The Genetic Parameters of Growth Traits and Breeding Value Estimation in Largemouth Bass (Micropterus salmoides)

CHAPTER 2

The Genetic Parameters of Growth Traits and Breeding Value Estimation in Largemouth Bass (Micropterus salmoides) Contents 2.1 Early-Stage Growth of Largemouth Bass 2.1.1 Materials and Methods 2.1.2 Results and Analysis 2.2 Morphological Traits of Largemouth Bass in Different Families During Early-Stage Growth 2.2.1 Materials and Methods 2.2.2 Results and Analysis 2.3 Influence of Morphological Traits on the Body Weight of Largemouth Bass 2.3.1 Materials and Methods 2.3.2 Results and Analysis 2.4 Heredity Parameters of Growth Traits in Largemouth Bass 2.4.1 Materials and Methods 2.4.2 Results and Analysis 2.5 The Breeding Value of the Growth Traits of Largemouth Bass 2.5.1 Materials and Methods 2.5.2 Results and Analysis References

43 44 46 55 56 57 64 65 66 74 75 78 80 80 81 85

2.1 EARLY-STAGE GROWTH OF LARGEMOUTH BASS Studies of fish growth are basic work toward their genetic improvement. The ideal fish growth curve not only provides the growth pattern, but can also predict the growth rate and feed consumption of the fish in different periods. In China, growth traits only in the larval and juvenile stages in largemouth bass have been studied (Lu, 1994; Liu et al., 1995; Li and Su, 2000). In other countries, researchers have mainly focused on the development of wild largemouth bass (Beamesderfer and North, 1995; Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass DOI: https://doi.org/10.1016/B978-0-12-816473-0.00002-5 Copyright © 2019 China Science Publishing & Media Ltd. Published by Elsevier Inc.

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Clugston, 1964; Lorenzoni et al., 2002; Schulz and Leal, 2005), and there are no reports of the growth of cultured largemouth bass. Therefore, in this study, we investigated the growth and developmental patterns of cultured largemouth bass. The results of this study can provide a basic reference for the management and breeding of cultured largemouth bass.

2.1.1 Materials and Methods 2.1.1.1 Family Management and Fish Selection Sixteen healthy largemouth bass were obtained from the breeding base of the Pearl River Fisheries Research Institute. These fish were reproduced artificially one-to-one to construct eight full-sib families. The eggs were hatched in an outdoor incubator at about 20˚C. The larvae hatched after incubation for 72 h. Each family was cultured individually and initially fed small zooplankton twice a day in the morning and evening. About 2 weeks after hatching, they were fed both tubificid worms and zooplankton. At about 1 month old, the fish were transferred to net cages (3 3 3 3 2 m3) at a density of 50 fish/m2 and trained to eat frozen and fresh fish twice a day. Fluorochrome markers (with color of yellow, white, red, green, blue, orange, and pink) were injected into the tail fin, caudal peduncle, and base anal fin of the fish at 3 months old (average body weight, 5 g). The fish from the same family were injected with the same color fluorochrome at the same position. After marking, all the families were cultured together in a single pond. About 30
40 fish were randomly selected every month and their body weight and body length were measured. 2.1.1.2 Measurement Methods The body length and body weight of each individual was measured every month with a standard method. Briefly, the fish were anesthetized with 30
100 mg/L MS-222. They were weighed and photographed with a digital camera. Body length was measured with the WinMeasure software. 2.1.1.3 Data Analysis The accumulated growth curve, relative growth curve, and absolute growth curve of the 1
7-month-old largemouth bass were drawn with Excel 2003 software. The relative growth rate and absolute growth rate were calculated in terms of body weight and body length, and the condition factors were analyzed. The data were analyzed with regression nonlinear modeling with the SPSS 15.0 software. The optimal estimated

The Genetic Parameters of Growth Traits and Breeding Value Estimation

Table 2.1 Three nonlinear models being fitted Model Formulae

Gompertz Logistic von Bertalanffy

Y 5 Ae2B exp(2kt) Y 5 A/(1 1 Be2kt) Y 5 A(1 2 Be2kt)3

45

Weight inflexion (WI)

Age inflexion (AI)

A/e A/2 8 A/27

(lnB)/k (lnB)/k (ln3B)/k

Note: A, limit grow value; k, growth rate; B, parameter; t, age (months); WI, weight inflexion; AI, age inflexion; W, body weight; L, body length; H, body height.

value of the model was calculated according to the body weight and body length data for the 1
7-month-old largemouth bass, and the growth models were constructed. The degree of fit (R2), or the “determination coefficient,” was used to estimate the models. The models used in the present study were shown in Table 2.1. The condition factors, also called the “fullness coefficients” (Dai et al., 2006), are another way to express the body weight and body length of fish. They are usually used as indicators of the measurement of fullness coefficients, nutrition, and environmental conditions. Different formulae are based on different assumptions. For example, for the Fulton state index K, body weight is considered proportional to the cube of the body length (b 5 3). For the Ricker relative state index K0 , the relationship still holds when b ¼ 6 3, but b must be known in advance. For the Jones state index B and Richter state index B0, the body height must be measured. In the present study, the correlation between body weight and body length was determined. The condition factors in 1
7-month-old largemouth bass were calculated according to the fitting results and the formulae: absolute growth rate (Yin, 1993): G 5 (W2 2 W1)/(t2 2 t1); G 5 (L2 2 L1)/(t1 2 t2); relative growth rate (Dai et al., 2006): G 5 (W2 2 W1)/W1(t2 2 t1); G 5 (L2 2 L1)/L1(t1 2 t2); Fulton state index (Dai et al., 2006) K: K 5 100 W/L3; Richer relative state index K0 (Bannister, 1976): K0 5 100 W/Lb; Jones state index (Jones et al., 1999) B: B 5 W/HL2; Richter state index (Richter et al., 2000) B0 : B0 5 W/H2L; power function: W 5aLb. 2.1.1.4 Test Methods for the Equation Fitting Analysis The three models used in this study had nonlinear differential equations. Therefore, the parameters of these models were iteratively computed

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

with the Gauss
Newton algorithm and the objective function minimum residual sum of squares with a convergent standard at 1 3 1028. The multiple correlation coefficients (R2) were then calculated and used to measure the goodness of fit.

2.1.2 Results and Analysis 2.1.2.1 Body Weight and Body Length of the 1
7-Month-Old Largemouth Bass and Their Multiple Comparisons Among Families The largemouth bass individuals from eight families were marked with different color fluorochromes at 3 months old. All the marked fish were cultured together in the same pond. As shown in Table 2.2, the standard deviations of their body weight and body length increased with age, indicating that the differential growth of the largemouth bass individuals increased. When cultured in the pond, the body weight and body length increased rapidly, which may be attributable to two major factors. First, the pond provided a vast living place for largemouth bass. Second, when the fish were 3 months old, the water temperature reached about 28˚C, which is optimal for largemouth bass growth. Multiple comparisons of the body weight of fish of the same age between every two families were made with the least squares method. As shown in Table 2.3, at 1 month old, the body weight of family 06 was significantly higher than those of the other families (P , 0.05); at 2 months old, the body weight of families 04, 05, and 06 did not differ significantly (P . 0.05), but these families were significantly heavier than the other families (P , 0.05); at 3 months old, the body weight of family 06 was significantly higher than those of the other families (P , 0.05); at 4 months old, body weight did not differ significantly among families 01, 04, 05, and 06 (P . 0.05), but these families were significantly heavier than the other families (P , 0.05); at 5 months old, body weight did not differ significantly among families 01, 04, 05, 06, and 09 (P . 0.05), but these families were significantly heavier than the other families (P , 0.05); at 6 months old, body weight did not differ significantly among families 05, 06, and 09 (P . 0.05), but these families were significantly heavier than the other families (P , 0.05); and at 7 months old, body weight did not differ significantly between families 05 and 06 (P . 0.05), but these families were extremely significantly heavier than the other families (P , 0.05). In summary, the growth rates of families 05, 06, and 09 were better than those of other families at different stages, and especially better than those of families 02, 07, and 10.

Table 2.2 Body weight and body length of largemouth bass at 1
7 months old Parameters

1 month (N 5 264)

2 months (N 5 300)

3 months (N 5 320)

4 months (N 5 260)

5 months (N 5 271)

6 months (N 5 249)

7 months (N 5 248)

Bodyweight (g) Body length (cm)

0.34 6 0.16 —

1.35 6 0.56 3.98 6 0.45

4.85 6 1.67 5.82 6 0.75

26.97 6 17.63 9.55 6 1.78

77.05 6 43.43 13.18 6 2.54

168.80 6 62.94 18.50 6 2.19

245.23 6 73.71 21.03 6 2.11

Table 2.3 Multiple comparisons of body weight among different families at different stages (1
7 months old) (g) Family number

1 month

2 months

3 months

4 months

5 months

6 months

7 months

01 02 04 05 06 07 09 10

0.37 6 0.19BCFbdf 0.30 6 0.14CEGceg 0.44 6 0.15ABb 0.27 6 0.08EGeg 0.52 6 0.09Aa 0.24 6 0.10Gg 0.38 6 0.15BDbd 0.25 6 0.09Gg

1.48 6 0.38ABb 0.96 6 0.24Ce 1.57 6 0.69ABa 1.68 6 0.42Aa 1.60 6 0.51ABa 1.05 6 0.32Cce 1.40 6 0.69Bbd 0.93 6 0.28Ce

4.88 6 1.76BDbcf 4.07 6 1.23BCeg 4.90 6 1.48Bbc 5.74 6 1.54Aa 5.03 6 1.21ABbd 3.66 6 1.48Cg 5.13 6 1.90ABb 4.19 6 1.54BCceg

31.95 6 19.02ABab 20.84 6 10.77BCdf 31.29 6 17.63ABab 37.93 6 20.73ABac 38.27 6 20.02Aa 18.68 6 12.60Cf 28.29 6 18.75Bbe 17.33 6 9.14Cf

74.11 6 29.07ABab 72.14 6 34.58ABb 91.84 6 37.83ACab 92.45 6 43.73Aa 85.58 6 57.80ABab 65.71 6 35.33Bb 90.12 6 51.49ABab 60.25 6 28.28Db

159.71 6 53.86ABDd 156.17 6 59.69BDde 160.13 6 41.40ABDbd 196.78 6 52.98Aa 196.12 6 84.46ACac 123.80 6 28.24De 180.29 6 57.90ABEabd 116.42 6 23.17Fe

214.90 6 55.56Cc 204.67 6 37.75Cc 244.42 6 69.13BCbc 307.17 6 71.61Aa 298.91 6 85.14ABab 192.11 6 51.51Cc 264.91 6 66.73Bb 187.48 6 42.82Cc

Note: Different upper-case letters in the same column indicate extremely significant differences between groups (P , 0.01); different lower-case letters in the same column indicate significant differences between groups (P , 0.05); the same lower-case letter in a single column indicates no significant difference (P . 0.05).

