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Genetic analysis of common carp (Cyprinus carpio) strains. II: Resistance to koi herpesvirus and Aeromonas hydrophila and their relationship with pond survival
Aquaculture 304 (2010) 7–13
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Aquaculture j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a q u a - o n l i n e
Genetic analysis of common carp (Cyprinus carpio) strains. II: Resistance to koi herpesvirus and Aeromonas hydrophila and their relationship with pond survival Jørgen Ødegård a,⁎, Ingrid Olesen a, Peter Dixon b, Zsigmond Jeney c, Hanne-Marie Nielsen a, Keith Way b, Claire Joiner b, Galina Jeney c, László Ardó c, András Rónyai c, Bjarne Gjerde a a b c
Nofima Marin, P.O. Box 5010, NO-1432 Ås, Norway CEFAS, Centre for Environment, Fisheries and Aquaculture Sciences, Weymouth DT4 8UB, UK HAKI, Research Institute of Fisheries Aquaculture and Irrigation, Anna Liget 8, Szarvas H-5540, Hungary
a r t i c l e
i n f o
Article history: Received 6 May 2009 Received in revised form 3 February 2010 Accepted 20 March 2010 Keywords: Common carp Cyprinus carpio Genetic parameters Pond survival Disease resistance KHV Aeromonas hydrophila
a b s t r a c t Estimates of strain effects, heritabilities and genetic correlations for pond survival, resistance to Aeromonas hydrophila and resistance to koi herpesvirus (KHV) were obtained from a diallel cross of 92 full-sib families of common carp produced from four strains (Szarvas 15, Tata, Duna and Amur) and using five females and ten males per strain. Disease resistance was obtained from survival data from challenge-tests using intraperitoneal injection for A. hydrophila and cohabitation for KHV. Two separate challenge-tests were conducted for each disease. The overall survival rates were 44% and 34% for the two tests of A. hydrophila, and 7% and 5% for the two tests of KHV. Pond survival (averaging 78%) was observed over a six months period prior to harvest (at approximately 18 months of age). The three traits were analysed jointly in a multivariate threshold model. For KHV the strain Szarvas 15 had the lowest observed (purebred) survival (0%) followed by Amur (11%), Duna (12%) and Tata (21%), while for A. hydrophila, the lowest (purebred) survival was observed for Duna (28%) followed by Amur (31%), Szarvas 15 (38%) and Tata (48%). Heterosis was not significant for KHV and A. hydrophila resistance, although highly significant for pond survival. The estimated heritability (on the underlying liability scale) was low (0.04± 0.03) for A. hydrophila resistance, very high (0.79±0.15) for KHV resistance, and moderate (0.34±0.09) for pond survival. The genetic correlation between the two challenge-tested diseases (KHV and A. hydrophila) was moderately high (0.61±0.29), although uncertain, while the estimated genetic correlations between pond survival and the two challenge-tested diseases were low and not significantly different from zero (0.01± 0.28 and −0.22±0.21 for A. hydrophila and KHV, respectively). The latter may be expected for KHV, as no outbreaks of the disease had been observed in Hungary. Based on the favourable heritabilities of KHV and pond survival there is good prospect for joint improvement of these two traits in common carps through genetic selection. © 2010 Elsevier B.V. All rights reserved.
1. Introduction In terms of volume produced, cyprinid species are, by far, the most important among the species used in fish farming on a worldwide basis (http://www.fao.org), and among these, common carp (Cyprinus carpio) is the third most important. Eastern European carp gene banks have been responsible for the genetic improvement of carp for intensive and semiintensive pond culture in Europe and their dissemination worldwide (Gorda et al., 1995). The main focus for genetic improvement work on common carp has mainly been crossbreeding of strains and inbred lines to exploit heterosis. Notable heterosis for growth has been documented (reviewed by Vandeputte, 2003). However, some pure strains appear to perform as well as the best crosses (Wohlfarth et al., 1975). The majority of worldwide carp production has so far been based on non-improved genetic stocks (Vandeputte, 2003). However, based on ⁎ Corresponding author. Tel.: + 47 45277801; fax: + 47 64949502. E-mail address: jorgen.odegard@nofima.no (J. Ødegård). 0044-8486/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.aquaculture.2010.03.017
existing literature disease resistance may be effectively selected for in common carp (Vandeputte, 2003). Disease is the major risk factor in commercial aquaculture causing annual losses of millions of dollars (Nielsen et al., 2001). Hence, sustainable breeding programs for aquaculture species should also aim at improving stocks with respect to health and survival traits. Outbreaks of mortality caused by koi herpesvirus (KHV) has been found in many countries all over the world, and the disease is currently considered as one of the highest risk factors affecting populations of koi (ornamental variety of common carp) and farmed common carps. The outbreaks are often characterized by very high mortalities at water temperatures above 16 °C (Dixon et al., 2009). The bacteria Aeromonas hydrophila is associated with various disease problems in carp aquaculture production worldwide (Nielsen et al., 2001). Pathogenicity of the bacteria appears to mainly affect stressed or compromised fish, and the infection is often secondary in character (Jeney and Jeney, 1995). For implementing traits in selective breeding programs, genetic parameters; i.e., heritabilities and genetic correlations, are needed for
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their documented breeding history in order to obtain the widest possible genetic differences between the strains. A diallel cross design between the four common carp strains was applied (Table 1). Five females and 10 males per strain was used to produce six full-sib families for each of the 16 cross combinations (four purebred strains and their six crossbred strains with reciprocals), resulting in 96 different families in total. The number of fish produced and individually tagged within each of the 96 family was 100. However, for one of these families, 400 fish were produced. Each of the 96 families (plus the 300 extra fish from one of the families) was held in separate tanks of 100 fish such that the total number of tanks was 99. Of these, 91 families were tested for KHV and 92 for A. hydrophila and pond survival.
the traits of interest. The aim of this study was therefore to estimate these parameters for resistance to KHV and A. hydrophila from experimental challenge-tests and for pond survival in a commercial production environment, using data from four different common carp strains (two domesticated strains, one wild strain of Hungarian origin and one wild strain of Russian origin). 2. Material and methods 2.1. Fish material and crossing design The current study is based on fish from the same population as described in Nielsen et al. (2010-this issue). Fish used in the experiment were the offspring produced by the Fish Biology Department at the Research Institute of Fisheries, Aquaculture and Irrigation (HAKI), at Szarvas, Hungary and were from four different strains provided from the live gene bank of common carp (Gorda et al., 1995). There were two strains representing “wild” strains (Duna and Amur), which are native in the Danube and Amur rivers but has been kept in the live gene bank by HAKI for at least three generations, and two farmed strains (Tata and Szarvas 15). Tata is presumably an inbred strain that has been selected for rapid growth and round body shape and Szarvas 15 has been selected for high heterosis in line crosses (Bakos and Gorda, 1995). These four different strains were selected based on known origin and
2.2. General management and recordings 2.2.1. Mating and production of fry The production of the full-sib families took place at HAKI on May 12, 2006. Males and females were held in separate tanks before artificial reproduction. At the end of July 2006, surplus fish exceeding 400 fish per tank were randomly removed. The fish were individually tagged with PIT-tags at an average body weight of 19.4 g within one week, starting on August 22, 2006. For each family, five random samples of 20 fish were tagged for different experimental purposes.
