genetic gain of fillet yield, and desirable genetic gain will be obtained using inter-family and within-family selections. Indirect selection traits with moderate correlation with fillet yield were found because correlation coefficient between phenotypic traits and fillet yield varied from low to moderate. In this study, the prediction accuracy of the constructed multiple linear regression equation for predicting fillet yield was low. Therefore, new technologies including ultrasound, magnetic resonance imaging should be developed, and new traits including cross-sectional area of muscle, circumference of segment should be measured in the future study.
Key words:  Litopenaeus vannamei  Family  Fillet yield  Correlation