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

2.1.2.2 Accumulated Growth Curves of Body Weight and Body Length for Largemouth Bass (1
7 Months Old) As shown in Figs. 2.1 and 2.2, the body weight of largemouth bass increased slowly in the first 3 months. However, it increased rapidly in an approximately straight line after 3 months old. Body length increased slowly in the first 2 months, but increased extremely rapidly thereafter, also in an approximately straight line. The relative growth rate is the ratio of the increase in body weight or body length to the body weight or body length, respectively, at the start of a given time interval (Yin, 1993). As shown in Figs. 2.3 and 2.4, the maximum relative growth rates of largemouth bass in terms of its body weight and body length occurred in the fourth month. Thereafter, the relative growth rate in body weight decreased dramatically. However, the

Body weight (g)

Body weight 350 300 250 200 150 100 50 0 0

1

2

3

4 5 Months

6

7

8

Figure 2.1 Accumulated growth curve of largemouth bass body weight (1
7 months old).

Body length (cm)

25 20 15 10 5 0

0

1

2

3

4

5

6

7

8

M onths

Figure 2.2 Accumulated growth curve of largemouth bass body length (2
7 months old).

Relative growth rate of body weight per month

The Genetic Parameters of Growth Traits and Breeding Value Estimation

49

500% 400% 300% 200% 100% 0%

0

1

2

3

4 5 Months

6

7

8

Relative growth of rate of standard length per month

Figure 2.3 Relative growth curve of largemouth bass body weight (1
7 months old).

70% 60% 50% 40% 30% 20% 10% 0%

0

1

2

3

4 5 Months

6

7

8

Figure 2.4 Relative growth curve of largemouth bass body length (2
7 months old).

relative growth rate in body length increased gently again to 6 months, but declined sharply thereafter. In theory, the relative growth curve is an asymptote of the growth curve. It should decline as the feeding time increases. However, the results of the present study were not identical to the theoretical values. In the fourth month, an abnormal relative growth rate in body weight was observed, which might be attributable to the more abundant food in the pond than in the cage. After largemouth bass were marked with fluorochromes, the fish were transferred to the pond and could ingest numerous zooplankton, benthic animals, small fish, and shrimp. However, over time, the fresh food decreased daily. The growth of largemouth bass was then no longer influenced by the external conditions, so the growth rates better approximated the theoretical pattern. As shown in Figs. 2.5 and 2.6, the absolute growth rate of largemouth bass in terms of body weight increased every month, reaching a maximum in the sixth month, after which it declined. The trend in the

Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Absolute growth of rate of body weight per month

50

100 80 60 40 20 0

0

1

2

3

4 5 M onths

6

7

8

Growth rate of standard length per month (cm/month)

Figure 2.5 Monthly absolute growth rate of largemouth bass in body weight.

6 5 4 3 2 1 0

0

1

2

3

4 5 Months

6

7

8

Figure 2.6 Monthly absolute growth rate of largemouth bass in body length.

absolute growth rate in terms of body length was similar to that of body weight, but decreased slightly in the fifth month. The absolute growth rate is the increase in body weight or body length within a given time interval (Dai et al., 2006). Theoretically, the absolute growth rate curve should be a parabola, and the growth of the animals can generally be divided into four periods. As shown in Figs. 2.5 and 2.6, the absolute growth rates in body weight and body length increased before the sixth month and then decreased. However, the absolute growth rates in body length were slightly lower in the fifth month than in the fourth month. This result is inconsistent with the theory and may be because body length is a quantitative trait, controlled by multiple quantitative trait locus. An increase in body length depends not only on the gene itself, but was also affected by the environment. Under natural conditions, the environmental factors involved are complex. Therefore, it is unavoidable that the data obtained in this study were not the expected data.

The Genetic Parameters of Growth Traits and Breeding Value Estimation

51

2.1.2.3 Model Fitting Analysis of Body Weight and Body Length in Largemouth Bass As shown in Table 2.4, the fitting precision (R2) was 0.99 when the data for the body weight and body length of largemouth bass were fitted to nonlinear models, including the Gompertz, logistic, and von Bertalanffy models. Among these, the logistic model best fitted the data, with fitting precision (R2) of 1.000 for body weight and 0.996 for body length. All the curves obtained with these models fitted the growth curves well. Table 2.5 shows both the observed and predicted values for body weight and body length in detail. For the 1- and 2-month-old largemouth bass, the Gompertz and von Bertalanffy models did not provide a good prediction of body weight. However, the estimation error was lower when predicted with the logistic model. All three models predicted body length well. Therefore, the logistic model is the best method for predicting the body weight and body length of largemouth bass. Before sexual maturity, it is not easy to differentiate male and female largemouth bass based only on external appearances, because no significant differences in the growth curves of male and female largemouth bass have been identified (Robert et al., 1960). Therefore, the sex differences in the growth curves were not clarified in the present study. Our results show that nonlinear models fitted the growth of largemouth bass well, and the fitting precision exceeded 0.99. The logistic model gave a perfect fit for body weight in young largemouth bass (R2 5 1), and was also better than the other two models in fitting body length (R2 5 0.996). These results indicate that the logistic model fits the growth in body weight and body length of largemouth bass better than other models, especially in the early stages of growth. The logistic growth curve is a standard S-shaped curve (Xiong et al., 1996). Theoretically, it reflects the different growth characteristics of a whole population objectively in different stages. In general, the growth of largemouth bass can be divided into four periods: the growth increase period, accelerated growth period, decelerated growth period, and growth cessation period. From the model, the inflection ages of largemouth bass for body weight and body length growth are 5.77 and 4.95 months, respectively. In other words, the increases in body weight and body length in largemouth bass slowed at 5.77 and 4.95 months, respectively. The inflection point for body weight and body length was 146.35 g and 13.75 cm, respectively. However, the models for largemouth bass differ from those of other species. The growth of the

Table 2.4 Estimates of parameters and degrees of fit for body weight and body length of largemouth bass with three models Models Parameters R2 Inflection point (Ti, Yi)

Bodyweight

Body length

Gompertz Logistic von Bertalanffy Gompertz Logistic von Bertalanffy

A

B

k

420.989 292.699 1723.956 40.963 27.508 60.869

3.287 2173.059 1.317 1.437 22.088 0.828

0.559 1.332 0.146 0.267 0.625 0.148

0.999 1.000 0.996 0.993 0.996 0.992

Table 2.5 Comparison of the observed and estimated values for body weight and body length in largemouth bass Models 1 month 2 months 3 months 4 months 5 months

Body weight (g)

Body length (cm)

Observed values Gompertz Logistic von Bertalanffy Observed values Gompertz Logistic von Bertalanffy

0.34 0.00 0.51 2 4.59





1.35 0.07 1.92 0.01 3.98 3.48 3.61 3.46

4.85 2.82 7.15 5.73 5.82 6.21 6.06 6.29

26.97 24.05 25.37 31.93 9.55 9.67 9.5 9.72

77.05 81.9 77.41 83.35 13.18 13.57 13.65 13.52

(2.13, (5.77, (9.41, (1.36, (4.95, (6.15,

154.87) 146.35) 510.80) 15.07) 13.75) 18.04)

6 months

7 months

168.80 165.06 168.81 157.61 18.50 17.59 17.82 17.5

245.23 246.44 245.21 249.45 21.03 21.45 21.31 21.5

The Genetic Parameters of Growth Traits and Breeding Value Estimation

53

Tibetan chicken fits the Gompertz growth model (Wang et al., 2005), and that of the Haimen goat also fits the Gompertz growth model (Jiang et al., 2001). Among fish species, the Gray dynamic growth model is suitable for the growth of Bostrychus sinensis (Zhang, 2002), and the Gompertz model is suitable for the body length growth of Cromileptes altivelis (Ou et al., 2007). However, the nonlinear growth model applicable to largemouth bass is rarely reported. Beamish et al. (2005) found that the von Bertalanffy models for wild male and female largemouth bass differed. The best models for different species or even the same species are not identical across different studies. These discrepancies may be attributable to the different growth conditions among studies. A report by Beamish et al. (2005) demonstrated that the growth of largemouth bass is affected by various factors, including latitude, temperature, feed, and subspecies (Beamish et al., 2005). The model parameters were affected by the fish shape, their growth conditions, and the abundance of food, and differ in different species or even within the same species in the same model. The growth rates of largemouth bass were reported to vary across regions and countries (Helser and Han, 2004), with a negative correlation between growth and latitude, so that fish at higher latitudes showed lower growth rates. Therefore, the growth model constructed under specific conditions only provides the appropriate feeding, breeding, and management information for similar situations. 2.1.2.4 Relationship Between Body Weight and Body Length Growth in Largemouth Bass A scatter diagram of the body weight and body length of largemouth bass in the early stages of growth was shown in Fig. 2.7. This is not a linear relationship. We used an exponential power function to fit the relationship between body weight and body length (Table 2.6). As shown in Table 2.6, the data fitted the power exponent function very well (R2 5 0.998). The parameter b 6¼ 3, representing the growth of largemouth bass in the early stage, was not constant, which is consistent with the general principles of fish growth. The growth function between body weight and body length for largemouth bass was: W 5 0.076L2.650 (R2 5 0.998). The power function has been widely used to study the body weight
body length relationship in numerous studies of fish growth and provides a very good fit of the relationship. Lu (1994) investigated the

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Body weight (g)

300 250 200 150 100 50 0

0

3

6

9

12

15

18

21

24

Body length

Figure 2.7 Scatter diagram of the relationship between body weight and body length in largemouth bass.