Table 1 Schematic presentation of the applied diallel crossing design between four carp strains (Duna, Amur, Tata, and Szarvas 15). Five females and ten males per strain was used to produce six full-sib families for each of the sixteen cross combinations (four purebred strains and their six crossbred strains with reciprocals). Female
Duna
Male
No
1
Duna
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
X X
Amur
Tata
Szarvas 15
Amur 2
3
4
5
1
Tata 2
3
4
5
1
Szarvas 15 2
3
4
5
1
X X
2
3
4
5
X X
X X
X X X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X
X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X
X X
X X X X X X
X X X X
X X
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2.2.2. Recording of pond survival On September 7, 2006 one of the four samples of 20 fish per family were transported from HAKI and stocked into an earthen pond (1 ha, 1.5–1.8 m water depth) at a commercial farm, Szeged Ltd, in the southern part of Hungary. On November 16, 2006 the body weights and lengths on all fish in the pond were recorded and stocked for wintering in the same pond. After wintering the same recordings were repeated on April 3, 2007 and on October 26, 2007 (harvesting). Fish were fed a catfish feed with 47% of protein and 6.5% of fat at starting feeding rate of 6% of body mass of fish per day. After wintering the fish were fed with Szarvasi common carp fingerling feed, which contained 24% of protein. Shortly after first stocking in the pond, and after the wintering, the fish were offered a medicated feed with Euroquin antibiotic as preventive measure against swim-bladder inflammation (typical to the given farm). In addition, the fish were also given a homeopathic treatment with Immunopics. Fish were scored as survived if weight/length were recorded in both April and October, and scored as dead if weight/length were recorded in April, but not in October (this trait is called S3 in Nielsen et al., 2010-this issue). No information was available about causes of mortality, but no severe disease outbreaks were observed during the experiment. Average body weight at harvest was 1181 g (CV = 0.24). 2.2.3. Challenge-testing A total of 20 (with some exceptions) tagged individuals from were challenge-tested at HAKI with Aeromonas hydrophila, and 20 (with some exceptions) tagged individuals per family were in September 2006 sent to CEFAS (United Kingdom) for challenge-testing with KHV. Challenge-testing with A. hydrophila was conducted using intraperitoneal injection of 0.1 ml per fish, using a suspension with 3 × 107 bacteria/ml. Testing was done under controlled tank conditions, at constant water temperature and pH (22–23 °C; pH 8.5). On the first three days after the challenge, mortalities were recorded hourly, on the following three days every 3 h, and later every 6 h. Mortalities were confirmed as being caused by A. hydrophila by bacteria isolation from the kidney. Two separate challenge-tests (appr. 5 + 15 fish per family) were conducted. The initial test started at January 22, 2007 (at an average weight of 126 g, CV = 0.62) and the last mortality was recorded at January 30, 2007. The second test started at March 20, 2007 (at an average weight of 146 g, CV = 0.65) and the last mortality was recorded at March 28, 2007. Both tests were run until the cumulative mortality reached a plateau. In total, 92 of the original 96 families were represented within the challenge-tests for A. hydrophila resistance. Challenge-testing with KHV was conducted using cohabitants. The testing procedure for this material has previously been described by Dixon et al. (2009). As for A. hydrophila, two separate challenge-tests (appr. 5 + 15 fish per family) were conducted. A single tank containing all fish was used in the initial challenge-test, while three tanks were used in the second test (each containing a random sample of fish). In the latter experiment, tank environments were standardized through circulation of water among the tanks, and the three tanks were thus assumed to be the same environment. Dead fish were recorded on a daily basis, and at least 10% of the dead fish checked for presence of KHV. The initial test was started at February 16 (at an average weight of 52 g, CV = 0.40), with the last recorded mortality at March 17, 2007. The second test was started at April 3 (at an average weight of 62 g, CV = 0.43), with the last recorded mortality at April 25, 2007. Both tests were run until the cumulative mortality reached a plateau. In total, 91 of the original 96 families were represented within the challenge-tests for KHV resistance. 2.3. Statistical analysis In the statistical analysis, pond- and challenge-test survival for all traits were defined as survived or dead (1/0), observed at the end of test.
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Pond survival was 78%, and A. hydrophila challenge-test survival was 44% (test 1) and 34% (test 2). For KHV the fraction of surviving individuals was low (5–7%). For such low frequencies, it is common to define a binary survival trait based on whether or not the fish was alive at 50% overall mortality. However, as preliminary analyses showed that the statistical analysis was sensitive to the exact truncation point (i.e., whether one defines the period until the day before or day after 50% mortality was reached), survival at the absolute endpoint of testing period was chosen, although this corresponded with low overall survival. Pond and challenge-test survival were analysed using a multivariate generalized linear mixed probit (threshold) model with the ASREML software (Gilmour et al., 2006), using REML methodology for estimation of variance components for random effects (additive genetic effects of sire and dam). A common environmental effect of full-sib family (e.g., due to common tank environment prior to tagging and non-additive genetic effects common to full sibs) was fitted as a random effect, but this effect was not significant for any of the traits, and was therefore omitted in the final model. A fixed effect of strain and a fixed effect of heterosis that was specific for each strain combination were fitted for all traits. For A. hydrophila and KHV the fixed heterosis effect was not significant and therefore omitted from the model for these traits. The favourable crossing effects on pond survival are described in more detail by Nielsen et al. (2010-this issue). The final model had the following characteristics: Pr (Sijklmno =1) Φ(μij +STRAINik +STRAINil +CROSSikl +damikm +sireiln) Sijklmno survival trait i (i=pond, KHV or A. hydrophila), of fish o, within trial j, from dam m within strain k, and sire n within strain l, μij overall mean for liability to survival trait i in trial j, STRAINiq fixed effect of parental strain q (strain 15, Amur, Duna, Tata) for trait i (q = k for dams and q = l for sires), CROSSikl fixed effect of strain cross combination kl for trait i (CROSSi12 = CROSSi21, …, CROSSi34 = CROSSi43), CROSSikl = 0 for k = l and/or i = KHV or A. hydr. damikm random additive genetic effect of dam m within strain k for trait i, sireiln random additive genetic effect of sire n within strain l for trait i. The additive genetic (sire and dam) effects were assumed ∼N(0, G⊗A), with G being the additive genetic (co)variance matrix for sire and dam effects of the three traits (assuming equal variance components for sires and dams), and A is the additive genetic relationship matrix for sires and dams (equals an identity matrix as sires and dams did not have any known relationships). As all traits were measured on different individuals, the only assumed correlations between the traits were due to the additive genetic effects, and residuals on the underlying scale were thus assumed to be ∼N(0,IN), where IN is an identity matrix with dimension equal to the total number of fish tested (over all traits). Fixed effects were tested in ASREML using single-trait models similar to the model above (including both fixed and random effects in the model). The method used for testing of fixed effects was an incremental Wald F-statistics (Gilmour et al., 2006). 3. Results Fig. 1 shows Kaplan–Meier survival curves for each of the separate A. hydrophila and KHV challenge-tests. For A. hydrophila the overall survivals at end of test were 44% and 34% for the initial and second test, respectively (Fig. 1). The relative differences in survival rates between different strains were moderate (Fig. 2), with the lowest observed (purebred) survival rate (not adjusted for family effects) for Duna (28%) followed by Amur (31%), Szarvas 15 (38%) and Tata (48%). Observed variation in survival at end of test between families within each strain and cross combination was moderate. For KHV, overall survivals at end of the two tests were only 7% and 5% for the initial and second test, respectively (Fig. 1). Despite low
