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Evolution: The Molecular Landscape

Cold Spring Harbor’s 74th Symposium
The Molecular Landscape
Edited by Bruce Stillman,
David Stewart, and
Jan Witkowski,
Cold Spring Harbor Laboratory


Chapter 20 Notes

Phenotypic Evolution


Evolutionary Optimization

Much of Evolution Can Be Understood as Optimization

Box 20.1 The Logic of Optimization Arguments

The Optimum Is Defined Relative to Constraints on What Is Possible


How Close to the Optimum Do We Expect Adaptations to Be?

There Are Trade-offs between Components of Fitness

Trade-offs May be Revealed by Patterns of Genetic Variation or by the Response to Artificial Selection


Aging Is Not Inevitable

Aging Evolves Because the Old Make Little Contribution to Fitness

Box 20.2 Selection Acts More Weakly on Later Life

Aging May Evolve as Part of an Optimal Life History

The Mutation Load May Be Concentrated on the Old

Aging Is Influenced by Conserved Mechanisms for Optimizing the Life History

Regulation of Aging in Nematodes, Flies, and Yeast

Evolutionary Games

An Evolutionarily Stable Strategy Cannot Be Displaced by Any Alternative

The Hawk–Dove Game

Competition between Viruses Is an Evolutionary Game

Experimental Demonstration of the Prisoner’s Dilemma

If There Is No ESS, Populations May Cycle: The Rock–Paper–Scissors Game

Behavioral Polymorphism in Lizards Gives a Natural Example of the Rock–Paper–Scissors Game

Sexual Selection

Sexual Selection Can Be Maladaptive

Sexual Selection Acts More Intensely among Males than among Females

Sperm Competition in Flies

Sexual Selection Involves Competition between Males and Choice of Males by Females

Female Preferences May Evolve by Direct Selection on Females or as a Side Effect of Selection on Other Traits

Indirect Selection on Preferences Can Lead to Fisher’s Runaway Process

Evolution of Female Preferences

Sexual Characteristics May Evolve to Signal Genetic Quality

It Is Difficult to Find Evidence on Whether Females Choose Males with Good Genes

Choice of Good Genes Requires Heritable Variation in Fitness


Evolutionary Optimization

Much of Evolution Can Be Understood as Optimization

Williams (1992) provides an excellent commentary on Paley’s arguments, together with extracts from Paley’s (1802) Natural Theology.

Box 20.1 The Logic of Optimization Arguments

The dung fly example is from Parker and Simmons (1994).

The example of metabolic networks in Escherichia coli comes from Ibarra et al. (2002); Edwards and Palsson (2000) explain the metabolic model.

The Optimum Is Defined Relative to Constraints on What Is Possible

Gould and Lewontin (1979) gave an influential critique of the adaptationist program. Parker and Maynard Smith (1990) clarify how optimization arguments can be used properly.

Here is an example of spandrels, which are used in the adaptationist argument by Gould and Lewontin (1979).

We have varied expectations as to how finely adjusted different features of organisms will be; this issue is discussed here.

There Are Trade-offs between Components of Fitness

The optimal size of the genetic alphabet is discussed by Szathmary (1991) and in a more sophisticated argument by Szathmary (1992). The set of 6 base pairs was from Piccirilli et al. (1990). Szathmary (2004) gives an up-to-date review.

The actual code is “almost” the most efficient, in that Szathmary found that only one alternative combination of bases was arguably more efficient.

Trade-offs can be investigated by observing genetic correlations or by artificial selection experiments. We discuss these methods here.

There has been extensive work on the adaptation of E. coli to changes in temperature; surprising, this does not seem to involve strong trade-offs. See Bennett et al. (1992) and subsequent papers in that series.


Aging Is Not Inevitable

The mortality data in Figure 20.8 are from Promislow (1991) and Ricklefs (1998).

Stewart et al. (2005) demonstrate senescence in the bacterium E. coli, which divides asymmetrically.

Aging Evolves Because the Old Make Little Contribution to Fitness

Fisher (1930) identified the weakened selection on later age, an argument from which Medawar (1946) identified the evolutionary explanation of aging. Hamilton (1966) gave the first mathematical analysis of how selection pressures change with age and set out the evolutionary explanation for senescence in detail. Charlesworth (2000) gives a history of these ideas.

