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EFFICIENCY AND LIMITATIONS OF ISOZYME STUDIES IN FOREST TREE GENETICS1

Gunter M. Rothe
Institut für Allgemeine Botanik, Fachbereich Biologie
Johannes Gutenberg-Universität
Saarstr. 21, 6500 Mainz, Germany

1. INTRODUCTION

Studies on the genetics of forest trees have been performed using mainly three categories of simply inherited traits: morphological markers, monoterpene variants and isozymes.

Morphological traits are easy to assess, but their use in genetic studies is limited, since phenotypic morphological characteristics are generally controlled by several genes, and quantitative factors are under strong environmental influence. Thus, contributions of individual genes cannot be identified, and specific genetic differences among individuals are not detectable.

In gymnosperms, single genes are controlling the level of a few monoterpenes. However, genetic interpretation of monoterpene patterns is complicated and analysis of large numbers of samples by gas-liquid chromatography is expensive and time consuming.

Compared to the above, isozymes are relatively easy to handle. Their use was introduced into forest tree genetics some 15 years ago and is now widely applied, based on the hypothesis that the isozymes are the direct products of specific allelic genes. Once identified, statistical methods are available to study their distribution (frequencies) within and among populations.

2. ALLOZYMES AS GENE MARKERS

Diploid, sexually reproducing organisms receive one complete set of chromosomes from each parent. Accordingly, they have each gene in duplicate; the homologous genes are called alleles. If more than one allele occurs at the locus of a structural gene, the varying enzyme products produced by them can either appear in a single diploid (heterozygotic) organism, or in different (homozygotic) members of a species.

The number of alleles at a given gene locus depends on the species and on the locus itself. Genes are characterized as polymorphic if they comprise two or more alleles. Invariant (monomorphic) genes are not suitable for genetic studies.

To interprete isozyme2 patterns correctly, their sub-unit composition (number of polypeptides forming the complete enzyme) must be known (Fig. 1).

The genes coding for allozymes are identified by an abbreviation of the enzyme name, e.g. “Aat” for aspartate amino transferase. If a gene comprises more than one locus (precisely defined site on the DNA molecule), then these loci are indicated by a capital letter (or a number) and linked to the gene name as a suffix, e.g. Aat-A or Aat-B (or Aat-1 or Aat-2). The corresponding alleles may be indicated by consecutive numbers such as Aat-Al, Aat-A2 etc. (or Aat-1, Aat-12) (Fig. 2, 3; Tab. 1, 2).

Allozymes can be used in genetic studies if the following conditions are fulfilled:

  1. the genotype is phenotypically expressed through given enzyme patterns, which can be observed in the laboratory. A prerequisite for this is that the enzyme forms of interest segregate in a Mendelian pattern (as shown in Fig. 1); and

  2. at least one locus per enzyme is polymorphic.

    Specific genotypes can be identified using:

  3. examination of progeny resulting from controlled crossings;

  4. comparative studies of haploid and diploid tissues of an individual (haploid endosperm and diploid embryo of gymnosperms, or haploid pollen and diploid embryo of angiosperms); or

  5. by applying Hardy-Weinberg's law in theoretical models (Rothe 1988).

2.2 TOOLS TO DETECT ISOZYMES

Identification of isozymes is based on their high substrate specificity and varying electrophoretic mobilities. If two allelic variants of an enzyme differ in the number of charged amino acids, then their different net charges can be used to separate them by electrophoresis. The primary structure (peptide backbone) of these enzymes is encoded in the two homologous strands of the DNA in the individual and, accordingly, allelic genes can be identified by differently charged allozymes. Unfortunately, however, two thirds of the proteinogeneous amino acids are uncharged, reducing the possibility for identification of existing allelic enzyme variants to less than 30 % of the total number present. However, for those variants which do have a charge, electrophoretic methods are relatively simple to carry out in practice. It is sufficient to place crude cell or tissue extracts on some type of electrophoretic separation medium such as starch gel-, cellogelR- or polyacrylamide gel; and subsequently stain the gel using a staining agent which permits only a specific enzyme and its multiple molecular forms to become visible, while leaving all other separated proteins (and enzymes) unstained (Rothe & Maurer 1986, Kephart 1990). Finally the stained enzyme forms are counted and the estimated frequencies are used for further genetic calculations (see Section (2) below; cf. also Fig. 2, 3).

