Natural Variation in Decision-Making Behavior in
Paige M. Miller1, Julia B. Saltz2,3, Veronica A. Cochrane1, Caitlin M. Marcinkowski1, Raisa Mobin1,
Thomas L. Turner1*
1Ecology, Evolution, and Marine Biology Department, University of California Santa Barbara, Santa Barbara, California, United States of America, 2Center for Population
Biology, University of California Davis, Davis, California, United States of America, 3Molecular and Computational Biology Department, University of Southern California,
Los Angeles, California, United States of America
There has been considerable recent interest in using Drosophila melanogaster to investigate the molecular basis of decision-
making behavior. Deciding where to place eggs is likely one of the most important decisions for a female fly, as eggs are
vulnerable and larvae have limited motility. Here, we show that many natural genotypes of D. melanogaster prefer to lay
eggs near nutritious substrate, rather than in nutritious substrate. These preferences are highly polymorphic in both degree
and direction, with considerable heritability (0.488) and evolvability. Relative preferences are modulated by the distance
between options and the overall concentration of ethanol, suggesting Drosophila integrate many environmental factors
when making oviposition decisions. As oviposition-related decisions can be efficiently assessed by simply counting eggs,
oviposition behavior is an excellent model for understanding information processing in insects. Associating natural genetic
polymorphisms with decision-making variation will shed light on the molecular basis of host choice behavior, the
evolutionary maintenance of genetic variation, and the mechanistic nature of preference variation in general.
Citation: Miller PM, Saltz JB, Cochrane VA, Marcinkowski CM, Mobin R, et al. (2011) Natural Variation in Decision-Making Behavior in Drosophila
melanogaster. PLoS ONE 6(1): e16436. doi:10.1371/journal.pone.0016436
Editor: Daniel J. Kliebenstein, University of California Davis, United States of America
Received October 21, 2010; Accepted December 20, 2010; Published January 20, 2011
Copyright: ? 2011 Miller et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the University of California, Santa Barbara. The funders had no role in study design, data collection and analysis, decision
to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
Drosophila melanogaster is often considered the consummate
generalist, as many different types of rotting fruit or vegetables
can be used as rearing substrate [1,2,3]. Adults are highly motile
, and can experience a wide variety of resources in their lifetime
(e.g. a fallen fruit in an orchard, a compost pile in a suburban area,
or a barrel of fermenting wine in a wine cellar ). In addition to
the wide differences between available food patches, each patch is
likely to be quite heterogeneous. Within a single rotting fruit, for
example, the stochastic nature of colonization by bacteria and
fungi may lead to considerable variation.0 Within this tremen-
dously varied environment, a female fly must assess possible
oviposition sites so that she can decide where to invest her most
valuable resource: her eggs. Females demonstrate plasticity in their
oviposition behavior and make choices that may benefit their
offspring . It was recently shown that flies undergo a search-like
behavior even on homogenous lab medium, and probe possible
oviposition sites with multiple sensory structures . They also
withhold eggs in the absence of quality oviposition media, further
supporting the idea that females are choosy regarding their
Yang and colleagues  recently proposed that oviposition-site
selection is an excellent model for investigating the molecular basis
of decision-making behavior. Surprisingly, these authors found that
females from the Canton-S lab line preferred to oviposit on sucrose-
free media when presented with media containing 1% agar, 1%
ethanol, +/- 1% sucrose. Though Drosophila females clearly need to
environments such as rotting fruit may contain patches of nutritious
substrate interspersed with areas that offer developing embryos
refuge from microbial decomposition. For example, on fruits that
have juststartedtodecompose,wehave observed thatD.melanogaster
females will deposit eggs into the stem cavity in addition to directly
ovipositing into a rotting abscess. If genetic and environmental
variation affects these decisions (as supported by previous studies of
oviposition behavior in Drosophila [6,8,9,10,11,12,13,14,15,16,17,
18,19,20,21,22]), this variation could be used as a model for
individual differences in preference behavior. Here we show that
natural isolates of Drosophila melanogaster have surprising preferences
when presented with simple media containing acetic acid, ethanol
and agar, with or without yeast extract. Though yeast extract
contains important nutrients for developing larvae , females of
many genotypes prefer to oviposit in media lacking yeast extract,
but only when the site is in close proximity to nutritious media. This
behavior requires the integration of multiple information sources,
and therefore presents an interesting opportunity to investigate the
mechanistic basis of decision-making. Moreover, this behavior
varies greatly between genotypes, and is affected by environmental
variables such as the overall concentration of ethanol. By adapting
an apparatus from Joseph et al. , we have quantified these
decisions in thousands of individuals, and established a system that
can be used for genome-wide association studies of decision-making
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To investigate genetic variation in oviposition-related decisions,
we used a two choice assay: two media were poured side-by-side in
a 35 mm petri plate lid, and this lid was presented overnight to
single mated females inside a 170 cc plastic arena. One option
consisted of 1% agar with 0.8% ethanol and 0.8% acetic acid:
ethanol and acetic acid are byproducts of microbial metabolism
which are attractive to D. melanogaster at these doses (see below), but
this substrate contains little nutritional value. The second option
presented was the same, with the addition of highly nutritious
yeast extract (1%). These options are intentionally simple:
preliminary experiments suggested that this 4-ingredient media
(agar, ethanol, acetic acid, +/- yeast) is one of the simplest
substrates females will accept. We expect that this assay (2 options
within a single 35 mm plate) is similar to the decision-making
process faced by females when confronted with a single
heterogeneous patch, such as a rotting fruit. This experiment
was designed not to mimic the natural environment precisely: we
attempted to create a simple, efficient assay that can assess
behavioral variation in a large number of genotypes and
environments. As such, behaviors in this assay could serve as a
simple model system to dissect natural variation in the insect
Genetic variation in decision-making behavior
To assess the extent of genetic variation in oviposition decision-
making, we assayed a total 5187 flies from 295 natural (‘‘wild-
type’’), inbred genotypes. As some genotypes were reticent to
oviposit on either option, five or more replicate females were
assessed from only 213 of these genotypes (mean replicates =11.6).
