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First published online February 12, 2007
Journal of Experimental Biology 210, 906-918 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.001354
Selection on the timing of adult emergence results in altered circadian clocks in fruit flies Drosophila melanogaster
Chronobiology Laboratory, Evolutionary and Organismal Biology Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, PO Box 6436, Jakkur, Bangalore 560064, Karnataka, India
* Author for correspondence (e-mail: vsharma{at}jncasr.ac.in)
Accepted 4 January 2007
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Summary |
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Key words: Drosophila, selection, circadian, emergence, locomotor activity, circadian period, PRC
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Introduction |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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;
Jackson, 1983;
Saunders, 1992;
Sheeba et al., 2001). Such
emergence patterns have facilitated efforts to derive the `early' and `late'
strains of Drosophila pseudoobscura
(Pittendrigh, 1966), D.
melanogaster (Clayton and Paietta,
1972) and Pectinophora gossypiella
(Pittendrigh and Minis, 1971).
The early and late strains of these species were derived by selecting for
individuals that emerged during the morning (lights-on) and the evening
(lights-off) hours under 12 h:12 h light:dark (LD) cycles. As a result, the
primary emergence peak of the early and late strains diverged by about
4–5 h, and their circadian periodicities (
) differed by about 2.5
h, after 50 generations of selection in D. pseudoobscura, 16
generations in D. melanogaster, and after 9 generations in P.
gossypiella. Furthermore, in D. pseudoobscura and P.
gossypiella, the early–late differences were maintained under a
wide range of photoperiods (Pittendrigh,
1981). Both species showed similar changes in circadian period;
i.e. the early strains had longer than the parental strains, whereas the
late strains had shorter than the parental strains. Although the phase
and of emergence rhythm differed among the selected strains, their
light-induced phase response curve (PRC, a plot of phase shift in the rhythm
as a function of phase of light pulse exposure) were strikingly similar,
suggesting that the circadian pacemakers of the selected and control strains
did not diverge. Pittendrigh interpreted these results in the light of his
`master–slave oscillator model'
(Pittendrigh, 1981) and argued
that the phase and period differences between the selected strains were not
because of the differences in their circadian pacemakers, but due to altered
coupling between the circadian pacemaker (master) and the driven (slave)
oscillators that govern adult emergence rhythm. Although it is possible to
obtain phase separation due to altered coupling between two oscillators, it is
hard to imagine how similar circadian pacemakers can generate oscillations
with widely different .
In a separate study, bimodality in locomotor activity rhythm was used to
derive early and late strains of an Indian population of Drosophila
(D. rajashekari) (Joshi,
1999). In this study, the selected strains were initiated from a
single isofemale line. Such selection schemes involve the highest degree of
inbreeding and linkage disequilibrium, which can lead to inbreeding depression
and elimination of variation from the population (reviewed in
Sharma and Joshi, 2002).
Surprisingly, despite a high degree of homozygosity (due to inbreeding), the
early and late strains not only survived for over 59 generations, but also
continued to respond to selection.
Of the few empirical studies on the selection for early and late emergence,
many suffer from numerous shortcomings that we can now identify and appreciate
with the benefit of hindsight gained through decades of empirical studies in
evolutionary genetics. For example, previous selection studies used
individuals as replicates within the selection regime. Individuals live,
reproduce and die, and as a consequence of heritable differences in
reproductive output among individuals, populations evolve. Hence, the unit of
replication in any study addressing evolutionary questions should be
population, not individuals. Therefore, it is not possible to rule out that
the changes in circadian phenotypes reported in early selection studies may be
a consequence of genetic drift or inbreeding that the populations may have
undergone (reviewed by Prasad and Joshi,
2003; David et al.,
2005; Miller and Hedrick,
2001).
