Previous studies of developmental rates in flies have focussed explicitly on pre-adult development. The results presented here demonstrate that there is significant genetic variation for the timing from eclosion to the age at which a female lays her first egg, that this duration shows a strong negative correlation with pre-adult developmental rate even when pre-adult development time is held constant between treatments during the selection process, and that the time from eclosion to first egg is positively correlated with adult life span.
Previous experiments on pre-adult development time in Drosophila have shown a relatively high amount of genetic variation, with realized heritabilities as high as 58% ( Sang & Clayton, 1957; Marien, 1958; Clarke et al., 1961 ; Marinkovic & Ayala, 1986; Zwaan et al., 1995a ). Our estimates of genetic variation for post-eclosion development are substantially lower, although continued selection may have uncovered more of a response. McMillan et al. (1970) found significant genotypic variance for age at first egg. However, that study did not measure additive genetic effects, and the actual trait was only measured indirectly. Life history theory suggests that age at maturity should be under very high selective pressure ( Cole, 1954; Dobzhansky et al., 1964 ; Lewontin, 1965). Thus, it is perhaps not surprising that we found very little genetic variation for time to egg laying.
In addition to strong selection, several other factors may have influenced the realized heritability in the study, including maternal effects, novel environment effects, inbreeding, drift and genetic trade-offs. In this study, we observed an initially high response to selection followed by a levelling off. This pattern is consistent with a strong maternal effect component influencing selection response ( Falconer, 1965; Kirkpatrick & Lande, 1989), with little or no heritable variation. A previous selection experiment on pre-adult development time in Drosophila found that after an initially rapid response, divergence between lines declined by the eighth generation of selection ( Zwaan et al., 1995a ). However, after approximately 12 generations of selection, the response began to increase again in Zwaan’s study, suggesting that both maternal and additive genetic effects may be important. In our own study, given the relatively small number of breeding pairs per line per generation (40 males and 40 females), we may have seen relatively low heritability because of loss of genetic variation from inbreeding or drift. Finally, novel environmental factors acting on wild-caught flies may have selected on traits other than those that we were directly selecting, leading to a reduced rate of response (see, for example, Van Tienderen & De Jong, 1994). We shall examine this last issue in greater detail later in the discussion.
At the same time that several factors may have limited genetic variation, in the longer term, the trade-off that we observed between pre- and post-eclosion development may help to maintain genetic variation. Our findings suggest that flies may be genetically and physiologically constrained such that they can alter the time from egg to eclosion, but not the minimum generation time (the time that it takes for a fertilized egg to develop into a mature female and produce a fertilized egg) (but see Chippindale et al., 1997 ). One evolutionarily important factor that this study does not address is the genetic variation not simply for the age at which the first egg is laid, but for the number of eggs laid early in life. We know that there is substantial genetic variation for fecundity at very early ages ( Tatar et al., 1996 ). In fact, Tatar et al. (1996) argue that this variation may be maintained by a trade-off between optimal time at eclosion and optimal age at maturity, consistent with the results that we found here.
The negative correlation between pre- and post-eclosion development time that we observed was consistent with much earlier work by Bonnier (1926) and Li (1927), who suggested that if one component of development were accelerated (in the present case, by artificial selection), the other component would ‘compensate’ by slowing down. In contrast, Chippindale et al. (1997) found a strong response to selection for decreased egg-to-egg development time, reducing the combined duration of pre- and post-eclosion development from 12 to 8 days over 125 generations. Although their study did not examine the correlation between larval and adult development, the strong response they found suggests that the negative genetic correlations could eventually be broken down if both traits are selected on simultaneously. However, attempts to deliberately disrupt genetic correlations through selection have met with mixed success, at least in plants ( Camara & Pigliucci, 1999; Camara et al., 2000 ). Of course, the negative genetic correlations that we observed for a recently caught wild strain may not have existed in the lab-adapted flies used by Chippindale et al.