3 APPLICATION OF ALLOZYME RESEARCH

3.1 IDENTIFICATION OF SEEDLOTS

Differences in allozyme frequencies can be used to determine the origin of a seedlot or of seedlings originating from a seed orchard or from different populations of a given tree species (Adams 1983 and Bergmann 1975a. See also e.g. Houston, 1978, for an example of identification of six geographically different seed sources of Quercus rubra through utilization of peroxidases). Particularly in Central Europe, however, identification of provenances of norway spruce (Picea abies) is difficult, since a large number of provenances have been introduced and their true origin is unknown (Bergmann 1975a).

For identification of spruce provenances, at least 7 seeds from each of 200 trees must be analyzed for determining allozyme frequencies (Adams 1983, Bergmann 1975a). According to Bergmann, (1975a), equal allozyme frequencies were found in seeds whether they originated from individual trees of a certain population, or from a mixture of seeds of that particular population. Examination of 100 diploid genome probes collected from a seed orchard (or 50 haploid endosperms of a coniferous species) allows detection of alleles occuring at a frequency of 0.03 or higher with a probability of 95 % (Adams 1983). However, if serious pollen contamination from non-orchard sources is suspected and isozyme analysis is performed to prove it, it is recommended to double the above sample to 100 haploid endosperms of seeds (Adams 1983).

In many countries forests have been divided geographically, topographically and ecologically into seed zones. Each zone is presumed to represent a relatively homogeneous environmental unit, within which the genotypes, in principle, are adapted for use in any other part within the same zone, while seeds from outside the zone are expected to be less well adapted (Adams 1983). Restricting seed used for reforestation to those collected from within selected seed zones, is thus expected to ensure that seed will be properly adapted to the conditions at the plantation site. The identity of seedlots can be verified following their collection by using isozyme techniques. However, if the genetic diversity between populations is small (do < 0.10)3, this will constrain the use of isozyme studies in the identification of seedlots from various seed zones (Adams 1983).

3.2 IDENTIFICATION OF CLONES

Isozymes can also be utilized to identify closely related individual trees, or clones (Adams 1983). Isozyme studies may be performed on winter buds, leaves or current year needles. For clone identification it is sufficient to compare phenotypic isozyme patterns, even without knowledge of their genetic base (Cheliak & Pitel 1984 and Bergmann 1987). In one study, analysis of six to seven variable enzyme systems, comprising 10 to 20 different loci, enabled certification of 50 to 100 clones of a norway spruce (Picea abies) multi-clone variety (See Table 3). This application of isozyme studies is potentially of great importance as multi-clone varieties have been developed in some countries as part of a clonal forestry strategy to help avoid reduction of genetic diversity in future generations of artificial populations (Rothe 1990).

3.3 DETERMINATION OF THE RELIABILITY OF CONTROLLED CROSSING AND LEVELS OF SELF FERTILIZATION

The reliability of controlled crossing can be assessed by examinating isozyme patterns in seeds resulting from such crosses, comparing the results with those theoretically expected based on the genotypes of the parents (Adams 1983). A controlled pollination can be considered a failure, if the seeds in one out of four samples (or, one out of two for coniferous species), contain alleles not present in either of the supposed parents (Adams 1983). Experiments carried out with douglas-fir (Pseudotsuga menziesii) showed that most failures in controlled crosses are due to pollen contamination by foreign pollen (Adams 1983).

Furthermore, isozyme gene markers can be used to identify self-fertilizing trees in seed orchards (Müller 1976, Moran; Bell & Matheson 1980 and Shen; Rudin & Lindgren 1981). Since self-fertilization affects the whole genome equally, it can be revealed through investigation of one single polymorphic gene locus. In norway spruce (Picea abies), at the leucine amino-peptidase B-locus (Lap-B), self-fertilization occured in two out of four genotypes. The rate of self-fertilization was estimated to be 15 % (Müller 1976). Since the genetic diversity of seeds of self-fertilizing trees is reduced, it is generally desirable to identify and eliminate such self-fertilizing individuals from seed orchards (Shaw & Allard 1981).

3.4 IDENTIFICATION OF TREE SPECIES

Variation in allozyme patterns can be utilized to distinguish different tree species or hybrids. Seeds of two larch species, Larix decidua and Larix kaempferi were separated by analysis of the mobility of shikimate dehydrogenase enzymes. In L. kaempferi, the enzyme migrated faster to the anode than in L. decidua. In hybrids of both parental species, both enzyme variants could be indentified (Bergmann 1975a).

