Introduction: transgenic vs enhanced selection
Aquaculture, like agriculture, is beset with problems of cost, price, and risk. Genetic research, in aquaculture as in agriculture, promises – or dangles – solutions to many of these problems “real soon now”. But what kinds of solution? Investors as well as farmers soon notice that there are two, competing styles of modern genetics, which in this paper are loosely termed “transgenic” and “enhanced selection”.
These styles are in vigorous competition for public attention and resources. History suggests that the first genetic style to gain a significant lead in solving an aquacultural problem is likely to drive the other style out of the game, probably forever. Inbred/hybrid corn technology effectively stopped the development of open-pollinated, pure-line varieties of corn (Kloppenburg, 1988), and the developers of fourway hybrid poultry have driven pure-line poultry breeding to commercial extinction in developed countries. Commercialization of transgenic salmon which grow twice as fast as existing strains could happen as early as this year, 2004 (Stokstad, 2002; Hoag 2003); if this were to occur classical salmon breeding programs could very well be put out of business. Transgenics with 2X or 4X current commercial growth rates are also available for species of tilapia (Rahman et al., 2001). In tilapia, however, the rate of broodstock improvement through wellconducted selection is so rapid (e.g. Bolivar and Newkirk, 2002) that step-wise transgenic technology may be unable to keep up or even gain a toe-hold. Both styles of genetics provide useful solutions to aquacultural problems but they have rather different consequences for the industry as well as for the consumer. The winning style in this technology race (more likely than not a winner-take-all race) cannot yet be predicted. This paper describes recent work which is representative of the two styles, in sufficient detail that the current level of sophistication of the science and the size of the outstanding problems can both be appreciated. The topics include possible biological limitations on transgenic growth, progress in transgenic growth and disease resistance, QTL selection, the crucial role of the major histocompatibility complex, and prevention of wasteful reproduction and pointless sexual dimorphisms.
The winner in the commercial (as opposed to technological) race between selection and transgenics will depend to a large extent on the willingness of the public to accept genetically engineered fish. Transgenic fish are looked at with strong disfavour at the present time (Hulata, 2001), but in the long term public opinion is an incalculable quantity. The two styles of genetics also have have different longterm consequences for farmers. Marker-assisted selection and genetic engineering can benefit the owners and developers of the technology and, eventually, the fish-eating public. They will also give transient economic benefits to “early adopter” farmers, but, in the long term, only those farmers who hold exclusive franchises or own part of the technology are likely to benefit from it.
The impossibility of standing still
Most farmers are unwilling simply to ignore genetics, for two reasons. One is the obvious opportunity cost – lost opportunity – of forgone genetic improvement. This cost, which can be estimated from simple economic models of the genetic process, is a commonplace of the promotional literature of aquaculture genetics. Opportunity costs calculated from projected farm revenues will, however, be overtaken in the long run by the larger cost of being forever left behind in the technology race. This is a world in which there are promoters, scientists, technology owners, early adopters, follow-on adopters and the fish-eating public. Only the swift-moving early-adopter farmers are likely to gain any longterm competitive advantage from new technology.
Large-scale commercial or national genetics programs tend to benefit the public, professional geneticists and the owners of the technology. Economic benefits to individual farmers who are competing with each other in a commodity market are less obvious unless they become early adopters and/or own part of the technology. The situation which confronts farmers is summed up in Alice’s conversation with the Red Queen in the Land of the Looking Glass: “ ‘Well, in our country’, said Alice, still panting a little, ‘you’d generally get to somewhere else - if you ran very fast for a long time as we’ve been doing.’ ‘A slow sort of country!’ said the Queen. ‘Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!’ ”
Increased growth rate through classical broodstock selection
Mass selection has been by far the most commonly used artificial selection procedure in aquaculture (Hulata, 2001). Hulata’s comprehensive review gives instances of successful mass selection performed on many aquacultural species. Even in common species like Atlantic salmon and tilapia, however, the procedure is sometimes successful (Sanchez et al., 1995) and sometimes not (Teichert-Coddington and Smitherman, 1988; Hulata et al., 1986). The frequent failure of well-conducted mass selection programs in aquaculture has yet to be satisfactorily explained.
It is certain, however, that hatcheries that adopt a ‘breed the biggest’ approach to mass selection for growth soon encounter practical problems arising from variation in spawning times and condition of the breeders. The biggest animals may be somewhat older, rather than faster growing, and may then have this initial, non-genetic, size advantage magnified by competition to such an extent that selection for size becomes ineffective.