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numbers of fish per family in the initial test and low survival at the end of both tests, the two challenge-tests for KHV showed surprisingly good agreement with respect to observed survival: 60 of the 91 families were completely exterminated in both challenge-tests, while 20 of the remaining 31 families had surviving family members within both tests. For the families with surviving family members, survival fraction varied from 5 to 47% (Fig. 3), with an average survival rate of 18%. Szarvas 15 had the lowest observed (purebred) survival rate (0%) followed by Amur (11%), Duna (12%) and Tata (21%). As in Nielsen et al. (2010-this issue), large strain differences were observed for pond survival (Fig. 4), with the lowest observed (purebred) survival rate for Szarvas 15 (56%), followed by Tata (60%), Amur (71%) and Duna (83%). There was also substantial variation in pond survival between families within each strain and cross combination (e.g., 0 to 81% for crosses between Szarvas 15 and Tata). Based on single-trait analysis, strain differences (taking sire and dam effects into account) were significant for KHV and pond survival (P b 0.01), but not for A. hydrophila (P = 0.20). Heterosis was significantly different from zero (favourable) for pond survival (P b 0.001), but not significant for the challenge-tested diseases. Reciprocal crosses were not significantly different for any of the traits. Table 2 shows the estimated heritabilities for A. hydrophila and KHV resistance and pond survival and the genetic correlations among these traits. All heritability estimates are presented as they appear on the underlying liability scale. The estimated heritabilities were low for A. hydrophila resistance (0.04 ± 0.03), extremely high for KHV resistance (0.79±0.14), and moderate for pond survival (0.34 ± 0.09, as in Nielsen et al., 2010-this issue). This indicates that the moderate family differences observed within strain and cross combination for A. hydrophila are largely a result of sampling (due to limited family sizes), while variations in family survival rates for KHV and pond survival are larger than what can be explained by random sampling. The high estimate of heritability for KHV resistance may be explained by observed differences in survival between families being rather extreme (0–47%, Fig. 3), even though the overall survival rate was only 5% and 7% in the two tests. The genetic correlation between the two challenge-tested diseases (KHV and A. hydrophila) was moderately high, although uncertain (0.61 ± 0.29), while the genetic correlations between pond survival and resistance to the challenge-tested diseases were not significantly different from zero (0.01 ± 0.28 and −0.22 ± 0.21 for A. hydrophila and KHV, respectively).
4. Discussion The estimated heritability of resistance to A. hydrophila challenge was low (0.04 on the underlying scale, corresponding to ∼0.03 on the observable scale). In a similar study of rohu carp (Mahapatra et al., 2008), the estimated heritability of resistance to A. hydrophila was 0.11 (on the underlying liability scale), using a similar challenge-test procedure as in the current study (intraperitoneal injection). However, the results of Mahapatra et al. (2008) were inconclusive due to lack of consistency across two replicated challenge-tests. In the current study, mortality increased extremely rapidly from start of test (injection of pathogen), but stabilised at an intermediate level after a few days. In most cases, natural A. hydrophila infections are secondary in character, and are associated with viral or parasitic infection or sudden environmental changes (Jeney and Jeney, 1995). Hence, challenge-test infections with cohabitants would be expected to be more realistic and give lower levels of mortality, but has so far not been successful for A. hydrophila. The underlying factors of resistance after intraperitoneal injection may be quite different from the major factors relevant for resistance after natural exposure to the pathogen (e.g., through cohabitants). For KHV the estimated heritability on the underlying scale was extremely high (0.79±0.14, corresponding to ∼0.3 on the observable scale), but the corresponding standard error was also substantial. Hence, the estimated heritability for KHV resistance was not significantly different from previously reported heritability estimates (0.5–0.6) for some of the other common diseases in aquaculture species (Kjøglum et al., 2008; Ødegård et al., 2007). Furthermore, recent results on Atlantic cod indicate a similar heritability (0.75±0.11) for survival after challenge with nodavirus (Ødegård et al., 2010). In the current study, overall survival rate in the KHV challenge-test was low (5% and 7%), which is unfavourable both with respect to estimation of genetic (co)variance components and for the accuracy of predicted breeding values. For example, at the end of test, most families will have no survival at all. However, in the present diallel crossing design, each sire and dam had offspring with multiple mating partners of different strains, and thus a reduced probability of complete mortality of all offspring, which is likely to improve precision of parameter estimates. Furthermore, the best families had survival close to 50%, although the overall survival was only 6%. The probability of observing such high levels of survival within a random sample of 20 fish would thus be less than 1:1,000,000, and substantial
Fig. 1. Kaplan–Meier survival curves for each of the A. hydrophila and KHV challenge-tests.
J. Ødegård et al. / Aquaculture 304 (2010) 7–13
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Fig. 2. Observed survival at end of test after challenge with A. hydrophila for 92 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T). Results are averaged across the two challenge-tests.
family effects are therefore to be expected. To our knowledge, there are no published estimates of heritability for KHV resistance in common carps, but considerable differences in KHV resistance has been found among different strains and strain crosses (Shapira et al., 2005). Furthermore, Rakus et al. (2009) identified several genotypes of MH class II B genes having significant effect on mortality after challenge-testing of different strain crosses of common carp. Common environmental effects may, if not accounted for, inflate estimates of heritability. In the current analysis, no common environmental effects were identified for any of the traits, although mating structure was optimized in order to be able to distinguish additive genetic and common environmental family effects. Still, such effects would most likely be more difficult to disentangle from the additive genetic effects at a low incidence of survival, which is the case for the KHV challenge-tests.
