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18. Breed Utilisation and Crossbreeding

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18. Breed Utilisation and Crossbreeding 18. Breed Utilisation and Crossbreeding Brian Kinghorn Learning objectives On completion of this topic you should: • Understand the issues that affect which is the best crossing system to adopt • Have a good feel for what makes dominance good and epistasis bad in crossing systems Key terms and concepts Dominance gain is good, Epistatic loss is bad, These two things can be difficult to estimate together as they are largely confounded, Crossbreeding decisions can be integrated with other issues. Introduction to the topic Selection and crossbreeding are two key tools for animal breeders. This topic gives sufficient theoretical background on crossbreeding to show how we can exploit it. It also introduces us to integrating crossbreeding with other issues in animal breeding. 18.1 Review of the mechanisms driving heterosis Figure 18.1 illustrates how crossbreeding can lead to dominance gain and epistatic loss. Figure 18.1 Mixing genes from different breeds leads to dominance gain and epistatic loss. Mix genes from different breeds (A and B) in one individual. DOMINANCE Where the individual's parents come from two different breeds, the individual will carry a wider range of genes, sampled from two breeds rather than just one. It is thought that this better equips the individual to perform well, especially under a varying or stressful environment. We would thus expect dominance to be a positive effect, and there is much evidence to support this. GENE422/522 Genetic Evaluation and Breeding - 18 - 1 ©2009 The Australian Wool Education Trust licensee for educational activities University of New England EPISTASIS When we cross breeds, genes find themselves having to interact or 'cooperate' with other genes which they are not used to. The crossbred animal may thus be ‘out of harmony’ with itself, and we predict that epistasis, if important, is a negative effect. A note on the dominance model The example on this page illustrates that "Breed-of-Origin heterozygosity" is proportional to Allelic heterozygosity. Genotype: A1A1 A1A2 A2A2 Frequency: p² 2pq q² Value: +a d -a Breed X px=0.3 qx=0.7 px=0.3 .09 .21 a d +a d -a d Breed X = -0.4a + 0.42d qx=0.7 .21 .49 qy= Breed Y py=0.9 0.1 Breed Y = 0.8a + 0.18d py=0.9 .81 .0 9 Parental Mean: P = 0.2a + 0.3d qy=0.1 .09 .0 1 F1 Cross px=0.3 qx=07 F1 Cross = 0.2a + 0.66d Heterosis = .36d = d(p - p )² x y py=0.9 .27 .63 Breed-of-origin Heterozygosity =1 qy=0.1 .03 .07 F2 Cross 0.6 0.4 F2 Cross = 0.2a + 0.48d px+py = 0.6 Heterosis =.18d = ½d (px -py)² 2 .36 .24 Breed-of-origin Heterozygosity =½ qx+qy .24 .16 = 0.4 2 18 - 2 - GENE422/522 Genetic Evaluation and Breeding ©2009 The Australian Wool Education Trust licensee for educational activities University of New England 18.2 Models of epistasis You can treat the detail in section 18.2 as background reading. But please note key concepts: Epistasis and dominance are difficult to estimate together; Epistatic loss can be damaging (e.g. Figure 18.2) A knowledge of the genetic basis of heterosis is fundamental to the planning of complex crossbreeding programs. As described above, the non-additive components of merit involved are based on interaction within loci (dominance) and interaction between loci (epistasis). When considering dominance as a component of heterosis, heterozygosity with respect to breed of origin of genes is taken into account. However, epistasis can be classified in two general categories: i. interaction between single genes and the total genotype at all other loci. This is seen as a scale effect (as described by Kinghorn 1982). ii. interaction within small groups of loci whose products are interdependent in function (eg. Dickerson 1969; Kinghorn 1980). Scale effects in the expression of heterosis can be tested for in a relatively simple manner (Mather and Jinks 1977; Kinghorn 1982), but interaction within small groups of loci is the subject of a number of models, as described by Kinghorn (1980; 1982; 1987) We will concentrate on the one specific model of epistasis which has been widely used - the additive x additive model. It is also the only model which has received some experimental support over its competitors (Kinghorn 1983; 1987). The additive x additive model of epistasis The proportion of maximum (F1) dominance gain [p(D)] that is expressed is equal to the degree (0 to 1) of heterozygosity with respect to breed of origin. This is quite simple because there are only two states (homozygous and heterozygous), the relative incidence of which can be described by one parameter. However the proportion of maximum epistatic loss which is expressed [p(E)] cannot be described so simply, as there are many possible states. For 2-locus epistasis, there can be (homo-homo), (homo-hetero), (hetero-homo), (hetero-hetero), and