Straight-forward mass selection often does work, however. In the shrimp Penaeus stylirostris, Goyard et al. (2002) showed that a straight-forward mass selection program can produce useful genetic gains in growth rate. Selection intensities, which ranged between 4% and 18%, were not especially high. The program produced a 21% increase in growth rate by the fifth generation nevertheless. Hetzel et al. (1999) developed two breeding lines in another species of shrimp, P. japonicus, one mass-selected for high weight and one for low weight. The direct response to this selection was an 8.3% gain in weight of the offspring of the high line. The low line lost about 13%. The authors conclude that the realized heritability of growth rate in mass selection is only moderate but the large family sizes and phenotypic variability (opportunity for selection) should permit rapid stock improvement. These remarks apply to all aquacultural fish and shellfish.
Surprisingly, the least successful selection programs tend to have been those which went well beyond simple mass selection in the sophistication of their statistical, quantitative genetic methodologies (i.e. index selection using the so-called ‘animal model’).
Several of the most widely promoted projects, continuing for decades in salmon and tilapia, have yet to publish any peer-reviewed proof of genetic gain. Successful index selection has in fact been described in the peer-reviewed literature only twice, to my knowledge (Hershberger et al., 1989; O’Flynn et al., 1999). The realized response to selection in those experiments was not, however, what the authors had predicted from their prior heritability estimates. Selection projects that have worked best in aquaculture have up to now been based on the simpler experimental designs.
It is not at all clear what has gone wrong with sophisticated index selection along classical lines. One possibility is that, as we now know, the genetic architecture of quantitative traits differs from the assumptions made when selection indices are calculated. The genetic basis of the variation in quantitative traits probably involves a few genes having large effects and many genes having small effect (Orr, 1999), contrary to the assumptions of the ‘infinitesimal model’ from which classical heritability estimates are usually derived.
COMPETITION EFFECTS IN SOPHISTICATED SELECTION DESIGNS
A more likely explanation, specific to aquaculture, are the statistical difficulties caused by competition among individual fish within a tank, cage or pond. It has been known for a very long time that competition can have drastic effects both on the estimation of genetic parameters and the outcome of selection programs (Doyle and Talbot, 1986; Jobling, 1983; Moav and Wohlfarth, 1974; Purdom, 1974). Estimates of genetic parameters such as heritabilities and genetic correlations, which are used in sophisticated breeding programs, are distorted because individual error terms in the statistical analyses are not independent, as they are assumed to be in the linear statistical models used to estimate them (Hamblin and Rosielle, 1978; Mazer and Schick, 1991). The food that one animal eats is not available to others; small individuals may be intimidated by others even when food is abundant, etc. The genetic variance component due to the genotypes of other individuals in the population is hidden from ordinary genetic analysis. Wolf (2003) found a negative covariance between direct and indirect (competitive) genetic effects, such that genes that make an individual bigger make other individuals smaller. This effect is surprisingly large, and furthermore it increases as the genetic relatedness of individuals in the competing group increases.
Thirty years ago Moav and Wohlfarth (1974) pointed out that in common carp non-genetic differences in size due to an age difference of only one day become magnified by competition and can dominate the outcome of a selection program. At the present time, however, the lamentable truth is that roughly 99.9% of aquaculture genetic analyses ignore competition despite the fact that it has major nongenetic effects on the variance of growth rate. There are, of course, exceptions, including the work of Moav and his colleagues in Israel. Another recent exception is the work of Brichette et al. (2001) on competitive growth of mussels grown in trays. The competition problem may disappear in index selection as selection incorporates information from more relatives extending over more generations.
Since the competition effect on index and combined selection has not been well studied mathematically, we do not know whether to expect that happy outcome or not. Information derived from DNA markers may perhaps be used to generate the required pedigree structure extending over several generations in populations that are grown and propagated together, as is often the case in aquaculture, but as yet no multigeneration selection experiments based on pedigree markers have been published. The accuracy of pedigree reconstruction from markers is turning out not to be especially high (Thomas et al., 2002; Coltman and Slate, 2003; Wilson et al., 2003).
The between-family component of a selection index is always suspect because of non-genetic, environmental effects common to members of a family even when families are reared together in a common tank and DNA markers used to sort them out (e.g. Cunningham et al., 2001; Fishback et al., 2002). The idea that animals in the same tank experience the same environment is an illusion; a family added to the tank on the last spawning day will have a smaller average size than a family added on the first day and will therefore be at a competitive disadvantage. It will also be relatively underfed if feed is supplied to the tank at a rate which is determined by the size and weight-specific metabolic rate averaged across all families.
Successful artificial selection programs in aquaculture tend to be those in which the effects of un-analysed competition are minimised operationally (e.g., by selection within families (Uraiwan and Doyle, 1986) rather than statistically. In pure within-family selection, the biggest animals in each (usually fullsib) family are selected as breeders (Hill et al., 1996).