It is believed that circadian clocks have evolved as a consequence of
natural selection under the influence of periodic selection pressures present
in our geophysical environment (reviewed in
Aschöff, 1964;
Hastings et al., 1991;
Saunders, 1992;
Pittendrigh, 1993;
Sharma, 2003a;
Dunlap et al., 2004). This
suggests that temporal scheduling of behaviour and physiology is central to
understanding the evolution of circadian clocks. Therefore, the most
appropriate way of empirically addressing this issue would be to carry out
rigorous and systematic long-term laboratory selection studies on the timing
of rhythmic behaviours, and then to supplement it with a critical evaluation
of its consequence on circadian clocks. In our opinion, this is the approach
that will provide us with meaningful insights into the possible evolutionary
processes that may have been instrumental in the fine-tuning of circadian
clocks.
In this paper, we report the results from the first 55 generations of our ongoing laboratory selection experiment aimed at studying whether circadian clocks in fruit flies D. melanogaster evolve as a consequence of selection on the timing of adult emergence. For this purpose, four replicates each of early, control and late populations were derived from four baseline populations of D. melanogaster. To assess the direct as well as correlated responses of selection on the timing of adult emergence, adult emergence rhythm of the selected and control populations was assayed every 15 generations under LD cycles, and emergence and locomotor activity rhythms were assayed under LD and constant darkness (DD) conditions at the 55th generation.
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Materials and methods |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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).
Briefly, they were maintained as large outbred populations under alternating
12:12 h LD cycles (light intensity 15±5 µW cm–2
s–1) with banana-jaggery food and water available ad
libitum. Temperature (25±1°C) and humidity (75±5%) were
maintained constant throughout the study. A total of 1200 breeding adults per
population, with roughly equal number of males and females, were maintained in
PlexiglasTM cages (25 cmx20 cmx15 cm) on a 21-day discrete
generation cycle. Eggs were collected by placing Petri dishes with food into
these cages during the light phase of the LD cycle, dispensed at a density of
about 300 eggs into vials (18 cm heightx2.4 cm diameter) containing 10
ml of food. Such a high density of eggs resulted in staggered adult emergence
for several cycles. Flies emerging between the 9th and 13th days after egg
collection were collected into PlexiglasTM cages containing a Petri dish
of food. On the 18th day, a generous smear of yeast-acetic acid paste was
applied on the food plates and kept in the cages. Three days later, eggs were
collected to initiate the next generation. These four populations (referred as
the baseline populations) served as the founder populations for the initiation
of the selection lines. From these four baseline populations, four early
(early1..4) and four late (late1..4)
populations were initiated by imposing selection for adult emergence during
the morning (05:00–09:00 h) and the evening (17:00–21:00 h) hour
(henceforth referred to as the morning and evening selection windows) under
12:12 h LD cycles, where lights came on at 08:00 h and went off at 20:00 h
(Fig. 1). Four control
populations (control1..4) were also initiated along with
the selected populations, where no conscious selection pressure was applied on
the timing of adult emergence. Each early, control and late
population was derived from one baseline population, thus forming matched
selected and control pair (earlyi,
controli and latei are more closely
related than earlyj, controlj and
latej, i,j=1–4). For example, the
early1, control1 and
late1 populations were initiated from baseline population
1. The four replicate populations with identical subscripts were treated as
random factor in the analysis of variance (ANOVA). The selected and control
populations were maintained under similar conditions, except that in each
generation the adult flies for the early populations were collected
between 05:00–09:00 h (M, morning window), for the late
populations between 17:00–21:00 h (E, evening window), and the
controls were collected through out the day, for 4–5 successive
days. Care was taken to maintain a large out-bred structure
(N
1200 with roughly equal numbers of males and females) of the
populations.
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Imposition of different maintenance regimes may induce nongenetic parental
effects. Therefore, all selected and control populations were subjected to one
generation of common rearing conditions prior to the assays, during which no
conscious selection pressure was imposed. Such treatment for one generation
has been shown to eliminate nongenetic parental effects
(Prasad et al., 2001). Eggs
were collected from the running cultures and dispensed into vials with about
10 ml of food at a density of about 300 eggs per vial. After the 12th day of
egg collection, adult flies were collected into PlexiglasTM cages with
abundant food. For the assays, flies were supplied with yeast-acetic acid
paste for 2 days prior to the egg collection. The progeny of these flies
hereafter will be referred as standardized flies.
