Kao, 2000). Information on the genetics of SI in monocotyledonous grasses is just beginning to emerge, but it appears that at least two independent loci are involved in self-recognition (Bauman et al., 2000).
SI can act both before or after fertilization. Prezygotic SI results when there is an interaction between maternal tissue and the male gametophyte that prevents self pollen tube development (Lewis, 1979; Williams et al., 1994). Postzygotic reductions in self-fertility can arise due to late acting or ovarian self-incompatibility (OSI) where there is synchronous embryo failure (Seavey and Bawa, 1986; Sageet al., 1994, 1999).
The modes of action of SI vary widely (McCubbin and Kao, 2000; Silva and Goring, 2001; Nasrallah, 2002). In the Brassicaceae (crucifers) with sporophytic incompatibility, self pollen germination is inhibited through the interaction of two pollen proteins (SP11/SCR), a stylar receptor kinase (SKR), a glycoprotein (SLG;
S-locus receptor kinase gene) and several other proteins. The exact mechanism of rejection is not known, but may involve hydration of the pollen grains. In the Papaveraceae (poppy) with gametophytic SI, self pollen tube growth is rejected at the stigmatic surface by the interaction of a stigmatic S protein, a pollen S receptor (SBP), a calcium-dependent protein kinase (CDPK) and a glycoprotein.
Pollen tube growth is arrested by a cascade of events associated with an increase in cytosolic calcium and a disruption of the cytoskeleton. In the gametophytic Solanaceae (tobacco, tomato, petunia and potato) and Rosaceae(apple, cherry and pear), self pollen tube growth is inhibited within styles by a pistil-released ribonuclease (S-RNase) that selectively destroys the RNA of self pollen tubes.
Pollen S proteins are thought either to selectively allow self S-RNAs to enter the pollen tube or to inhibit non-self S-RNAs.
Self-sterility in some species is also caused by early acting inbreeding depression, where embryos abort as deleterious alleles are expressed during seed development or the outcrossed progeny display a hybrid vigour that enables them to outcompete the selfed ones (Charlesworth and Charlesworth, 1987; Waser, 1993). Evidence for this system is growing, par- ticularly in long-lived, outcrossing species (Weins et al., 1987; Seavey and Carter, 1994; Husband and Schemske, 1996; Carr and Dudash, 1996, 1997). Lucerne, blueberries and coffee have such a system (Busbice, 1968;
Crowe, 1971; Krebs and Hancock, 1991). Such species are often misclassi- fied as self-incompatible due to poor selfed seed set, but they are distinct from SI in that they commonly display the following: (i) a range in self-fertil- ity among different genotypes; (ii) a significant positive correlation between self and outcross fertility; (iii) a significant correlation between the per cent aborted ovules and the inbreeding coefficient; and (iv) embryos abort at dif- ferent stages of development (Hokanson and Hancock, 2000).
tence of a gene, including germination rate, seedling survival, adult mortal- ity, fertility and fecundity.
The fitness of a genotype is mathematically defined as the mean num- ber of offspring left by that genotype relative to the mean number of prog- eny from other, competing genotypes. It is commonly designated by the letter W. Since it is a relative measure, the genotype with the highest fitness (most fit) is assigned a value of 1. Other fitness values are decimal fractions ranging between 1 and 0. The selection coefficient is the proportional reduc- tion in each genotype’s fitness due to selection.
Suppose a population had the following genotype frequencies before and after selection:
AA Aa aa
Frequency before selection 0.25 0.50 0.25 Frequency after selection 0.35 0.48 0.17 The relative reproductive contribution of each genotype would be:
Reproductive contribution AA 0.35/0.25 = 1.40 Aa 0.48/0.50 = 0.96 aa 0.17/0.25 = 0.68
To assign the most fit a value of 1, we must divide each genotype by the reproductive contribution of the most successful genotype:
Fitness (W) AA 1.4/1.4 = 1 Aa 0.96/1.4 = 0.7 aa 0.68/1.4 = 0.4
The selection coefficient is 1 W; so:
AA 1.0 1.0 = 0 Aa 1.0 0.7 = 0.3 aa 1.0 0.4 = 0.6
Jain and Bradshaw (1966) found selection coefficients in nature to range from 0.001 to 0.5. Humans probably used even more extreme values in the domestication of crop species (Ladizinsky, 1985).