Mean differences among families, such as age effects, which can be magnified by competition, are ignored. Because aquacultural species usually produce large broods, selection intensities within families can be high. Bolivar and Newkirk (2002) described a withinfamily selection experiment in tilapia, which achieved a realized heritability estimate of only 0.14 over 12 generations. However, within-family selection permitted high selection intensities of about 2%. The result was that the size of the fish at 16 weeks more than doubled after 12 generations.
Families must be distinguishable in within-family selection, either by growing them in separate tanks until they are big enough to be tagged or by using DNA markers for identifying families. The latter procedure, called ‘walk-back’ (Doyle and Herbinger, 1994), maximizes effective population size and can achieve very high selection intensities in aquaculture because of the large fecundities. The potential benefit of this procedure over ordinary within-family selection is that families do not have to be reared separately until they are big enough to be physically tagged.
Selection among families (as opposed to within families) is probably only useful when the selected trait cannot be directly measured on the individual chosen to become a breeder. In practice, this probably limits its utility to selection for resistance to or tolerance of disease when challenge tests are used to identify superior families. Non-challenged and therefore non-infected siblings are used as breeders (e.g. Argue et al., 2002; Henryon et al., 2002; Oliver et al., 2000; Sarder et al., 2001).
Transgenics and bioengineering
Much of the current excitement in aquaculture genetics – as in all other areas of genetics – lies in transgenesis and bioengineering. This excitement is fully justified by the rapid progress of the technology for introducing foreign gene constructs into aquacultural species, in the identification of candidate genes and target metabolic pathways for transgenesis, and in the spectacular growth of genetically modified organisms.
The insertion of growth hormone genes has increased the growth of many species of fish (Devlin et al., 2001; Dunham et al., 2001). Fourfold increases without obvious side effects have been reported in salmon (Devlin et al., 1994) and 2.5- to 4-fold increases in tilapia (Rahman et al., 2001). The coding sequences used in transgenesis have sometimes been exogenous, such as human or bovine growth hormone, or have sometimes been isolated from the host species and then spliced to an exogenous, nontranscribed control region to enhance the expression of the gene (Devlin et al., 1995; Martinez et al., 2000).
Aquaculture bioengineering projects with growth hormone have been going on for more than a decade (Fischetti, 1991) and have already resulted in patents such as one granted to A/F Protein Limited (Anonymous, 2000). In the A/FP procedure a salmon growth hormone gene is spliced to a promoter sequence from another fish, the ocean pout, which causes the transgene to transcribe growth hormone in the liver. Unlike the normal salmon gene, which is expressed only some of the time, in the pituitary gland, the transgene is continuously switched on in the liver by its liver-specific promoter. The salmon reach a size of 8 lbs in about 1.5 years. These transformed Atlantic salmon broodstocks are ready for commercial production pending regulatory approval. The review paper by Hulata (2001) discusses the status of growth-rate transgenesis in aquaculture in considerable detail.
An interesting example of genetic engineering which has nothing to do with production is the development of transgenic tilapia with the potential for treating human diabetes (Wright and Pohajdak, 2001). Of course in the ordinary course of things tilapia have evolved to produce tilapia insulin, not human insulin, but genetic engineering has overcome this flaw in the Great Chain of Being. Wright and his colleagues have developed procedures for encapsulating and implanting fish tissue into diabetic mice, where it accurately regulates blood glucose levels. Tilapia and human insulin differ by 17 amino acids but Wright and Pohajdak cloned, sequenced, and modified the tilapia insulin gene by site-directed mutagenesis. The product was a tilapia insulin gene that codes for ‘humanized’ insulin while maintaining all of the tilapia regulatory sequences. They proceeded to develop a strain of transgenic O. niloticus that produces humanized insulin along with its normal insulin. Work still needs to be done to replace the normal tilapia gene with the humanized gene by homologous recombination, and/or to make the humanized gene homozygous and adjust the genetic background.
The objective of the project is to use the tilapia as a source of tissue-transplant material for treatment of type II diabetes. Insulin-producing tissue is much easier and cheaper to collect from tilapia than from mammals, so insulin-producing tissue from the genetically modified tilapia should have a markedly lower production cost and, probably, enhanced safety relative to the present mammalian xenogenetic transplant donors, which are usually pigs.
POPULAR PRESSURE TO ACCEPT ‘FRANKENFISH’ (?)