The challenge-tests for resistance against KHV and A. hydrophila infection were split in two separate tests conducted at different times and at somewhat different ages and weights of the fish. Differences in overall mortality in the two tests are accounted for through the fixed effects in the model. However, the analysis assumes that resistance against a given pathogen is the same genetic trait across tests. This was supported by preliminary analyses (of KHV and A. hydrophila), which indicated that the genetic correlations between the two tests were approximately unity and that the genetic variances did not differ significantly. Hence, pooling of data from the two tests seems appropriate. The genetic correlation between resistance to KHV and A. hydrophila was positive and moderately high, but uncertain (0.61±0.29), which may be explained by the low and rather inaccurate heritability estimate for A. hydrophila resistance. The rather different infection regimes in the two diseases (cohabitants versus injection) may reduce the estimated
Fig. 3. Observed survival at end of test after challenge with KHV for 91 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T). Results are averaged across the two challenge-tests.
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Fig. 4. Observed pond survival for 92 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T).
genetic correlation between the traits. The result is, however, in accordance with Ødegård et al. (2007), showing a low but significantly positive genetic correlation (0.15±0.05) between resistance to infectious salmon anaemia (a viral disease, mainly tested through intraperitoneal injection) and furunculosis (caused by the bacteria A. salmonicida, induced through cohabitants) in Atlantic salmon. The heritability of pond survival was moderate (0.34 on the underlying scale, corresponding to ∼0.2 on the observable scale). Moreover, Nielsen et al. (2010-this issue) estimated a favourable genetic correlation (0.65± 0.15) between pond survival (S3, being the same trait as in the current study) and harvest weight. However, the results of the current study revealed that the correlated effect on pond survival is likely to be very small when selecting for improved resistance to A. hydrophila and KHV. This outcome is, however, to be expected if the tested diseases are of limited importance for the actual mortality in the observed pond environment. With respect to KHV, showing the largest genetic variability among the tested diseases, no cases have so far been detected in Hungary (http://www.fvm.hu). The bacteria A. hydrophila is, however, common in aquatic environments, but pathogenicity is often stress-induced, and no outbreaks were observed in this specific pond. In rainbow trout, Vehviläinen et al. (2008) estimated a wide range of heritability values and genetic correlations between field survival for different year classes and environments, and concluded that the genetic architecture of field survival was not stable over generations and environments. Hence, the genetic (co)variance components for pond survival obtained in this study should be interpreted with care and not be generalized to other current or future rearing environments for the common carp. As the statistical model used in this study also included effects of parental strains, (and heterosis for pond survival) the estimated
Table 2 Sire–dam variances (on the diagonal) and genetic correlations (above the diagonal), residual variances and heritabilities of A. hydrophila resistance, KHV resistance and pond survival on the liability scale. Factor
Trait
A. hydrophila
KHV
Pond survival
Sire–dam (co) variance
A. hydrophila KHV Pond survival
0.011 ± 0.007
0.614 ± 0.286 0.327 ± 0.099
1.000 0.043 ± 0.027
1.000 0.790 ± 0.145
0.005 ± 0.277 −0.219 ± 0.215 0.100 ± 0.031 1.000 0.335 ± 0.086
Residual variancea Heritability a
Residual variances of liabilities for all binary traits were restricted to unity.
additive genetic variances are indicators of the average genetic variability within each strain. However, as all these strains are likely to be more or less inbred (Nielsen et al., 2010-this issue), the additive genetic variance is expected to be higher in a synthetic population (based on these four strains, from generation F2 and onwards), due to a lower level of inbreeding. 5. Conclusion The estimated underlying heritability for resistance to A. hydrophila infection was low, while the estimated heritability for KHV resistance estimated was extremely high on the underlying scale and moderately high on the observed scale, although overall mortality for KHV was unfavourable (N90%). A moderately high, although uncertain, favourable genetic correlation was estimated between resistance against A. hydrophila and KHV infections. Pond survival showed no significant genetic correlation with resistance to the two diseases. Based on the results from the current study there are good prospect for joint genetic improvement of resistance to KHV infection and pond survival in common carps through genetic selection based on challenge-test and field data, respectively. Acknowledgements The work was carried out as a part of the FP6 STREP project no. 022665, EUROCARP “Disease and stress resistant common carp: combining quantitative, genomic, and proteomic and immunological marker technologies to identify high performance strains, families and individuals”. Funding of this project was given by the EU commission and by Defra contracts F1167 and F1170. References Bakos, J., Gorda, S., 1995. Genetic improvement of common carp strains using intraspecific hybridization. Aquaculture 129, 183–186. Dixon, P.F., Joiner, C.L., Way, K., Jeney, G., Jeney, Z., 2009. Comparison of the resistance of selected families of common carp, Cyprinus carpio (L.), to koi herpesvirus: preliminary study. Journal of Fish Diseases 32, 1035–1039. Gilmour, A.R., Gogel, B.J., Cullis, B.R., Thompson, R., 2006. ASReml User Guide Release 2.0. VSN International Ltd, Hemel Hempstead. Gorda, S., Bakos, J., Liska, J., Kakuk, C., 1995. Live gene bank of common carp strains at the Fish-Culture-Research-Institute, Szarvas. Aquaculture 129, 199–202.
J. Ødegård et al. / Aquaculture 304 (2010) 7–13 Jeney, Z., Jeney, G., 1995. Recent achievements in studies on diseases of common carp (Cyprinus carpio L.). Aquaculture 129, 397–420. Kjøglum, S., Henryon, M., Aasmundstad, T., Korsgaard, I., 2008. Selective breeding can increase resistance of Atlantic salmon to furunculosis, infectious salmon anaemia and infectious pancreatic necrosis. Aquaculture Research 39, 498–505. Mahapatra, K.D., Gjerde, B., Sahoo, P.K., Saha, J.N., Barat, A., Sahoo, M., Mohanty, B.R., Ødegård, J., Rye, M., Salte, R., 2008. Genetic variations in survival of rohu carp (Labeo rohita, Hamilton) after Aeromonas hydrophila infection in challenge tests. Aquaculture 279, 29–34. Nielsen, M.E., Hoi, L., Schmidt, A.S., Qian, D., Shimada, T., Shen, J.Y., Larsen, J.L., 2001. Is Aeromonas hydrophila the dominant motile Aeromonas species that causes disease outbreaks in aquaculture production in the Zhejiang Province of China? Diseases of Aquatic Organisms 46, 23–29. Nielsen, H.M., Ødegård, J., Olesen, I., Gjerde, G., Ardo, T., Jeney, G., Jeney, Z., 2010. Genetic analysis of common carp (Cyprinus carpio) strains: I: Genetic parameters and heterosis for growth traits and surviva. Aquaculture 304, 14–21 (this issue). Ødegård, J., Olesen, I., Gjerde, B., Klemetsdal, G., 2007. Positive genetic correlation between resistance to bacterial (furunculosis) and viral (infectious salmon anaemia) diseases in farmed Atlantic salmon (Salmo salar). Aquaculture 271, 173–177.
