In situ Conservation Methodology for Farm Animals
T. Furukawa1, H. Takeda2, M. Satoh1, K. Ishii1 and C. Hicks1
1 National Institute of Animal Industry, PO Box 5, Norindanchi, Tsukuba, 305-0901, Japan
2 National Institute of Agrobiological Resources, Kannondai, Tsukuba, 305-8602, Japan
There are three major methods used in conservation of farm animal genetic resources (Hansen, 1992). The first involves conservation of living ova, embryo, semen or somatic cell stored cryogenically in liquid nitrogen. The second encompasses preservation of genetic information in form of DNA, stored in frozen samples of blood or other animal tissue or as DNA segments. The third involves conservation of living population, i.e. in situ conservation.
Hansen (1992) pointed out that there is no single method of preservation which is optimal for all situations. However, in situ conservation has a number of advantages, and may be the only option available in some instances. In situ conservation is very flexible in its application and allows for the development and utilization of breeds (Weiner, 1989). However, because of limited facilities and budget constraints, in situ conservation may be restricted to a small population. The genetic properties in a small population change rapidly as generations advance causing two problems namely, loss of genetic peculiarities and a reduction in genetic variability. It is therefore imperative to use a sustainable conservation program like in situ that maintain genetic peculiarities and genetic variability of a population.
Genetic peculiarities of a breed usually do not change if the population is kept as a pure breed. This problem becomes a matter of concern when crossbreeding is use to in order to restore genetic variability. Therefore, the most important problem in considering in situ conservation is how to keep genetic variability within the population while maintaining genetic peculiarities without reducing allelic or genotype frequencies. Discussion in this paper will focus on random drift, evaluation of genetic variability and methods for keeping genetic variability in farm animals.
1. Random drift and reduction of genetic variability
An offspring inherits one allele from both parents at each locus. It is, however, at random that it inherits an allele from a pair of alleles from each parent. That means, the number of offspring which inherit a certain allele of an individual parent could be larger or smaller by chance, even if each individual has a constant number of offspring. For example, one allele of the pair will fail to be transmitted to the next generation with the probability of 0.25, if the individual has 3 offspring. The range of the probability would be wider if the variation in the number of offspring is taken into account. That is taking into account changes in allele or genotype frequencies. The phenomenon involving changes in allele frequencies by chance is called "random drift".
The influence of random drift is little in a large population. But it causes a severe reduction in genetic variability in a small population. For example, if we assume a population consisting of four individuals and with two types of alleles in the same number, the probability that the next generation will lose one type of allele is 1/128. This may not be considered to be so severe. However, this probability reaches 1/2 after only nine generations. Moreover, considering that there are many loci, we can safely say that many types of allele are lost in a small population after a few generations. A reduction in genetic variability causes the following problems:
1) Increase of homozygous loci
As the genetic variability decreases, the proportion of the homozygous loci in an individual becomes larger. It means the appearance of homozygous recessive genes with undesired effects, loss of dominant effects, and it results in inbreeding depression which affects viability, adaptability and reproductivity. Inbreeding depression will cause a decrease in population size and may lead to extinction.
2) Homogeneity of the population
As the genetic variability decreases, the genetic properties of the individuals in the population become more homogeneous causing uniformity in the population. It means that most individuals are likely to be sensitive to the same kind of disease or environment. So, if they become homogeneous and are faced with the undesirable disease or environment, the risk of extermination may increase. The homogeneity of the population makes it difficult to show efficient selection response that is required to make genetic improvement of the population viable.
3) Loss of the useful genes
Wild or local breeds probably have many useful alleles which are rare in other breeds, even though many of them are not recognized. The reduction of genetic variability increases the probability that they may be lost.
2. Evaluation of genetic diversity
The first step in maintaining genetic diversity is to evaluate and establish the level of genetic diversity in the population in question. Discussion in the following sections will therefore focus on the methods for evaluating ideal genetic diversity of a population, some procedures popular in population genetics and some practical simple methods for evaluating genetic diversity.
1) Gene diversity or average heterozygosity
The gene diversity or the average heterozygosity is the best index of the genetic variability of a population (Nei, 1987). In a random mating population, if a frequency of allele i of one locus is xi, the heterozygosity (h) of this locus is calculated using the sum of squares of frequencies in all alleles as shown in the following equation:
h = 1 – Sxi2. (1)
The average heterozygosity of a population is defined as the average over heterozygosities of all loci. Since we cannot know the genotypes of every locus in all the individuals, this method is thought as the concept or the ideal value of genetic diversity to be estimated. Without the knowledge of the genotypes of each individual, the best way to keep genetic diversity may be by keeping the alleles derived from different alleles in the first generation as many as possible. The methods for evaluating the possibility that a pair of alleles is identical by descent are discussed in the subsequent sections.