Public anxiety over the use of genetically modified organisms (GMOs) in food makes it impossible to predict when transgenic aquaculture species will enter commercial production. It is the view of most geneticists that acceptance will be very slow, partly because the public is thought to see nothing beneficial in the technology which would offset the perceived risks. In the case of agriculture this may very well be true, at least in developed countries. The GMOs developed so far have been corn, soybeans etc. modified for the economic advantage of seed companies, growers and herbicide manufacturers, not the end consumers (Charles, 2001). An editorial in Nature (Anonymous, 1999) sums up this attitude: “GM soybeans? Who needs them?” The same question can fairly be asked about genetically modified aquacultural species, which, with few exceptions, have been developed with increased production in mind.
The dismissal of conventional, production-oriented GMOs may however be expressive of a parochial point of view. The need for GMO technology in some developing countries is actually rather obvious. The answer to the rhetorical question “Who needs them?” may be, “practically everyone in the third world”. Trewavas (1999) makes a case for believing that a new agriculture, combining genetic modification technology with sustainable farming, is our best or only hope for staving off an ecological catastrophe.
If we don’t use biotechnology, he says, we are going to run out of arable land and water. The conflict between environmental activists and starving thirdworld pragmatists made headlines at the World Summit on Sustainable Development, held in August 2002 in Johannesburg. Zambian President Levy Mwanawasa (who had declared a food emergency three months previously) announced that he had stopped the distribution of 17,000,000 kg of corn because some of it is genetically modified. “We would rather starve than eat something toxic”, the President said, voicing the anti-GMO viewpoint of the developed world (Wente, 2002). Not everyone in Zambia agrees. Wente cites a Los Angeles Times reporter who was told by a Zambian, “We don’t care if it is poisonous because we are dying anyway”. Public perception, not science, is the key to the future. Pressure to accept GMO technology which increases yield may bring GMO crops into production in the poorer and more ecologically stressed parts of the world much sooner than many people expect.
BIOLOGICAL LIMITATIONS ON TRANSGENIC GROWTH
Transgenics stands far above all other productivityenhancing genetic technology in terms of potential payoff and risk. However, there are some preliminary indications that the most direct transgenic procedure, inserting a transgenic growth hormone, may be relatively ineffective in lines which have already been selected for high growth (Devlin et al., 2001; Parks et al., 2000). It appears that selective improvement and transgenesis may not combine additively. To the extent that this turns out to be true in general, selected strains that achieve growth rates comparable to transgenics may remain competitive with transgenics, with much lower development costs. The effect of a transgene on growth may be strongly influenced by the genetic background of the host.
Devlin et al. (2001) compared the effect of a growth hormone transgene in slow-growing, wild rainbow trout with its effect in rainbow trout that had a long prior history of domestication and selection for fast growth. They comment that “the growth response is strongly influenced by the intrinsic growth rate and genetic background of the host strain, and that inserting growth-hormone transgenes into highly domesticated fish does not necessarily result in further growth enhancement.” The growth of the transgenic fish speeded up 17-fold (!) but was still not faster than that of the highly domesticated strain. The domesticated strain hardly responded to the transgene at all. Cranial abnormalities were seen in the transgenic but not in the domesticated animals, which were growing at about the same rate, suggesting that ordinary homeostatic mechanisms were not coping with the novel pathways of growth and development induced by the transgene.
Devlin and his co-authors conclude that “The effect of introducing a growth-hormone gene construct into fish to increase growth rates appears to be dependent on the degree to which earlier enhancement has been achieved by traditional genetic selection. Such effects are likely to be specific for different species, strains and transgenes — in selected mice or in domesticated, rapidly growing farm animals, for example, growthhormone transgenesis can have little effect on growth or it can induce pathological effects, as we have seen in transgenic salmonids.”
Aquaculture geneticists, like other biologists, may be able to learn a lot from the study of mice. Bunger and Hill (1999) selected lines of mice for high and low body weight for more than 50 generations, after which the high and low lines had diverged approximately 3-fold in their weight at 98 days. The authors then eliminated growth hormone from the metabolism of the mice by genetic ‘knock out’, which they achieved by backcrossing a defective growth hormone (GH) releasing factor receptor gene into both lines. Control high and low lines with the normal GH gene were also maintained.
Both lines of mice carrying the knock-out gene, which were thereby deficient in GH, were much smaller than the normal control mice at 98 days. There is no doubt that growth hormone makes mice grow quickly. What is surprising is that the divergence of the high and low lines was almost as great in the absence of growth hormone (2.4-fold divergence) as in its presence (3.1-fold). The authors conclude that after appropriate scale transformation, “changes in the GH system contribute only a small part of the selection response in growth ... [and] other systems contributed most of the selection response”. This experiment should interest the aquaculture community even though it was performed on mice. We know that transgenic fish carrying extra growth hormone genes, or modified genes that express GH continuously, are fast-growing fish - sometimes very fast-growing. This ingenious knock-out experiment on mice is a hint that the converse may not be true. Selection of fast-growing fish by classical methods may evoke an entirely different kind of genetic change that does not involve growth hormone. Furthermore, it suggests that if crosses between highand low-selected lines are used in searches for growth QTLs, the growth hormone system will not necessarily provide the best candidate genes.
