【作者】 何铜；

【导师】 刘小林；

【作者基本信息】 西北农林科技大学 ， 遗传学， 2010， 硕士

【摘要】 凡纳滨对虾(Litopenaeus vannamei)具有良好的适应性,快速的生长速度,较强的抗病力和抗逆能力等优良的特点,因而该对虾品种被大量地引进我国并且得到广泛的推广,结果凡纳滨对虾现在已经成为沿海和内陆地区的主要对虾养殖品种,其养殖量占对虾总养殖量的70%。因为我国海域没有凡纳滨对虾的自然分布,所以我国只能养殖多年前从国外引进的亲虾的多代留种后代。由于当时引进的凡纳滨对虾群体没有采取严格的和系统的良种选育和原种保存,结果导致凡纳滨对虾的生长性状表现了显著的变化,有利的表现包括降低的发病率,但是不良的表现包括减慢的生长速度,延长的养殖周期和分化严重的个体大小。近些年来,为了缓解凡纳滨对虾生长性状的退化,我国有些部门再次从国外引进大量的亲虾,采取这些方式确实可以使亲体的Fl代表现良好的生长性状,但是抗逆能力还是较低。虽然F2具有较高的抗逆能力,但是生长性状有显著的退化,另外大量引进亲体导致大量的外汇流失。因为上述的原因,所以需要尽快进行凡纳滨对虾的原种保存和建立良种选育体系。本研究建立在凡纳滨对虾新品种培育的基础上,进行了与目标性状相关的生长性状间的回归分析和判别分析,估计了凡纳滨对虾五月龄生长性状的遗传参数,为凡纳滨对虾的选择育种提供基本参数,科学合理地指导对虾生产实践。主要研究内容如下：1.凡纳对虾形态性状对体重的逐步回归分析选择5月龄凡纳对虾900只,测定了全长、体长、第一腹节背高、第三腹节背高、第一腹节背宽、头胸甲长、头胸甲宽、头胸甲高和体重共9个性状,采用相关分析和通径分析方法,计算了各形态性状与体重两两之间的相关系数、各形态性状为自变量对体重作依变量的通径系数及决定系数,定量地分析了形态性状对体重的影响效果。结果表明：凡纳对虾8个形态形状与体重两两之间的相关系数均达到极显著水平(P<0.01)；通径分析揭示了多元分析中多个自变量与依变量的真实关系,全长、体长、第一腹节背高、第一腹节背宽、头胸甲宽和头胸甲高对体重通径系数达到极显著或显著水平,所以它们是直接影响体重的重要指标,其中全长对体重的直接影响(0.32838**)最大,是影响体重的最主要因素,其次为头胸甲宽(0.24249**)、体长(0.15095**)、头胸甲高(0.12038**)和第一腹节背宽(0.10981**),第一腹节背高对体重的直接影响(0.04922*)最小；第三腹节背高与体重的相关系数很大(0.73571**),但它与头胸甲长对体重的直接影响都非常小,所以它们主要通过与其它性状的相关来间接影响体重,是影响体重的次要因素,均被剔除；决定系数和通径分析结果有一致的变化趋势,所选形态性状与体重的复相关系数为R2=0.9449,说明影响体重的主要自变量已经找到；逐步回归分析建立了全长(X1)、体长(X2)、第一腹节背高(X3)、第一腹节背宽(X5)、头胸甲宽(X7)和头胸甲高(X8)对体重(Y)的多元回归方程,回归截距和相应的回归系数分别为-22.599,1.043,0.547,0.969,2.279,6.118和2.797,本研究为对虾育种提供了理论依据。2.凡纳对虾各月龄性状的主成分与判别分析为了研究凡纳对虾各性状增长规律和判定错过最佳生长季节的凡纳对虾的与其大小相符的月龄,本研究选择1-6月龄凡纳对虾各1000只,测定了全长、体长、第一腹节背高、第三腹节背高、第一腹节背宽、头胸甲长和体重共7个性状,采用主成分与判别分析方法。结果表明：各月龄凡纳对虾性状之间均呈现显著的正相关(P<0.01),其中以全长与体长的相关性最为明显,1月龄凡纳对虾体重与形态性状的相关系数较小。各月龄凡纳对虾的主成分有所不同,1-2月龄凡纳对虾的第一主成分为长度因子,第二主成分为宽度因子,第三主成分为高度因子；3月龄凡纳对虾的第一主成分与1-2月龄凡纳对虾一致,但第二主成分为高度因子,第三主成分为体重因子；4-6月龄凡纳对虾的第—主成分为体重因子,第二主成分为高度因子,第三主成分为宽度因子。由这些结果可以分析出：1-3月龄凡纳对虾形态性状的发育优先于体重,但4-6月龄凡纳对虾形态性状的发育被体重追赶上。错过最佳生长季节的凡纳对虾的与其大小相符的月龄可通过本文所述的判别式来判断,判别结果为：总的判别准确率为98.98%,其中2-4月龄凡纳对虾的判别准确率为100%。3.凡纳对虾五月龄生长性状遗传参数的估计采用系统设计(巢式设计)方法,每尾雄虾交配3尾雌虾,共建成21个父系半同胞家系,47个全同胞家系,分别测定了全长(TL)、体长(BL)、头胸甲长(CL)、头胸甲宽(CW)、头胸甲高(CD)、第一腹节背高(FASD)、第三腹节背高(TASD)、第一腹节背宽(FASW)和体重(BW)等9个性状,对虾测量总数为1387尾。利用MANOVA分析方法,利用MtdfremL软件中的多变量混合动物模型进行分析,估计了所有性状遗传力和遗传相关系数。结果表明全长(TL)、体长(BL)、第一腹节背高(FASD)、第三腹节背高(TASD)、第一腹节背宽(FASW)、头胸甲长(CL)、头胸甲宽(CW)、头胸甲高(CD)和体重(BW)的遗传力分别为0.39±0.08、0.30±0.07、0.23±0.09,0.25±0.05,0.33±0.12,0.28±0.06,0.32±0.07,0.35±0.14,0.46±0.11,均属于中度遗传力范围,其中第一腹节背高(FASD)的遗传力最低,体重(BW)的遗传力最高。各个性状间表现出高的正相关,其中全长(TL)和体重(BW)的遗传相关最大,全长(TL)和第三腹节背高(TASD)的遗传相关最小。更多还原

【Abstract】 Litopenaeus vannamei has shown an excellent speed of cultivation since it was brought into our country. Because of its good compatibility, strong disease resistance, and high speed of growth, Litopenaeus vannamei has become the major cultivation breed. Litopenaeus vannamei has not been distributed to the coastal area of China and at present our country’s variety is mainly the descendant of that introduced from overseas many years ago. Due to the fact that it has not been preserved as the original variety and selectively bred as a good variety, its growth characters have changed obviously, for example in spite of the low disease incidence rate, the growth speed has been reduced and the period of cultivation has been lengthened. Besides the size differentiation is quite serious. In resent years, minority departments have been making their efforts to solve the character evolution problem. Every year they bring in numerous parents from abroad for breeding, which not only loses lots of foreign exchange but also decreases the resistance ability of F1 and