Estimates of correlations for shell morphological traits on body weight of interspecific hybrid abalone (Haliotis discus hannai and Haliotis gigantea).
KEY WORDS: Haliotis discus hannai, Haliotis gigantea, hybrid abalone, correlation analysis, path analysis, multiple regression analysis
Pacific abalone Haliotis discus hannai is the most popularly cultivated abalone in China, Japan, and South Korea, known for its delicate flavor and high market value. To meet the increasing commercial demand, large-scale culture of Pacific abalone started in China during the late 1980s and entered a stage of rapid development during the past 2 decades (Guo et al. 1999).
The Xishi abalone, Haliotis gigantea (formerly Haliotis sieboldii Reeve 1846 (Naganuma et al. 1998)), which is naturally distributed along coasts of Japan, was introduced to China in 2003. Artificial hybrids between Haliotis discus hannai and H. gigantea have been produced and cultured on a commercial scale (Luo et al. 2006). Studies of genetic analysis and resistance-related physiological characteristics of hybrid abalone have been conducted. Genetic analysis by using SSR and AFLP confirmed that the hybrids should be the offspring of the genetic combination of the 2 parents (Luo et al. 2010a, Luo et al. 2010b). A previous study showed that interspecific hybrid abalone (H. discus hannai x H. gigantea) have a better growth rate and environmental adaptability than parental species (Luo 2009).
Correlations analyses between morphological traits and live weight in various shellfish have been reported (Liu et al. 2002, Deng et al. 2008, Li et al. 2008, Chang et al. 2009, Huo et al. 2010, You et al. 2010). These results demonstrated that assessment of the growth-related traits used for selective breeding could facilitate genetic improvement significantly, and with more genetic progress, to make possible the construction of a viable selection program for interspecific hybrid abalone in which economically important traits could be incorporated. The objective of the current study was to analyze the effects of shell morphological traits on body weight of reciprocal hybrid abalone.
MATERIALS AND METHODS
Abalone and Mating Design
The broodstock of Haliotis gigantea (G) and Haliotis discus hannai (D) were stocked in the Jiefeng Abalone Farm, Fuzhou City, China. The 2 species were placed separately in two 20-[m.sup.3] concrete tanks. Abalone were fed to satiation with Laminaria japonica and water was changed daily.
In November 2006, a classic nested mating design was carried out in which each mature male was mated with 3 heterospecific females. An equal amount of eggs from each of the 3 female breeders were fertilized with sperm from a single heterospecific male using the procedures described by Luo et al. (2010a). Ten males and 30 females were used to generate 30 full-sib families in each cross (DG, Haliotis discus hannai [female] x Haliotis gigantean [male]; GD, H. gigantean [female] x H. discus hannai [male]). Conditions such as water temperature, salinity, and light intensity were maintained the same for all pure and hybrid abalone.
Morphological Trait Measurements
A random sample of 30 abalone from each family in 30 full-sib families in heterospecific crosses (DG and GD) were chosen for weighing and measuring. Shell length ([X.sub.1], in millimeters), shell width ([X.sub.2], in millimeters), apex height ([X.sub.3], in millimeters), shell height ([X.sub.4], in millimeters), and body weight (Y, in grams) were measured at 540 days postfertilization. Shell length, shell width, shell height, and apex height were measured using vernier calipers (accuracy, 0.02 mm), whereas body weight was measured using an electronic balance (accuracy, 0.01 g).
The correlation coefficient, path coefficients, and determination coefficients among these growth-related traits were calculated. The multiple regression equation of the body weight (Y) was obtained. Pairwise phenotypic correlations among traits were estimated using Pearson's correlation coefficient, as implemented in SPSS version 11.5, the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL). Genetic correlation SEs were estimated as in Becker (1984). Significance was set at P < 0.05.
Means, SDs, and coefficients of variation (measured as a percent) for 4 shell morphological traits and body weight of reciprocal hybrids are summarized in Table 1. The offspring mean weight was 21.63 g in DG, which was higher than that in GD (19.69 g). Coefficients of variation between different characters were highly variable in DG and GD. The rank order of variation in DG was high for body weight (25.02%) and lowest for shell width (12.09%). The variation in traits had a similar order in GD, with 31.03% for body weight and 12.78% for shell width.
Phenotype correlation coefficients for all traits in DG and GD are shown in Tables 2 and 3, respectively. All phenotypic correlations between morphological traits and body weight in reciprocal hybrids were positive. In DG, the highest correlation coefficient between body weight and shell height was 0.891, whereas the lowest correlation coefficient (0.812) was between body weight with apex height. Moreover, in GD, the order of correlation coefficients between body weight and morphological traits was shell length (0.885), shell height (0.872), apex height (0.823), and shell width (0.789).