TRANSGENIC DISEASE RESISTANCE
Resistance to disease is of particular interest in the culture of salmonids and shrimp, a fact which is reflected in the focus of ongoing projects in genetic engineering. Standard techniques for inserting foreign genes have been difficult to apply to shrimp because embryos of Penaeus are released from their mothers at a relatively advanced stage. Newlyfertilized eggs are essentially unavailable at the appropriate stage for microinjection or electroporation. Sarmasik et al. (2001) may have found a way around this problem, which is expected to work in other crustaceans and live-bearing fish. The foreign gene is carried into the host by an extensively engineered viral vector. One engineered feature of the vector makes it unable to replicate. Other features, derived from the hepatitis B virus and the vesicular stomatitis virus (a pathogen similar to hoof and mouth disease which infects mammals, insects and possibly plants), enable the vector to stick to the cell membrane of a wide variety of organisms. Immature gonads of the crayfish were injected with a solution of the vector about one month before the normal age of first reproduction. When they matured the injected individuals were mated with normal individuals. Sarmasik et al. (2001) provide proof of integration, expression and transmission of the reporter transgene for at least three generations.
Some of the more promising transgenes for disease resistance are genes encoding lectin molecules. Lectins are small peptides (amino acid sequences) that bind to sugar molecules exposed on the surface of cell membranes. After binding, some types of lectin lyse the phospholipid bilayer of the membrane, killing the cells. Lytic peptides are proving to be potent toxins to a broad range of bacterial, fungal and protozoan pathogens. Much work has gone into producing transgenic plants and mice that express enhanced levels of lectins as built-in fungicides, bactericides and insecticides.
Disease-related transgenic experiments in aquaculture have focused on Cecropin-B, an antimicrobial peptide of about 35 amino acids which is synthesized in the pupae of the silk moth in response to bacterial infection. Electroporation has been used to incorporate cecropin-producing genes into Medaka, with a resulting increase in resistance to Pseudomonas fluorescens, Aeromonas hydrophila, and Vibrio anguillarum (Sarmasik et al., 2002). Challenge studies showed that while about 40% of the controls were killed by both pathogens, only up to 10% of the F2 transgenic Medaka were killed by P. fluorescens and about 10% to 30% by V. anguillarum.
A similar transgene construct and insertion procedure greatly increased the resistance of the channel catfish Ictalurus punctatus to the epizootic of Flavobacterium columnare in an earthen pond (Dunham et al., 2002). Fully 100% of the transgenic catfish survived a natural exposure to the flavobacterium, versus 27% survival of normal fish. When challenged in tanks with Edwardsiella ictaluri, a bacterium that causes enteric septicaemia in catfish, survival of the transgenic fish was 41% versus 15% for the controls.
The use of cecropin transgene in aquaculture has been patented (Cooper and Enright, 1999). The patent claims that “Augmentation of the host’s defences against infectious diseases or tumours is achieved by “arming” the host’s cells with an exogenous gene encoding a natural or synthetic lytic peptide. …The transformed cells have the ability to produce and secrete a broad spectrum chemotherapeutic agent that has a systemic effect on certain pathogens, particularly pathogens that might otherwise evade or overcome host defences.”
MARKER-ASSISTED AND QTL SELECTION
The search for disease-resistance and other loci that have effects which are large enough to be useful but not large enough to be obvious by simple segregation analysis (quantitative trait loci, or QTLs) is following two approaches, marker-assisted selection (MAS) and the search for ‘candidate genes’. Both approaches are expected to be most useful when ordinary quantitative genetic procedures for estimating breeding values have especially low accuracy – in particular, when selecting for disease resistance if the selected animals cannot be exposed to the disease. MAS and QTL selection will be less useful in selecting for growth where heritabilities are usually reasonably high and estimation of the breeding values of individuals from their phenotypes is reasonably accurate. Simulation studies of selection on growth rate, a trait that is measured on all animals prior to selection, find only small gains from addition of marker data (Lande and Thompson, 1990).
A typical example of MAS for a disease-related trait in aquaculture is provided by the work of Ozaki et al. (2001) on QTLs associated with susceptibility to infectious pancreatic necrosis virus (IPNV) in rainbow trout (Oncorhynchus mykiss). Backcrosses between resistant and susceptible strains were used to identify several chromosome regions containing putative QTL genes that affect disease resistance. Fifty-one microsatellite markers were used for the linkage analysis.