Genetic constraints clearly play an important role in the short term evolution of life history strategies in flies. What might account for the apparently tight constraint that regulates the total ‘egg-to-egg’ development time in the population of Drosophila examined in this study? One possibility is that the response to selection on age at first egg is not a result of differences in rates of physiological maturity, but simply of the duration that a female holds fertilized eggs before laying them. If females in the L lines held eggs longer than females in the E lines, once the eggs were laid, we may expect them to hatch and mature sooner. However, the total development time from the time of fertilization would be no different. This trade-off may be relevant for flies in natural conditions, where the cost of delaying the time to lay eggs may be offset by the benefit of increased time available to find an ideal site for larval development. Future experiments will need to examine the physiological basis of this trade-off in greater detail.
The response to selection that we observed was confined to females. This is not surprising, given that the selection in this experiment focused primarily on female age at maturity. However, comparative evidence suggests that the greatest interspecific variation for age at maturity within the genus Drosophila is found in males ( Pitnick et al., 1995 ). Future studies might benefit from direct selection on male age at maturity to determine if genetic variance for male age at maturity is commensurate with high among-species variation.
Lab vs. wild flies
This study differs from most other selection studies on ageing in its use of flies newly caught from the wild. In a highly influential paper, Service & Rose (1985) argued that in order to obtain unbiased estimates for genetic correlations, one needs to use organisms that have adapted to the environment in which the selection will take place. The risk with wild-caught organisms is two-fold. First, those individuals with genotypes that are well-adapted to the new lab environment could show relatively high values for most fitness traits. Thus, genetic correlations will appear to be positive, solely as a result of the effects of the novel environment. Second, during the course of the selection experiment, the response to direct selection by the experimenter may be limited by selection on other, unexamined traits imposed by the novel laboratory regime (e.g. Van Tienderen & De Jong, 1994).
The flies we used had been brought into the lab very recently, and had therefore not yet adapted themselves lab culture. In light of recent studies on the genetic structure of laboratory populations ( Promislow et al., 1999 ; Sgrò & Partridge, 2000), we were specifically interested in finding evidence for standing genetic variation in natural populations. By using divergent selection, we were able to identify natural genetic variation and, at the same time, to minimize the confounding effects of lab adaptation. Presumably, the lab environment would have led to selection in the same direction for both E and L treatments. In this case, the effect of inadvertent selection would have been to increase type II error rates – a conservative response. Similarly, if the influence of the novel lab environment had affected observed correlations, we would have been more likely to observe positive correlations between age to first egg and both egg-eclosion duration and adult mortality. In both cases, we observed negative correlations. Whether these fitness trade-offs would be maintained in the lab environment over the long term remains to be seen ( Leroi et al., 1994a , b).
Over the past 20 years, a series of selection experiments has addressed the relationship between age at maturity and longevity in Drosophila ( Rose & Charlesworth, 1981; Luckinbill et al., 1984 ; Rose, 1984a; Partridge & Fowler, 1992; Zwaan et al., 1995b ; Partridge et al., 1999 ). In each of these studies, age at maturity has been defined as the age at which flies are allowed to breed. We refer to this approach as selection on demographic maturity. By contrast, in this case we have used artificial selection to alter the age at physiological maturity. This latter approach has enabled us to look directly at the relationship between adult development and ageing. The approach is relevant for testing two models of ageing.
The first model, the developmental theory of ageing ( Lints & Lints, 1969), predicts a positive genetic correlation between pre-adult development time and longevity. A series of studies in the past 5 years has rekindled interest in this theory ( Zwaan et al., 1991 , 1992; Chippindale et al., 1994 , 1995a), although in general, this work fails to support the developmental theory. In the present study, we found that after a relatively short period of selection, flies selected for slow post-eclosion development had longer life span, although the effect was found only in females and was relatively weak. In fact, the negative genetic correlation that we found between larval and adult development implies a negative correlation between larval development and longevity – the opposite of that predicted by Lints & Lints (1969).