Table 2.6 Fitting parameters for body weight and body length in largemouth bass Parameter Estimated Standard 95% Confidence interval value error Upper Lower confidence limit confidence limit

A B R2

0.076 2.650 0.998

0.025 0.112

0.006 2.340

0.146 2.961

weight and length of largemouth bass larvae with a power function. Although their research differed from ours, we both obtained good results using this function. The growth function of largemouth bass for body weight and body length in the present study fitted the power function well (W 5 0.076L2.650, R2 5 0.998) and the results indicate that the fish in this study were in an allometric growth period. Huang and Chang (1999) summarized the results of previous studies and found that the parameter b is usually less than three in juvenile fish populations, indicating strong allometric growth. However, the allometry weakens and the differences become smaller as the fish grow. Our results are consistent with those of previous studies. 2.1.2.5 Fatness of Largemouth Bass As shown in Table 2.7, the fatness of largemouth bass increased with increasing age. It was relatively low at 2 to 3 months, which may be attributable to the small culture space, which strongly restricted the growth and development of the fish.

The Genetic Parameters of Growth Traits and Breeding Value Estimation

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Table 2.7 Fatness of largemouth bass at 2
7 months old Age Fulton state Ricker relative Jones state (months) index K state index K0 index B

Richter state index B0

2 3 4 5 6 7

0.29 0.29 0.33 0.35 0.41 0.26

2.14 2.46 3.10 3.37 2.67 2.64

3.23 4.15 6.05 7.24 6.34 6.52

0.08 0.08 0.10 0.11 0.10 0.08

2.2 MORPHOLOGICAL TRAITS OF LARGEMOUTH BASS IN DIFFERENT FAMILIES DURING EARLY-STAGE GROWTH Breeding from a family line is one of the major methods used for selective fish breeding. Together with population breeding, it is widely used in breeding several fish species, including Oreochromis niloticus L. (Ponzoni et al., 2005), Salmo gairdneri (Donaldson and Olson, 1955), and Salmo salar (Refstie and Steine, 1978). Series of fast-growing, disease-resistant species have been generated with this method. For instance, the economic traits of S. salar were improved twofold in Norway, and their culture cycle was reduced from 4 years to 18 months after six generations of selection (Refstie and Steine, 1978). Therefore, this method is highly successful in fish breeding. Family breeding can also provide material for genetic analysis. For example, the construction of genetic linkage maps requires genetic information from both the parents and offspring in the family (Xia et al., 2010). Since 2005, the Pearl River Fisheries Research Institute (CAFS) has focused on the artificial selection of largemouth bass in China. A new variety was generated, whose growth rate increased to 117.8%
125.3% of that of un-selective largemouth bass (Li et al., 2009), and population breeding of largemouth bass has progressed rapidly. On the basis of these results, future research should focus on family breeding. In the present study, one-to-one artificial reproduction was used to construct 17 families of largemouth bass. The morphological traits of each individual were measured. The “goodness” of the families was estimated by comparing the morphological differences between different families. These data provide basic information for family selection in largemouth bass.

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

2.2.1 Materials and Methods 2.2.1.1 Experiment Fish This experiment was conducted at the breeding base of the Pearl River Fisheries Research Institute (CAFS). The parent largemouth bass were from Jinhui Farm in Jiujiang town, in Foshan city. The basic largemouth bass population was from farms at Nanhai and Shunde districts of Foshan city (Li et al., 2009). In February 2009, individuals with a body weight of 400
500 g were selected as parents for breeding. When 24 pairs were randomly matched and allowed to reproduce one-to-one, 17 full-sib families were ultimately obtained, and designated S01D01, S02D02, S03D03, S04D04, S05D05, S06D06, S07D07, S08D08, S09D09, S10D10, S11D11, S12D12, S13D13, S14D14, S15D15, S16D16, and S17D17. 2.2.1.2 Fish Cultivation and Marking The larvae were placed into 9 m2 cement tanks and each family was cultured individually. They were fed small zooplankton twice a day in the morning and evening. About 2 weeks after hatching, the fish were also fed tubificid worms. At about 2 months old, the fish were marked with fluorochromes (with yellow, red, green, blue, orange, and pink color), which were injected into the head skin, tail fin, caudal peduncle, and anal fin. Fish from the same family were injected with the same color fluorochrome at the same positions. After marking, all the families were cultured in a single pond. 2.2.1.3 Data Collection The 4- and 6-month-old fish were caught in July 2009 and September 2009, respectively. They were differentiated into families by the color and location of the fluorescent marks. They were then anesthetized with an appropriate concentration of MS-222. Photographs were taken with a digital camera and analyzed with the WinMeasure software. Six morphological traits including full length, body length, head length, caudal peduncle length, body height, and caudal peduncle height were measured. 2.2.1.4 Data Analysis The morphological traits were analyzed with SPSS and EXCEL software, with a correlation analysis, principal components analysis, variance analysis, and multiple comparisons.

The Genetic Parameters of Growth Traits and Breeding Value Estimation

57

Absolut growth rate 5 (L2 2 L1)/(t2 2 t1), where L1 and L2 represent the overall length at t1 and t2, respectively (Yin, 1993). Growth index 5 (log L2 2 log L1)/(0.4343 3 L1), where L1 and L2 represent the overall length at t1 and t2, respectively (Shen and Liu, 1999). Body index 5 full length/body height or caudal peduncle length/caudal peduncle height. Variable coefficient (CV) 5 σ/μ, where σ represents the standard deviation and μ represents the mean value.

2.2.2 Results and Analysis 2.2.2.1 Phenotypic Parameters of Morphological Traits of Largemouth Bass and Their Correlations The morphological traits were analyzed statistically according to their phenotypic parameters and are shown in Table 2.8. The correlation coefficient matrix for largemouth bass at 4 and 6 months was generated with a correlation coefficient method (Table 2.9). These six traits correlated positively with one another, with varying correlation coefficients. In the 4-month-old largemouth bass, the correlation coefficients between the caudal peduncle length and the other five traits were low (0.796
0.869). However, the correlation coefficients were .0.89 for the other correlations. In the 6-month-old largemouth bass, the caudal peduncle length correlated with the head length with low correlation coefficients (0.565
0.875), whereas the correlation coefficients were .0.93 among the remaining four characters. 2.2.2.2 Principal Components Analysis of the Morphological Traits of Largemouth Bass The morphological traits of largemouth bass at 4 and 6 months were analyzed individually with a principal components analysis. Only the first principal component was found, with eigenvalues at 5.537 and 5.184 at 4 and 6 months, respectively. The eigenvectors for the morphological traits in the principal components analysis and their contributions are shown in Table 2.10. These results indicate that the major eigenvectors of the first principal components of the 4- and 6-month-old largemouth bass were full length and body length. Therefore, length was used as the first principal component of the parameters for the morphological traits of largemouth bass. Among these traits, full length contributed most, with contribution rates of 92.29% and 84.60% at 4 and 6 months, respectively.

Table 2.8 Phenotypic parameters of the morphological traits of largemouth bass (cm) Traits 4 months (N 5 579)

Full length Body length Head length Body height Caudal peduncle length Caudal peduncle height

Minimum

Maximum

Mean 6 SD

7.72 3.44 2.19 1.92 1.02 0.72

20.4 18.07 6.14 6.14 3.42 2.31

11.667 9.989 3.265 3.031 2.103 1.236

6 6 6 6 6 6

1.929 1.742 0.569 0.589 0.367 0.237

Table 2.9 Correlation coefficients for the morphological traits of largemouth bass Age Trait Full length Body Head length length

4 months

6 months

Full length Body length Head length Body height Caudal peduncle Caudal peduncle Full length Body length Head length Body height Caudal peduncle Caudal peduncle

length height

length height

1 0.984 0.939 0.964 0.869 0.942 1 0.990 0.698 0.954 0.875 0.930

6 months (N 5 361) Minimum

Maximum

Mean 6 SD

10.56 8.92 2.86 2.44 1.58 1.06

23.02 19.87 12.55 6.93 4.13 2.60

15.689 13.518 4.409 4.125 2.861 1.693

6 6 6 6 6 6

1.872 1.678 0.714 0.606 0.397 0.231

Body height

Caudal peduncle length

Caudal peduncle height

1 0.935 0.954 0.860 0.935

1 0.923 0.796 0.897

1 0.839 0.949

1 0.806

1

1 0.737 0.956 0.881 0.932

1 0.694 0.565 0.669

1 0.810 0.937

1 0.826

1

The Genetic Parameters of Growth Traits and Breeding Value Estimation

59

Table 2.10 Eigenvectors of the morphological traits of largemouth bass in a principal components analysis and their contributions Trait 4 months old 6 months old

Full length Body length Head length Body height Caudal peduncle length Caudal peduncle height

Eigenvector

Contribution rate (%)

Eigenvector

Contribution rate (%)