Eclosion assay
The percentage of flies emerging during the M and E windows of selection,
phase-relationship between the eclosion peak and LD cycle, waveform of
emergence rhythm under LD cycles were estimated at 5th, 10th, 25th, 40th and
55th generations, and the waveform and of the emergence rhythm under DD
were assessed at the 55th generation. For these assays, eggs of approximately
same age were collected from the standardized flies and dispensed at
approximately 300 eggs per vial into vials with 10 ml of food. These vials
were kept under LD and DD conditions. Ten such vials were set up per
population for assays under each light condition. These vials were monitored
for the first emergence and thereafter checked regularly at 2 h intervals for
10 consecutive days, and the number of flies was recorded. The percentage of
flies emerging during the M and E windows was estimated by normalizing the
total number of flies emerging during these windows by the total number of
flies that emerged in one complete cycle. The phase-relationship of the
emergence rhythm was estimated as the average time interval between the peak
of eclosion and lights-on in the LD cycle. The phase-relationship values were
considered to be negative if the peak followed lights-on and were taken to be
positive when the peak preceded lights-on. Under DD conditions, adult
emergence was monitored under dim red light (
>640 nm) at 2 h
intervals for 10 consecutive days.
Light pulse phase-response curve (PRC) for emergence rhythm
Light pulse-induced phase-response curves (PRC) were constructed for the
selected as well as the control populations to estimate the extent of clock
sensitivity to light. To estimate the emergence rhythm PRC, flies from
selected and control populations were subjected to brief light stimuli at
circadian time 2 (CT2), CT8, CT14 and CT20. For this assay, eggs of
approximately same age were collected from the standardized populations and
dispensed into vials containing 10 ml of food at an egg density of 300
per vial and maintained under 12 h:12 h LD cycles. After 5 days, flies were
transferred to DD and exposed to light stimuli of 1000 lux intensity and 15
min duration at CT2, CT8, CT14 and CT20, in the first circadian cycle. Ten
such vials were used for light exposure from each replicate population at each
phase and ten more vials served as the experimental controls. The control
vials at each tested CT were transported in light-tight containers (wrapped
additionally with black cloth) along with the experimental vials to ensure
that light pulse per se and not the disturbances associated with
handling, transfer and human interference, cause phase shift. From the primary
data, we estimated the mean phase of primary eclosion peak under LD as well as
DD conditions for the experimental as well as control vials. Phase shifts were
estimated using the method suggested previously
(Sharma and Daan, 2002).
Briefly, two regression lines were drawn through the peaks of emergence, one
immediately following the light pulse and the other preceding it. The phase
shift values were obtained by subtracting control phase shift values (obtained
for the control vials, which were not subjected to the light pulse) from the
experimental phase shift values.
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and waveform of locomotor activity rhythm under DD were estimated at the
55th generation. For the assays, eggs were collected from the standardized
populations and dispensed into vials containing 10 ml of food at a density of
about 300 eggs per vial. Freshly emerged adult flies were transferred
individually into activity monitors within 24 h of their emergence
(Sharma, 2003b). The locomotor
activity behaviour of the flies was monitored for the first 10 days under
12:12 h LD cycles and for about 15 days in DD. The percentage of activity
during the M and E windows of selection was estimated by normalizing the
amount of activity exhibited during these windows by the total amount of
activity in one complete cycle. The phase of the morning and evening activity
peaks under LD cycles were estimated using CLOCKLAB (Actimetrics, Evanston,
IL, USA) taking activity data collected for 10 successive days.
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of emergence rhythm under DD was estimated by subjecting time
series data collected over 10 consecutive cycles to Fourier spectral analysis
using StatisticaTM (rel.5.0B)
(Statistica, 1995).