Oaks (Quercus spp.) comprise a taxonomically complex group. More than 50 tree-like oak-species occur in USA, and the total number of species in this genus is more than 300. Some of these possess unique and easily identifiable morphological and anatomical traits, however several are difficult to identify and differentiate from each other. Taxonomic identification is further complicated by apparent hybridization among a number of species. Over 60 hybrids have been reported in the USA alone. (Fernald & Gray 1950).

Investigations of buds and acorn cotyledon tissue originating from various seed sources of northern red oak (Quercus rubra L.), black oak (Q. velutina Lam.), white oak (Q. alba L.), swamp white oak (Q. bicolor Willd), bur oak (Q. macrocarpa Michx.) and chinkapin oak (Q. muehlenbergii Engelm.), showed that most isozyme bands of leucine aminopeptidase, alcohol dehydrogenase, acid phosphatase and aspartate amino transferase were common to two or more of these species (Tobolski 1978). This similarity in isozyme patterns is likely to be a reflection of their close taxonomic (and thus genetic) relationship. However, individuals of some species exhibited distinctive genotypes in the analysis; these could also be readily distinguished through differing phenotypes (Tobolski 1978).

The species Quercus petraea and Q. robur, could be classified according to their peroxidase patterns (Olsson 1975). Some populations of Q. petraea showed evidence of introgression with Q. robur.

3.5 CHARACTERISTICS OF FOREST TREE POPULATIONS

In addition to the above uses, the following genetic characteristics of populations have been studied utilizing allozyme frequencies:

  1. the level of genetic variability within a population;

  2. the variation between populations;

  3. possible factors accounting for the observed variation;

The genetic structure of populations, reflected in inter-locus variance in allozyme studies is subject to evolutionary forces such as mutation, selection and random genetic drift. The intra-locus variance identifiable in laboratory studies depends on the sample size and gene frequencies at the locus studied (Nei & Roychoudhury 1974). The degree of heterozygosity4 (H) in forest tree populations has been found to range from 0.19 to 0.41, with the higher values being typical in conifers (Tab. 4 and 5).

Allelic variation can be defined as “the expected proportion of heterozygotes per locus per population”, as is generally marked h. Calculations of an average value for h in 10 different populations of sitka spruce (Picea sitchensis (Boug.) Carr.), an important forest tree native to the west coast of Northern America, yielded values ranging from 0.475 (glucose 6-phosphate dehydrogenase, G6pdh) to 0.001 (phosphoglucomutase, Pgm-2). This wide range in h, with values near zero, is typical for several coniferous species (Yeh & El-Kassaby 1980).

The level of genetic diversity in conifers is usually high. This is due to: (i) divergent selection for macro-geographical adaptation, (ii) balancing selection for micro-geographical differentiation, and (iii) a breeding system which facilitates gene flow within and between subpopulations. Heterosis might further promote the maintenance of genetic variability (Yeh & El-Kassaby 1980). Studies of genetic variation in ten IUFRO5 populations of sitka spruce (Picea sitchensis) showed that (i) the amount of genetic polymorphism varied considerably from locus to locus; (ii) several populations were similar in the amount and pattern of genetic variability, in regard to most of the loci studied; while (iii) some specific loci exhibited large differences between populations (Yeh & El-Kassaby 1980). Despite large geographic distances between seed sources tested, the differences in genetic constitution of sitka spruce did not increase appreciably in proportion with geographic separation.

Genetic differences between populations expose these differently to natural selection at the population level, favouring population selection (Yeh & El-Kassaby 1980). This conclusion has been confirmed for several tree species in addition to sitka spruce, like for instance Picea abies (L.)Karst. (Bergmann 1974), Pinus monticola Dougl. (Steinhoff; Joyce & Fins 1983) and Pseudotsuga menziesii (Mirb.) Franco (Yeh & O'Malley 1980). In Scandinavia, the frequencies of alleles situated at the locus for acid phosphatase-B, were more frequent in southern norway spruce populations than in northern ones (Bergmann 1978).

Generally, conifers exhibit high levels of heterozygosity. A notable exception to this rule is Pinus resinosa (Fowler & Morris 1977). One of the theories explaining the lack of variability in P. resinosa is that this lack is the result of a severe population bottleneck, which probably occured during the Pleistocene period, when the distribution of the species was reduced to small refugial populations, as a result of glaciation.