The effects of shell morphological traits on body weight in DG and GD are listed in Tables 4 and 5. In DG, the path coefficients of morphological traits on body weight were 0.2685 for shell length, 0.2128 for shell width, 0.1963 for apex height, and 0.3504 for shell height. Moreover, the path coefficients of shell length, shell width, apex height, and shell height on body weight in GD were 0.2749, 0.2875, 0.1993, and 0.2497, respectively. In DG, the direct effect of shell height on body weight was the highest (0.3504), whereas the direct effect of shell width on body weight was the highest (0.2875) in GD.
Tables 6 and 7 show the coefficient of determination of shell morphological traits on body weight in DG and GD. In DG, the coefficients of determination for morphological traits range from 0.1228 ([X.sub.4])-0.0453 ([X.sub.2]). In GD, the coefficients of shell length, shell width, apex height, and shell height were 0.0756, 0.0827, 0.0397, and 0.0624, respectively.
Furthermore, multiple regression equations in reciprocal hybrids were established.
Y = -181.723 + 2.4327 [X.sub.1] + 1.2548 [X.sub.2] + 1.2128 [X.sub.3] + 2.2128 [X.sub.4]
Y = -241.131 + 3.1122[X.sub.1] + 2.0166[X.sub.2] + 1.7543[X.sub.3] + 2.7312[X.sub.4]
In shellfish genetic improvement, analysis of the relationship between shell morphological traits and body weight are important not only for routine breeding management but also to assess marketable weight from a marketing point of view. Genetic parameter estimates for growth traits at juvenile and adult stages in abalone have been documented (Deng et al. 2007, You et al. 2009). An early study of genetic parameters for growth traits of the Pacific abalone Haliotis discus hannai reported positive genetic and phenotypic correlations at different ages (Deng et al. 2007). You et al. (2009) analyzed the correlation coefficient between grow-related traits in the small abalone Haliotis diversicolor and found that body weight had the highest correlation coefficient with shell length, and muscle weight had the highest correlation coefficient with shell width. Therefore, the correlation of morphological traits on body weight should be analyzed because this is useful in selecting important growth-related traits in interspecific hybrid abalone.
The results of this study show that the phenotypic correlations between morphological traits and body weight in reciprocal hybrids were significant (P < 0.05). Statistics from phenotypic traits indicate that there were very high positive phenotypic correlations between body weight and morphological traits in reciprocal hybrids, suggesting pleiotropy in the determination of those traits. Path analysis was then conducted while the phenotypic correlations coefficients, which were treated as the independent variables, were significant. The total coefficients of determination of shell morphological traits on body weight in DG and GD were 0.91 and 0.8737, respectively. Huo et al. (2010) analyzed that the determination coefficients for all the morphological traits relative to the live body weight traits were greater than 0.85, indicating that the listed morphological traits were the main factors affecting live body weight. Similar results have been observed for some bivalves, such as Chlamys farreri, Saxidomus purpuratus, Amusium pleuronectes, Patinopecten yessoensi, and Pecten maximus (Liu et al. 2002, Deng et al. 2008, Li et al. 2008, Sun et al. 2008, Chang et al. 2009, Wang et al. 2009). Our results show that the total coefficient of determination was greater than 0.85, suggesting that the listed shell morphological traits were the main factors affecting body weight in reciprocal hybrid abalone. Path analysis was able to provide estimates of the magnitude and significance of hypothesized causal connections between sets of variables, which makes it a useful tool for analyzing growth-related traits in aquatic animal. Our results showed that shell height was highly correlated with body weight among the 4 morphological traits in DG, where the direct effects were the largest. Furthermore, shell width was highly correlated with body weight in GD, where the direct effects were the largest.
Multiple regression analysis, which focuses on the relationship between a dependent variable and one or more independent variables, can be used to understand which independent variables are related to the dependent variable, and to explore these relationships. Multiple regression is a flexible method of data analysis that may be appropriate whenever a quantitative variable (the dependent variable) is to be examined in relation to any other factors (expressed as independent or predictor variables). Relationships may be nonlinear, independent variables may be quantitative or qualitative, and one can examine the effects of a single variable or multiple variables with or without the effects of other variables taken into account (Cohen et al. 2003). In our study, we obtained the multiple regression equations in DG and GD. The estimated values and the actual observed values were no statistically significant with P > 0.05. We can conclude that the equations for DG and GD may be reliable when applied to selective breeding of hybrid abalone.
Results obtained from this study will help abalone breeding practices and may lead to an increase desirable weight values in hybrid abalone populations by guiding breeders to select the best shell morphological traits in reciprocal hybrid abalone.