Perry et al. (2001) employed a rather similar approach in finding a QTL for upper thermal tolerance in outbred strains of rainbow trout. Segregation at the microsatellite marker for the QTL explained 7.5% of the variance in thermal tolerance in the trout progenies. This is about what we would expect for a relatively large QTL.
The candidate gene approach to finding QTLs involves looking for genetic variants in biochemical or developmental pathways that are known, or strongly suspected, to affect the trait of interest. An example is the work of Schulte et al. (2000) on the lactate dehydrogenase-B gene (Ldh-B) in northern and southern populations of the fish Fundulus heteroclitus. Northern (Newfoundland) fish grow better at lower temperatures while fish from Florida are superior at higher temperatures. The experimental details are too complicated to be easily summarized here but they include temporary transgenesis of the regulatory sequences into the livers of experimental fish; deletion studies to identify the approximate location within the regulatory sequence where the adaptive changes in the transcript occurred; stress tests of live fish to see which alleles (northern or southern) drive the transcription of the gene. A difference of only one base pair in the regulatory sequence accounts for the adaptive difference between the northern and southern populations.
It appears that over the long term, phenotypic selection for quantitative traits may give better results than either MAS or QTL selection. In a simulation study Villanueva et al. (2002) found that selecting for one particular gene allows the other additive ‘background’ genes to drop out of the population by chance (inbreeding rate will usually be an indicator of this effect). Thus there is a loss of additive genetic variance with QTL and MAS selection relative to phenotypic selection, and the ultimate selection limits are lower. Interestingly, the reverse seemed not to happen in the simulation - only very rarely was the advantageous QTL allele lost during phenotypic selection. However, in the short term, both QTL and MAS gave a more rapid initial response than phenotypic selection. Salmon and some other aquacultural species have such long generation intervals that rapid response could actually be worth more, by an economic calculation like net present value, than a high selection plateau that might not be approached for 100 years.
The major histocompatibility complex and disease resistance
Interest in genetic variation in the major histocompatibility complex of fish (MHC) is running high these days. The diversity of the MHC loci, which are the foundation of vertebrate immune systems, appears to be driven by the diversity of pathogens in the environment (Penn et al., 2002). Fish may choose their mates to optimize the MHC genotype of their offspring (Landry et al., 2001). The preferred explanation for this ‘disassortative mating’, in which fish choose mates which are genetically unlike themselves, is that MHC heterozygotes are intrinsically more fit than homozygotes (overdominant selection at MHC loci; Arkush et al., 2002). The thought is that heterozygosity at MHC loci may enhance a host animal’s resistance to pathogens by increasing both the diversity of peptide antigens it presents to T-cells and the diversity of the T-cells themselves.
But there is also evidence (Miller et al., 2001) that particular MHC alleles may be directionally selected, i.e. towards homozygosity, possibly on a lake-specific basis. Heterozygotes would not be more fit than MHC homozygotes and disassortative mating should not be selected in such lakes. And in an experiment in an aquaculture-like environment where exposure to specific pathogen strains was controlled, particular MHC alleles appeared to have a selective advantage but heterozygosity did not (Lohm et al., 2002).
Along with laboratory, field and theoretical studies of the advantages of immune-system diversity per se, there have also been demonstrations that specific pathogens can exert strong selection on particular MHC alleles in fish. Lohm et al. (2002) reported on the resistance to furunculosis in Atlantic salmon originating from the Akvaforsk strain currently reared by AquaGen AS in Norway. Families of salmon were mated on the basis of their MHC genotypes so as to generate mixtures of homozygous and heterozygous individuals within the same full-sib families, thus controlling the genetic background against which specific MHC alleles were expressed. Surprisingly, in this controlled breeding experiment MHC heterozygosity per se did not improve resistance to the furunculosis challenge test. It was particular Class II MHC alleles that conferred relative fitness differences as great as 0.5. The authors write, “This study clearly shows a strong survival advantage for individuals carrying a high-resistance allele when exposed to a bacterial infection. … directional selection acting on the MHC despite its high polymorphism stresses the importance of renewal of genetic variation at these kinds of loci, either from mutation, recombination or immigration from other populations, when combating new or coevolving virulent pathogens.”
A recent study by Cohen (2002), which delved deeper into the molecular structure of the MHC antigen-binding sites, could be a harbinger of more powerful ways to investigate and exploit MHC variation in fish. A population of Fundulus heteroclitus was found to have adapted to an environment which has been grossly polluted with PCBs and other contaminants for more than half a century and which is toxic to other Fundulus. The population also tolerates high loads of parasites (helminths and others) which are rare or absent in other populations. By studying this and control populations living in more benign environments the authors found amino acid substitutions which tend to be concentrated in different parts of the antigenbinding region of the molecule. They proved that the MHC variation is driven by selection, not drift. The first step in applying this technique in other situations, e.g. searching for selectable QTLs in an aquaculture broodstock, would seem to be finding a population that is unusually well adapted to the targeted stress.
