Evolution, 56(5), 2002, pp. 927–935
THE ROLE OF PARENTAL AGE EFFECTS ON THE EVOLUTION OF AGING
NICHOLAS K. PRIEST,1,2 BENJAMIN MACKOWIAK,1
1 Department
AND
DANIEL E. L. PROMISLOW1
of Genetics, University of Georgia, Athens, Georgia, 30602-7223
Abstract. Many studies have found that older parents have shorter-lived offspring. However, the evolutionary significance of these findings is poorly understood. We carried out large-scale demographic experiments to examine the
direct effect of maternal age and paternal age on offspring aging in inbred and outbred strains of the fruit fly Drosophila
melanogaster. We found that the age of mothers and, to a lesser extent, the age of fathers can have a large influence
on both offspring longevity and the shape of the age-specific mortality trajectory. In two independent experiments
we found that older mothers generally produced shorter-lived offspring, although the exact effect of maternal age on
offspring longevity differed among strains. These results suggest that maternal age effects on progeny aging may
influence the evolution of aging.
Key words.
nescence.
Aging, Lansing effect, maternal age effects, mortality rate, offspring quality, paternal age effects, se-
Received July 24, 2001.
Accepted January 22, 2002.
The youngest mother, on the average, had the longestlived offspring.—Alexander Graham Bell (1918)
The phenotype of an individual can be influenced not only
by its genotype and the environment in which it is raised,
but also by the genotype and condition of its parents. This
type of parental inheritance results from factors transmitted
from parents to offspring other than simple nuclear DNA
sequences (Mousseau and Fox 1998). Although parental effects are known to have an important role in the development
of offspring, we know little about the importance of parental
effects on adult traits, such as aging.
Famed inventor Alexander Graham Bell first examined the
influence of maternal age at childbirth on the life expectancy
of children (Bell 1918). From the genealogical records of
8797 descendants of a colonial American family, Bell found
that children from older mothers had 45% shorter lives than
children from younger mothers. In the years since Bell’s
study, researchers have found that older mothers have shorter-lived offspring in rotifers (Jennings and Lynch 1928; Lansing 1947, 1948, 1954), duckweed (Ashby and Wangerman
1954), house flies (Rockstein 1957), stink bugs (Kiritani and
Kimura 1967), fruit flies (Goetsch 1956; Butz and Hayden
1961; O’Brian 1961), flour beetles (Raychaudhuri and Butz
1965), mealworms (Tracey 1958; Ludwig and Fiore 1960),
nematodes (Klass 1977), and yeast (Egilmez and Jazwinski
1989). This pattern is referred to as the ‘‘Lansing effect,’’
after Albert Lansing’s (1947, 1948, 1954) widely cited work
on rotifers.
Many investigators have questioned the validity of the Lansing effect (e.g., Comfort 1953; Rose 1991). Evolutionary
theories of aging, which assume that parental age effects do
not influence life span, predict that cultivating old females
should produce offspring that are longer-lived, not shorterlived (Hamilton 1966; Williams 1966; Edney and Gill 1968;
Charlesworth 1994). Artificial selection experiments on longevity conducted after the late 1960s support this prediction.
Cultivating older mothers for several generations typically
2 Present address: Department of Biology, 259 Gilmer Hall, University of Virginia, Charlottesville, Virginia 22904-4328; Email:
[email protected].
produces strains that are longer-lived (Rose 1991). Still, the
role of parental age in the response to selection on aging is
unknown. In addition, adequate explanations for the Lansing
effect have not been offered (Lints and Hoste 1974; King
1983; Finch 1990; Rose 1991; Lynch and Walsh 1998).
The Lansing effect may have an important role in the evolution of senescence. If the effect of parental age on offspring
longevity varies among genotypes, then selection on the quality of offspring produced by parents of different ages can
influence the evolution of aging. Accordingly, in this paper
we examine the direct effect of parental age on offspring
aging in two outbred and four inbred strains of fruit flies to
address two questions: (1) Do maternal and paternal age influence progeny aging? (2) Do the effects of maternal and
paternal age vary among genotypes?