Statistical significance of rhythmic contributions from different frequencies
in the periodogram was tested using Siegel's modification of the Fischer test
(Siegel, 1980). This method
delineated the frequency components present in the time series by defining a
threshold value (Rao and Sharma,
2002). The of locomotor activity rhythm under DD was
estimated by subjecting time series data collected over ten consecutive cycles
to Lomb-Scargle Periodogram analysis using CLOCKLAB (Actimetrics, Evanson, IL,
USA). The circadian parameters of emergence and locomotor activity rhythms were subjected to separate mixed model analysis of variance (ANOVA) treating replicate as random factor, whereas generation and population as fixed factors crossed with replicates. The percentage of flies emerging during the M and E windows was used as fixed factor crossed with generation, population and replicate. In all statistical analyses, population means were used as the unit of analysis. Multiple comparisons were done using 95% confidence intervals (95%CI) around the mean. The error bars used throughout the text as well as figures, unless otherwise specified are 95%CI to facilitate visual hypothesis testing. Therefore, overlapping error bars would imply that the values do not differ significantly.
The phase-relationship, timing of morning and evening activity peak and
of emergence and locomotor activity rhythms were used as data in a mixed
model ANOVA crossed with replicate and population. The `difference waveforms'
of emergence and locomotor activity rhythms of the selected and control
populations were analyzed using Kolmogorov–Smirnov two-sample test. All
analyses were implemented using Statistica for Windows (rel.5.0B)
(Statistica, 1995).
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Results |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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Emergence rhythm under LD
The `difference waveforms' of the early and late
populations are shown generation-wise in the
Fig. 3. With increasing
generations, a peak began to emerge during the morning in the `difference
waveform' of the early populations, while in the late
populations a similar peak emerged in the evening, indicating that the
waveforms of the selected populations are gradually diverging from the
controls. In addition, a prominent trough appeared (especially in the 40th and
the 55th generation assays) in the early populations, immediately
after the morning peak, suggesting that the percentage of flies emerging at
this phase decreases significantly in the early populations compared
to the controls. Interestingly, this also happens to be the phase of
maximum emergence in the controls
(Fig. 3). The
Kolmogorov–Smirnov two-samples revealed that the `difference waveforms'
of the early and late populations were significantly
different in the 40th (P<0.05) and the 55th (P<0.01)
generation assays.
The primary peak of emergence occurred early in the morning in the early populations, followed by the controls, and then the late populations, and the separation between the peaks of the three populations gradually increased with generation (Fig. 4A; Table 2). Though the emergence peak of the late populations diverged significantly from the early and controls by the 10th generation, those of the early and controls took 25 generations to move away from each other (Fig. 4A). The divergence in the emergence peaks of the selected and control populations is clearly evident in the frequency distribution plot of the phase-relationship of their adult emergence rhythm obtained at the 55th generation (Fig. 4B).
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Emergence rhythm under DD
At the 55th generation, we assayed the adult emergence rhythm of the
selected and control populations under DD. The Kolmogorov–Smirnov test
for two samples revealed that the average `difference waveforms' of the
early and late populations were significantly different
(P<0.01 for each replicate pair).
ANOVA on showed a significant main effect of population
(F2,6=9.51; P<0.01). Multiple comparisons
using 95%CI revealed that the mean of the early populations was
significantly shorter than the controls, while that of the
late populations was significantly longer than the controls
(Fig. 5A). The frequency
distribution of the of emergence rhythm differed among the selected and
control populations (Fig.
5B).
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Locomotor activity rhythm under LD
To estimate the correlated response to selection on the timing of adult
emergence we assayed the locomotor activity rhythm of individual flies from
the selected and control populations. Activity levels during the M and E
selection windows were compared among the early, control and
late populations. The early flies were more active in the
morning, the late flies were more active in the evening, while the
controls were as active in the morning as in the evening
(Fig. 7A–H;
Table 4). The average activity
level during the M window was about 26.2%, 21.0% and 20.1% in the early,
control and late populations
(Fig. 7A), while that during
the E window was about 21.0%, 25.7% and 30.0%
(Fig. 7B). The differences in
the locomotor activity patterns of the selected and control flies persisted
even in the first cycle of DD, following a LD to DD transfer. In DD, the
activity peak of the early flies was restricted to the mid subjective
day, while that of the control and late flies was shifted
towards the late subjective day (Fig.