2) Effective population size
In order to illustrate the random drift, the idealized population was proposed (Falconer and Mackay, 1996). There is one large base population under random mating and a large number of subpopulation subdivided from the base population. The subpopulations are referred to as lines. The base population has infinite size and each line has size N. The idealized population is assumed as follows: (1) mating is restricted within the subpopulation without migration, (2) no overlapping generation, (3) the number of breeding individuals in each line is the same for all lines and in all generations, (4) mating is random within each line, including self-fertilization, (5) no selection, (6) no mutation. Under the assumptions of this idealized population, the basic theory of population genetics was developed. Unfortunately the actual animal population cannot satisfy the above conditions. Therefore, we have to convert the population size to the size of the idealized population showing an equivalent degree of random drift. This is the effective number of breeding individuals, or the effective population size, Ne. The effective population size can be derived from the actual number as follows.
- With self-fertilization excluded,
Ne = N + 1/2. (approx.) (2)
- With sib-mating also excluded,
Ne = N + 2. (approx.) (3)
- With different number of males and females, N = Nm + Nf, where Nm and Nf are the number of males and females respectively,
1 / Ne = 1 / 4Nm + 1 / 4Nf. (approx.) (4)
- With unequal numbers in successive generations,
1 / Ne = (1/N1 + 1/N2 + ... + 1/Nt) / t. (approx.) (5)
- With non-random distribution of family size (Wright , 1938),
Ne = (4N - 2) / (Vk + 2) (approx.) (6)
where, Vk is the variance of family size.
- With different variance of family size by sex (Hill, 1972),
1 / Ne = [2 + Vkmm + 2(Nm/Nf) Cov(kmm, kmf) + (Nm/Nf)2 Vkmf] / 16Nm
+ [2 + Vkff + 2(Nm/Nf) Cov(kfm, kff) + (Nf/Nm)2 Vkfm] / 16Nf (7)
where Vksm and Vksf are the respective variances of male and female progeny contributed by a parent of sex s, Cov(ksm, ksf) are the covariances of numbers of male and female progeny, respectively, contributed by a parent of sex s. The larger number of population size makes it easier to maintain genetic diversity in the population than a smaller one.
3) Inbreeding coefficient
The inbreeding coefficient is the probability that the two genes at any locus in an individual are identical by descent, under the condition that the two genes of parents are randomly transferred to progenies with the probability of 1/2. The inbreeding coefficient is not the true probability of homozygosity because the probability is biased due to selection, the probability refers only to a distinct generation, the probability of homozygosity without identical by descent i.e. identical in state is not considered and the possibility of mutation is neglected. But, the inbreeding coefficient is also a good measure of homozygosity. The rate of inbreeding (DF) in an idealized population is,
DF = 1 / 2N. (8)
The expected inbreeding coefficient of individuals in the tth generation is therefore,
Ft = DF + (1 - DF) Ft-1
= 1 - (1 - DF)t. (9)
The general formula of the inbreeding coefficient of an individual with pedigree is
Fx = S(1/2)n (1+FA) (10)
where n is the number of individuals in any path of relationship counting the parents of X, the common ancestor, and all individuals in the path connecting parents to common ancestor; summation is over all paths of relationship; FA is the inbreeding coefficient of a common ancestor (Falconer and Mackay, 1996). The inbreeding coefficient is also an important indicator of inbreeding depression. Therefore, preventing an increase in the level of inbreeding coefficient using in situ conservation is important aspect in maintaining genetic diversity. Inbreeding coefficient can be computed by the method of coancestry as described below.
The coancestry of two individuals is the probability that two gametes taken randomly, one from each, carry alleles that are identical by descent. This value is identical with the inbreeding coefficient of their offspring. Consider individual X, its parents P and Q, and grandparents A, B, C, and D. The coancestry f is under the following rules:
fPQ = (fAC + fAD + fBC + fBD) / 4 (11)
FX = fPQ (12)
fPC = (fAC + fAD) / 2 (13)
fXX = (1 + FX) / 2 (14)
The coancestry is important because it indicates the inbreeding coefficient of the next generation. Furthermore, coancestry has a high correlation with the gene diversity, so it is a good index for measuring genetic diversity using in situ conservation (Furukawa et al., 1996).