The fruit fly is an ideal system in which to study these
questions. In Drosophila, parental age effects influence juvenile fitness traits and the heritability of morphological traits
(e.g., Parsons 1962; Beardmore et al. 1975; Mills and Hartmann-Goldstein 1985; Fox 1993; Mousseau and Fox 1998;
Hercus and Hoffman 2000; Kern et al. 2001). Molecular genetic studies have identified several genes associated with
life span in Drosophila (e.g., Lin et al. 1998; Parkes et al.
1998; Regina et al. 2000; Clancy et al. 2001; Tatar et al.
2001). In addition, quantitative genetic studies have established Drosophila as an ideal model system in which to test
evolutionary theories of aging (e.g., Rose and Charlesworth
1980; Rose 1984; Partridge and Fowler 1992; Zwaan et al.
1995; Promislow et al. 1996; Nuzhdin et al. 1997; Leips and
Mackay 2000; Vieira et al. 2000). Still, the role that parental
age effects play in the genetic basis of aging has been largely
neglected (but see Lynch and Ennis 1983; Kern et al. 2001).
In the study described here we used the fruit fly Drosophila
melanogaster to examine the direct effect of maternal age
(controlling for paternal age) and paternal age (controlling
for maternal age) on offspring longevity and age-specific
mortality rate. We carried out these experiments with largescale biodemographic techniques, involving nearly 150,000
animals. One potential confounding factor in studies of parental age effects is genetic heterogeneity (Vaupel and Yashin
1985). If parents differ genetically in their underlying rates
927
q 2002 The Society for the Study of Evolution. All rights reserved.
928
NICHOLAS K. PRIEST ET AL.
of aging, then as individuals that are genetically predisposed
to high mortality die off, the genetic constitution of a sameaged cohort will change over time. Thus, differences in the
longevity of offspring from old versus young parents could
be due to initial genetic heterogeneity among parents. Our
first set of experiments used genetically heterogeneous outbred strains, but in a second set of experiments described
here, we controlled for genetic heterogeneity by using inbred
strains.
MATERIALS
AND
METHODS
We performed two independent experiments to determine
the effects of maternal age and paternal age on offspring
longevity in six strains of D. melanogaster. Experiment I
examined maternal and paternal age effects in two genetically
outbred strains, UGA98 and Canton-S. Experiment II studied
maternal and paternal age effects in four inbred strains, 79L,
67L, 58S, and 35S.
Stocks
The UGA98 strain was generated from about 250 inseminated females collected from a peach orchard in Watkinsville, Georgia in August 1998, six months before the start of
Experiment I. The laboratory strain, Canton-S, was obtained
from the Drosophila Stock Center in Bloomington, Indiana.
The 79L, 67L, 58S, and 35S strains are from a set of 98
recombinant inbred lines developed for quantitative-trait-loci
mapping by T. F. C. Mackay and colleagues at North Carolina
State University, Raleigh, North Carolina (Nuzhdin et al.
1997). Throughout the experiments the flies were maintained
on a standard yeast-agar-cornmeal-molasses medium at 248C
on a 12:12 L:D cycle. Before the start of both experiments,
to remove any residual parental effects, the strains were cultured in plastic half-pint bottles at a density of approximately
250 eggs/bottle for two generations. The experiment was designed so that the grandparents of the flies used in the aging
analysis were 1 week old for all strains.
The strains were chosen because of their particular genetic
characteristics. Whereas recently wild-caught strains have a
genetic makeup that is representative of fruit flies in nature,
laboratory strains kept in a 2-week culture are under intense
selection for early-life reproduction and thus may have a quite
different genetic structure (Promislow and Tatar 1998; Sgrò
and Partridge 2000; Linnen et al. 2001). In experiment I, we
examined how parental age effects differed between a wildcaught and a laboratory-cultured strain. In experiment II, we
chose four genetically inbred strains to eliminate the possibility that the effects seen in experiment I could be due to
genetic heterogeneity (Vaupel and Yashin 1985).