The genetic variability in deciduous trees is generally smaller than in conifers. In 17 Quercus populations, the average value of polymorphic loci was 30 %, with 2.32 alleles per polymorphic locus. Low estimates of genetic diversity between populations may indicate that a greater genetic variability resides within populations than between them (Manos & Fairbrothers 1987).

3.6 ADAPTATION OF TREES TO DIFFERENT ENVIRONMENTS

Trees are long-lived organisms, and must therefore be well-adapted to their native habitats and expected environmental fluctuations within the habitats over long periods of time. This may be accomplished either by a broad adaptation within the population, or by population-specific adaptations to specific site conditions. In norway spruce (Picea abies) and douglas-fir (Pseudotsuga menziesii), a gene locus coding for acid phosphatase was identified, which showed a significant, environmentally dependent variation. In both species, the Acp-alleles coding for single-band enzymes dominate in colder zones of the distribution range of the species, whereas the alleles coding for double-band enzymes occur more frequently in all moderate climatic zones (Bergmann 1975).

The variation between populations can be quantified by a single number, the genetic distance (do) (see e.g. Nei & Roychoudhury 1974 and Surles; Hawrick & Bongarten 1989). Genetically completely different populations are characterized by a value of do = 1, while the value is zero for identical populations. In Finnish stands of Picea abies, a complete random distribution of genes within stands has been observed using allozymes of leucine aminopeptidase, Lap; peroxidase, Pod, and esterase, Est (Tigerstedt 1973). However, for a number of other species, a correlation between genetic and geographic distances seem to occur, e.g. Camellia japonica L. (Wendel & Parks 1985), Picea abies (L) Karst. (Bergmann 1975), Pinus monticola Dougl. (Steinhoff; Joyce & Fins 1983) and Pseudotsuga menziesii (Mirb.) Franco (Yeh & O'Malley 1980). Isolation by distance may be an important factor in population differentiation of these species (cf. Perry & Knowles 1988).

3.7 IMPACT OF AIR POLLUTANTS ON THE GENETIC STRUCTURE OF FOREST TREES

Numerous data concerning genetic differentiation of trees in regard to their sensitivity to pollutants, have been reviewed by Gerhold, (1977). Statistically significant differences exist between populations of norway spruce (Picea abies) in their sensitivity to SO2. The most tolerant populations seem to be of northern high altitude origin (Tzschacksch & Weiss 1972). The average heterozygosity of individuals of spruce growing in the Harz Mountains of Germany, which were undamaged when exposed to SO2 plus O3, was larger than that of damaged individuals (Bergmann & Scholz 1987). However, SO2 -tolerant provenances of norway spruce showed lower frequencies of rare alleles occurring at the Gpdh-A1 and Mdh-C3 loci, than sub-populations which were sensitive to SO2 (Bergmann & Scholz 1987). In contrast to complex environmental variables, single air pollutants such as SO2 or O3, lead to selection towards reduced genetic diversity (Bergmann & Scholz 1987). Similar observations were made for beech (Fagus sylvatica), where the selection of resistant genotypes mainly occurred in the first (F1) generation (Müller-Starck 1985).

Two main conclusions can be drawn from investigations of the impact of air pollutants on the genetic structure of forest trees:

  1. highly heterozygotic trees seem to be better adapted to a multiplicity of simultaneously acting environmental impacts than trees with a lower degree of heterozygosity, and

  2. contamination by air pollutants cause a reduction in genetic diversity of the population. The reasons for this decrease in diversity (and hence, overall adaptability) are (1) increased levels of directional natural selection, and (2) decreasing gene flow.

The resistance of forest trees to air pollutants is assumed to be determined by pre-adaptive genes. These are highly adaptive genes, which already exist in the genome, but which are not identifiable before exposure to the toxic agent (Gregorius; Hattemer; Bergmann & Müller-Starck 1985).

Note from Editor: For further information on biotechnology in tree improvement programmes, see also article by Cheliak, W.M. & Rogers, D.L. in section (iv) of Recent Literature of Interest.

Figure 1

Schematic representation of isozyme patterns resulting in heterozygotes when the enzyme is a mono-, di-, or tetramer (containing one, two or four polypeptides) and at least two different alleles appear at the locus that codes for them. It is further presumed the sub-units combine freely and segregate according to Mendelian patterns.

Figure 2

Quercus robur L.