5) Coefficient of relationship
The coefficient of relationship shows the correlation of breeding values between two individuals. The coefficient of relationship of relatives in a random mating population is about twice their coancestry. The coefficient of relationship can be computed from the following formula,
R = 2fPQ / [(1 + FP)(1 + FQ)]1/2. (15)
6) Genetic conservation index
The objective of a conservation program is to retain the full range of alleles possessed by the base population. The ideal animal would receive equal contribution from all the founder ancestors in the population. From this view point the value of an animal can be determined by calculating the effective number of founders in its pedigree using the following genetic conservation index, GCI (Alderson, 1992).
GCI = 1 / SPi2 (16)
where Pi is the proportion of genes of founder animal i in the pedigree.
The GCI can be used either by individual breeders as an aid to the selection of a herd sire, or within an overall breed policy to formulate a group breeding program. However, the index has limitations such as not accounting for any concentration of breeding to non-founder animals in subsequent generations in a pedigree and is inapplicable without pedigree records (Alderson, 1992).
7) Coefficient of genetic contributory variation
Pi in formula (16) is the genetic contributory of founder animal i in the subsequent generations. A similar idea of GCI was applied to population level. That is maintaining subsequent populations while keeping the genetic structure in the base population. In the ideal genetic structure, every founder animal would keep the same contribution to subsequent populations. In order to indicate the bias between an actual genetic contributory and an ideal genetic contributory, the coefficient of genetic contributory variation, CGCV was proposed by Abe and Furukawa (1982, mimeograph).
CGCV = 2Nm SPmi2 + 2Nf SPfj2 – 1 (17)
where Nm and Nf are the respective numbers of founders in male and female, Pmi and Pfj are the genetic contributory of male founder i and female founder j, respectively. CGCV is used to maintain the designated pig strains in Japan by the Japanese Pig Registration Association (Obata et al., 1994). CGCV shows high correlation with the true genetic diversity in the initial generations, however the correlation becomes lower in the later generations (Furukawa et al., 1996).
The methods of evaluating genetic diversity discussed above have different characteristics. The gene diversity of all loci cannot be estimated actually, but if many DNA markers are genotyped the average heterozygosity could be used as the index of the genetic diversity. The effective population size, the inbreeding coefficient, the coancestry and the coefficient of relationship have been popular in population genetics. The effective population size is useful to compare the structures of different population. The inbreeding coefficient indicates the degree of gene fixation. The coancestry includes both parameters of inbreeding and relationship, so the coefficient of relationship is less useful. GCI and CGCV are useful in practice because they are easy to calculate in a pedigree population. However, their application to evaluation of genetic diversity is limited to initial generations.
3. Maintaining of genetic diversity
In order to maintain genetic diversity in a population, the effect of random drift should be suppressed and the probability of gene fixation should be minimized. For this objective, the simplest method is not to allow the replacement of generation. The methodology will be described in the paper concerning ex situ conservation. The effect of random drift and the probability of gene fixation are lower in a larger population, but the number of animals kept for in situ conservation is limited. Here some procedures to retain the genetic diversity with an infinite population size are discussed.
1) Mating to avoid inbreeding
Mating between relatives such as sib mating produces progenies with high coefficient of inbreeding. Therefore mating to avoid relatives can suppress an increase of inbreeding coefficient and can prevent harmful effects of inbreeding. The effective population size avoiding sib mating was described above as follows,
Ne = N + 2.
If the population size is not large,
Ne = N + 1 (18)
should be approximated (Wang, 1995). However, as understood from formula (18), in case that population size is large enough, mating to avoid relatives does not affect effective population size.
To suppress the increase in inbreeding coefficient in a population, "maximum avoidance of inbreeding" mating was proposed by Wright (1921) where matings between most unrelated individuals are systematically carried out in every generation. The rate of inbreeding under the mating with maximum avoidance of inbreeding is predicted approximately as follows,
DF = 1 / 4N. (19)
This is a half of the rate of inbreeding with random mating. However, it becomes difficult to keep DF small in the later generations.