other combinations when more than two breeds are involved. For epistatic loss we should have a biologically sensible model of how genes interact. Figure 18.2 illustrates the most used model, additive x additive epistatic interaction. GENE422/522 Genetic Evaluation and Breeding - 18 - 3 ©2009 The Australian Wool Education Trust licensee for educational activities University of New England Figure 18.2 A biological interpretation of additive x additive epistatic interaction between 2 loci. K and L represent alleles derived from different breeds. In this illustration both loci shown are heterozygous for breed of origin. Products from the two loci combine to form dimers. Where coadaptation has taken place within breeds, products derived from the same breed are more compatible than products derived from different breeds. For the genotype configuration shown, half the dimers are expected to involve a difference in breed of origin of component gene products, such that only half of the favourable epistatic effect is expressed. Source: Kinghorn (1987). Figure 18.2 shows two loci randomly sampled from, in this case, an F1 cross between breeds K and L. We assume that merit is related directly to the proportion of dimer enzymes which are 'harmonised'. If this biological model were an accurate reflection of all 2-locus interactions, then p(Eaa) = ½ for an F1 cross, as half the dimers are 'harmonised'. In general, the coefficient for a given configuration is the probability that two alleles chosen randomly, one from each locus, are of different breed-of-origin. Table 18.1 lists some coefficients of D and Eaa, and Figure 18.3 illustrates the relationships between them. Table 18.1 Coefficients of D and Eaa under various mating systems. GENOTYPE p(D) p(Eaa) Purebred 0 0 F1 Cross 1 ½ Ax(BxC) 1 5/8 Ax(AxB) ½ 3/8 (AxB)x(CxD) 1 3/4 n breed synthetic (n-1)/n (n-1)/n n breed rotation (2n-2)/(2n-1) 2(2n-2)/3(2n-1) 18 - 4 - GENE422/522 Genetic Evaluation and Breeding ©2009 The Australian Wool Education Trust licensee for educational activities University of New England Figure 18.3 The relationship between the coefficients of dominance (p(D)) and epistatic loss (p(Eaa)) under various mating systems. p(Eaa) The solid line relates to coefficients for repeated backcrossing involving two breeds, one parent always being purebred. Here p(Eaa) = p(D) - p(D)²/2. For these mating systems alone, the coefficient of dominance describes about 92% of the variation in the coefficient of epistatic loss, and vice versa. Rotational crosses are at equilibrium for the number of breeds indicated. The slope for synthetic or “composite” breeds covers both balanced and unbalanced breed mixtures, but numbers given indicate the number of breeds involved for balanced synthetics. It can be seen that there is a strong co-linearity between p(D) and p(Eaa). This means that fitting p(Eaa) in an analysis of crossbred data tends to explain little more variation if p(D) has already been fitted. This observation has been taken to mean that epistasis is of little importance, and yet such a judgment cannot be made in this way, as the argument works just as well the other way around! Evidence for epistatic interaction Evidence for epistatic loss has been found has been found in chickens, sheep and notably dairy cattle under tropical conditions. Sheridan (1981) gave a comprehensive review of this area. Recombination loss [This section is for clarification alone, not to be examined.] Dickerson (1969) used the term 'Recombination loss', r, to describe loss due to epistatic effects. This is related to Eaa and d as follows (Kinghorn, 1983): p(Eaa) = (p(r) + p(d))/2 Analyses that fit recombination loss are equivalent to those that additive x additive epistasis. This is because these analyses also fit the parameter h (heterosis, see Dickerson, 1969), which in fact involves both full dominance and some epistatic effects. Coefficients of h and D are always identical. Koch et al. (1985) accommodate a range of models in their analysis, including a modified version of recombination loss (Dickerson, 1973), all of these being equivalent to additive x additive epistasis. GENE422/522 Genetic Evaluation and Breeding - 18 - 5 ©2009 The Australian Wool Education Trust licensee for educational activities University of New England 18.3 Evaluating breed resources Genetic evaluation of breed resources is relatively simple wherever good estimates of mean performance are available for the environment and production systems of interest. This is because the effects involved can be measured with high accuracy from much data, and can be treated as fixed effects. These effects constitute an inventory of genetic resources, and the economic value of each breed genotype can be estimated by simply multiplying predicted performance for each trait by its corresponding economic weight, and summing across traits.
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