Organisms that suffer less predation will also show less senescence, because survival and reproduction later in life will then be maintained by selection. One piece of evidence in favor of this evolutionary explanation is that birds show lower mortality than do mammals of similar size. Williams (1992) has another explanation in his book (p. 151): Birds typically become sexually mature long after they stop growing, whereas mammals start reproduction just before becoming fully grown. So, birds have to maintain their bodies for a long period before reproduction, and they just carry on working after that. These explanations are not incompatible. The first theory describes the selection regime that has been altered as a result of lower predation, and the other theory describes the physiological basis of the trade-off that has been reset in response (L. Partridge, pers. comm.). (A further complication in this example is that birds have been selected for small size, to enable flight, and so may tend to have a life history typical of mammals of larger size, including a longer life span.)

The example from social insects is from Keller and Genoud (1997).

Other examples of the loss of unselected functions include the evolution of host preferences in checkerspot butterflies (Euphydras editha) in response to loss of their usual food plant. Singer et al. (1993) show that this has led to an increase in preference for the new plant and a corresponding loss of preference for the original host. We see how changes in host preference can lead to speciation on pages 653–654.

Box 20.2 Selection Acts More Weakly on Later Life

This example comes from Roper et al. (1993); it is an extension of ideas presented in Chapter 17 (see Chapter 17 Web Notes).

Aging May Evolve as Part of an Optimal Life History

The effects of genetic or experimental sterilization of Drosophila are reviewed by Partridge and Barton (1993).

The effects of manipulating egg number are reviewed by Godfray et al. (1991).

The effects of castration on wild Soay sheep is described by Jewell (1997). For estimates of survival rate, see Catchpole et al. (2000).

The Mutation Load May Be Concentrated on the Old

Haldane (1941) suggested that modifiers that postpone the age of onset of deleterious mutations might accumulate, leading to senescence.

Cooper and Lenski (2000) demonstrate the loss of catabolic functions in replicate E. coli lines grown on minimal medium (see Fig. 18.5). This is an example where trade-offs can be distinguished from mutation accumulation. Selection positively favored deletions that caused loss of function, indicating that a new optimal life history is being approached through the trade-off between ability to metabolize different energy sources. This is not an instance of increased load from deleterious mutations, because the deletions are positively selected.

Hughes et al. (2002) observed an increase in additive variance in late life, which they took as evidence for mutation accumulation as a cause of senescence. However, other observations of how genetic variance and inbreeding depression change through time have given mixed results. See Snoke and Promislow (2003).

Aging Is Influenced by Conserved Mechanisms for Optimizing the Life History

Conserved mechanisms that regulate aging are explained here. For a readable account of work on aging in yeast, see Guarente (2002). For recent reviews, see Guarente (2001) and Partridge and Gems (2002).

Evolutionary Games

An Evolutionarily Stable Strategy Cannot Be Displaced by Any Alternative

W.D. Hamilton (1966) introduced the idea of an evolutionarily stable strategy (ESS), but called it an “unbeatable strategy.”

Further details of the hawk–dove game are given here.

Competition between Viruses Is an Evolutionary Game

The DIV (defective interfering virus) example of Figure 20.15 is from Nee and Maynard Smith (1990).

The Prisoner’s Dilemma game has been illustrated by an elegant experiment with bacteriophage φ6.

The term “tragedy of the commons” is from Hardin (1968).

If There Is No ESS, Populations May Cycle: The Rock–Paper–Scissors Game

Strictly speaking, in the E. coli example, strategy S is an ESS, because C can only displace it above a critical threshold frequency, at which the poison becomes effective. However, this threshold is very low.

The different outcome in the E. coli experiment with an agar plate is due to the localization of interactions, rather than the growing conditions. If the transfer between agar plates is made by pressing the velvet pad several times in different orientations, the R strain fixes, just as in a stirred flask.

The E. coli bacteriocin example is from Kerr et al. (2002); see also Kirkup and Riley (2004).

Behavioral Polymorphism in Lizards Gives a Natural Example of the Rock–Paper–Scissors Game

In the Uta example, note that there are intermediate morphs that correspond to heterozygotes and that there is also a female polymorphism probably caused by the same locus. The cycling of males and females is coupled, and models suggest that the male cycles are speeded up by coupling with a female two-year cycle. See Sinervo (1996, 2001).

Sexual Selection

Sexual Selection Can Be Maladaptive

Eberhard (1986) gives a fascinating account of how sexual selection has led to extraordinary variation in animal genitalia (e.g., see Figs. 20.20 and 20.26).

The stickleback example of Figure 20.22 is from Hagen and Moodie (1979), and Hagen et al. (1980).