0.368 0.366 0.355 0.364 0.333

92.29 4.03 1.78 0.92 0.73

0.366 0.368 0.287 0.359 0.332

86.40 7.99 3.44 1.34 0.69

0.358

0.24

0.355

0.13

The second principal component was body length, which contributed 4.03% and 7.99%, respectively. 2.2.2.3 Variance Analysis of Full Length in Different Families In Table 2.11, the variance of fish in different families was analyzed. These results indicated that the full length of the fish varied across the different families. In the 4-month-old largemouth bass, families S07D07 and S08D08 had the optimal full lengths of 13.0842 6 3.751 and 13.524 6 2.063 cm, respectively. In the 6-month-old largemouth bass, families S03D03, S07D07, S08D08, and S14D14 had the optimal full lengths of 16.234 6 2.94, 18.232 6 2.633, 17.779 6 2.244, and 16.047 6 1.623 cm, respectively. 2.2.2.4 Absolute Growth Rates of Full Length and Growth Indices As shown in Table 2.12, a variance analysis was performed on the absolute growth rate of the full length and the growth index. It revealed that families S03D03, S04D04, S07D07, S09D09, and S15D15 differed significantly from the other families in their absolute growth rates and full lengths. Families S07D07 and S15D15 were the optimal families in these respects. 2.2.2.5 Principal Components Analysis of Body Indices The body indices of largemouth bass at 4 and 6 months was analyzed individually with a principal components analysis. Only the first principal

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Table 2.11 Variance analysis of full length in different families Family

S01D01 S02D02 S03D03 S04D04 S05D05 S06D06 S07D07 S08D08 S09D09 S10D10 S11D11 S12D12 S13D13 S14D14 S15D15 S16D16 S17D17

Full length (4 months old)

Full length (6 months old)

Mean 6 SD

Variable coefficient (%)

Mean 6 SD

11.261 6 1.787CD 12.153 6 1.915BC 11.751 6 1.893BC 10.845 6 1.353CD 10.765 6 1.422D 11.134 6 1.986CD 13.084 6 3.751AB 13.524 6 2.063A 10.884 6 1.778CD 11.264 6 2.055CD 11.782 6 1.347BC 11.135 6 1.602CD 12.221 6 1.766B 12.057 6 2.112BC 9.767 6 1.375E 11.032 6 1.123CD 11.676 6 1.637C

15.86 15.75 16.11 12.47 13.21 17.83 27.73 15.25 16.33 18.24 11.43 14.38 14.45 17.49 14.07 10.18 14.02

15.585 15.168 16.234 15.483 15.079 15.155 18.232 17.779 15.662 15.646 15.756 15.155 15.786 16.047 15.038 15.002 14.767

Variable coefficient (%)

6 1.572D 6 1.322D 6 2.94ABD 6 1.51D 6 2.086D 6 1.466D 6 2.633A 6 2.244AC 6 0.654D 6 2.341D 6 1.669D 6 2.44D 6 1.659BD 6 1.623ABD 6 0.582D 6 1.420D 6 2.029D

10.08 8.71 18.11 9.75 13.83 9.67 14.44 12.62 4.18 14.96 10.59 16.1 10.51 10.11 3.87 9.46 13.74

Note: Different letters (A, B, C, or D) in the same column indicate significant differences between groups (P , 0.05); the same letter in a single column indicates no significant difference (P . 0.05).

Table 2.12 Variance analysis of absolute growth rate and growth index in different families Family Absolute growth rate (cm/day) Growth index

S01D01 S02D02 S03D03 S04D04 S05D05 S06D06 S07D07 S08D08 S09D09 S10D10 S11D11 S12D12 S13D13 S14D14 S15D15 S16D16 S17D17

2.162 6 0.108B 1.507 6 0.297D 2.241 6 0.526AB 2.319 6 0.078AB 2.157 6 0.332B 2.011 6 0.260B 2.574 6 0.559AB 2.127 6 0.090B 2.389 6 0.562AB 2.191 6 0.143B 1.987 6 0.161B 2.010 6 0.417B 1.782 6 0.053BC 1.995 6 0.245B 2.636 6 0.397A 1.985 6 0.148BD 1.545 6 0.196C

3.647 2.673 3.796 3.858 3.627 3.408 4.249 3.696 3.907 3.697 3.424 3.431 3.121 3.424 4.181 3.391 2.742

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

0.069AB 0.428E 0.851AB 0.186AB 0.546B 0.293B 0.596A 0.209AB 0.671AB 0.307AB 0.292B 0.682B 0.029BC 0.285B 0.401AB 0.266BD 0.352CE

Note: Different letters (A, B, C, or D) in the same column indicate significant differences between groups (P , 0.05); the same letter in a single same column indicates no significant difference (P . 0.05).

The Genetic Parameters of Growth Traits and Breeding Value Estimation

61

Table 2.13 Eigenvectors of the body indices of largemouth bass in a principal components analysis and their contributions Body indices 4 months old 6 months old

Full length/ body height Caudal peduncle length/caudal peduncle height

Eigenvector

Contribution (%)

Eigenvector

Contribution (%)

0.302

65.94

0.309

69.08

0.302

34.06

0.309

30.92

component was found, with eigenvalues of 1.319 and 1.382 at 4 and 6 months, respectively. The eigenvectors of the morphological traits in the principal components analysis and their contributions were shown in Table 2.13. For different ages (months), the eigenvalues for full length/ body height and caudal peduncle length/caudal peduncle height were equal. However, the contribution of full length/body height was clearly greater than that of caudal peduncle length/caudal peduncle height. Specifically, the contribution of full length/body height was greater at 6 months than at 4 months, whereas the contribution of caudal peduncle length/caudal peduncle height was greater at 4 months than at 6 months. 2.2.2.6 Variance Analysis of Body Indices in Different Families The variance analysis of the body indices in different families is summarized in Tables 2.14 and 2.15. As shown in Table 2.14, in the 4-monthold largemouth bass, most families had good full length/body height values, except S04D04, S05D05, S09D09, S15D15, S16D16, and S17D17. The minimum value was observed in family S07D07 (3.751 6 0.225). In the 6-month-old largemouth bass, better ratios for full length/ body height were observed in families S03D03, S04D04, S06D06, S07D07, and S15D15. The minimum value was observed in family S07D07 (3.613 6 0.199). As shown in Table 2.15, in the 4-month-old largemouth bass, the families with good caudal peduncle length/caudal peduncle height ratios were S03D03, S06D06, S08D08, and S10D10. The minimum ratio was observed in family S06D06 at both 4 months (1.572 6 0.217) and 6 months (1.466 6 0.156).

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Table 2.14 Variance analysis of body indices (full length/body height) in different families Family 4 months old 6 months old

S01D01 S02D02 S03D03 S04D04 S05D05 S06D06 S07D07 S08D08 S09D09 S10D10 S11D11 S12D12 S13D13 S14D14 S15D15 S16D16 S17D17

3.835 3.858 3.824 3.931 3.974 3.797 3.751 3.858 4.021 3.785 3.802 3.859 3.887 3.805 3.900 4.004 3.903

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

0.229D 0.192D 0.212D 0.160ABD 0.192AC 0.124D 0.225D 0.165D 0.308A 0.218D 0.188D 0.177D 0.226BD 0.185D 0.235ABD 0.210A 0.221ABD

3.809 3.886 3.716 3.699 3.887 3.745 3.613 3.775 3.848 3.777 3.837 3.842 3.890 3.768 3.680 3.923 3.811

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

0.177ABD 0.168AC 0.216DE 0.154DE 0.151A 0.109DE 0.199E 0.150D 0.171ABD 0.164BD 0.170ABD 0.248ABD 0.169A 0.172D 0.130DE 0.082A 0.208ABD

Note: Different letters (A, B, C, and D) in the same column indicate significant differences between groups (P , 0.05); the same letter in a single column indicates no significant difference (P . 0.05).

Table 2.15 Variance analysis of body indices (caudal peduncle length/caudal peduncle height) in different families Family 4 months old 6 months old

S01D01 S02D02 S03D03 S04D04 S05D05 S06D06 S07D07 S08D08 S09D09 S10D10 S11D11 S12D12 S13D13 S14D14 S15D15 S16D16 S17D17

1.702 1.724 1.667 1.713 1.759 1.572 1.717 1.652 1.839 1.685 1.739 1.769 1.737 1.693 1.708 1.727 1.719

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

0.184B 0.205AB 0.164BC 0.136B 0.164AB 0.217C 0.229B 0.185BC 0.333A 0.227BC 0.207AB 0.228AB 0.178AB 0.203B 0.221B 0.124AB 0.208B

1.693 1.719 1.766 1.669 1.675 1.466 1.807 1.641 1.695 1.704 1.694 1.718 1.747 1.673 1.649 1.752 1.681

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

0.129ABD 0.135ABD 0.103A 0.109D 0.115D 0.156E 0.239A 0.145D 0.179ABD 0.186ABD 0.129ABD 0.114ABD 0.123AC 0.122D 0.079D 0.108A 0.101BD

Note: Different letters (A, B, C, and D) in the same column indicate significant differences between groups (P , 0.05); the same letter in a single column indicates no significant difference (P . 0.05).