Generating Progeny from Parents of Different Ages
Both experiments were designed so that mortality assays
of progeny from parents of different ages and genotypes could
be started simultaneously. We collected parents every 2
weeks from grandparental cohorts cultured in half-pint food
bottles. For each time point we collected 3000 virgin males
and 3000 virgin females over a 2-day interval. On the day
after we finished the collection, we pooled males and pooled
females and placed the animals in holding jars at 1000 flies
per jar (three virgin male jars and three virgin female jars).
We changed the food in the jars every other day and held
the flies in the jars until we mated them. After 9 weeks, we
had holding jars with virgin males and females of ages 1, 3,
5, 7, and 9 weeks.
To examine maternal age effects we mated virgin females
of each age to 1-week-old males (1 3 1, 3 3 1, 5 3 1, 7 3
1, 9 3 1). To examine paternal age effects, we mated virgin
males of each age to 1-week-old females (1 3 1, 1 3 3, 1
3 5, 1 3 7, 1 3 9). For each cross we isolated flies from
the holding jars under minimal CO2 anesthesia and placed
12 pairs of males and females in 48 half-pint food bottles,
for a total of 864 food bottles (48 bottles for each of nine
treatments and two strains). Egg density can affect patterns
of mortality (Clare and Luckinbill 1985). To provide an approximate control for egg density in experiment I, after 2
days of egg-laying we subsampled bottles from each treatment and removed adults when, on average, more than 200
eggs were visible. In most cases, 1-week-old mothers laid
eggs for 2 days and all other mothers laid eggs for 3 days.
Although there was variation in egg number per bottle (many
bottles had many as 250 eggs), the variation was evenly distributed across treatments. Starting on the second day of
emergence, we collected offspring every 24 h for 3 days and
placed 0.41 g of mixed-sex flies (measured on a table scale
without CO2 anesthesia) in cages designed to allow dead flies
to be removed and food vials to be replaced.
The procedure in experiment II was very similar, except
we controlled for egg density much more carefully and did
not collect animals for the week 9 parental age treatment,
because the inbred flies were shorter lived. We isolated the
parental flies from the holding jars and filled 672 bottles of
food (24 bottles for each of seven treatments and four strains).
To control for genetic and age-related variation in fecundity,
for each of the genotypes and parental age treatments, we
adjusted the number of pairs of parents (from 10 to 22 pairs)
we placed in each bottle so that egg productivity and adult
emergence would be similar for all genotypes: for 79L we
placed 12, 14, 16, and 18 pairs of parents corresponding to
the week 1, 3, 5, and 7 maternal age treatments; for 67L, 12,
14, 16, and 18 pairs; for 58S, 10, 12, 14, and 16 pairs; and
35S, with the lowest egg productivity and hatchability, 16,
18, 20, and 22 pairs.
After the first day we subsampled four bottles every few
hours from each of the parental age treatments and genotypes
and counted eggs. When the average number of eggs counted
was within 15 of our standard for each genotype (250 eggs
for 79L and 67L, 200 for 58S, and 275 for 35S, determined
in egg-to-emergence preliminary trials), we cleared the bottle
of adults. On average, 1-week-old mothers laid eggs for 2
days and all other mothers laid eggs for 3.0 to 3.5 days. When
the offspring started emerging from the bottles, we collected
all offspring every 24 h for 10 days, until the emergence
stopped. Each collection, we pooled all the offspring for each
parental age treatment and genotype and placed 0.40 g of
mixed-sex flies into each of several cages (the mass of flies
per cage was reduced because the inbred strains were lighter).
Sufficient numbers of animals were not available to analyze
the week 7 maternal age treatment for the 79L, 67L, or 58S
929
PARENTAL AGE EFFECTS ON AGING
TABLE 1. Analysis of variance of maternal age effects on offspring longevity, mortality intercept, and slope for each genotype and offspring
sex in experiments I and II, with 1 df. Percent change in offspring mortality parameters, F-statistics (in parentheses), and associated P-values
are provided. The results in bold are significant at P , 0.05 after sequential Bonferroni correction within offspring sex by experiment (I vs.
II) blocks.