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Ødegård, J., Kettunen Præbel, A., Sommer, A.I., 2010. Heritability of resistance to viral nervous necrosis in Atlantic cod (Gadus morhua L.). Aquaculture 300, 59–64. Rakus, K.L., Wiegertjes, G.F., Adamek, M., Siwicki, A.K., Lepa, A., Irnazarow, I., 2009. Resistance of common carp (Cyprinus carpio L.) to Cyprinid herpesvirus-3 is influenced by major histocompatibility (MH) class II B gene polymorphism. Fish & Shellfish Immunology 26, 737–743. Shapira, Y., Magen, Y., Zak, T., Kotler, M., Hulata, G., Levavi-Sivan, B., 2005. Differential resistance to koi herpes virus (KHV)/carp interstitial nephritis and gill necrosis virus (CNGV) among common carp (Cyprinus carpio L.) strains and crossbreds. Aquaculture 245, 1–11. Vandeputte, M., 2003. Selective breeding of quantitative traits in the common carp (Cyprinus carpio): a review. Aquatic Living Resources 16, 399–407. Vehviläinen, H., Kause, A., Quinton, C., Koskinen, H., Paananen, T., 2008. Survival of the currently fittest: genetics of rainbow trout survival across time and space. Genetics 180, 507–516. Wohlfarth, G., Moav, R., Hulata, G., 1975. Genetic differences between Chinese and European races of common carp. 2. Multi-character variation — response to diverse methods of fish cultivation in Europe and China. Heredity 34, 341–350.
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Aquaculture j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a q u a - o n l i n e
Genetic analysis of common carp (Cyprinus carpio) strains. II: Resistance to koi herpesvirus and Aeromonas hydrophila and their relationship with pond survival Jørgen Ødegård a,⁎, Ingrid Olesen a, Peter Dixon b, Zsigmond Jeney c, Hanne-Marie Nielsen a, Keith Way b, Claire Joiner b, Galina Jeney c, László Ardó c, András Rónyai c, Bjarne Gjerde a a b c
Nofima Marin, P.O. Box 5010, NO-1432 Ås, Norway CEFAS, Centre for Environment, Fisheries and Aquaculture Sciences, Weymouth DT4 8UB, UK HAKI, Research Institute of Fisheries Aquaculture and Irrigation, Anna Liget 8, Szarvas H-5540, Hungary
a r t i c l e
i n f o
Article history: Received 6 May 2009 Received in revised form 3 February 2010 Accepted 20 March 2010 Keywords: Common carp Cyprinus carpio Genetic parameters Pond survival Disease resistance KHV Aeromonas hydrophila
a b s t r a c t Estimates of strain effects, heritabilities and genetic correlations for pond survival, resistance to Aeromonas hydrophila and resistance to koi herpesvirus (KHV) were obtained from a diallel cross of 92 full-sib families of common carp produced from four strains (Szarvas 15, Tata, Duna and Amur) and using five females and ten males per strain. Disease resistance was obtained from survival data from challenge-tests using intraperitoneal injection for A. hydrophila and cohabitation for KHV. Two separate challenge-tests were conducted for each disease. The overall survival rates were 44% and 34% for the two tests of A. hydrophila, and 7% and 5% for the two tests of KHV. Pond survival (averaging 78%) was observed over a six months period prior to harvest (at approximately 18 months of age). The three traits were analysed jointly in a multivariate threshold model. For KHV the strain Szarvas 15 had the lowest observed (purebred) survival (0%) followed by Amur (11%), Duna (12%) and Tata (21%), while for A. hydrophila, the lowest (purebred) survival was observed for Duna (28%) followed by Amur (31%), Szarvas 15 (38%) and Tata (48%). Heterosis was not significant for KHV and A. hydrophila resistance, although highly significant for pond survival. The estimated heritability (on the underlying liability scale) was low (0.04± 0.03) for A. hydrophila resistance, very high (0.79±0.15) for KHV resistance, and moderate (0.34±0.09) for pond survival. The genetic correlation between the two challenge-tested diseases (KHV and A. hydrophila) was moderately high (0.61±0.29), although uncertain, while the estimated genetic correlations between pond survival and the two challenge-tested diseases were low and not significantly different from zero (0.01± 0.28 and −0.22±0.21 for A. hydrophila and KHV, respectively). The latter may be expected for KHV, as no outbreaks of the disease had been observed in Hungary. Based on the favourable heritabilities of KHV and pond survival there is good prospect for joint improvement of these two traits in common carps through genetic selection. © 2010 Elsevier B.V. All rights reserved.
1. Introduction In terms of volume produced, cyprinid species are, by far, the most important among the species used in fish farming on a worldwide basis (http://www.fao.org), and among these, common carp (Cyprinus carpio) is the third most important. Eastern European carp gene banks have been responsible for the genetic improvement of carp for intensive and semiintensive pond culture in Europe and their dissemination worldwide (Gorda et al., 1995). The main focus for genetic improvement work on common carp has mainly been crossbreeding of strains and inbred lines to exploit heterosis. Notable heterosis for growth has been documented (reviewed by Vandeputte, 2003). However, some pure strains appear to perform as well as the best crosses (Wohlfarth et al., 1975). The majority of worldwide carp production has so far been based on non-improved genetic stocks (Vandeputte, 2003). However, based on ⁎ Corresponding author. Tel.: + 47 45277801; fax: + 47 64949502. E-mail address: jorgen.odegard@nofima.no (J. Ødegård). 0044-8486/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.aquaculture.2010.03.017
existing literature disease resistance may be effectively selected for in common carp (Vandeputte, 2003). Disease is the major risk factor in commercial aquaculture causing annual losses of millions of dollars (Nielsen et al., 2001). Hence, sustainable breeding programs for aquaculture species should also aim at improving stocks with respect to health and survival traits. Outbreaks of mortality caused by koi herpesvirus (KHV) has been found in many countries all over the world, and the disease is currently considered as one of the highest risk factors affecting populations of koi (ornamental variety of common carp) and farmed common carps. The outbreaks are often characterized by very high mortalities at water temperatures above 16 °C (Dixon et al., 2009). The bacteria Aeromonas hydrophila is associated with various disease problems in carp aquaculture production worldwide (Nielsen et al., 2001). Pathogenicity of the bacteria appears to mainly affect stressed or compromised fish, and the infection is often secondary in character (Jeney and Jeney, 1995). For implementing traits in selective breeding programs, genetic parameters; i.e., heritabilities and genetic correlations, are needed for
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their documented breeding history in order to obtain the widest possible genetic differences between the strains. A diallel cross design between the four common carp strains was applied (Table 1). Five females and 10 males per strain was used to produce six full-sib families for each of the 16 cross combinations (four purebred strains and their six crossbred strains with reciprocals), resulting in 96 different families in total. The number of fish produced and individually tagged within each of the 96 family was 100. However, for one of these families, 400 fish were produced. Each of the 96 families (plus the 300 extra fish from one of the families) was held in separate tanks of 100 fish such that the total number of tanks was 99. Of these, 91 families were tested for KHV and 92 for A. hydrophila and pond survival.