7I–K). The morning activity peak occurred significantly
earlier in the early flies compared to the late and
controls, while the evening activity peak occurred significantly
later in the late flies compared to the early and
controls (Fig. 8A,B;
Table 5). The frequency
distribution of phase of the morning and evening activity peaks differed among
the selected and control populations (Fig.
8C,D).
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Locomotor activity rhythm under DD
The circadian period () of locomotor activity rhythm of the selected
populations was altered in response to selection
(Fig. 9A–D). ANOVA showed
a significant main effect of population on
(F2,6=0.005; P<0.001). Multiple comparisons
revealed that the mean of the early populations was
significantly shorter than the controls, while that of the
late flies was significantly longer than the controls
(Fig. 9D). As illustrated in
the frequency distribution plot, a greater percentage of early flies
had shorter compared to the controls, while a greater
percentage of late flies had longer compared to the
controls (Fig. 9E).
Further, the of the locomotor activity and adult emergence rhythms
showed a significant positive correlation (r=+0.76;
P<0.003) (Fig.
10).
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Discussion |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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Under LD cycles, the morning peak of activity in the early
populations occurred earlier than the controls, while that of the
late populations occurred later than the controls, thus
unerringly mimicking the adult emergence patterns
(Fig. 7C–H). Although the
total amount of daily activity did not differ among the early,
control and late populations, the waveforms of their locomotor
activity rhythm were significantly different
(Fig. 7C–H;
Fig. 8A,B). The early
flies started activity earlier than the controls and were generally
more active in the morning than evening, while the late flies started
activity later than the controls and were more active in the evening
than morning. The control flies showed bimodal activity pattern and
were as active in the morning as in the evening. Further, the early
flies showed greater anticipation to lights-on, while the late flies
showed greater anticipation to lights-off
(Fig. 7C–E), which is
consistent with their faster and slower circadian periods. Interestingly, the
differences between the activity patterns of the early and
late flies were retained in the first cycle of DD, following an LD to
DD transfer, indicating that the changes in the locomotor activity patterns
are inherent (Fig. 7I–K).
Further, the of emergence and locomotor activity rhythms showed a
significant positive correlation (Fig.
10), suggesting that these two rhythms are genetically correlated.
Such correlations between adult emergence and locomotor activity rhythms have
been previously reported in an early study on the period mutants of
D. melanogaster (Konopka and
Benzer, 1971).
Given that the phase-relationship between a circadian rhythm and LD cycle
depends upon the , and the light pulse PRC of the underlying circadian
clocks (Pittendrigh and Daan,
1976; Sharma and Chidambaram,
2002), the gradual divergence in the phase-relationship of
emergence peaks of the early and late populations
(Fig. 3,
Fig. 4A,
Fig. 8A,B) can be ascribed to
gradual changes in (i) , or (ii) PRC, or (iii) both and PRC. We
observed that both and the PRC of the selected populations have diverged
from each other as well as from the controls. Compared to the
controls, the early populations had shorter , smaller
phase delay at CT14, and larger phase advance at CT20, while the late
populations had longer , greater phase delay at CT14, and smaller phase
advance at CT20 (Fig. 6). While
interpreting the differences in the PRC among the selected and control
populations, one should consider the differences in their values. The
mean of the emergence rhythm of the early and the late
populations differs by about 1.5 h, which could lead to a difference of about
an hour or so in the phase of light exposure in their clocks. While having
little effect during the subjective day, this could have a major impact during
the subjective night when the PRC slopes are steeper. For example, faster
clocks in the early populations would allow the light pulse to fall
at a later phase than the controls, and as a result during the early
subjective night phase delays would be larger, and phase advances during the
late subjective night would be smaller, than the controls. The slower
clocks in the late flies would allow the light pulse to fall at an
earlier phase than the controls, and therefore during the early
subjective night the phase delays would be smaller and phase advances during
the late subjective night would be larger than the controls. However,
such limitations do not weaken the strength of our conclusions on the PRC,
since compared to the controls the early populations undergo
smaller phase delay at CT14 and larger phase advance at CT20, while the
late populations undergo larger delay at CT14 and smaller phase
advance at CT20. This suggests that the actual PRC differences between the
selected and control populations were even larger than those depicted in their
PRCs (Fig. 6). Taken together,
the results of our study indicate that circadian clocks of the early
and late populations have diverged from the controls by
altering their as well as PRC. These results are, however, in sharp
contrast to a few early findings, where the early and late strains were
reported to have a longer and a shorter compared to the parental
controls (Pittendrigh, 1966;
Pittendrigh and Minis, 1971).