Outbred strains
Genotype
Daughters
Sons
Longevity
Intercept
Slope
Longevity
Intercept
Slope
UGA98
212.2
4.67
10.2
23.81
1.55
3.12
(9.04)**
(1.55)
(1.1)
(1.80)
(0.07)
(0.17)
Inbred strains
Canton-S
10.2
28.13
8.01
9.27
28.36
2.87
(4.89)*
(3.09)
(1.03)
(4.49)*
(2.18)
(0.12)
79L
25.00
2.90
21.98
0.56
25.89
15.4
(0.58)
(0.35)
(0.06)
(0.02)
(3.07)
(6.94)*
67L
226.3
9.41
23.53
24.71
9.41
218.1
58S
(19.5)***
(5.06)*
(0.06)
(1.37)
(5.06)
(5.14)*
214.5
15.1
221.6
28.73
18.2
223.5
35S
(13.8)** 218.2 (01.6)**
21.7 (17.6)**
(10.8)**
(6.11)* 239.0 (12.2)**
4.70 (3.13)
(4.38)
(23.3)*** 28.99 (3.37)
13.9 (2.40)
(19.1)***
* P , 0.05; ** P , 0.01; *** P , 0.001.
genotypes and only one cage of flies was collected for the
35S treatment. We kept the cages that corresponded to peak
offspring emergence and randomized the placement of those
cages in a large walk-in incubator. For both experiments, we
removed dead flies from cages, exchanged food vials, and
recorded whether any flies had escaped or were killed accidentally every 2 days. For every cage we determined dx, the
number of deaths at age x.
Data Analysis
From the sum of the dx-values we calculated the total initial
number of flies in each cage (N0) and the number alive at
each age (Nx). We estimated mean longevity as S Nx/N0. The
mortality rate (mx) was defined as
mx 5 2ln(Nx1Dx/Nx)/Dx
(1)
over the time interval Dx (Elandt-Johnson and Johnson 1980).
For large sample sizes the mortality rate is well described by
the Gompertz equation, mx 5 AeBx, where A and B are the
age-independent mortality intercept term and age-specific
slope of the mortality curve, respectively. The slope parameter, B, is often used as a measure of the rate of aging (e.g.,
Promislow 1991). We estimated the mortality intercept and
slope for each sex within each cage using WinModest (Pletcher 1999), a maximum-likelihood model that accounts for censored data (i.e., escaped flies). We ln-transformed values of
the intercept, A, to improve normality. Within strains, we
used least-squares multiple regression analysis to determine
the relationship between parental age and offspring mean
longevity, the age-independent mortality intercept term, and
age-specific slope of the mortality curve, with sex-specific
data from each cage counted as a datapoint.
We were also interested in testing for the relative effect
of parental age on sons versus daughters and the effect of
parental age in different genotypes. For these analyses, we
used a mixed-model ANCOVA, with parental age as a fixed
(continuous) effect, parental sex and offspring sex as fixed
effects, and genotype as a random effect. Offspring in each
cohort emerged over several days in these experiments. To
control for any effects of day of emergence, we included this
as a random effect in all analyses. All analyses were carried
out using JMP (SAS Institute 1995).
For each strain and sex we calculated the estimated longevity, mortality intercept, and mortality slope values for
offspring from the oldest mothers and from 1-week-old moth-
ers. We determined the percentage change in the mortality
parameters with maternal age: percent change 5 [(estimated
mortality parameter for oldest mother—estimated mortality
parameter for 1-week-old mother)/estimated mortality parameter for 1-week-old-mother].
To reduce the effects of variation in initial density on mortality rates, we eliminated any cages from further analysis
that had fewer than 300 or greater than 500 flies (10 of 330
cages removed). In addition, upon completing both experiments I and II, we found a few cages that had unexpectedly
high mortality. These data were removed as outliers from the
analysis based on the Dixon and Grubbs test (Sokal and Rohlf
1995) when P , 0.001 (seven of 640 datapoints). Subsequent
reanalysis including data from these cages did not substantially change the results (data not shown). The average number of cages (datapoints) for each genotype/sex/parental age
treatment was 38 for experiment I and 21 for experiment II.