We would like to know what the best genetic management strategy is: selection for homozygosity of particular MHC alleles, or selection for MHC diversity per se. The answer is important both to conservationists and to geneticists who hope to profit from the development of proprietary ‘super breeds’ for aquaculture. Evidence from other organisms (e.g. mice; Penn et al., 2002) suggests that it probably depends on the variety and timing of challenges anticipated from pathogens. Optimal selection strategies for populations growing in extensive and ‘biosecure’ aquaculture systems may be even more different than we thought. MHC diversity considerations may become crucial, both practically and politically, in the design of captive breeding and aquaculture genetics programs (Arkush et al., 2002).
Diversion of resources away from growth and into reproduction
Early-maturing male salmon and trout are a problem for aquaculture because male fish are physically unappealing and their growth slow. Age-at maturation is genetically the same trait in both sexes in salmon, judging by the strong genetic correlation between the males and females for both age of maturation and weight (Kause et al., 2003). Thus it will not be easy to develop a strain in which males mature late but maturation of females is unchanged. The heritability of both traits is sufficiently high, though, that selection for late maturation of both sexes should work if performed on either sex.
There is an analogous problem in tilapia with the difference that the female, not the male, diverts resources towards reproduction at the expense of growth. An ingenious genetic work-around for sexual dimorphism in tilapia has been found and is achieving considerable commercial success. As described by Mair et al. (1997), the procedure involves five preparatory generations of progeny testing and hormonal sex reversal, both male-to-female and the reverse. The final result is a set of YY ‘supermales’ which, when mated with normal XX females, produce offspring which are nearly 100% normal XY males. The YY supermales have a few female offspring, however, presumably because of the multifactor sex determination in this species. YY male breeders are now used commercially in many places to generate grow-out populations that consist entirely of genotypically normal XY males. The lack of females contributes to uniformity and more rapid growth and also stops unwanted reproduction in aquaculture ponds.
The only major problem with the above procedure is that it interferes with selection for traits such as growth rate (in the YY male donor line, at least) because of the five generations of preparation. The lag could be reduced considerably if the genotypic sexes could be identified without progeny testing. There is reason to hope that commercially useful sex-specific markers can be found in tilapia. Harvey et al. (2002) report the development of in situ hybridization probes to identify sex-specific sequence differences in the long arm of chromosome 1 of the tilapia species Oreochromis niloticus. The binding difference between the probe sequences from X and Y chromosomes is small, which is not surprising.
The authors comment that “Only limited sequence divergence between the X and Y chromosomes would be expected as YY individuals can develop into males or, if hormone treated, females that are both viable and fertile, although growth and survival rates are somewhat lower in YY than XY males.... This suggests that only a very limited loss of function can have occurred in Y-linked genes and that sequence differences between the X and Y chromosomes are largely confined to non-coding regions.” Lee et al. (2003) used bulked segregant (BS) analysis to search for microsatellite marker genes associated with phenotypic sex in tilapia. (In BS analysis DNA from many individuals with the same phenotype is pooled and compared to a pool of DNA from a contrasting phenotype. The contrast here was male vs female phenotypes.) Ten markers were found, all on linkage group 8, which is therefore the (or a) putative Y-chromosome. The linkage of two markers with the sex-determining region was so tight that the sex of offspring of two families was correctly predicted 95% of the time. Unfortunately the markers were not linked to sex in the third family, which shows that we are still some distance away from using markers instead of progeny testing in the commercial production of tilapia YY-supermales.
The existential dilemma of aquaculture farmers
Farmers beset with problems of cost, price and risk are faced with a dilemma because ignoring genetics is likely to be just as costly as paying for it. Practical decisions about genetics must be made every time fish or shellfish are stocked. Are these breeders the best available? Are they are even average? Would one of the breeds promoted on the worldwide web grow well enough to stave off bankruptcy? The application of modern genetics is often listed as one of the highest priorities in aquaculture research and development agendas. Nevertheless, farmer associations and government agencies are slow to invest in ‘big genetics’, as has often been noted and lamented by professional geneticists. This is not because ‘big business’ is attempting to direct publicsector research towards its own interests, as it is reputed to have done during the development of scientific agriculture (Kloppenburg, 1988). Individual farmers just seem to prefer activities that they can do themselves on their own farms.