Later, Kimura and Crow (1963) showed that there were some mating systems that can reduce inbreeding coefficient in the later generations. However, these methods produce higher inbreeding coefficient in initial generations than mating with maximum avoidance of inbreeding. The circular mating is one example of them. The rate of inbreeding in a large population under circular mating is approximated as follows,
DF = p2 / 4(Ne + 2)2. (20)
2) Group mating
In the in situ conservation program, since the number of animals kept in one place is usually limited, the population is sometimes maintained with divided subpopulations. In this case, it is difficult to carry out random mating over all subpopulations and it is effective to change males among the subpopulations instead of overall random mating (Yamada, 1980). Maintenance of animals in different locations has the additional merit of reducing the risk of accidental loss of the population (Nomura and Yonezawa, 1996).
An example of a group mating scheme based on circular subpopulation mating was proposed by Kimura and Crow (1963). Under this mating system, subpopulations are located circular and reproductive males in subpopulations are provided systematically from the neighboring subpopulations. The rate of inbreeding in the overall population with a large number of subpopulations is approximated as follows,
DF = p2 / 16(k/2 + Ne + 1)2 (21)
where k is a number of subpopulations, Ne is the effective population size of subpopulation.
Robertson (1964) generalized that the mating together of close relatives within the population leads to greater initial inbreeding but a lower final rate of approach to the limit. Recently, Nomura and Yonezawa (1996) theoretically compared some circular group mating systems where the cyclical system may restrict the rate of inbreeding in initial generations more than the circular subpopulation mating.
3) Uniformity of the family size
One of the most efficient techniques to keep genetic variability is to make the family size as equal as possible. It may be easy to imagine that the extinction probability of a certain allele is less in the case that every reproductive animal produces two progenies for the next generation than in the other case that one reproductive animal produce ten progenies and the others produce non. It is usual in a population of domestic animals that males are extremely less than females, but the difference in the number of males and females is not desirable for the small population of the genetic resources, since it means the extreme difference in the number of progenies. When the number of population is fixed, we can minimize the reduction of genetic diversity by equalizing the number of progeny from each individual.
The effect of uniformalizing of family size can be predicted from formula (6). If the individuals are chosen equally from all families, there is no variation in family size, and Vk=0. Then the effective population size is
Ne = 2N – 1 (22)
which is about twice the size of a population bred from the equal numbers of males and females. If the numbers are not equal in each sex, the variance of family size within sex as defined in formula (7) can be reduced to zero by choosing one male from each sire's progeny and one female from each dam's progeny as parents for the next generation. The rate of inbreeding is given by the following formula (Gowe et al., 1959).
1 / Ne = 3 / 32Nm + 1 / 32Nf (23)
The effect of simultaneously uniformalizing of family size and maximum avoidance of inbreeding was investigated by Robison and Bray (1965). If both procedures are carried out simultaneously, the inbreeding coefficient in the initial generations remain lower but the population with only uniformalizing family size could keep lower inbreeding coefficient finally.
4) Use of information from genetic markers
The degree of inbreeding is estimated from pedigree information based on the probability that the alleles of parents are transmitted to the next generation with the probability of 1/2, since we cannot know which of the pair have been transmitted. Recent developments in genome analysis provide linkage maps of a lot of genetic markers like microsatellite for many livestock species. When the genotypes of parents and their progenies are distinct, we can know which allele of the parents has been transmitted to the progenies. By using this information combined with the pedigree information, we can estimate the degree of inbreeding in progenies more exactly (Takeda et al., 1997).
The correlation between the average heterozygosity of genetic markers and the realized genetic diversity is expected to be constant over generations. If we can use a lot of genetic markers to calculate the average heterozygosity it is useful as the index of the genetic diversity. And this information would assist to select suitable mating pairs to retain the genetic diversity in the population (Takeda et al., 1998).
In order to maintain genetic diversity using in situ conservation program, it is better to maintain a large number of animals. However, maintaining a large number of animals is costly, in view of this, maintaining a relatively smaller number under a well managed in situ conservation program would be more economically efficient. The most effective way of conserving genetic resources is through economical utilization of the animals in the production system. However, improved breeds from Western countries tend to outperform native breeds in developing countries in terms of productivity, this makes promotion of utilization of pure native breeds difficult. This problem may be overcome by crossbreeding native breeds with improved breeds as shown by Furukawa et al. (1998).
In situ conservation is the easiest way from methodological viewpoint and can be applied to any species of livestock. On the other hand, ex situ preservation is a technique that allows keeping genetic diversity of the population permanently. However, ex situ preservation of germplasm can be adapted and used to supplement in situ conservation program of animal genetic resources. Cryopreservation of males in the base population could help recovering of the genetic diversity of animal genetic resources. Therefore, in conclusion, it is suggested that the efficient combination of in situ and ex situ conservation programs should be considered.
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