We used sequential Bonferroni correction for each sex within
each experimental block (I vs. II) for the offspring mortality
parameters (longevity, intercept, and slope) to determine statistical significance after correction for multiple comparisons.
We show the uncorrected and corrected statistics in Tables
1 and 2, but discuss only the uncorrected statistics in the
results and discussion.
RESULTS
Maternal Age Effects
For experiments I and II, we found that maternal age had
a large influence on offspring longevity and there was significant among-strain variation in the effects of maternal age
on offspring longevity.
In experiment I, for the wild-caught strain UGA98, daughters of older mothers were significantly shorter-lived than
daughters from younger mothers (F1,31 5 9.04, P 5 0.0052),
with a 12% decrease in longevity overall. In contrast, for the
laboratory strain, Canton-S, daughters of older mothers were
significantly longer-lived than daughters of younger mothers
(F1,38 5 4.89, P 5 0.0331), with a 10% increase in longevity.
Maternal age effects on sons were in the same direction as
the effects on daughters, but in this case, only Canton-S
showed a significant correlation (F1,38 5 4.49, P 5 0.0407;
Table 1, Fig. 1). In the ANCOVA combining both genotypes,
the effects of maternal age differed significantly between
930
NICHOLAS K. PRIEST ET AL.
FIG. 1. Maternal age effects on offspring longevity. Mean longevity (6SE) of offspring (in days) from mothers of different ages (in
weeks) is provided for daughters and sons for each of the genotypes in experiments I and II. The regression lines are fitted to the actual
data. Genotypes in experiment I: UGA98, filled circles; Canton-S, open circles. Genotypes in experiment II: 58S, filled circles; 35S,
filled triangles; 79L, open triangles; 67L open circles.
these two strains (genotype 3 maternal age, F1,141 5 19.27,
P , 0.0001).
For experiment II, older mothers produced daughters with
shorter lives (longevity declined by 5% for 79L, 26% for
67L, 15% for 58S, and 18% for 35S; Table 1, Fig. 1). Maternal age was only weakly correlated with life expectancy
of sons. The effect of maternal age on daughters was significantly greater than on sons (maternal age 3 offspring sex,
F1,120 5 9.11, P 5 0.0031). There was evidence for genotypic
variation in maternal age effects (genotype 3 maternal age,
F3,120 5 3.59, P 5 0.0158).
was no evidence for genotypic variation in paternal age effects (genotype 3 paternal age, F1,145 5 6.98, P 5 0.9542).
In experiment II, paternal age was not significantly correlated with offspring longevity in any strain (Table 2, Fig.
2). In the analysis with all four strains, the age of the father
did not significantly influence offspring longevity (F1,168 5
2.59, P 5 0.1095). Paternal age effects were not related to
paternal genotype or offspring sex (genotype 3 paternal age,
F3,168 5 0.27, P 5 0.8497; sex 3 paternal age, F1,168 5 0.85,
P 5 0.3568).
Parental Age Effects and Age Specific Mortality
Paternal Age Effects
In experiment I, but not experiment II, paternal age significantly influenced offspring longevity. In both experiment
I and II, there was no evidence for genotypic variation in the
effects of paternal age on offspring longevity.
In experiment I, older fathers produced longer-lived offspring in both strains (Table 2, Fig. 2), although the paternal
age effect was only significant for sons in UGA98 and daughters in Canton-S (longevity increased 10% and 6.9%, respectively). The ANCOVA model, combining both strains,
showed that older fathers had offspring with significantly
longer lives (paternal age, F1,145 5 6.98, P 5 0.0092). There
We found that maternal and paternal age influenced the
age-independent intercept term and the age-specific slope of
the mortality curve of offspring (Tables 1, 2). In experiment
I, maternal age did not significantly alter mortality slope or
the intercept for any particular sex in the two genotypes.