the traits of interest. The aim of this study was therefore to estimate these parameters for resistance to KHV and A. hydrophila from experimental challenge-tests and for pond survival in a commercial production environment, using data from four different common carp strains (two domesticated strains, one wild strain of Hungarian origin and one wild strain of Russian origin). 2. Material and methods 2.1. Fish material and crossing design The current study is based on fish from the same population as described in Nielsen et al. (2010-this issue). Fish used in the experiment were the offspring produced by the Fish Biology Department at the Research Institute of Fisheries, Aquaculture and Irrigation (HAKI), at Szarvas, Hungary and were from four different strains provided from the live gene bank of common carp (Gorda et al., 1995). There were two strains representing “wild” strains (Duna and Amur), which are native in the Danube and Amur rivers but has been kept in the live gene bank by HAKI for at least three generations, and two farmed strains (Tata and Szarvas 15). Tata is presumably an inbred strain that has been selected for rapid growth and round body shape and Szarvas 15 has been selected for high heterosis in line crosses (Bakos and Gorda, 1995). These four different strains were selected based on known origin and
2.2. General management and recordings 2.2.1. Mating and production of fry The production of the full-sib families took place at HAKI on May 12, 2006. Males and females were held in separate tanks before artificial reproduction. At the end of July 2006, surplus fish exceeding 400 fish per tank were randomly removed. The fish were individually tagged with PIT-tags at an average body weight of 19.4 g within one week, starting on August 22, 2006. For each family, five random samples of 20 fish were tagged for different experimental purposes.
Table 1 Schematic presentation of the applied diallel crossing design between four carp strains (Duna, Amur, Tata, and Szarvas 15). Five females and ten males per strain was used to produce six full-sib families for each of the sixteen cross combinations (four purebred strains and their six crossbred strains with reciprocals). Female
Duna
Male
No
1
Duna
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10
X X
Amur
Tata
Szarvas 15
Amur 2
3
4
5
1
Tata 2
3
4
5
1
Szarvas 15 2
3
4
5
1
X X
2
3
4
5
X X
X X
X X X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X
X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X X X
X X X X
X X
X X X X
X X
X X
X X
X X
X X
X X
X X
X X X X X X
X X X X
X X
J. Ødegård et al. / Aquaculture 304 (2010) 7–13
2.2.2. Recording of pond survival On September 7, 2006 one of the four samples of 20 fish per family were transported from HAKI and stocked into an earthen pond (1 ha, 1.5–1.8 m water depth) at a commercial farm, Szeged Ltd, in the southern part of Hungary. On November 16, 2006 the body weights and lengths on all fish in the pond were recorded and stocked for wintering in the same pond. After wintering the same recordings were repeated on April 3, 2007 and on October 26, 2007 (harvesting). Fish were fed a catfish feed with 47% of protein and 6.5% of fat at starting feeding rate of 6% of body mass of fish per day. After wintering the fish were fed with Szarvasi common carp fingerling feed, which contained 24% of protein. Shortly after first stocking in the pond, and after the wintering, the fish were offered a medicated feed with Euroquin antibiotic as preventive measure against swim-bladder inflammation (typical to the given farm). In addition, the fish were also given a homeopathic treatment with Immunopics. Fish were scored as survived if weight/length were recorded in both April and October, and scored as dead if weight/length were recorded in April, but not in October (this trait is called S3 in Nielsen et al., 2010-this issue). No information was available about causes of mortality, but no severe disease outbreaks were observed during the experiment. Average body weight at harvest was 1181 g (CV = 0.24). 2.2.3. Challenge-testing A total of 20 (with some exceptions) tagged individuals from were challenge-tested at HAKI with Aeromonas hydrophila, and 20 (with some exceptions) tagged individuals per family were in September 2006 sent to CEFAS (United Kingdom) for challenge-testing with KHV. Challenge-testing with A. hydrophila was conducted using intraperitoneal injection of 0.1 ml per fish, using a suspension with 3 × 107 bacteria/ml. Testing was done under controlled tank conditions, at constant water temperature and pH (22–23 °C; pH 8.5). On the first three days after the challenge, mortalities were recorded hourly, on the following three days every 3 h, and later every 6 h. Mortalities were confirmed as being caused by A. hydrophila by bacteria isolation from the kidney. Two separate challenge-tests (appr. 5 + 15 fish per family) were conducted. The initial test started at January 22, 2007 (at an average weight of 126 g, CV = 0.62) and the last mortality was recorded at January 30, 2007. The second test started at March 20, 2007 (at an average weight of 146 g, CV = 0.65) and the last mortality was recorded at March 28, 2007. Both tests were run until the cumulative mortality reached a plateau. In total, 92 of the original 96 families were represented within the challenge-tests for A. hydrophila resistance. Challenge-testing with KHV was conducted using cohabitants. The testing procedure for this material has previously been described by Dixon et al. (2009). As for A. hydrophila, two separate challenge-tests (appr. 5 + 15 fish per family) were conducted. A single tank containing all fish was used in the initial challenge-test, while three tanks were used in the second test (each containing a random sample of fish). In the latter experiment, tank environments were standardized through circulation of water among the tanks, and the three tanks were thus assumed to be the same environment. Dead fish were recorded on a daily basis, and at least 10% of the dead fish checked for presence of KHV. The initial test was started at February 16 (at an average weight of 52 g, CV = 0.40), with the last recorded mortality at March 17, 2007. The second test was started at April 3 (at an average weight of 62 g, CV = 0.43), with the last recorded mortality at April 25, 2007. Both tests were run until the cumulative mortality reached a plateau. In total, 91 of the original 96 families were represented within the challenge-tests for KHV resistance. 2.3. Statistical analysis In the statistical analysis, pond- and challenge-test survival for all traits were defined as survived or dead (1/0), observed at the end of test.