The response of quantitative traits to selection can be predicted by the equation, R = h2S, where h2is the estimate of heritability and Sis the selec- tive differential or the difference between the mean of the selected parents (µs) and the mean of all individuals in the parental population (µ) (Falconer and Mackay, 1996). The truncation point (T) represents the point at which individuals are either selected for or against (Fig. 2.6). For example, if we are
interested in a trait such as pod length with a high heritability of h2= 0.60 and our total parental population has a mean of 12.30 cm and our selected population has a mean of 15.20 cm, then R= 0.60 (15.20 cm 12.30 cm)
= 1.80 cm. This means that our progeny population will have pods 1.80 cm longer than the original population.
Types of selection
There are three primary types of selection: (i) directional; (ii) stabilizing; and (iii) disruptive or diversifying (Fig. 2.7). In directional selection, one side of a distribution is selected against, resulting in a directional change. Under stabi- lizing selection, both extremes are selected against and the intermediate type becomes more prevalent. In disruptive selection, the intermediate types are selected against, resulting in the increase of divergent types. The amount of genetic variability present in a population and the strength of the selection coefficient determine how fast and how much a population will change.
µ
µs
µ′
T
R = µ′ − µ S = µs − µ (A)
(B)
Fig. 2.6. (A) Quantitative distribution of phenotypes in a parental population with the mean µ. Only those individuals with phenotypes above the truncation point (T) produced progeny in the next generation. The selected parents are denoted by shading and their mean phenotype by µs. (B) Distribution of phenotypes in the next generation from offspring derived from the selected parents. The mean phenotype is denoted µ. Srepresents the selection differential, and Ris called the response to selection. (Used with permission from D.L. Hartl, © 1980, Principles of Population Genetics, Sinauer Associates, Inc., Sunderland, Massachusetts.)
Fig. 2.7. Comparison of the three major types of natural selection. Each population is depicted initially as a normal distribution with the cross-hatched areas
representing the less fit individuals. The rate of change is dependent on the degree of genetic variability present and the selection coefficient (see text). The bars represent how the proportions change each generation.
Numerous examples of directional selection have been presented in the evolutionary literature. Perhaps the most striking and repeatable is the evolution of heavy-metal tolerance in those plant species that come in contact with mine borders (Jain and Bradshaw, 1966; Antonovics, 1971). In less than 200 years, pasture species such as Anthoxanthum odoratumand Agrostis tenuis evolved distinct morphologies and means of coping with high levels of copper, lead and zinc in the face of substantial gene flow. As is shown in Fig. 2.8, a distinct change in metal tolerance can be observed across only a few metres. The domestication of maize also offers a dramatic example of directional selection.
Under human guidance, the size of the ear was increased between 7000 and 3500 before present (BP) from about 2.5 cm to well over 15 cm (Fig. 2.9).
The fact that we recognize most species as definable entities argues that stabilizing selection is common in nature or else species lines would be much more blurred than they are. Huether (1969) provided some of the strongest evidence of stabilizing selection when he showed that Linanthus androsaceus almost always have five lobes per flower even though their environments vary greatly and there is genetic variation for the trait at every site. Plant taxonomists often find floral traits to be the most dependable species markers, because they are generally less variable than other traits.
Documentation of disruptive selection has come most frequently by corre- lating gene frequency with environmental variation – one of the most com- monly cited examples is the work of Allard and co-workers (Allard and Kahler, 1971; Allard et al., 1972) where they found reproducible correlations between allozyme frequencies in the oat Avena barbataand the relative moisture content of soils in California. Distinct allozyme frequencies are found on the wettest (mesic) and driest (xeric) sites (Table 2.5). These allozymes may not have been the specific traits selected, but they were at least associated with the selected loci through genetic linkage and/or partial selfing (Hedrick, 1980; Allard, 1988).
Many unique races of crops were developed by human beings through disruptive selection as they gathered and grew populations from distinct regions and habitats (see Chapter 7). Perhaps the most distinct alteration came in Brassica oleracea, where several distinct crops were developed, including kale, broccoli, cabbage, kohlrabi and Brussels sprouts (see Fig.
11.3). Diverse races of rice, chickpea and chilli peppers also emerged in response to isolation and differential selection pressure from humans.
Plant breeders have on numerous occasions employed diversifying selec- tion to produce differences in harvest dates and quality factors. For example, dramatic changes in the protein content of maize were produced over 60 generations by selecting repeatedly for high and low values (Fig. 2.10).