The Genetic Parameters of Growth Traits and Breeding Value Estimation

63

2.2.2.7 Correlation and Principal Components Analyses of Morphological Traits of Largemouth Bass A correlation analysis of the morphological traits of largemouth bass showed strong positive mutual correlations between the six traits in the 4- and 6-month-old largemouth bass. These results are consistent with the results of He et al. (2009), which showed that the morphological traits of adult largemouth bass (431.0
967.5 g), including the full length, body length, body height, body width, interorbital distance, head length, lip length, caudal peduncle length, and caudal peduncle height, correlated strongly positively with one another. This suggests that the correlations are not related to age. However, a correlation involves the direct relationships and indirect relationships between two variates (Yuan et al., 2001). A correlation analysis alone cannot remove the overlapping information caused by correlations with one another. Therefore, a principal components analysis is used together with the correlation analysis to simplify the multiple traits to single or several comprehensive but simple traits (He et al., 2009; Xiong et al., 2006; Pu et al., 2009). Their relationships are then analyzed further. In this study, the results of the principal components analysis revealed that the first principal component represented the six morphological traits of largemouth bass. Length was the eigenvector. This suggests that an increase of full length and body length would be prior to the changes in the other traits. The contributions of full length to the 4- and 6-month-old largemouth bass were 92.29% and 86.40%, respectively. Therefore, full length contributes most to the variance of all six traits. Strong positive correlations were also found between full length and the other traits. Therefore, full length can be used as an index for the selection of morphological traits in largemouth bass. The contribution of full length/body height (65.94%) was larger than that of caudal peduncle length/caudal peduncle height (69.08%) at the different ages (months), based on the results of the principal components analysis. However, the accumulated contribution rate was less than 85%, suggesting that both indices can be used as standards for body index selection in different largemouth bass families. 2.2.2.8 Construction of Largemouth Bass Families to Provide Material for Breeding Abundant genetic variation is necessary for breeding. During the process of fish breeding, families have been constructed to obtain abundant genetic variation in the selection group in fish such as Paralichthys

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

olivaceus (Liu and Liu, 2008), O. niloticus (Dong et al., 2008), and S. gairdneri (Donaldson and Olson, 1955). According to the results of our variance analysis and the variable coefficients for full length and body indices, the largemouth bass families in the present study contain abundant genetic variation and can be used for family line selection. In the variance analysis of full length, only two families were optimal at 4 months. However, four families were optimal at 6 months. This suggests that some genes may be expressed at the later stage of the growth in largemouth bass. Therefore, future studies should focus on the growth within each family to obtain more material upon which to build vigorous growth. Although both families S07D07 and S08D08 performed well in full length and coefficient of variance at both 4 and 6 months old, family S07D07 was used as the parents for breeding because its absolute growth rate, growth indices, and body indices were better than those of family S08D08.

2.3 INFLUENCE OF MORPHOLOGICAL TRAITS ON THE BODY WEIGHT OF LARGEMOUTH BASS One of the targets of animal breeding is to increase the animal’s body weight. However, when the hereditary capacity is low, it is difficult to obtain the desired result with direct selection. Therefore, indirect selection targeting traits that are strongly related to the desired result will achieve better results. Correlation analyses and multivariate regression analyses have been widely used to determine these target traits in animal breeding (Zhou et al., 1994; Yi et al., 2002; He et al., 2004). Numerous studies have been undertaken in shrimp (Liu et al., 2004), crab (Geng et al., 2007), shellfish (Liu et al., 2002), and fish (Deboski et al., 1999; Hong and Lee, 1999; Myers et al., 2001; Neira et al., 2004; Vandeputte et al., 2004; Wang et al., 2006; Tong et al., 2007). A correlation analysis of phenotypic characters is frequently used in such studies, but it is limited in identifying the real relationships between independent and dependent variables. In this section, phenotypic correlation, path analysis, and multivariate regression were used to identify the major traits and their direct and indirect effects on the body weight of largemouth bass. The multiple regression equation for body weight was also determined to provide a theoretical basis for index selection in largemouth bass breeding.

The Genetic Parameters of Growth Traits and Breeding Value Estimation

65

2.3.1 Materials and Methods 2.3.1.1 Animals The largemouth bass used in the study were from the breeding bases of Nanshui in Shunde, Foshan, Guangdong Province. On April 3, 2007, the larval fish were placed in a 15 m2 pond and cultured until May 13. They were then transferred to a 3335 m2 pond for adult fish culture. When the average full length of these fish was about 4 cm, they were fed freshfrozen small miscellaneous fish twice a day. The feed levels were adjusted as necessary. On December 3, the fish were caught for marketing. One hundred and forty-four fish with body weights of 431.0
967.5 g were randomly selected for the experiment. Ten indices were measured: body weight (Y), full length (X1), body length (X2), body height (X3), body width (X4), interorbital distance (X5), head length (X6), lip length (X7), caudal peduncle length (X8), and caudal peduncle height (X9). 2.3.1.2 Measurement Methods The fish were anesthetized with 100 mg/L MS-222 before their body weight and morphological traits were measured. They were then weighed (accuracy, 0.1 g) with electronic scales. According to the measurement standard (Meng et al., 1995), the morphological traits were measured with a Vernier caliper (accuracy, 0.02 mm). EXCEL 2003 and SPSS 15.0 were used for the data analysis. To ensure that the morphological traits and body weights of largemouth bass were normally distributed or approximately normally distributed, the primary data were log10 transformed before statistical analysis. The values for each phenotypic parameter were estimated. The indirect and direct effects of each phenotype on body weight were analyzed with phenotype correlations (Pearson’s correlation), path analysis, and determination coefficients. Stepwise multiple linear regression was then used to construct the regression equation relating the morphological traits and body weight. The formula was (Zhang, 2004):  n  n . n P P P n xi yi 2 xi yi i51 i51 i51 rxy 5 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  n 2 . ffisffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  n 2 . n n P P P 2 P 2 2 xi 2 xi yi 2 yi n n i51

i51

i51

i51

The path coefficient (Py.x, abbreviated as Pi) is the standardized regression coefficient. In the case of multiple variables, it is also the standardized partial regression coefficient. The square of the path coefficient from an independent variable to a dependent variable is the decision coefficient

66

Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

  from an independent variable to a dependent variable dyUxi . Twice the product of the correlation coefficient between the two independent variables and their path coefficient from themselves to dependent variables were the  common  2 determination coefficients for the two independent variables dyUxi xj . R is the determination coefficient of multiple independent variables to the dependent variable. The formulization of the path coefficients and determination coefficients is as follows (Li, 2003; Gu, 2006): σx PyUx 5 byUx σy 2 dyUxi 5 PyUx i

dyUxi yj 5 2rxi xj PyUxi PyUxj P 2 P R2 5 Pi 1 2 rij UPi Pj

2.3.2 Results and Analysis 2.3.2.1 Estimates of Phenotypic Parameters Measured in Largemouth Bass The phenotypic statistics of the logarithmically transformed data for the morphological traits and body weights measured in largemouth bass (n 5 114) are summarized in Table 2.16. It can be seen that the largest variable coefficient was in lip length, followed by interorbital distance, caudal peduncle height, and body width. The variable coefficients for full length and body length were relatively small. 2.3.2.2 Correlation Coefficients of the Traits The correlation coefficients (Pearson’s correlation coefficient) between body weight and the morphological traits of largemouth bass are shown in Table 2.17. These results show that the Pearson’s correlation coefficients were extremely significant (P , 0.01). The relative strengths of the correlation coefficients were body width . body height . caudal peduncle height . body length . full length . interorbital distance . head length . caudal peduncle length . lip length. It is clear that the largest correlation coefficient was between body width and body weight, whereas the smallest was between lip length and body weight. The correlation coefficients between the traits were extremely significant (P , 0.01), and the traits correlated strongly with one another, so multicollinearity was probably present. Therefore, a path analysis was used to test

Table 2.16 Phenotypic statistics for the measured traits (n 5 114) Trait

Bodyweight

Full length

Body length

Body height

Body width

Interorbital distance

Head length

Lip length

Caudal peduncle length

Caudal peduncle height

Mean SD Skewness Kurtosis Variable coefficient (%)

6.1047 0.3611 0.1670 0.0530 5.92

3.3747 0.1026 0.2500 0.3650 3.03

3.2437 0.1090 0.2290 0.3490 3.36

2.1219 0.1495 0.4960 0.1760 7.05

1.4821 0.1501 0.1530 2 0.0530 10.13

0.7784 0.1255 2 0.0590 2 0.0490 16.12

2.1085 0.1083 2 0.3050 0.4340 5.14

0.3764 0.1499 0.2100 2 0.1190 39.82

1.6238 0.1186 2 0.0260 0.3000 7.3

1.1834 0.1307 0.2160 2 0.0480 11.04

Full length

Body length

Body height

Body width

Interorbital distance

Head length

Lip length

Table 2.17 Correlation coefficients of traits Traits

Bodyweight

Body weight Full length Body length Body height Body width Interorbital distance Head length Lip length Caudal peduncle length Caudal peduncle height

1 0.937 0.942 0.964 0.979 0.928

1 0.996 0.956 0.906 0.871

1 0.959 0.911 0.871

1 0.946 0.885

1 0.898

1

0.906 0.788 0.802

0.945 0.800 0.855

0.948 0.796 0.859

0.912 0.798 0.830

0.873 0.773 0.766

0.861 0.754 0.776

1 0.815 0.800

1 0.640

1

0.945

0.946

0.947

0.960

0.925

0.889

0.905

0.774

0.836

Note:



indicates an extremely significant difference (P , 0.01).

Caudal peduncle length

Caudal peduncle height

1

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

this assumption. A stepwise multiple regression was used to determine the regression equations between body weight and the morphological traits. 2.3.2.3 Path Coefficients of Three Morphological Traits to Body Weight Based on the principles of path analysis, the path coefficient between each morphological trait and body weight was calculated with the SPSS 15.0 software. Significance testing indicated that the associations between the three variables of body width, body length, and interorbital distance were significant. The path coefficients for body width, body length, and interorbital distance were 0.599, 0.231, and 0.189, respectively. The path coefficients demonstrate the direct effects of the independent variables on the dependent variable. Therefore, among the morphological traits of largemouth bass, body width affected body weight most strongly, whereas interorbital distance affected it least. 2.3.2.4 Influences of the Three Morphological Traits on Body Weight  Based on the composite effects of the correlation coefficient rxUy , the phenotypic correlation coefficient between the morphological traits and body weight can be divided into two parts: the direct effects of the morphological traits of largemouth bass and its body weight (path coefficient Pi) and effects of other  P the indirect P morphological traits on body weight rxi Uxj pj . Thus, rx:y 5 pi 1 rxi :xj pj . The results were shown in Table 2.18. As shown in Table 2.18, the direct effect of body width on body weight (0.599) was larger than the indirect effect. However, the indirect Table 2.18 Effects of the three morphological traits on body weight in largemouth bass Traits Correlation Direct Indirect effects rxi xj pj coefficient effect Sum Body Body Interorbital Pi width/ length/ distance/X5 X4 X2