However, the combined genotype ANCOVA model revealed
that the differences in the effect of maternal age on longevity
in the UGA98 and Canton-S strains, which were described
above, resulted from changes in the intercept (maternal age
3 genotype, F1,141 5 4.29, P 5 0.0402) and not the slope
(maternal age 3 genotype, F1,141 5 0.02, P 5 0.8854). In
experiment II, maternal age significantly influenced the mor-
931
PARENTAL AGE EFFECTS ON AGING
TABLE 2. Analysis of variance of paternal age effects on offspring longevity, mortality intercept, and slope for each genotype and offspring
sex in experiments I and II, with 1 df. Percent change in offspring mortality parameters, F-statistics (in parentheses), and associated P-values
are provided. The result in bold is significant at P , 0.05 after sequential Bonferroni correction within offspring sex by experiment (I vs. II)
blocks.
Outbred strains
Genotype
Daughters
Sons
Longevity
Intercept
Slope
Longevity
Intercept
Slope
UGA98
5.58
27.56
7.89
9.70
214.7
14.1
(1.86)
(5.28)*
(1.84)
(6.56)*
(5.64)*
(4.31)*
Inbred strains
Canton-S
6.37
210.9
26.0
4.17
24.73
3.12
(4.61)*
(7.91)**
(5.18)*
(2.18)
(1.85)
(0.19)
79L
26.09
3.81
23.30
0.13
0.15
21.92
(2.84)
(1.52)
(0.25)
(0.002)
(0.002)
(0.12)
67L
26.54
3.36
0.23
22.90
4.77
210.1
(1.40)
(0.78)
(0.001)
(2.88)
(4.94)*
(4.54)*
58S
1.66
21.24
1.07
22.34
21.32
4.46
(0.30)
(0.03)
(0.04)
(0.85)
(0.15)
(1.31)
35S
210.2
6.56
24.25
4.49
210.6
16.7
(4.37)
(2.30)
(0.25)
(2.59)
(5.96)*
(5.75)*
* P , 0.05; ** P , 0.01; *** P , 0.001.
tality intercept and slope of daughters in many of the inbred
strains (Table 1). Although it did not significantly influence
the longevity of sons, maternal age had significant influences
on the mortality intercept and slope of sons in 79L, 67L, and
58S. The combined genotype ANCOVA on mortality slope
and intercept revealed that maternal age significantly increased the intercept (F1,120 5 26.15, P , 0.0001) and decreased the slope (F1,120 5 13.71, P 5 0.0003). The genetic
variation that we found in our analysis of maternal age effects
on longevity appeared to be due to changes in both intercept
(maternal age 3 genotype, F3,120 5 9.68, P , 0.0001) and
slope (maternal age 3 genotype, F3,120 5 6.29, P 5 0.0005).
The sex-specific maternal age effects on longevity resulted
from changes in intercept (maternal age 3 sex, F1,120 5
29.5638, P , 0.0001) and not slope (maternal age 3 sex,
F1,120 5 2.68, P 5 0.104).
Although paternal age had weak or nonsignificant effects
on offspring longevity, in both experiment I and II paternal
age influenced the mortality intercept and slope of offspring.
In experiment I, paternal age significantly decreased the mor-
FIG. 2. Paternal age effects on offspring longevity. Mean longevity (6SE) of offspring (in days) from fathers of different ages (in
weeks) is provided for daughters and sons for each of the genotypes in experiments I and II. The regression lines are fitted to the actual
data. Genotypes in experiment I: UGA98, filled circles; Canton-S, open circles. Genotypes in experiment II: 58S, filled circles; 35S,
filled triangles; 79L, open triangles; 67L open circles.
932
NICHOLAS K. PRIEST ET AL.
tality intercept and increased the mortality slope (paternal
age, F1,145 5 12.72, P 5 0.0005; F1,145 5 9.88, P 5 0.002,
respectively). In experiment II, paternal age significantly influenced the mortality intercept and slope of only certain
strains and sexes (Table 2).
After sequential Bonferroni correction for each sex within
each experimental block, nine of 15 of the significant maternal age effects on offspring mortality parameters (longevity, intercept, and slope) remained significant at alpha 5 0.05;
however, only one of 11 significant paternal age effects remained significant at alpha 5 0.05. Tables 1 and 2 show the
Bonferonni correction, but the discussion of the results is on
the uncorrected statistics.