Figure 2

Isozyme patterns and genetic interpretation of leucine aminopeptidase found in Quercus robur. Isozymes were extracted from 35 acorn cotyledon tissues of Q robur, separated by polyacrylamide gradient gel electrophoresis and finally visualized within the gel by applying a histochemical staining method. Acorns came from a Q. robur stand in Rheinland Pfalz (Germany). A total of 13 different isozyme patterns were observed, comprising seven different isozymes. It is assumed that two different loci (Lap-A and Lap-B) code for these seven isozymes, representing four alleles at the A-locus and three alleles at the B-locus (Dankwardt and Rothe, unpubl.).

Figure 3

Quercus petraea (Matt.) Liebl.

Figure 3

Isozyme patterns observed in 35 acorn cotyledon tissues of Quercus petraea. Acorns came from a stand in Rheinland Pfalz (Germany). Compared to Q. robur (Figure 2) only five instead of 13 isozyme patterns were identified. The patterns 1,5 and 6 are similar to the patterns of the same numbers in Q. robur, but the frequencies differ. The patterns 14 and 15 were exclusively found in Q. petraea while the isozyme patterns 2– 4 and 7– 13 were typical for Q. robur. Accordingly populations of the species can be distinguished on their isozyme patterns. However, identification of individuals of both species requires further studies on isozyme systems (Dankwardt and Rothe, unpubl.).

Table 1

Enzyme gene loci and number of alleles as found in norway spruce (Picea abies (L.) Karst.) and used for genetic studies

AspartateAat-AAat-BAat-C  
aminotransferase 331 Lagercrantz 1988
444 Lundquist 1979
213 Poulsen et al. 1983
23  Muona et al. 1987
Acid phosphataseAcp-AAcp-B   
14  Bergmann 1978
7   Lunquist 1977
DiaphoraseDia-ADia-B   
21  Lagercrantz 1988
EsteraseEst-AEst-BEst-C  
332 Bergmann 1973
Glucose-6-phosphate dehydrogenaseGpdh-A    
2   Scholz & Bergmann 1984
3   Muona et al. 1987
Glutamate dehydrogenaseGdh-AGdh-B   
2   Scholz & Bergmann 1984
 2  Lundquist 1979
2   Lagercrantz 1988
Glucose-6-phosphate dehydrogenaseGpi-AGpi-B   
51  Lagercrantz 1988
     
Isocitrate dehydrogenaseIdh-AIdh-B   
22  Scholz & Bergmann 1984
31  Lagercrantz 1988
Leucine aminopeptidaseLap-ALap-B   
14  Bergmann 1973
44  Lundquist 1979
34  Poulsen et al. 1983
55  Lagercrantz 1988
Malate dehydrogenaseMdh-AMdh-BMdh-CMdh-D 
1222Poulsen et al. 1983
  4 Scholz & Bergmann 1984
?21?Lagercrantz 1988
Phosphoglucose isomerasePgi-APgi-B   
?4  Muona et al. 1987
6-Phospho-gluconate dehydrogenasePgd-APgd-BPgd-C  
243 Poulsen et al. 1983
411 Lagercrantz 1988
Phosphogluco-mutasePgm-APgm-B   
22  Poulsen et al. 1983
22  Scholz & Bergmann 1984
Superoxide dismutaseSod-ASod-B   
11  Lagercrantz 1988

Table 2

Enzyme gene loci and alleles studied in deciduous trees and utilized for genetic analyses

SpeciesEnzyme loci and number of allelesReference
Aat-Aco-Acp-Ald-Est-GdhGpdh-Idh-Lap-Mdh-Per-Pgd-Pgi-Pgm-
  
 ABCABABABAB ABABABABCABCDABCDABCABC
Alnus crispa112    2   1  1 112?     23  12 31 Bousquet et al. 1987
Alnus rugosa?22    1   1    11142    43  12    Bousquet et al. 1987
Castanea sativa            2 3          2         Fineschi 1988
Fagus sylvatica4   42       2444?3223  2         Kim 1979, Müller-Starck 1985
       (3)              (4)              
Juglans regia221      ?2                  12 31 Arulsekar et al. 1985
Populus balsamifera322               22     13  1314  Farmer et al. 1988
Populus tremula         32          12  22        Guzina 1978, Bergmann 1987
Populus tremuloides11312    323  42     33  422 34334 Hyun et al. 1987
    (4)(3)                        (13)    Cheliak and Pitel 1984
Populus trichocarpa21 4312  12 2     12         12    Weber and Stettler 1981
Robinia pseudoacacia       13333  45     434333332  343Surles et al. 1988
Quercus petraea         12 21  33   94            Dankwardt and Rothe unpubl.
          (2)                         Aas 1987
Quercus robur         12 21  34   94            Dankwardt and Rothe unpubl.
          (2)                         Aas 1987
Quercus subg. Erythrobalanus              ?43??2313  12  ?8 54 Manos and Fairbrothers 1987