While directional selection can eliminate variability in a population, stabiliz- ing and disruptive selection often act to maintain it. Dobzhansky (1970) called this maintenance of genetic polymorphism balancing selection. Disruptive selection maintains polymorphism when different genotypes are favoured in different environments. Stabilizing selection acts to maintain polymorphisms if heterozygotes produce the favoured phenotype. Numerous examples have been provided where superior vegetative or reproductive vigour have been asso- ciated with heterozygosity (Mitton and Grant, 1984; Strauss and Libby, 1987).
Fig. 2.8. Zinc tolerance in populations of Anthoxanthum odoratumlocated at different distances from a mine border (redrawn with permission from T. McNeilly and J. Antonovics, 1968,Heredity23, 205–218, and J. Antonovics and A.D.
Bradshaw, 1970, Heredity27, 349–362).
Fig. 2.9. Increase in maize cob size between 7000 and 3500BPin Tehuacan Valley, Mexico. The cob on the left was about 1 inch long. (Used with permission from D.S. Byers (ed.), © 1967, The Prehistory of the Tehuacan Valley, Vol. 1.
Andover Foundation for Archaeological Research, University of Texas, Austin.) Table 2.5. Genotype frequencies in two populations of oats
(Avena barbata) found in California. Three loci of esterase (E1, E4and E10) and one each of phosphatase (P5) and anodal peroxidase (APX5) are represented. (From Marshall and Allard, 1970.)
Frequency
Locus Genotype Mesic population Xeric population
E1 11 0.76 0.00
12 0.07 0.00
22 0.17 1.00
E4 11 1.00 0.30
12 0.00 0.11
22 0.00 0.59
E10 11 1.00 0.46
12 0.00 0.13
22 0.00 0.41
P5 11 0.00 0.40
12 0.00 0.15
22 1.00 0.45
APX5 11 0.86 0.48
22 0.00 0.41
33 0.09 0.00
12 0.00 0.11
13 0.05 0.00
23 0.00 0.00
Disruptive selection occurs not only across spatially heterogeneous envi- ronments, but also across time. Polymorphisms can be maintained across temporally varying environments, different life stages and variant sexes.
There are also examples of polymorphisms being maintained by differing population frequencies and genetic backgrounds. Some alleles, such as the S alleles associated with SI, are even favoured when they are in low fre- quency, but disfavoured at high frequency.
Factors limiting the effect of selection
Several important factors limit the influence of selection on gene frequen- cies: (i) amount of genetic variability present; (ii) generation time; (iii) strength of the selective coefficient; (iv) degree of dominance; (v) initial fre- quency of the advantageous allele; and (vi) intragenomic interactions.
The only way a population can change is if there is genetic variability present. Many a breeding programme has stalled or species become extinct when the genetic variability for a particular trait was extinguished. This is true both for single gene traits and for quantitative traits where more than one locus is involved. In 1930, Fisher outlined his fundamental theorem of natural selection, which stated: ‘The rate of increase in fitness of any organ- ism at any time is equal to its genetic variance at that time.’
The mating behaviour of a species has important long term evolutionary ramifications. Outcrossed species often have high levels of heterozygosity and gene combinations are continually shuffled during reproduction through crossing over and independent assortment. Selfing species are frequently very homozygous and specific gene combinations are rarely disrupted by sexual recombination. An outcrossed, heterozygous species has a considerable amount of genic flexibility with which to meet environmental change, but the Fig. 2.10. Change in protein content of maize during 60 generations of artificial selection by E. Leng and Associates at the Illinois State Experiment Station. (Used with permission from V. Grant, © 1977, Organismic Evolution, W.H. Freeman and Company, San Francisco.)
selfing, homozygous ones may be better adapted to specific, unchanging con- ditions. An intermediate strategy with variable outcrossing rates may yield the greatest long term success in an unpredictable world; this may be why few extreme selfers or outcrossers are found (Allard, 1988). Gornall (1983) has suggested that ‘those colonizing species which had extraordinary flexible recombination systems, which allowed them both to store and release large amounts of variability, were in a sense pre-adapted to successful cultivation’.
The strength of selection will critically influence the rate of change in a pop- ulation, as the greater the proportion of individuals being selected each year, the more rapid the change. Likewise, the generation time of an organism can have a strong effect on the rate of evolution simply because the longer the period between reproductive episodes, the longer the separation between meiotic reas- sortments of genes and seedling selection. Generation times in higher plants vary from a few weeks in Arabidopsisto dozens of years in some tree species.
The degree of dominance has an influence on rates of change because recessive alleles in the heterozygous state are masked from selection.