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Pond survival was 78%, and A. hydrophila challenge-test survival was 44% (test 1) and 34% (test 2). For KHV the fraction of surviving individuals was low (5–7%). For such low frequencies, it is common to define a binary survival trait based on whether or not the fish was alive at 50% overall mortality. However, as preliminary analyses showed that the statistical analysis was sensitive to the exact truncation point (i.e., whether one defines the period until the day before or day after 50% mortality was reached), survival at the absolute endpoint of testing period was chosen, although this corresponded with low overall survival. Pond and challenge-test survival were analysed using a multivariate generalized linear mixed probit (threshold) model with the ASREML software (Gilmour et al., 2006), using REML methodology for estimation of variance components for random effects (additive genetic effects of sire and dam). A common environmental effect of full-sib family (e.g., due to common tank environment prior to tagging and non-additive genetic effects common to full sibs) was fitted as a random effect, but this effect was not significant for any of the traits, and was therefore omitted in the final model. A fixed effect of strain and a fixed effect of heterosis that was specific for each strain combination were fitted for all traits. For A. hydrophila and KHV the fixed heterosis effect was not significant and therefore omitted from the model for these traits. The favourable crossing effects on pond survival are described in more detail by Nielsen et al. (2010-this issue). The final model had the following characteristics: Pr (Sijklmno =1) Φ(μij +STRAINik +STRAINil +CROSSikl +damikm +sireiln) Sijklmno survival trait i (i=pond, KHV or A. hydrophila), of fish o, within trial j, from dam m within strain k, and sire n within strain l, μij overall mean for liability to survival trait i in trial j, STRAINiq fixed effect of parental strain q (strain 15, Amur, Duna, Tata) for trait i (q = k for dams and q = l for sires), CROSSikl fixed effect of strain cross combination kl for trait i (CROSSi12 = CROSSi21, …, CROSSi34 = CROSSi43), CROSSikl = 0 for k = l and/or i = KHV or A. hydr. damikm random additive genetic effect of dam m within strain k for trait i, sireiln random additive genetic effect of sire n within strain l for trait i. The additive genetic (sire and dam) effects were assumed ∼N(0, G⊗A), with G being the additive genetic (co)variance matrix for sire and dam effects of the three traits (assuming equal variance components for sires and dams), and A is the additive genetic relationship matrix for sires and dams (equals an identity matrix as sires and dams did not have any known relationships). As all traits were measured on different individuals, the only assumed correlations between the traits were due to the additive genetic effects, and residuals on the underlying scale were thus assumed to be ∼N(0,IN), where IN is an identity matrix with dimension equal to the total number of fish tested (over all traits). Fixed effects were tested in ASREML using single-trait models similar to the model above (including both fixed and random effects in the model). The method used for testing of fixed effects was an incremental Wald F-statistics (Gilmour et al., 2006). 3. Results Fig. 1 shows Kaplan–Meier survival curves for each of the separate A. hydrophila and KHV challenge-tests. For A. hydrophila the overall survivals at end of test were 44% and 34% for the initial and second test, respectively (Fig. 1). The relative differences in survival rates between different strains were moderate (Fig. 2), with the lowest observed (purebred) survival rate (not adjusted for family effects) for Duna (28%) followed by Amur (31%), Szarvas 15 (38%) and Tata (48%). Observed variation in survival at end of test between families within each strain and cross combination was moderate. For KHV, overall survivals at end of the two tests were only 7% and 5% for the initial and second test, respectively (Fig. 1). Despite low
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numbers of fish per family in the initial test and low survival at the end of both tests, the two challenge-tests for KHV showed surprisingly good agreement with respect to observed survival: 60 of the 91 families were completely exterminated in both challenge-tests, while 20 of the remaining 31 families had surviving family members within both tests. For the families with surviving family members, survival fraction varied from 5 to 47% (Fig. 3), with an average survival rate of 18%. Szarvas 15 had the lowest observed (purebred) survival rate (0%) followed by Amur (11%), Duna (12%) and Tata (21%). As in Nielsen et al. (2010-this issue), large strain differences were observed for pond survival (Fig. 4), with the lowest observed (purebred) survival rate for Szarvas 15 (56%), followed by Tata (60%), Amur (71%) and Duna (83%). There was also substantial variation in pond survival between families within each strain and cross combination (e.g., 0 to 81% for crosses between Szarvas 15 and Tata). Based on single-trait analysis, strain differences (taking sire and dam effects into account) were significant for KHV and pond survival (P b 0.01), but not for A. hydrophila (P = 0.20). Heterosis was significantly different from zero (favourable) for pond survival (P b 0.001), but not significant for the challenge-tested diseases. Reciprocal crosses were not significantly different for any of the traits. Table 2 shows the estimated heritabilities for A. hydrophila and KHV resistance and pond survival and the genetic correlations among these traits. All heritability estimates are presented as they appear on the underlying liability scale. The estimated heritabilities were low for A. hydrophila resistance (0.04 ± 0.03), extremely high for KHV resistance (0.79±0.14), and moderate for pond survival (0.34 ± 0.09, as in Nielsen et al., 2010-this issue). This indicates that the moderate family differences observed within strain and cross combination for A. hydrophila are largely a result of sampling (due to limited family sizes), while variations in family survival rates for KHV and pond survival are larger than what can be explained by random sampling. The high estimate of heritability for KHV resistance may be explained by observed differences in survival between families being rather extreme (0–47%, Fig. 3), even though the overall survival rate was only 5% and 7% in the two tests. The genetic correlation between the two challenge-tested diseases (KHV and A. hydrophila) was moderately high, although uncertain (0.61 ± 0.29), while the genetic correlations between pond survival and resistance to the challenge-tested diseases were not significantly different from zero (0.01 ± 0.28 and −0.22 ± 0.21 for A. hydrophila and KHV, respectively).
4. Discussion The estimated heritability of resistance to A. hydrophila challenge was low (0.04 on the underlying scale, corresponding to ∼0.03 on the observable scale). In a similar study of rohu carp (Mahapatra et al., 2008), the estimated heritability of resistance to A. hydrophila was 0.11 (on the underlying liability scale), using a similar challenge-test procedure as in the current study (intraperitoneal injection). However, the results of Mahapatra et al. (2008) were inconclusive due to lack of consistency across two replicated challenge-tests. In the current study, mortality increased extremely rapidly from start of test (injection of pathogen), but stabilised at an intermediate level after a few days. In most cases, natural A. hydrophila infections are secondary in character, and are associated with viral or parasitic infection or sudden environmental changes (Jeney and Jeney, 1995). Hence, challenge-test infections with cohabitants would be expected to be more realistic and give lower levels of mortality, but has so far not been successful for A. hydrophila. The underlying factors of resistance after intraperitoneal injection may be quite different from the major factors relevant for resistance after natural exposure to the pathogen (e.g., through cohabitants). For KHV the estimated heritability on the underlying scale was extremely high (0.79±0.14, corresponding to ∼0.3 on the observable scale), but the corresponding standard error was also substantial. Hence, the estimated heritability for KHV resistance was not significantly different from previously reported heritability estimates (0.5–0.6) for some of the other common diseases in aquaculture species (Kjøglum et al., 2008; Ødegård et al., 2007). Furthermore, recent results on Atlantic cod indicate a similar heritability (0.75±0.11) for survival after challenge with nodavirus (Ødegård et al., 2010). In the current study, overall survival rate in the KHV challenge-test was low (5% and 7%), which is unfavourable both with respect to estimation of genetic (co)variance components and for the accuracy of predicted breeding values. For example, at the end of test, most families will have no survival at all. However, in the present diallel crossing design, each sire and dam had offspring with multiple mating partners of different strains, and thus a reduced probability of complete mortality of all offspring, which is likely to improve precision of parameter estimates. Furthermore, the best families had survival close to 50%, although the overall survival was only 6%. The probability of observing such high levels of survival within a random sample of 20 fish would thus be less than 1:1,000,000, and substantial
Fig. 1. Kaplan–Meier survival curves for each of the A. hydrophila and KHV challenge-tests.