influences growth traits in F2 negatively.1. Regression analysis of traits of Litopenaeus vannamei at different agesThe effects of eight morphometric attributes on body weight of Litopenaeus vannamei were analyzed by studying the data collected from 900 five-month-old Litopenaeus vannamei in Banqiao Village of Dongfang City, Hainan Province. The total length(X1), body length(X2), first abdominal segment depth(X3), third abdominal segment depth(X4), first abdominal segment width(X5), carapace length(X6), carapace width(X7), carapace depth(X8) and body weight(Y) were measured. Correlation coefficients among all attributes were calculated. Also, path coefficients and determination coefficients were calculated in path analysis where eight morphometric attributes(X1-X8) were regarded as independent variables and body weight(Y) was used as a dependent variable. The results indicated that all correlation coefficients between morphometric attributes and body weight all achieved very significant difference (P<0.01) level. The path coefficient analysis revealed a truthful relationship between independent variables and the dependent variable. The path coefficients of total length(X1), body length(X2), first abdominal segment depth(X3), first abdominal segment width(X5), carapace width(X7), and carapace depth(X8) to body weight all reached a level of significance. These attributes were quite indicative of determining body weight, among which total length(X1) weighs the most(0.32838**) to body weight, so it was a key effective factor, while the direct effect of first abdominal segment depth(X3) on body weight was least(0.04922*). Although the correlation coefficient between third abdominal segment depth(X4) and body weight is rather large (0.73571**), its direct influence on body weight is quite small just like carapace length(X6). Therefore, third abdominal segment depth(X4) and carapace length(X6) affect body weight mainly by their relationship with other attributes, so they are insignificant factors influencing body weigh and eliminated. Similar results appear by calculating determination coefficients and path analysis. Furthermore, the multiple-correlation coefficient between the chosen attributes and body weight reaches as high as R2=0.9449. All above illustrate that the main attributes determining body weight have already been discovered. The stepwise regression analysis establishes the multiple regression equation on the overall effect of total length(X1), body length(X2), first abdominal segment depth(X3), first abdominal segment width(X5), carapace width(X7) and carapace depth(X8) on body weight(Y). The regression intercept and partial regression coefficients of the equation are 1.043,0.547,0.969,2.279,6.118 and 2.797. This paper lays a solid theoretical foundation for breeding shrimps.2. Principal component and discriminant analysis of traits of Litopenaeus vannamei at different agesIn order to research on the rule of the relative growth of traits of Litopenaeus vannamei and judging the age matching with the size of Penaeus vannamei missing the best growing season, the data acquired by measuring the total length(X1), body length(X2), first abdominal segment depth(X3), third abdominal segment depth(X4), first abdominal segment width(X5), carapace length(X6) and body weight(Y) of Penaeus vannamei at different ages in Banqiao Village of Dongfang City, Hanan Province were analyzed by principal component and discriminant