Frequencies of a newly arisen recessive allele will therefore change very slowly in a population until its frequency is quite high (Fig. 2.11). Frequencies of codominant alleles or those with an intermediate effect in a heterozygote will change more rapidly than those of recessives, since they have a partial influence on the phenotype of heterozygotes. Frequencies of dominants will initially change more abruptly than those of either recessives or intermediates, but the rate of change will eventually slow as the frequency of recessives becomes so low that most are ‘hidden’ in heterozygotes. In all cases, popula- tions with intermediate gene frequencies change more rapidly than those with low frequencies of deleterious or advantageous alleles (Fig. 2.11).
The number of selective deaths involved in one complete allelic substi- tution has been called the genetic cost (Haldane, 1957, 1960). By similar logic, the number of individuals that will die each generation due to selec- tion has been called the genetic load (Wallace, 1970). The cost factor is high when the favoured allele is at a low frequency, and decreases as the initial frequency increases. Obviously, a population can tolerate only a limited number of genetic deaths each generation if it is to avoid extinction.
The adaptiveness of an allele is influenced not only by the external envi- ronment, but also by the other genes in the genome. In most of our discussion so far, we have treated genes as if they are independent entities; however, the genome is in reality a tightly interacting unit. This concept will be discussed at length in the next chapter on the complexity of plant genomes.
Coevolution
Most of this chapter has concerned selection within a single species. However, there are numerous examples of what is called coevolution, where species have evolved together rather than independently. The most commonly cited exam- ples concern mutualism, character displacement and host–pathogen evolution.
In mutualism, there is a symbiotic reaction in which two species benefit by their interaction. Two classic examples in plants are soil mycorrhizae and nitrogen fixation bacteria. In both cases, microbes have become intimately associated with plant roots such that the plant gains mineral nutrients and the fungi or bacteria receive a carbon source. An even more dramatic exam- ple is found between the tree Acaciaand the ant Pseudomyrmex, where the ant receives nourishment from the tree’s nectaries and the ants defend the tree against herbivores and competing vegetation (Janzen, 1966).
When two species have overlapping ranges, one species is either selec- tively eliminated or the two undergo character displacements that minimize competition (Roughgarden, 1976). For example, where the ranges of Phlox pilosa and Phlox glaberrima do not overlap, they both have pink flowers, but, in areas of overlap, P. pilosa frequently has white flowers. Interspecific Fig. 2.11. Increase of advantageous alleles with different degrees of dominance.
(A) New mutation with a very low frequency (p= 0.01). (B) Existing polymorphism at p= 0.10. (Used with permission from D.J. Futuyma, © 1979, Evolutionary Biology, Sinauer Associates, Sunderland, Massachusetts.)
hybridizations are minimized because insects have a tendency to carry pollen from white to white flowers rather than from pink to white or vice versa (Levin and Kerster, 1967). Ecological races of many species also have differ- ent flowering times, which reduce the chance of hybridization. In some cases, these displacements are thought to be an early step in speciation (Chapter 5).
There are also numerous examples of host–parasite evolution, where there is widespread matching of host alleles conferring resistance to specific parasite strains (Flor, 1954; Vanderplank, 1978; Allard, 1990). Most of the best studied examples come from agricultural systems where constant battles are fought to find new sources of resistance to rapidly evolving pest popula- tions (Wahl and Segal, 1986; Allard, 1990). For example, dominant alleles have been identified at more than five loci in wheat that confer resistance to the Hessian fly, but alleles exist for each locus in the fly that confers counter- resistance (Hatchett and Gallum, 1970). Dozens of examples of ‘gene-for- gene’ relations have been described in pathogen/host systems where there is a gene for susceptibility or resistance in the crop to match each gene for vir- ulence or avirulence in the pathogen (Table 2.6). Numerous studies have been devoted to determining the nature of these resistances (Martin and Ellingboe, 1976; Leath and Pederson, 1986; Hautea et al., 1987; Pederson and Leath, 1988).
Table 2.6. The reaction of 16 genotypes of wheat to three Canadian races of Puccinia graminis tritici (from Vanderplank, 1978).
Resistance Race
genes C10 C33 C35
Sr 5 S S S
Sr 6 R R S
Sr 7a R S S
Sr 8 R S S
Sr 9a S R S
Sr 9b S R S
Sr 9d S S R
Sr 9e S S R
Sr 10 S S R
Sr 11 S S R
Sr 13 S R R
Sr 14 S S S
Sr 15 S R S
Sr 17 S R R
Sr 22 R R R
Sr T2 S R R
S, susceptible; R, resistant.