The question a farmer asks about programs that promise to provide ‘super fish’ or ‘super shrimp’ is which program will bring the largest economic benefit to his own farm. As indicated earlier, modern genetics has shown itself capable of producing genetic productivity gains measured not by increments but by multiples of the existing standard. Every time a farmer stocks or re-stocks his farm he realizes the existential horror of his predicament: the available genetic information is irrelevant and incomplete in its most crucial practical aspects; doing nothing about genetics is also taking action; the appropriate emotions for the practical person are anguish and dread.
When a new agricultural technology is introduced everyone involved can be considered either a beneficiary, a bystander or a victim. The immediate beneficiaries are easy to identify. Professional geneticists (some of them) will benefit from being the heroes of the technology and so will their research sponsors. The owners of the technology when it is successfully commercialized will also benefit. The fish-eating public will, eventually, be able to buy fish at a lower price.
Some farmers - the early adopter farmers - will also obtain a competitive commercial advantage which benefits them in the short term. The same competition, however, victimizes follow-on farmers in the short term. Simple economic theory predicts that farm-gate prices will go down, production will be up and farmers will become increasingly dependent on technology over which they have no control, just as in modern terrestrial agriculture (Allen, 1984; Kloppenburg, 1988; Weller, 1999). The owners of the technology and the fish-eating public will be sharing the benefits of the higher productivity permitted by the new technology and farmers will be in the same cost-price squeeze as they were before - essentially, bystanders.
If a new strain of fish or shellfish is available to all producers, market competition occurs and a new equilibrium price is reached at the new and lower production cost which, however, now includes whatever extra fees the producers have to pay for the new strain. It will of course benefit the technology developers to make their technology universally available – for a price - and not restrict it to a few producers. The benefits of the increased production efficiency accrue to the public, which may pay less for fish, and to the sellers of the technology. Competition for market share again requires producers to reduce their price and profits to the lowest tolerable level.
The above reasoning leads to the conclusion that farmers who want to benefit from purveyors of advanced technology should try to become early adopters and possibly insist on some sort of exclusive franchise arrangement to protect their competitive advantage as long as possible. The farmer should also attempt to obtain sole or part ownership of the technology in order to continue benefiting as bioeconomic equilibrium is approached. The developers of the technology will be anxious to attract early adopters for promotional reasons and the leverage this gives the farmer might be translated into franchises or ownership.
It should be emphasized that there is a divergence of interest between the developers of the technology and the farmers who use it. The former group wishes to maximise the spread of the new technology, for reasons of professional prestige (including institutional prestige in the case of universities, governments and international development agencies) as well as commercial gain.
The dilemma of aquaculture genetics companies
James (2000) recently distinguished between three types of genomics companies: product providers, information providers and technology providers. Although he wrote about companies that are working on human health issues, his analysis applies equally well to genetics in aquaculture. Companies in these three areas are now racing for primacy and moving into each other’s commercial strategy space. The question which interests Mr. James is how to invest money. The question which interests aquaculturists is how to bet the future of the fish farm, since a bet on genetics must be made.
If we apply James’s analysis to aquaculture genetics we conclude that companies which provide proprietary products like vaccines or genetically improved broodstock and fingerlings can potentially make the highest profit but also experience the highest risk, in particular the risk that someone else will develop a product which is cheaper or more effective. Purveyors of aquaculture genetic information about genomic sequences, markers and maps are mostly but not entirely in the public sector. The opportunity to generate value from proprietary information about QTLs, pathogens and broodstock genotypeenvironment interaction in aquaculture is not being ignored, however. The commercial risk to information suppliers is that their proprietary information will become ‘commoditised’ and freely available. Some people are even making a moral crusade out of the public right to raw genetic data. Spider Robinson neatly summed it up in the Toronto Globe & Mail on 18 March, 2000: “It’s as though an explorer took the first photo of a zebra - then claimed ownership of zebras, the concept of stripedness, and anything else substantially zebraic in nature”.
Both in human genomics and in aquaculture genetics there are companies that develop technology for use by other companies e.g. for on-farm broodstock improvement. (My own consulting company falls into this category.) James notes that such companies “though in some ways offering the lowest risk for investors, are always in danger of becoming generic or outdated as new ways for tackling a problem are developed.”
Given the entirely rational preference that farmers have for technologies over which they have sole ownership, professional geneticists could usefully focus more effort on developing high- as well as lowtechnology procedures that can be applied on a small scale. Farmer-breeders would then have more scientific support and information when choosing how to act at the farm level. They might then feel more comfortable in their existential dilemma where any procedure for choosing breeders, even random choice, has genetic consequences. Such procedures would enable individuals to develop proprietary breeds on their own farms and should speed up the application of modern genetics to aquaculture.
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Author: ROGER W. DOYLE
Genetic Computation Limited, Halifax, Nova Scotia, Canada