Body width/X4 Body length/X2 Interorbital distance/X5

0.979

0.599

0.380

0.2104

0.942

0.231

0.711

0.5457

0.928

0.189

0.739

0.5379

0.1697 0.1646

0.2012

The Genetic Parameters of Growth Traits and Breeding Value Estimation

69

Table 2.19 Determination coefficients of the three morphological traits on body weight Trait Body width Body length Interorbital distance

Body width Body length Interorbital distance

0.3588 0.2521 0.2033

0.0534 0.0761

0.0357

effects of body length and interorbital distance on body weight (0.711 and 0.739, respectively) were much larger than the direct effects. The direct effect of body width on body weight was much larger than those of the other two indices, and was larger than the sum of the direct effects of body length and interorbital distance on body weight (0.420). 2.3.2.5 Determination Coefficients of the Three Morphological Traits on Body Weight The determination coefficients between the morphological traits and body weight, based on the determination coefficients between single traits and body weight and the codetermination coefficients between any two traits and body weight, were shown in Table 2.19. The data on the diagonal are the determination coefficients between each single trait and body weight. The data on the lower left diagonal are the codetermination coefficients between the two traits and body weight. As shown in Table 2.19, the determination coefficients between body width, body length, or interorbital distance and body weight in largemouth bass were 35.88%, 5.34%, and 3.57%, respectively. From the codetermination coefficients, the greatest impact was between body width and body weight (25.21%), whereas the minimum effect was between interorbital distance and body length (7.61%). The degree of determination for the combined effects of the multiple traits on body weight was 97.98%. 2.3.2.6 Multiple Correlation Analysis and Regression Analysis A multiple correlation analysis and a regression analysis were included in the data analysis. The results of the multiple correlation analysis were shown in Table 2.20. The multiple correlation coefficients indicate the close relationships between all the independent and dependent variables. The inclusion of more variables resulted in larger multiple correlation coefficients. As shown in Table 2.20, the multiple correlation coefficient between the three independent variables and body weight was 0.990, and the

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Table 2.20 Multiple correlation analysis of three morphological traits and body weight in largemouth bass Multiple One Two Three correlation independent independent independent analysis variable variables variables

Multiple R R2 Adjusted R Standard error F statistic Sig. F statistic

0.979 0.959 0.959 0.074 2615.440 0.000

0.987 0.973 0.973 0.060 59.280 0.000

0.990 0.980 0.979 0.052 34.086 0.000

Table 2.21 Variance analysis of the multiple regression equation Mean Variance Degree of Number of square SS freedom independent (df) variables

One

Two

Three

Note:



Regression Residual Total Regression Residual Total Regression Residual Total

14.126 0.605 14.731 14.337 0.394 14.731 14.43 0.301 14.731

1 112 113 2 111 113 3 110 113

14.126 0.005 7.169 0.004 4.81 0.003 4.810 0.003

F

2615.442 2017.848 1757.575

indicates extremely significant difference (P , 0.01).

corrected correlation index was 0.979. The error probability was 0.000 (P , 0.01), which is extremely significant. These results also indicate that body width, body length, and interorbital distance are the major morphological traits affecting body weight. The independent variables that did not seem to significantly affect body weight, based on the contribution rates and the significance of the standardized partial regression coefficient, were removed, including lip length, and caudal peduncle length. Full length, head length, body height, and caudal peduncle height, which were collinear with body length, were also removed. The steps in the stepwise multivariate regression analysis are shown in Tables 2.21 and 2.22.

Table 2.22 Significance testing of the partial regression coefficients and regression constants T-statistic Step Variable Regression coefficient Standardized partial Coefficients SE regression coefficient

First

Regression constant

2.641

0.069

38.099

P value

Lower 95% confidence limit

0.000

Upper 95% confidence limit

2.750 2.478

Body width

2.355

0.046

0.979

51.141

0.000

2.447 2.264

Second

Regression constant

0.439

0.288

Body width

1.719

0.091

0.715

1.527

0.130

18.964

0.000

2 0.131

1.01 1.899

1.54 Body length

0.961

0.125

0.290

7.699

0.000

1.208 0.714

Third

Regression constant

1.065

0.274

3.881

0.000

1.609 0.521

Body width

1.441

0.093

0.599

15.546

0.000

1.625 1.258

Body length

0.765

0.115

0.231

6.673

0.000

0.992 0.538

Interorbital distance

0.543

0.093

0.189

5.838

0.000

0.728 0.359

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

2.3.2.7 Determining the Multiple Regression Equation The Pearson’s correlation analysis showed that all the morphological traits measured in largemouth bass were extremely significantly related to body weight (P , 0.01). In the path analysis, the traits lip length and caudal peduncle length, which were not significant, were removed from the regression equation. In the multiple stepwise regression analysis, the traits including full length, head length, body height, and caudal peduncle height, which were strongly collinear, were also removed from the equation. The multiple regression equation in which body weight was the dependent variable and body width, body length, and interorbital distance were the independent variables was calculated to be: log Y 5 1.065 1 0.765 log X2 1 1.441 log X4 1 0.543 log X5. Significance testing was performed on the multiple regression coefficients and the standardized partial regression coefficients. The results indicated that all the regression constants and the standardized partial regression coefficients were extremely significant (P , 0.01). The corrected multiple correlation index was 0.979, indicating that the estimated values and actual values do not differ significantly. This regression equation can be applied in fish production. 2.3.2.8 Characteristics of the Correlation Analysis and Path Analysis and the Establishment of the Multiple Regression Equation In the correlation analysis, the phenotypic correlation of the independent variables and dependent variables can be divided into direct and indirect actions. The direct action is the direct impact of the independent variable on the dependent variable, whereas the indirect action is the indirect impact of the independent variable on the dependent variable. In the present study, significant or extremely significant phenotypic correlations were found between body weight and the other traits examined. This is attributable to the interference from other variables. To quantify the real relationships between body weight and the morphological traits, and to remove the collinearity of the independent variables in the regression equation, a path analysis was used to explore the relationships between body weight and the morphological traits. The results indicate that the standardized partial regression coefficients between body weight and body width, body length, or interorbital distance were extremely significant. The regression equation was established with a multiple stepwise regression analysis. The traits lip length and caudal peduncle length, which were not significant, were removed. Full length, head length, body

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height, and caudal peduncle height, which were strongly collinear, were also removed. The establishment of the regression equation quantified the relationships between body weight and body length, body width, and interorbital distance. 2.3.2.9 Determination of the Major Morphological Traits of Largemouth Bass that Affect Body Weight In this study, three independent variables (body width, body length, and interorbital distance) were selected for the regression equation after a correlation analysis and path analysis. The codetermination coefficient between body weight and the three variables was 0.9798. This suggests that 97.98% of the variation in body weight is attributable to these three variables. The other 2.02% is attributable to factors not examined in this study or to random errors. In the path analysis, the direct action of body width on body weight was much larger than those of the other two indices (body length and interorbital distance). It was also larger than the sum of the direct actions of those two indices on body weight. 2.3.2.10 Quantitative Traits of Fish in Selective Breeding Body weight is one of the most important target traits for selective breeding. Quantifying the effects of morphological traits on body weight is the basic principle underlying variety improvement. Bodyweight correlates inordinately with morphological traits such as full length, body length, and body height as a result of the gene linkage and pleiotropism underlying these quantitative traits (Li et al., 2006). During the practice of fish breeding, good results are not achieved with direct selection when the heritability of body weight is low. However, better results can be achieved when morphological traits that correlate strongly with body weight are used for selection. It has been reported that the body length and body height of the filial generation red Cyprinus carpio x Huanghe C. carpio var. are critical for their body weight gain (Tong et al., 2007), whereas the full length and body length are major factors for red common carp (Li et al., 2006). Based on the information discussed above, body length is critically important for body weight gain. In the present study, body width, body length, and interorbital distance showed outstanding positive linear correlations with body weight in largemouth bass. Therefore, they are the major morphological traits that affect the body weight of largemouth bass in a direct or indirect way. The discrepancies between our study and similar studies may be attributable to differences in the traits selected or the

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species investigated. Until now, no study has reported the heredity or genetic correlations of morphological traits, such as body weight, body length, and body width, in different stages of largemouth bass. The genetic improvement of largemouth bass not only depends on the direct selection of body weight, but also on the indirect selection of morphological traits that correlate significantly with body weight gain. We suggest here that body width, body length, and interorbital distance are important indices for the selection of largemouth bass.

2.4 HEREDITY PARAMETERS OF GROWTH TRAITS IN LARGEMOUTH BASS Heredity parameters and breeding values are extremely important in developing and optimizing breeding schemes (Liu et al., 2005; Luan et al., 2008). Since 1971, the sib correlation method has been used to estimate the heritability of body weight and body length in the rainbow trout (Aulstad et al., 1972). Since then, the methods of estimating heredity parameters and breeding values for fish growth traits have been developed gradually. Specifically, the best linear unbiased prediction method (BLUP) was first applied to the estimation of breeding values by Henderson (1975), and provided new methods for estimating heredity parameters and breeding values in fish. There are two statistical models in the BLUP method: the sire model and the animal model. The sire model requires that the males are randomly selected from groups in a normal distribution, with no relative correlations among the females (Liu et al., 1998). However, it is very difficult to satisfy both criteria in practice, resulting in low heredity parameters and large errors (Tim et al., 2006). In contrast, the results of the animal model are more accurate because the genetic connections among the individuals, information from different sources, some of the fixed effects, and the random effects are all taken into account in this model (Luan et al., 2008). Therefore, the animal model of the BLUP method is the primary method used for the selective breeding of aquatic animals (Tim et al., 2006; Marc et al., 2005; Joseph et al., 2008; Saillant et al., 2006; Mathilde et al., 2008; Gall and Bakar, 2002; Ponzoni et al., 2005; Roberto et al., 2006). The heredity parameters of growth traits have been estimated in several commercial fish, including Tilapia mossambica (Marc et al., 2005), S. salar (Joseph et al., 2008), and jewfish (Saillant et al., 2006; Mathilde et al., 2008). In breeding T. mossambica (Gall and Bakar, 2002; Ponzoni et al., 2005),

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S. salar (Roberto et al., 2006), and the rainbow trout (Wang et al., 2009), good results were achieved when the breeding value was used for selection. Largemouth bass is one of the most commercially important freshwater fish in China. Since 2005, the artificial selection of largemouth bass has been performed successfully at the Pearl River Fisheries Research Institute (CAFS) (Li et al., 2009). The one-to-one reproduction method was used to establish full-sib families in the present study, and the animal model of the BLUP was used to estimate the heredity parameters of the growth traits in 4- and 6-month-old largemouth bass. This study provides a theoretical basis and technological support for the selective breeding of largemouth bass.