Acronyms
Aat: aspartate aminotransferase
Aco: aconitase
Acp: acid phosphatase
Ald: aldolase
Est: esterase
Gdh: glutamate dehydrogenase
Gpdh: glucose-6-phosphate dehydrogenase
Idh: isocitrate dehydrogenase
Lap: leucine aminopeptidase
Mdh: malate dehydrogenase
Per: peroxidase
Pgd: 6-phosphogluconate dehydrogenase
Pgi: phosphoglucose isomerase
Pgm: phosphoglucomutase

Table 3

Characterization of 16 late-budding norway spruce clones (Picea abies [L.] Karst.) using isozyme patterns of six different enzymes of current-year needles (Rothe 1990)

 
Clone number:1G7G8G10G14G15G16G17G18G21G84B89B93B94B95B105B
Phenotypic isozyme patterns:                
ADH1273753575881648
EST4455552123111111
G6pDH3113332333336454
LDH1121221111221221
6PGDH3144223556333753
SHDH4434331122332223

Acronyms:ADH: alcohol dehydrogenase;
EST: esterase (stained with c-naphthylphosphate andFast blue RR);
G6pDH: glucose-6-phosphate dehydrogenase;
LDH: lactate dehydrogenase;
6PGDH: 6-phosphogluconate dehydrogenase;
SHDH: shikimate dehydrogenase
NB:The clones number 1 to 24 were selected from trees of the provenance Goldap (G) while those numbered 84 to 105 were selected from spruce of the provenance Borken (B), both being located in Poland.

Table 4

Average heterozygosity (H) of some deciduous tree populations (of. Perry and knowles 1988)

SpeciesH
Acer saccharum0.27
Alnus crispa0.136
Populus balsamifera0.037
Populus tremuloides0.42
Populus trichocarpa0.09
Quercus subg. Erythrobalanus0.081

Table 5

The genetic variability of coniferous populations expressed by average heterozygosity (H) (of. Kormutak et al. 1982)

SpeciesH
Pinus contorta0.19
Pinus jeffreyi0.26
Pinus lambertina0.26
Pinus silvestris0.41
Pinus taeda0.34
Pseudotsuga menziesii0.33
Sitka spruce0.15

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1 Manuscript received July 1990. The article is an updated version of an article published by the author in German : Möglichkeiten und Grenzen von Isozym-Analyser zur Ermittlung der genetischen Konstitution von Waldbäumen". The original article was published in Allgemeine Forstzeitschrift 43(49), 1988, pp. 1336– 1338.

2 Definitions: The general term “isozymes”, by definition, includes a range of enzyme types with equal substrate specificity, occurring either in a single individual or in different members of the same species (of. Markert 1975). Isozymes are divided into three categories depending on the way they are biosynthesized:

(i) isoenzymes arise from multiple gene loci, which code for structurally distinct polypeptide chains of the enzyme;

(ii) allozymes (or alleloenzymes), are structurally distinct variants of a particular polypeptide chain, coded by multiple alleles at a single locus;

(iii) secondary isozymes result from post-translational modifications of the enzyme structure;

The distinction between multiple alleles and multiple gene loci as causes of isozyme formation is that multiple alleles are the result of differences between individual members of a certain species, whereas multiple loci are common to all members of a species.

3 Genetic distance:

The genetic distance (do) is a quantification of the difference between two statistical distributions of gene frequencies. The genetic distance can obtain values ranging from 0 to 1. The value 1 is obtained, when no common alleles are present in the two populations. The value 0 indicates, that the populations are genetically identical (Rothe 1988).

4 Average hetorozygosity (H) is a quantification of the width of genetic variation in a population:
H = ∑h1/r where h1 = 1 - ∑Xi2 for the first locus, r = number of examined loci and Xi = frequency of allele no. i of a locus.

The average heterozygosity is the same as the average probability of two genes selected at random not being identical. The figure is independent of the frequency of observed heterozygotes, since it does not take non-random crossings and selection into account. It is based only the observed gene-frequencies. (Rothe 1988).

5 International Union of Forest Research Organizations


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