This research was supported by the National Natural Science Foundation of China (no. 41106120), the Hi-Tech Research and Development (863) Program of China (no. 2012AA10A412), the China Postdoctoral Science Foundation (nos. 20110490846 and 2012T50555), the Fujian Science and Technology Program (no. 2012N5012), PCSIRT (no. IRT0941), and the Earmarked Fund for Modern Agro-Industry Technology Research System (no. CARS-48).
Becker, W. A. 1984. Manual of quantitative genetics. Pullman, Washington: Academic Enterprises. 190 pp.
Chang, Y. Q., C. S. Zhang, X. B. Cao, X. G. Yan& Y. F. Lin. 2009. Effect of morphometrical traits on weight traits in one-year old yesso scallop Patinopecten yessoensis. J. Dalian Fish. Univ. 23:330-334.
Cohen, J., P. Cohen, S. G. West & L. S. Aiken. 2003. Applied multiple regression/correlation analysis for the behavioral sciences, 3rd edition. Mahwah, NJ: Lawrence Erlbaum Associates. 703 pp.
Deng, Y. W., X. D. Du, Q. H. Wang, S. Fu & R. L. Huang. 2008. Correlation and path analysis for growth traits in F1 population of pearl oyster Pinctada martensii. Mar. Sci. Bull. 10:68-73.
Deng, Y. W., X. Liu, G. F. Zhang & H. E. Zhao. 2007. Genetic parameter estimates for growth traits at early stage of Pacific abalone, Haliotis discus hannai Ino. Acta Oceanol. Sin. 26:90-95.
Guo, X. M., S. E. Ford & F. S. Zhang. 1999. Molluscan aquaculture in China. J. Shellfish Res. 18:19-3l.
Huo, Z. M., X. W. Yah, L. Q. Zhao, Y. H. Zhang, F. Yang & G. F. Zhang. 2010. Effects of shell morphological traits on the weight traits of Manila clam ( Ruditapes philippinarum). Acta Ecol. Sin. 30:251-256.
Li, J., Z. P. Wang, R. H. Yu & T. Zhao. 2008. Quantitative analysis of the relationship between shell characters and live body weight of Saxidomus purpuratus Sowerby. Mar. Fish. Res. 29:71-76.
Liu, X. L., Y. Q. Chang, J. H. Xiang, J. Song & J. Ding. 2002. Analysis of effects of shell size characters on live weight in Chinese scallop Chlamys farreri. Oceanol. Limnol. Sin. 33:73-78.
Luo, X. 2009. Study on genetic basis of hybridization between Haliotis sieboldii Reeve and Haliotis discus hannai Ino. PhD diss., Xiamen University. 189 pp.
Luo, X., C. H. Ke, W. W. You, J. X. Yang & J. Wu. 2006. Preliminary studies on hybridization between the abalone Haliotis sieboldii and H. discus discus. J. Xiamen Univ. (Nat. Sci.) 45:602-605.
Luo, X., C. H. Ke, W. W. You & D. X. Wang. 2010a. Molecular identification of interspecific hybrids between Haliotis discus hannai Ino and H. gigantea Gmelin using AFLP and microsatellite markers. Aquacult. Res. 41:1827-1834.
Luo, X., C. H. Ke, W. W. You, D. X. Wang & F. Chen. 2010b. AFLP analysis on populations of Haliotis discus hannai, Haliotis gigantea and their hybrids. J. Shellfish Res. 29:731-734.
Naganuma, T., K. Hisadome, K. Shiraishi & H. Kojima. 1998. Molecular distinction of two resemblant abalone, Haliotis discus discus and Haliotis discus hannai by 18S rDNA sequences. J. Mar. Biotechnol. 6:59-61.
Sun, X. J., A. G. Yang, Z. H. Liu & L. C. Zhou. 2008. Comparative analysis of morphological indices of Japanese scallops with shell colors. J. Anhui Agric. Sci. 36:10008-10010.
Wang, Y., L. Ye, X. Chert, Q. B. Yang, W. G. Wen & K. C. Wu. 2009. Path analysis on the morphological and weight characters of wild Amusiumpleu ronectes in Hainan. J. Anhui Agric. Sci. 37:3570-3572.
You, W. W., C. H. Ke, X. Luo & D. X. Wang. 2009. Growth and survival of three small abalone Haliotis diversicolor populations and their reciprocal crosses. Aquacult. Res. 40:1474-1480.
You, W. W., C. H. Ke, X. Luo & D. X. Wang. 2010. Genetic correlations to morphological traits of small abalone Haliotis diversicolor. J. Shellfish Res. 29:683-686.