analysis. The results illustrate that correlation coefficients between any two traits of Litopenaeus vannamei at different ages all reach very significant difference(P<0.01), among which those between the total length(X1) and body length(X2) are relatively larger and those between body weight(Y) and morphometric attributes are relatively smaller. The principal components of Litopenaeus vannamei at different ages are different. For example, the first principal component of Litopenaeus vannamei at from one month’s age to two months is length factor, the second principal component is width factor and the third principal component is depth factor. Also, for Litopenaeus vannamei at three months’age, its first principal component is the same as that at from one month’s age to two months, but its second principal component is depth factor and its third principal component is body weight factor. Finally, the first principal component of Litopenaeus vannamei at from four months’age to six months is body weight factor, the second principal component is depth factor and the third principal component is width factor. The results of principal component analysis reflect that the growth of morphometric attributes of Penaeus vannamei at from one month’s age to three months takes priority compared with that of body weight, but the growth of body weight of Penaeus vannamei at from three months’age to six months is given priority to compared with that of morphometric attributes. The month age closely related to the size of Penaeus vannamei which has missed the best growing period can be deduced by employing the discriminant equations mentioned in this paper and the results of the discriminant analysis demonstrate that the overall accuracy is 98.98% and those of Litopenaeus vannamei at two months’age to four months all reach 100%.3. Estimates of the heritability for growth traits in market size of Pacific white shrimp, Litopenaeus vannameiHeritabilities were estimated for the body weight (BW), total length (TL), the body length (BL), first abdominal segment depth (FASD), third abdominal segment depth (TASD), first abdominal segment width (FASW), carapace length (CL), carapace width(CW) and carapace depth(CD) of Litopenaeus vannamei in the size of market at 5 month of age in Banqiao Village of Dongfang City, Hainan province. The estimates were calculated from 9 body measurements on progeny resulting from a nested mating design.21 half-sib families and 47 full-sib families of Litopenaeus vannamei were obtained by artificial assistant fertilization of 3 females by single male and measurements were made at the age of 5 months after metamorphism. Point estimate for heritabilities based on the sire component were moderate,0.39±0.08、0.30±0.07、0.23±0.09,0.25±0.05,0.33±0.12,0.28±0.06, 0.32±0.07,0.35±0.14 and 0.46±0.11 for total length (TL), the body length (BL), first abdominal segment depth (FASD), third abdominal segment depth (TASD), first abdominal segment width (FASW), carapace length (CL), carapace width(CW), carapace depth(CD) and the body weight (BW). All estimated heritabilities differ significantly from zero (P<0.01).The analysis of genetic correlations between traits demonstrated that strong positive genetic correlations existed between traits and the genetic correlation between total length (TL) and body weight (BW) is the largest while that between total length (TL) and third abdominal segment depth (TASD) is the smallest.更多还原