DISCUSSION
This study was designed to address two questions: Do maternal and paternal age influence offspring aging? Is there
genotypic variation in the effect of maternal and paternal age?
Our results affirm both questions, with clear differences between the maternal and paternal age effects.
Parental Age Effects on Offspring Aging
This study shows that both maternal age and paternal age
can influence offspring aging. Maternal age had a remarkably
different effect on offspring mortality parameters for each
sex and in each strain (Table 1). Older mothers produced
shorter-lived daughters in five of the six strains we examined.
The maternal age effects were very large, from a 10% increase
in longevity of daughters for Canton-S to a 26% decrease in
longevity for 67L. The magnitude of these single-generation
maternal age effects are comparable to longevity changes in
multigenerational selection experiments. For example, Rose
(1984) found a 25% increase in longevity after 12 generations
of selection on longevity. In the inbred strains maternal age
effects had a much larger influence on daughters than sons.
The effects on longevity were largely consistent with the
Lansing effect studies conducted over the past 50 years (Butz
and Hayden 1961; Lints and Hoste 1974; Finch 1990).
This is one of the few studies to independently consider
the effects of maternal and paternal age (but see Butz and
Hayden 1961). Overall, we found that paternal age had a
much weaker affect on offspring longevity than maternal age,
although both maternal and paternal age influenced offspring
mortality trajectories (Tables 1, 2). In general, maternal age
effects appeared to have a greater influence on daughters than
sons, whereas paternal age effects seemed to have a larger
influence on sons than daughters.
The sex-specific nature of these parental age effects can
occur for strictly genetic reasons. Recent work by Rice and
colleagues shows that a gene expressed in a male can have
very different (and sometimes completely opposite) effects
on fitness compared to the very same gene expressed in females (reviewed in Rice and Chippindale 2001). Gene 3 sex
epistatic interactions could certainly account for the observed
differences in the effect of maternal age on daughters and
sons.
It is not surprising that maternal age has a greater effect
than paternal age on offspring longevity because the mother
contributes most of the mRNA, lipid, carbohydrate, and pro-
tein molecules in the zygote cytoplasm. As mothers age, shifting resource demands between reproduction and survival may
influence the gene products secreted by the nurse cells into
the developing oocyte, and thereby alter the life history of
offspring. Paternal age effects may influence offspring quality directly, through factors in the sperm pronucleus, or indirectly, through manipulation of the female during mating.
Because accessory-gland proteins (ACPs) carried in the male
ejaculate can have a large influence on female physiology
(Chapman et al. 1995; Wolfner 1997), one intriguing possibility is that paternal age effects result from the response
of mothers to changes in the ACP content of male ejaculate.
These kinds of effect have large implications for models of
age-specific mate preference (reviewed in Brooks and Kemp
2001).
We suggested earlier that genetic heterogeneity for mortality rate could confound studies of parental age effects
(Vaupel and Yashin 1985). Although this could be a concern
in the two outbred strains, the increased longevity in offspring
of older mothers in the inbred strains suggests that heterogeneity is unlikely to have influenced our results. The effects
of heterogeneity were most likely in Canton-S, in which flies
are genetically variable and the relatively high adult mortality
rates provide plenty of opportunity for within-generation selection. Although this study found that older Canton-S mothers mated to young males produce longer-lived offspring,
results from a concurrent experiment found that older mothers
mated to same-aged males show no effect on offspring longevity (Priest 2001). This result suggests that even in the
outbred strains, genetic heterogeneity was unlikely to have
confounded our results because, in that case, we would have
expected older mothers to produce longer-lived offspring regardless of the age of the mate. A recent study of parental
age effects on juvenile survival in fruit flies, which statistically accounted for genetic and environmental heterogeneity
by including individual mother as factor in their analysis,
found that offspring quality declined with maternal age, independent of possible changes in cohort heterogeneity (Kern
et al. 2001).