Tuttle and Ryan (1981) give a striking example of the costs of frog calls: Calling males are eaten by bats.

Sexual Selection Acts More Intensely among Males than among Females

Clutton-Brock (1988) reviews evidence on the variance in fitness in the two sexes; see also Merila and Sheldon (2000).

Clark (2002) reviews work on sperm competition in Drosophila and discusses how it may maintain variation.

Figures for fitness variance in red deer are from Kruuk et al. (2000).

Clark et al. (1995) show wide variation between genotypes of Drosophila melanogaster in sperm offense and defense. They also report an association between accessory protein alleles and sperm defense ability.

The quote is from Darwin (1882, p. 224). In this section, Darwin asks why the struggle is “between males for the possession of females” (to use his description of sexual selection in On the Origin), but does not clearly state the modern explanation.

Figure 20.24 is based on Harcourt et al. (1981).

The arctic skua example of Figure 20.25 is based on a series of papers by O’Donald and colleagues (see O’Donald et al. 1974; O’Donald 1980).

Sexual Selection Involves Competition between Males and Choice of Males by Females

The damselfly example of Figure 20.26 is from Eberhard (1986).

The interaction between male and female genotypes seen in Figure 20.28 can maintain genetic variation (see Clark et al. 1999; Clark 2002).

Female Preferences May Evolve by Direct Selection on Females or as a Side Effect of Selection on Other Traits

Reviews of the evolution of female preference include Kirkpatrick and Ryan (1991), Andersson (1994), Ryan (1998), and Maynard Smith and Harper (2003).

The example of direct selection in blue tits comes from Norris (1990). Examples of increased fecundity due to nuptial gifts are from Butlin et al. (1987).

The nursery web spider example of Figure 20.29 is from Stalhandske (2002).

The Physalaemus example of Figure 20.30 is described by Ryan et al. (1990) and Ryan (1998). Note that in tungara frogs, there is a preference for larger males; this may be directly selected, because a larger male is more likely to be able to fertilize all the female’s eggs.

Indirect Selection on Preferences Can Lead to Fisher’s Runaway Process

Fisher (1915) first described indirect selection on female preference; the runaway process is described in Fisher (1930).

Recent work on the evolution of female preferences was stimulated by Lande’s (1981, 1982) models of sexual selection in which female preference and male trait were represented by quantitative traits. Shortly after, Kirkpatrick (1982) analyzed a similar model in which preference and trait were determined by two Mendelian genes. Lande’s (1981) model is explained here.

Sexual Characteristics May Evolve to Signal Genetic Quality

Zahavi (1975) first described the handicap theory. Grafen (1990a,b) gives a clear analysis which shows that Zahavi’s theory is distinct from Fisher’s and does not rely on indirect selection.

The detailed argument that male traits may evolve as signals of male quality is quite delicate, because three sources of selection must be allowed for. The sons of females that mate with preferred males will be of higher genetic quality; they will also inherit the signal trait, which increases their mating success but reduces other components of fitness.

The association between signal trait and genetic quality may come about in two ways. The most straightforward is a so-called condition-dependent handicap. Here, males that are in good condition (partly because of heritable variation in fitness) express the signal more strongly. For example, a bird that is sick, as a result of infectious or inherited disease, may have drab plumage and be unable to make bright colors. Alternatively, there may be an epistatic handicap. Here, expression of the signal in any one male is independent of other fitness components. The association between the trait and genes that confer higher viability comes about because the survival of the more vigorous males is reduced less by the costly signal trait than is the viability of less vigorous males.

It Is Difficult to Find Evidence on Whether Females Choose Males with Good Genes

The great tit example of Figure 20.32 is from Norris (1993).

The cockroach example of Figure 20.33 is from Moore (1994).

The great reed warbler example of Figure 20.34 is from Hasselquist et al. (1996).

Bro-Jørgensen et al. (2007) show that variation in swallow tail length—a classic example of a male signal (see Chapter 19 opening figure)—is due to variation in the aerodynamic optimum between individuals. Thus, it need not be a sexually selected signal of male quality.

Figures on the frequency of extra-pair fertilization are from Griffith et al. (2002).

Choice of Good Genes Requires Heritable Variation in Fitness

Hamilton and Zuk (1982) argued that coevolution between hosts and parasites is responsible for maintaining high fitness variation and that male traits evolve to signal this variation. Hamilton (1996) gives a somewhat idiosyncratic summary of the subsequent debate.


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