2.4.1 Materials and Methods 2.4.1.1 Experiment Fish and Their Culture and Marking In March 2009, the parent largemouth bass (400
500 g) were selected from the breeding ponds of the Pearl River Fisheries Research Institute (CAFS). Each pair of parent fish was placed into an individual pond and allowed to reproduce artificially. Thirty-six full-sib families were generated in the following two days. The offspring of the families were then cultivated individually in equally sized (about 9 m2) tanks. The fish were fed small zooplankton twice daily, in the morning and evening. About 2 weeks after hatching, tubificid worms were also fed to the fish. At about 2 months old, fluorochrome markers (yellow, red, green, blue, orange, and pink colors) were injected into the head skins, pelvic fins, and tail fins of the fish. Fish from the same family were injected with the same color fluorochrome. After marking, the families were cultured in two ponds, each containing 18 families. 2.4.1.2 Data Acquisition and Processing Body weight, body height, and body length were measured in 4- and 6month-old largemouth bass. All the data were organized with the EXCEL software according to the requirements of the MTDF-REML software (Bolman et al., 1995). 2.4.1.3 Normal Distribution Testing The data for body weight, body height, and body length measured in the 4- and 6-month-old largemouth bass were analyzed with the χ2 test. As shown in Table 2.23, except for body length in the 4-month-old fish, the data for these growth traits were normally distributed at both time points.

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Table 2.23 Normal distribution testing of the growth traits in 4- and 6-month-old fish Trait 4 months old 6 months old

χ2 value Significance (p)

Body weight

Body length

Body height

Body weight

Body length

Body height

312.28 1.00

242.87 1.00

292.65 0.00

225.98 0.39

117.52 1.00

233.85 0.074

Table 2.24 Effects related to growth traits in the early stage Traits Random Fixed Concomitant variables effects effects Family

4-month body weight (g) 4-month body length (cm) 6-month body weight (g) 6-month body length (cm) 6-month body height (cm) 

Pond

Age (days)

Initial body weight

3.701

94.627

61.348

17.712

4.135

26.765

10.563

21.470

2.729

107.702

84.560

2.086

2.559

80.339

77.448

3.553

2.667

69.776

75.272

1.856

P , 0.01.

2.4.1.4 Variance Analysis and Regression Analysis Variance and regression analyses were performed with the SPSS software based on the results for the three growth traits in 4- and 6-month-old largemouth bass (except body height at 4 months old). The significance of the effects that were related to growth traits were included in the tests, including fixed effects, random effects, and concomitant variables. The results indicate that all the growth traits in both the 4- and 6-month-old fish exerted fixed effects and random effects, namely pond effects and family effects (Table 2.24). However, the concomitant variables were different. The concomitant variables for body weight and body length in the 4-month-old largemouth bass were the age (days) and initial body weight of the family, whereas the concomitant variable for body weight, body length, and body height in the 6-month-old largemouth bass was the age (days) of the family.

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2.4.1.5 Establishing Statistical Models Based on the significance of the effects on each trait (Table 2.24), genetic analysis models, including the single-trait animal model and the multipletrait animal model, were established as follows: 1. Single-trait animal model: yijk 5 u 1 ai 1 fj 1 Pk 1 bxijk 1 eijk where u represents the population mean, yijk represents the observed values of the traits, ai represents the additive genetic effect, fj represents the full-sib random effects, Pk represents the fixed effect from ponds, xijk represents the concomitant variables, b represents the regression coefficient, and eijk represents the random residual effects. 2. Multiple-trait animal model: yijkt 5 u 1 ait 1 fjt 1 Pkt 1 bxijkt 1 eijkt where u represents the population mean, ait represents the additive genetic effect of trait t, fjt represents the full-sib random effects of trait t, Pkt represents the fixed effect of the ponds of trait t, xijkt represents the concomitant variables of trait t, b represents the regression coefficients, and eijkt represents the random residual effects of trait t. The single-trait animal model was applied to estimate heritability, whereas the multiple-trait animal model was used to estimate the genetic correlation between two traits. 2.4.1.6 Standard Error of the Hereditary Parameters and its Significance Testing The standardp error of the hereditary parameters (Falconer and Mackay, ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 1996): σh2 5 16h2 =T , where h2 represents the heritability, T represents the number of samples. t testing (Sheng and Chen, 1999): t 5 h2 =σh2 . The standard error of the genetic correlations (Falconer and Mackay, 1996): sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð1 2 r 2A Þ σðh2x Þ σðh2y Þ ; σðr A Þ 5 pffiffiffi h2x h2y 2

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

where h2x and h2y represent the heritabilities of traits x and y, respectively; σðh2x Þ and σðh2y Þ represent the standard errors of the hereditary of traits x and y, respectively. pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi t testing (Xie and Xu, 2003): t r ðxyÞ 5 r ðxyÞ = V ðr ðxyÞ Þ.

2.4.2 Results and Analysis 2.4.2.1 Phenotypic Parameters of Each Growth Trait The phenotypic parameters were obtained from the measurements of the morphological traits in 4- and 6-month-old largemouth bass (Table 2.25). The CV was largest for body weight: 0.40 and 0.53 for the 4- and 6month-old largemouth bass, respectively. The CVs for body length and body height were relatively low. 2.4.2.2 Heritabilities and Full-Sib Coefficients for Each Growth Trait in Largemouth Bass The components of variance, the heritabilities, and the estimated full-sib coefficients were obtained for each trait of the 4- and 6-month-old largemouth bass with the single-trait animal model (Tables 2.26 and 2.27). The heritabilities of body weight and body length in the 4-month-old largemouth bass were 0.29 6 0.08 and 0.31 6 0.08, respectively, whereas the heritabilities of body weight, body length, and body height in the 6-month-old largemouth bass were 0.28 6 0.10, 0.26 6 0.10, Table 2.25 Phenotypic parameters of growth traits in largemouth bass Traits Mean Minimum Maximum SD

CV

4-month 4-month 6-month 6-month 6-month

0.40 0.13 0.53 0.15 0.18

body body body body body

weight (g) length (cm) weight (g) length (cm) height (cm)

23.69 9.92 74.39 14.01 4.31

6.70 6.63 14.50 8.92 2.44

49.30 13.54 213.50 20.86 6.63

9.44 1.32 39.72 2.14 0.76

Table 2.26 Components of variance in the major growth traits of 4- and 6-monthold largemouth bass Trait Additive Full-sib Residual Phenotypic variance variance variance

4-month 6-month 4-month 6-month 6-month

body body body body body

weight (g) weight (g) length (cm) length (cm) height (cm)

21.153 221.139 0.516 0.679 0.096

5.413 85.867 0.160 0.263 0.036

47.048 474.528 1.003 1.645 0.203

73.615 781.535 1.679 2.588 0.335

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79

Table 2.27 Heritabilities and estimated full-sib coefficients of the major traits in 4- and 6-month-old largemouth bass Trait

4-month body weight

6-month body weight

4-month body length

6-month body length

6-month body height

Heritability (h2) Full-sib coefficient (C2)

0.29 6 0.08 0.07

0.28 6 0.10 0.11

0.31 6 0.08 0.09

0.26 6 0.10 0.10

0.29 6 0.10 0.10



indicates P , 0.01.

Table 2.28 Phenotypic correlations (top right) and genetic correlations (bottom left) between the three traits in largemouth bass Trait Age Bodyweight Body length Body (months) height

Bodyweight Body length Body height 

4 6 4 6 4 6

1 0.75 6 0.082 0.79 6 0.094
0.82 6 0.081

0.905 0.945 1
0.99 6 0.001


0.948
0.975 1

indicates P , 0.01.

and 0.29 6 0.10, respectively, which are all medium heritabilities. This indicates that the three growth traits of largemouth bass can be greatly improved by controlling their additive effects. A t test was applied to the heritabilities of each trait, and the results showed that all the P values were less than 0.01. The full-sib coefficients for each growth trait in the 4- and 6-month-old largemouth bass were 0.07
0.11. 2.4.2.3 Genetic and Phenotypic Correlations of Traits The genetic correlations of the traits were estimated with the multipletraits animal model, and the phenotypic correlations were estimated with the CORRELATE module of SPSS. The results are shown in Table 2.28. Strong positive correlations were found between the three growth traits of largemouth bass. The largest genetic correlation was between body height and body length (ra 5 0.99 6 0.001), whereas the smallest was between body weight and body length (ra 5 0.75 6 0.082, 0.79 6 0.094). The phenotypic correlations were identical to the genetic correlations. When the phenotypic correlations and genetic correlations were tested for significance, all the P values were less than 0.01. Heritability is one of the genetic parameters used in selective breeding. Until now, a number of studies have reported fish growth traits, and these traits displayed medium heritability in most of the species

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

investigated. For example, their heritability was 0.25
0.27 in T. mossambica (Marc et al., 2005), 0.12
0.53 in S. salar (Joseph et al., 2008), 0.24
0.44 in European jewfish (Mathilde et al., 2008), 0.36
0.6 in rainbow trout (Fishback et al., 2002), and 0.25
0.30 in colored carp (Wang et al., 2006). In the present study, the single-trait animal mode was used to assess their heritability in 4- and 6-month-old largemouth bass. Our results show that their heritability in largemouth bass was 0.26
0.31, indicating their medium heritability. This result indicates that the growth traits of largemouth bass exert a relatively high additive genetic effect. Therefore, largemouth bass will be improved if population selection and family selection are applied during selective breeding. This result explains our previous result wherein the average growth rate increased by 8% after population selection for three generations (Li et al., 2009). During the process of breeding, the selection efficiency was also improved by indirect selection based on the correlation of traits. In the present study, the growth traits of largemouth bass were closely related to the positive genetic correlation. This result is almost identical to those for other fish species (Myers et al., 2001; Vandeputte et al., 2002). However, the genetic correlation of body weight and body length in largemouth bass was smaller than that of the other traits. This suggests that both body weight and body length should be taken into account when breeding largemouth bass to produce an excellent fish with a good growth rate and a nice body shape.