Evolutionary Significance of Parental Age Effects on Aging
Our findings of genetic variation in maternal age effects
on adult mortality, together with Kern et al.‘s (2001) finding
of genetic variation for maternal age effects on juvenile mortality, suggest that parental effects may play a fundamental
role in the evolution of aging. Senescence occurs for both
genetic and physiological reasons. Evolutionary theory suggests that two processes lead to the accumulation of genes
that cause senescence. In the first, the age-related decline in
the force of selection leads to the accumulation of late-acting
deleterious mutations (Medawar 1952). In the second model,
senescence is caused by genes that lead to trade-offs between
early-age and late-age fitness traits (Williams 1957, 1966).
Both of these models have implications for the influence of
maternal age on the evolution of aging. First, parental age
effects can alter the rate of mutation accumulation by changing the age-specific decline in the force of selection (Kern
et al. 2001). For example, if offspring fitness deteriorates
with maternal age, the age-related decline in force of selection
933
PARENTAL AGE EFFECTS ON AGING
will be greater, allowing for greater accumulation of lateacting deleterious mutations and more rapid evolution of senescence. Second, parental age effects can influence the nature of life-history trade-offs. The life history of an individual
may involve balancing resources not only for early-age and
late-age fitness traits, but also for fitness traits of offspring
(Trivers 1974). The nature of the trade-offs between the fitness of parents and offspring may change as parents age.
Third, to the extent that fitness of an individual is determined
by the fitness of offspring (Grafen 1988), aging could evolve
through selection on parental age effects on offspring aging.
Our finding of genetic variation in maternal age effects on
offspring aging suggests that there is ample genetic variation
for this kind of selection.
Ultimately, the effect of parental age on the evolution of
senescence also depends on the nature of the genetic variation. When there are negative genetic correlations between
maternal and offspring genotypes, maternal effects can cause
time lags and temporary reversal in the response to selection
(Kirkpatrick and Lande 1989; Wolf and Brodie 1998). In light
of the results presented here, it would be worth developing
an explicit model of the effects of maternal age on shortterm changes in patterns of aging. Such effects could explain
what at first glance appears to be a rather unexpected result.
In a selection experiment on longevity that involved cultivating older fruit flies for several generations, Lints and Hoste
(1974) found that longevity declined for two generations and
subsequently increased over time. Most of the later selection
experiments by other researchers did not measure longevity
each generation, so it is difficult to know whether time lags
and reversals in the response to selection on longevity are
typical (Rose 1991).
lesworth 1994). Age-structured models that incorporate parental effects may provide a more comprehensive theory for
the evolution of senescence (Austad 1997; Carey and Gruenfelder 1997). The results presented here suggest that tradeoffs can occur between fitness of a parent and the fitness of
its offspring (Kern et al. 2001). In this sense, inclusive fitness
and parent-offspring conflict theories, as developed by Hamilton (1964) and Trivers (1974), respectively, may turn out
to play a critical role in the evolution of aging. Inclusive
fitness models that incorporate parent-offspring fitness tradeoffs into life-history theory might provide a remarkably different insight into the mechanisms and evolution of aging.
ACKNOWLEDGMENTS
We thank J. Avise, K. Fielman, L. Galloway, T. Haselkorn,
D. Hoyt, A. Keyser, P. Mack, R. Mauricio, G. Priest, and D.
Roach for comments on earlier versions of the manuscript.
We are greatly indebted to A. Berwald, L. Dougherty, A.
Garman, B. Greyson, B. Hammock, T. Haselkorn, J. Kerr,
A. Keyser, C. Linnen, P. Mack, J. Pease, S. Rao, M. Snoke,
L. Yampolsky, and especially L. Pearse for technical assistance. We thank J. Leips, T. Mackay, and S. Nuzhdin for
generously providing the inbred strains. We also thank S.
Kern and T. Kawecki for sharing their manuscript before
publication. We are grateful for the helpful comments of M.
Whitlock and two anonymous reviewers. We extend our gratitude to P. Holtsberg for the Bell (1918) reference. This project was funded by a Georgia Gerontology Consortium Seed
Grant to NKP, a Glenn-American Federation of Aging Research Scholarship to NKP, an NIH traineeship to NKP, and
National Institute on Aging grant AG14027 to DP.
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Corresponding Editor: M. Whitlock