J. Ødegård et al. / Aquaculture 304 (2010) 7–13
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Fig. 2. Observed survival at end of test after challenge with A. hydrophila for 92 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T). Results are averaged across the two challenge-tests.
family effects are therefore to be expected. To our knowledge, there are no published estimates of heritability for KHV resistance in common carps, but considerable differences in KHV resistance has been found among different strains and strain crosses (Shapira et al., 2005). Furthermore, Rakus et al. (2009) identified several genotypes of MH class II B genes having significant effect on mortality after challenge-testing of different strain crosses of common carp. Common environmental effects may, if not accounted for, inflate estimates of heritability. In the current analysis, no common environmental effects were identified for any of the traits, although mating structure was optimized in order to be able to distinguish additive genetic and common environmental family effects. Still, such effects would most likely be more difficult to disentangle from the additive genetic effects at a low incidence of survival, which is the case for the KHV challenge-tests.
The challenge-tests for resistance against KHV and A. hydrophila infection were split in two separate tests conducted at different times and at somewhat different ages and weights of the fish. Differences in overall mortality in the two tests are accounted for through the fixed effects in the model. However, the analysis assumes that resistance against a given pathogen is the same genetic trait across tests. This was supported by preliminary analyses (of KHV and A. hydrophila), which indicated that the genetic correlations between the two tests were approximately unity and that the genetic variances did not differ significantly. Hence, pooling of data from the two tests seems appropriate. The genetic correlation between resistance to KHV and A. hydrophila was positive and moderately high, but uncertain (0.61±0.29), which may be explained by the low and rather inaccurate heritability estimate for A. hydrophila resistance. The rather different infection regimes in the two diseases (cohabitants versus injection) may reduce the estimated
Fig. 3. Observed survival at end of test after challenge with KHV for 91 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T). Results are averaged across the two challenge-tests.
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Fig. 4. Observed pond survival for 92 full-sib families. Average survivals within each strain/cross are presented as horizontal black lines. Families are sorted on survival within each strain/cross combination, ignoring reciprocals (Szarvas 15 = 15, Amur = A, Duna = D, Tata = T).
genetic correlation between the traits. The result is, however, in accordance with Ødegård et al. (2007), showing a low but significantly positive genetic correlation (0.15±0.05) between resistance to infectious salmon anaemia (a viral disease, mainly tested through intraperitoneal injection) and furunculosis (caused by the bacteria A. salmonicida, induced through cohabitants) in Atlantic salmon. The heritability of pond survival was moderate (0.34 on the underlying scale, corresponding to ∼0.2 on the observable scale). Moreover, Nielsen et al. (2010-this issue) estimated a favourable genetic correlation (0.65± 0.15) between pond survival (S3, being the same trait as in the current study) and harvest weight. However, the results of the current study revealed that the correlated effect on pond survival is likely to be very small when selecting for improved resistance to A. hydrophila and KHV. This outcome is, however, to be expected if the tested diseases are of limited importance for the actual mortality in the observed pond environment. With respect to KHV, showing the largest genetic variability among the tested diseases, no cases have so far been detected in Hungary (http://www.fvm.hu). The bacteria A. hydrophila is, however, common in aquatic environments, but pathogenicity is often stress-induced, and no outbreaks were observed in this specific pond. In rainbow trout, Vehviläinen et al. (2008) estimated a wide range of heritability values and genetic correlations between field survival for different year classes and environments, and concluded that the genetic architecture of field survival was not stable over generations and environments. Hence, the genetic (co)variance components for pond survival obtained in this study should be interpreted with care and not be generalized to other current or future rearing environments for the common carp. As the statistical model used in this study also included effects of parental strains, (and heterosis for pond survival) the estimated
Table 2 Sire–dam variances (on the diagonal) and genetic correlations (above the diagonal), residual variances and heritabilities of A. hydrophila resistance, KHV resistance and pond survival on the liability scale. Factor
Trait
A. hydrophila
KHV
Pond survival
Sire–dam (co) variance
A. hydrophila KHV Pond survival
0.011 ± 0.007
0.614 ± 0.286 0.327 ± 0.099
1.000 0.043 ± 0.027
1.000 0.790 ± 0.145
0.005 ± 0.277 −0.219 ± 0.215 0.100 ± 0.031 1.000 0.335 ± 0.086
Residual variancea Heritability a
Residual variances of liabilities for all binary traits were restricted to unity.
additive genetic variances are indicators of the average genetic variability within each strain. However, as all these strains are likely to be more or less inbred (Nielsen et al., 2010-this issue), the additive genetic variance is expected to be higher in a synthetic population (based on these four strains, from generation F2 and onwards), due to a lower level of inbreeding. 5. Conclusion The estimated underlying heritability for resistance to A. hydrophila infection was low, while the estimated heritability for KHV resistance estimated was extremely high on the underlying scale and moderately high on the observed scale, although overall mortality for KHV was unfavourable (N90%). A moderately high, although uncertain, favourable genetic correlation was estimated between resistance against A. hydrophila and KHV infections. Pond survival showed no significant genetic correlation with resistance to the two diseases. Based on the results from the current study there are good prospect for joint genetic improvement of resistance to KHV infection and pond survival in common carps through genetic selection based on challenge-test and field data, respectively. Acknowledgements The work was carried out as a part of the FP6 STREP project no. 022665, EUROCARP “Disease and stress resistant common carp: combining quantitative, genomic, and proteomic and immunological marker technologies to identify high performance strains, families and individuals”. Funding of this project was given by the EU commission and by Defra contracts F1167 and F1170. References Bakos, J., Gorda, S., 1995. Genetic improvement of common carp strains using intraspecific hybridization. Aquaculture 129, 183–186. Dixon, P.F., Joiner, C.L., Way, K., Jeney, G., Jeney, Z., 2009. Comparison of the resistance of selected families of common carp, Cyprinus carpio (L.), to koi herpesvirus: preliminary study. Journal of Fish Diseases 32, 1035–1039. Gilmour, A.R., Gogel, B.J., Cullis, B.R., Thompson, R., 2006. ASReml User Guide Release 2.0. VSN International Ltd, Hemel Hempstead. Gorda, S., Bakos, J., Liska, J., Kakuk, C., 1995. Live gene bank of common carp strains at the Fish-Culture-Research-Institute, Szarvas. Aquaculture 129, 199–202.
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