2.5 THE BREEDING VALUE OF THE GROWTH TRAITS OF LARGEMOUTH BASS The estimation of breeding values is extremely important in developing and optimizing breeding schemes. The one-to-one reproduction method was used in the last section to establish full-sib families, and the heredity parameters for their growth traits were estimated. Based on these results, the animal model of the BLUP method was used to estimate the breeding values of individual traits in 4- and 6-month-old largemouth bass.

2.5.1 Materials and Methods 2.5.1.1 Materials and Data Processing Methods These methods included the establishment of a largemouth bass population and its cultivation and marking, data acquisition and processing, normal distribution testing, variance analysis, regression analysis, and the

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81

development of statistical models, which were performed as described in Section 2.4.1. 2.5.1.2 Estimation of the Aggregate Breeding Value Multiple traits were selected according to their importance. They were weighted appropriately and integrated as a unit, with arbitrary units (U), as the index. U was used to estimate the value of aggregate breeding (Ai). Ai 5 W 1 a1i 1 W 2 a2i W1 is the weighting factor for body weight was 0.006 U; a1i is breeding value of body weight for i; W2 is the weighting factor for body length was 0.63 U; a2i is breeding value of body length for i.

2.5.2 Results and Analysis 2.5.2.1 Phenotypic Parameters of Growth Traits The phenotypic parameters were obtained from the measurement of the morphological traits in 4- and 6-month-old largemouth bass (Table 2.25). The CV was greatest for body weight: 0.40 and 0.53 in the 4- and 6-month-old largemouth bass, respectively. The CVs for body length and body height were relatively small. 2.5.2.2 Comparison of Breeding Values and Phenotypic Values The single-trait animal model was used to estimate the breeding values of largemouth bass individuals, which were then ordered according to their breeding values and phenotypic values. In the top 10% of individuals, the rates for the individuals selected with the two methods combined were as follows: in the 4-month-old largemouth bass, the rate for body weight was 66.20% and the rate for body length was 70.42%, whereas in the 6-month-old largemouth bass, the rate for body weight was 48.78% and that for body length was 39.02% (Table 2.29). The average breeding values for the top 10% of individuals calculated with the two methods differed. In 4-month-old largemouth bass, the body weight for breeding value selection was 5.01 g, whereas it was 4.46 g for phenotypic value selection. Thus, the latter value was 12.33% higher than the former value. In the 6-month-old largemouth bass, the average values for body weight were 17.70 and 12.58 g, respectively, and the former value was 40.70% higher than the latter value. In 4-month-old M. salmoides, body length was 0.73 cm for breeding value selection, but

82

Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Table 2.29 Rates of the top 10% of individuals according to the breeding values and phenotypic values Rates (%) Breeding values for body Breeding values for body weight length

Phenotypic value (%)

4 months old

6 months old

4 months old

6 months old

66.20

48.78

70.42

39.02

(A)

EBV selection

20 weight–EBV (g)

Pheotypic selection

15 10 5 0 4–month–old

(B)

Length–EBV (cm)

1

6–month–old

EBV selection Pheotypic selection

0.8 0.6 0.4 0.2 0 4–month–old

6–month–old

Figure 2.8 Comparison of mean single-trait breeding values in the top 10% of individuals according to their breeding values and phenotypic values. (A) Body weight; (B) body length.

0.68 cm for phenotypic value selection. The former value is 7.35% higher than the latter value. In 6-month-old largemouth bass, the average body length was 0.84 for breeding value selection and 0.70 cm for phenotypic value selection, and the former is 20.00% higher than the latter (Fig. 2.8). These results indicate that the selection efficiency will decline if phenotypic values are used for the selection of individual largemouth bass.

The Genetic Parameters of Growth Traits and Breeding Value Estimation

83

2.5.2.3 Aggregated Breeding Values and Single-Trait Breeding Values All the individual fish were ordered by their aggregated breeding values and their single-trait breeding values, and the results indicate that the rankings of the individuals differed. Table 2.30 shows the ordered individual breeding values for 6-month-old largemouth bass. A rank correlation analysis of the different estimates of breeding value was performed with SPSS. As shown in Table 2.31, the rank correlation coefficients showed that the aggregated breeding values correlated extremely significantly with the single-trait breeding values (P , 0.01). The rank correlation coefficients of the aggregated breeding values to the breeding values of body length and body weight in both the 4- and 6-month-old largemouth bass were larger than the breeding values of body length and body weight. On the basis of the sequences and their rank correlation coefficients, there was little difference between the two parameters: aggregated breeding values and single-trait breeding values. However, the aggregated breeding values contain more information and reduce the deviations inherent in single-traits values (Wang et al., 2009). Our results also suggest that both body weight and body length should be used simultaneously in largemouth bass breeding. Therefore, the animal model in BLUP was used for genetic evaluations. First, the aggregated breeding value, calculated from the body weight and body length, was used to select the strain that grew most rapidly. Characters such as fertility, viability, and stress resistance should then be taken into account to improve the selection method. The animal-model BLUP takes various sources of information into consideration. It significantly accelerates the process of breeding, especially in species with low- and medium-heritability traits (Belonsky and Kennedy, 1988). In recent years, researchers have found that in T. mossambica (Gall and Bakar, 2002), the Chinese shrimp (Zhang et al., 2008), and turbot (Ma et al., 2009), the animal-model BLUP is superior to the phenotypic value method in breeding practice. In the present study, the animal-model BLUP showed higher selection efficiency and was also superior to the phenotypic value method in selecting for body weight and body length in largemouth bass. Second, the generation interval for largemouth bass is short. The parent fish updates rapidly. Therefore, genetic evaluation of individuals is required for breeding. The animal-model BLUP satisfies this

Table 2.30 Ordered breeding values of 6-month-old largemouth bass Sequences Individual Breeding value Individual no. (body weight) no.

Breeding value (body length)

Individual no.

Aggregated breeding value

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

1.534406 1.515959 1.419869 1.225573 1.223442 1.179799 1.176480 1.138348 1.086838 1.025902 1.000076 0.951628 0.947467 0.936816 0.934290 0.931169 0.902104 0.886089 0.883183 0.846040

20090261 20090355 20090136 20090322 20090293 20090235 20090400 20090335 20090202 20090104 20090380 20090321 20090301 20090330 20090001 20090346 20090032 20090216 20090139 20090174

1.202887 1.185427 1.121998 0.987927 0.942423 0.921314 0.868416 0.844526 0.819901 0.79405 0.721803 0.720367 0.699063 0.698895 0.688496 0.680759 0.665314 0.663737 0.662283 0.660163

20090261 20090355 20090136 20090322 20090293 20090202 20090400 20090235 20090032 20090001 20090321 20090016 20090330 20090301 20090104 20090335 20090046 20090174 20090061 20090069

39.368546 38.395408 37.913359 36.193098 33.191525 31.642102 25.209493 24.867134 22.051397 22.015209 20.140123 18.876538 18.709660 18.410073 18.223572 17.223835 17.117758 16.987802 16.931749 16.206198

20090261 20090355 20090136 20090235 20090322 20090293 20090335 20090400 20090104 20090380 20090202 20090321 20090216 20090346 20090301 20090330 20090139 20090174 20090001 20090032

The Genetic Parameters of Growth Traits and Breeding Value Estimation

Table 2.31 Rank correlation of different breeding values in Age Breeding value Aggregated (months) breeding value

4 months old

6 months old



Aggregated breeding value Breeding value (body weight) Breeding value (body length) Aggregated breeding value Breeding value (body weight) Breeding value (body length)

85

largemouth bass Breeding Breeding value value (body (body length) weight)


0.923




1.000

0.914





0.919




0.998

0.890




indicates P , 0.01.

requirement. The growth traits of largemouth bass display medium heritability, so better results will be obtained if the animal-model BLUP is used in largemouth bass breeding.

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Genetic Breeding and Molecular Marker-Assisted Selective Breeding of Largemouth Bass

Dai, Q., Dai, J., Li, C., et al., 2006. Discussion on relative fatness. Chin. J. Appl. Environ. Biol. 12 (5), 715
718. Deboski, P., Dobosz, S., Robak, S., et al., 1999. Fat level in body of juvenile Atlantic salmon (Salmo salar L.), and sea trout (Salmo trutta M. trutta L.), and method of estimation from morphometric data. Archroes Pol. Fish. 7 (2), 237
243. Donaldson, L.R., Olson, P.R., 1955. Development of rainbow trout brood stock by selective breeding. Trans. Am. Fish. Soc. 85, 93
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34. Falconer, D.S., Mackay, T.F.C., 1996. Introduction to Quantitative Genetics, fourth ed. Pearson Education Limited, Longman, Essex, UK, pp. 301
311. Fishback, A.G., Danzmann, R.G., Ferguson, M.M., et al., 2002. Estimates of genetic parameters and genotype by environment interactions for growth traits of rainbow trout (Oncorhynchus mykiss) as inferred using molecular pedigrees. Aquaculture 206, 137
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