Second, the approach that we have used here offers a novel and potentially fruitful way to address predictions derived from Williams’ antagonistic pleiotropy theory of senescence. Based on his theory, Williams predicted that ‘rapid individual development should be correlated with rapid senescence’ ( Williams, 1957; p. 409). To test these theories of aging ( Medawar, 1952; Williams, 1957), Edney & Gill (1968) proposed breeding only from young flies. Trade-offs between early vigor and late survival would then lead to higher late-age mortality. They dismissed as too difficult attempts to select on increased longevity by reducing late-age mortality rates. But it was this latter prediction that led to a series of experiments where researchers selected on demographic maturity by breeding from flies that survived to a relatively late age. In one sense, these experiments were enormously successful ( Rose & Charlesworth, 1981; Luckinbill et al., 1984 ; Rose, 1984a; Partridge & Fowler, 1992; Zwaan et al., 1995b ; Partridge et al., 1999 ). By enforcing a regime of delayed breeding, researchers were able to dramatically increase longevity in selected lines.
However, the degree to which these experiments actually support Williams’ hypotheses has been questioned ( Clark, 1987; Partridge & Fowler 1992; Curtsinger et al., 1995 ). In most cases the selection regime creates an effectively semelparous population, where generations do not overlap and individuals have only a few days during which breeding is possible, spaced apart by as much as 10 weeks (but see Stearns et al., 2000 ). The most successful individuals in this regime will be those that can survive to relatively late age, and having survived, are the most fecund. Thus, as Partridge & Fowler (1992) noted, in an attempt to determine whether there is a correlation between age-specific fecundity and survival, most experimenters have inadvertently selected on both traits simultaneously, thereby creating the very correlation one was hoping to find. Whereas many of the potentially confounding effects of earlier selection experiments have been rectified in recent work ( Partridge et al., 1999 ), to our knowledge only one study has fully eliminated the coupled selection on survival and fecundity ( Zwaan et al., 1995b ).
Notwithstanding the problems with these ‘delayed breeding’ experiments, the evidence is incontrovertible that demographic selection experiments can extend longevity. Our more immediate concern with these studies, and one which is directly relevant to the study we have carried out, is our belief that at least some of these experiments have been based on a misinterpretation of Williams’ original theory.
By delaying the onset of reproduction, selection will be maintained at a high and constant level until reproduction starts ( Hamilton, 1966). Thus, a demographic delay in reproduction is equivalent to a demographic delay in the onset of the decline in selection intensity ( Rose, 1991).
Unfortunately, this focus on demographic maturity has led us to ignore much of Williams’ original focus. In his discussion on reproductive maturity, Williams is clearly referring not to demographic maturity (i.e. age at breeding), but to actual physiological maturity. Williams defines the life course as ‘a fixed developmental sequence’, and says that ‘if development were greatly accelerated…senescence would be accelerated and appear at the usual developmental stage’ ( Williams, 1957; pp. 409–410). By ‘usual developmental stage’, he means age at physiological maturity. From this and the subsequent discussion in his paper, it is clear that Williams is thinking of maturity as a part of the developmental process. Delayed breeding experiments alter the age at which adults are allowed to breed, but do not directly select on their developmental trajectory. Williams predicted that delayed maturity should lead to extended life span, and conversely, individuals that mature earlier should show more rapid senescence and that the onset of ageing should coincide with the onset of reproduction. In each case, we think he could only have been referring to age at physiological maturity. Each of these predictions relating to age at physiological maturity has hitherto been ignored.