Further, in these studies the PRCs of the selected strains were also similar.
On the other hand, in a separate study
(Pittendrigh and Takamura,
1987) where a different species of Drosophila (D.
auraria) was used to raise the early and late emerging strains, the
results were just the opposite. In this case, the early strains had faster
running clocks and the late strains had slower clocks, quite similar to the
results of the present study. It is known that modes of evolutionary
fine-tuning of a trait depend upon a number of factors such as the genetic
architecture of the founder population, especially the available genetic
variance for the trait in question, strength of selection, environmental
conditions and population size. Therefore, it is possible that the differences
in the outcome of studies on the early and late emerging strains were due to
one or more such factors. Moreover, lack of replicates within selection lines,
and inadequate information about the population size and rearing protocols,
make it difficult to estimate the extent of genetic drift or inbreeding that
the selected populations may have undergone in these studies. In addition,
most previous studies were not continued for a long enough time to confirm
whether the selection responses had reached steady state. Some were terminated
as early as the 9th generation and others lasted for not more than 15
generations.
The results of our study can also be taken as empirical evidence for the
morning and evening (M–E) oscillator model proposed by Pittendrigh and
Daan (Pittendrigh and Daan,
1976) and subsequently elaborated by Daan et al.
(Daan et al., 2001). The model
assumes that circadian clocks comprise two oscillators (the M and E
oscillators), which track the `dawn' and `dusk' of the natural LD cycles by
maintaining a precise and reproducible phase-relationship with them. The M
oscillator was proposed to have shorter period and to rely more on phase
advances than delays, whereas the E oscillator was considered to have longer
period and to rely more on phase delays than advances. The early
populations have evolved morning circadian phenotypes with faster running
clocks and PRC with smaller phase delays and greater advances, while the
late populations have evolved evening circadian phenotypes with
slower running clocks and PRC with greater phase delays and smaller advances.
The M–E oscillator model was also critically analyzed in a few recent
studies in Drosophila, where flies with either morning or evening
activity patterns were created by genetically manipulating a small group of
clock neurons (Grima et al.,
2004; Stoleru et al.,
2004). These studies suggest that the morning and evening activity
bouts in locomotor activity cycles are controlled by different sets of
neurons. Given that the early and late flies have evolved
morning and evening circadian phenotypes with almost all the features of the M
and E oscillators proposed in the model, it would be interesting to
investigate if the morning and evening activity patterns in these flies are
regulated by different subgroups of clock neurons or by altered circadian
waveforms of the core clock genes.
Our study is by far the most rigorous and unequivocal of all selection studies done so far on any rhythm or rhythm-related trait. The results are based on genetically independent, random mating, large populations of Drosophila derived from common ancestors, and clearly demonstrate that the time course and waveform of emergence and locomotor activity rhythms diverge from the controls in response to selection on the timing of adult emergence, and as a consequence circadian clocks of the selected populations evolve. The results are borne out of consistent heritable genetic changes in response to selection on the timing of adult emergence and not due to random genetic drift or due to some unknown environmental or non-genetic effect. The results further provide valuable functional insights into the genetic architecture of behavioral rhythms such as emergence and locomotor activity and the underlying genetic correlations between them. The results of our study can also be taken to suggest that one of the possible ways in which circadian clocks evolve, is through the process of adaptive evolution under the influence of periodic selection pressures present in the environment.
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Acknowledgments |
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