XUAN LUO, CAIHUAN KE * AND WEIWEI YOU
State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, PR China; College of Ocean & Earth Sciences, Xiamen University, Xiamen, 361005, PR China
* Corresponding author. E-mail address: email@example.com
TABLE 1. Mean, SD, and coefficient of variation (CV) for 5 growth-related traits in reciprocal hybrids. Haliotis discus hannai [female] x Haliotis gigantea [male] [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] Y (g) (mm) (mm) (mm) (mm) Mean 21.63 51.97 34.99 9.43 10.43 SD 5.41 7.86 4.23 1.27 1.27 CV (%) 25.01 15.12 12.09 13.47 12.18 Haliotis gigantea [female] x Haliotis discus hannai [male] [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] Y (g) (mm) (mm) (mm) (mm) Mean 19.69 50.39 34.51 9.28 10.11 SD 6.11 6.07 4.41 1.38 1.41 CV (%) 31.03 12.04 12.78 14.87 13.95 TABLE 2. Phenotype correlation coefficient among the traits of Haliotis discus hannai [female] x Haliotis gigantea [male]. Traits [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.1] 1 0.826 ([dagger]) 0.804 * [X.sub.2] 1 0.869 ([dagger]) [X.sub.3] 1 [X.sub.4] Y Traits [X.sub.4] Y [X.sub.1] 0.886 ([dagger]) 0.841 ([dagger]) [X.sub.2] 0.754 * 0.817 ([dagger]) [X.sub.3] 0.730 * 0.812 ([dagger]) [X.sub.4] 1 0.891 ([dagger]) Y 1 * P < 0.05. ([dagger]) P < 0.01. TABLE 3. Phenotype correlation coefficient among the traits of Haliotis gigantea [female] x Haliotis discus hannai [male]. Traits [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.1] 1 0.907 * 0.783 * [X.sub.2] 1 0.795 ([dagger]) [X.sub.3] 1 [X.sub.4] Y Traits [X.sub.4] Y [X.sub.1] 0.735 * 0.885 ([dagger]) [X.sub.2] 0.784 * 0.789 * [X.sub.3] 0.800 ([dagger]) 0.823 ([dagger]) [X.sub.4] 1 0.872 ([dagger]) Y 1 * P < 0.05. ([dagger]) P < 0.01. TABLE 4. Effects of shell morphological traits of Haliotis discus hannai [female] x Haliotis gigantea [male] on body weight. Direct Traits Correlation effect [X.sub.1] 0.841 0.2685 [X.sub.2] 0.817 0.2128 [X.sub.3] 0.812 0.1963 [X.sub.4] 0.891 0.3504 Indirect effect Traits [summation] [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] [X.sub.1] 0.5725 0.1176 0.2822 0.1727 [X.sub.2] 0.6042 0.1966 0.2974 0.1102 [X.sub.3] 0.6157 0.1311 0.1624 0.3222 [X.sub.4] 0.5406 0.3011 0.1121 0.1274 TABLE 5. Effects of shell morphological traits of H. gigantea [female] x Haliotis discus hannai [male] on body weight. Direct Traits Correlation effect [X.sub.1] 0.885 0.2749 [X.sub.2] 0.789 0.2875 [X.sub.3] 0.823 0.1993 [X.sub.4] 0.872 0.2497 Indirect effect Traits [summation] [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] [X.sub.1] 0.6101 0.3121 0.1033 0.1947 [X.sub.2] 0.5015 0.1148 0.1683 0.2184 [X.sub.3] 0.6237 0.3116 0.1155 0.1966 [X.sub.4] 0.6223 0.1237 0.2351 0.2635 TABLE 6. Coefficient of determination of shell morphological traits of Haliotis discus hannai [female] x Haliotis gigantea [male] on total weight. Shell Traits [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] [X.sub.1] 0.0721 0.0944 0.0848 0.1667 [X.sub.2] 0.0453 0.0726 0.1124 [X.sub.3] 0.0385 0.1004 [X.sub.4] 0.1228 TABLE 7. Coefficient of determination of shell morphological traits of Haliotis gigantea [female] x Haliotis discus hannai [male] on total weight. Shell Traits [X.sub.1] [X.sub.2] [X.sub.3] [X.sub.4] [X.sub.1] 0.0756 0.1434 0.0858 0.1009 [X.sub.2] 0.0827 0.0911 0.1126 [X.sub.3] 0.0397 0.0796 [X.sub.4] 0.0624
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|Author:||Luo, Xuan; Ke, Caihuan; You, Weiwei|
|Publication:||Journal of Shellfish Research|
|Date:||Apr 1, 2013|
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