In this light, demographic selection experiments that delay breeding, but which do not select on reproductive maturity, do not directly test the predictions about development as outlined by Williams. Although the demographic approach is certainly useful in understanding some elements of the ecological and genetic basis of senescence, it does not address predictions about the effects of variation in physiological maturity. One well-known proponent of demographic approaches to studying ageing has defined senescence as ‘a persistent decline in the age-specific fitness components of an organism because of internal physiological deterioration’ ( Rose, 1984b; p. 20). For evolutionary biologists interested in senescence, ageing is typically measured in demographic terms, but as Rose’s definition illustrates, the phenomenon itself is inextricably linked with underlying physiological processes. While some workers have attempted to select on physiological traits and determine if these traits are genetically correlated with longevity ( Rose et al., 1992 ; Zwaan et al., 1995a ), no one to our knowledge has tried to examine the correlation between physiological maturity and longevity in Drosophila. This is particularly surprising, given the central role that age at maturity plays in the fitness of an organism ( Lewontin, 1965).
This distinction between demographic and physiological selection is further complicated by the fact that Drosophila is a mitotically limited organism. In Drosophila, almost all cells are post-mitotic soon after eclosion. This clearly limits the degree to which the developmental trajectory can be altered, at least in terms of continued growth into adult life. In many organisms, continued growth is a critical component of the maturation process, and may play an important part in senescence ( Finch, 1990). It may turn out that at least the more developmental aspects of Williams’ model are best tested with organisms that are not mitotically limited.
One might argue that the distinction between physiological and demographic selection that we make here is misleading, as the demographic selection approach used by Rose and colleagues has led to a delay in pre-adult development time ( Chippindale et al., 1994 ) – surely a physiological parameter – as predicted by Williams (1957). However, there is an alternative explanation for the result of Chippindale et al. (1994) . In their study, which found a correlation between longevity and pre-adult development, the nonselected, short-lived lines had been maintained in standard 2-week culture. In this culture regime, flies are placed in bottles, allowed to lay eggs, and then discarded. Two weeks after the bottles are set up, newly emerged flies from the next generation are transferred to fresh bottles, and the cycle starts anew. This culture regime leads to extremely strong selection for rapid development. Flies that do not eclose and develop a large number of mature oocytes before being transferred to fresh bottles will be unlikely to contribute offspring to subsequent generations ( Clark, 1987; Promislow & Tatar, 1998; Sgrò & Partridge, 2000). In contrast, in the ‘delayed breeding’ selection regime, flies can delay development substantially (caused by mutation accumulation and genetic drift) without negative consequences on fitness. Thus, the delay in development could be a result of a relaxation of directional selection on rapid development seen in control lines, rather than direct selection favouring delayed development in selection lines.
The trade-off that we observed between different components of development suggests that the relationship between development and ageing in insects may be more complicated than was previously thought. If different elements of development show negative pleiotropy, there can be no simple relationship between rates of ageing and rates of development, as put forth by Williams (1957) and Lints & Lints (1969). Further work is needed to determine the generality of the trade-off that we observed (which was not seen in Chippindale et al., 1997 ), and which particular elements of development are most likely to influence adult life history traits.
In conclusion, we have drawn an explicit distinction between demographic selection and physiological selection on age at maturity. Demographic selection changes the ecology or external environment of the organism, whereas physiological selection changes the physiology, or internal environment of the organism. We think that both can contribute to our understanding of the genetics and evolution of senescence. But selection on physiological age at maturity provides new opportunities for analysing the genetics of ageing by effectively reversing the classical approach carried out by so many previous workers. Rather than selecting on longevity and asking how early adult reproductive traits respond, we advocate an approach where one selects instead on early adult reproductive traits and measures the response in survival. This approach avoids the confounding effects of simultaneously selecting on fecundity and longevity ( Partridge & Fowler, 1992). It takes the phenotypic approach whereby costs of reproduction are measured by manipulating reproductive effort and measuring survival (e.g. Partridge & Andrews, 1985; Partridge et al., 1987 ; Sgrò & Partridge, 1999) and uses artificial selection to determine the genetic basis of the relationship (see Reznick, 1985). Our approach addresses an essential component of Williams’ theory that has long been neglected. It is our hope that through continued selection experiments on early adult reproductive physiology, we may be able to understand more fully the physiological and genetic basis of ageing and life history strategies.