The average preference for each of these 213 genotypes is shown
in figure 1. Ninety-six of these 213 genotypes were collected at a
fruit market in Raleigh, North Carolina (by T. F. C. Mackay ),
and 117 were collected from a fruit orchard in Winters, California
(by S. Nuzhdin ): the trait values of the two populations are
not significantly different (Raleigh mean =0.775, Winters mean
=0.750, t=1.04, p=0.30), so all genotypes were considered
The average proportion of eggs laid on yeast-free (y-) medium
varied considerably between inbred lines, with one line laying
100% of eggs on y-media in each of 11 replicates, while at the
other extreme a line averaged only 10.4% of eggs laid on this
option. Most lines had less extreme preferences, laying some eggs
on each substrate, but preferring y-: only 9% of genotypes
averaged ,50% on y-. To estimate the proportion of variation in
this trait that results from genetic variation, we partitioned the
variance into within- and among-line components using sum of
squares. The among-genotypes component of variance, which
provides an estimate of the broad-sense heritability, is found to be
considerable: 48.8%. As variance is not homogenous across lines
(some lines have near zero variance), the proportional data are
very non-normal, and sample sizes differ across lines, we
determined the statistical significance of the among-genotype
variance by resampling data 100,000 times and partitioning
variance among this permuted data. Permuted data sets averaged
9.4% among-genotype variance, with no values greater than 14%;
the observed value of 48.8% is therefore clear evidence of
substantial genotypic variation in decision-making (p,1.0e1025).
The among-genotypes component of variance estimates the total
contribution of genetic variation, including additive, dominance,
and epistatic components. To characterize this variation further, we
crossed two of the most extreme genotypes from the Raleigh (RAL)
collection of lines. The RAL-555 line averaged 99% of eggs on y-: of
the 486 eggs laid over 31 replicates, this line laid only 4 eggs on the
y+option. In contrast, RAL-365 laid 270/397 eggs on y+media,
averaging 28.4% of eggs on y-across 20 replicates (fig. 2). Trait
values of F1 genotypes reveal that preference for y-is largely
dominant, with 97% of F1 individuals preferring y-more than the
midparent value. Preferences do not show complete dominance,
however, as only 12.5% of F1 individuals laid 100% of eggs on y-,
Figure 1. The average proportion of eggs laid on y-media for
213 inbred lines. Variance and sample sizes vary considerably
between genotypes (see text), and only means are shown for each
genotype, for clarity. On the right, a histogram of the same data is
shown. Minimum sample size per line =5 females, mean =11.6
Figure 2. The distribution of preferences among females of two
RAL genotypes (R555 and R365), their F1 offspring (with R555
as the maternal parent), and their F2 offspring. Median (line),
75% quartile (box), and range excluding outliers (whiskers), and outliers
(circles) are shown.
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and the distribution of F1 and RAL-555 preferences are
significantly different (Wilcoxon p,1.0e27). In contrast, the
distribution of 346 F2 individuals averaged 57% of eggs on y-, near
the mid-parent value of 63.5%. This may indicate that the apparent
dominance seen in F1 genotypes is due to epistasis, or that there are
threshold effects when phenotypes are near the boundary of 100%.
In any case, these data are consistent with quantitative variation in
We used artificial selection to directly assess the evolvability of
oviposition preferences. An outbred population was created by
cross-mating virgin females and males from 173 inbred lines from
the RAL collection (see methods). After eight generations of
stochastic recombination, we quantified the preferences of 863
outbred individuals from this population. Consistent with partial
dominance, the average preference of these outbred F8individuals
was biased more towards the y-substrate compared to the
distribution of inbred lines (inbred mean =0.76, outbred mean
=0.89; fig. 3). We then divided these 863 females into four
populations: those with preferences above the median value were
divided into two populations to start selection in the y-direction,
and those below the median were used to found two populations in
the y+direction. As shown in figure 3, selection in the y-direction
was immediately and dramatically successful. When realized
heritability is calculated as the ratio of the response to selection
over selection differential, heritability in this direction is estimated
to be slightly more than 1.00 (realized h2=1.10,1.02 for y-1 and y-
2 populations, respectively). In the y+direction, we selected for two
generations: average realized heritability over these two genera-
tions was 0.66 and 0.81 for each population.
For the quantification of preference behavior discussed above,
we discarded data from females who laid fewer than 5 eggs, as
preferences were difficult to assess in these individuals. In
preliminary trials with a small number of genotypes, these
individuals represented a small proportion of the females tested.
As more genotypes were tested, however, we found that the
number of eggs laid was highly variable among genotypes,
and that females of some lines never laid eggs in this assay.
This variation could be due to many factors, but may in part
reflect differences in acceptance of oviposition media between
Of the 282 genotypes for which 5 or more females were
presented with the assay, females from 15 genotypes never laid a
single egg in any replicate. As these lines all oviposit on standard
Drosophila culture media, this may indicate that both of the
substrate options presented are considered inadequate by these
genotypes: rather than choosing between y-and y+media, these
females may be withholding eggs from both options in deference
to potential future options. Figure 4 shows the distribution of
average egg number among genotypes: when partitioning with
sum of squares, 37.3% of this variation is among genotypes,
indicating significant genetic variation for egg number (maximum
of 100,000 permutations =7.40%, p,1.0e1025). Egg number
was significantly correlated with preference among these lines
(r=0.26, p=1.1e24), suggesting that some genetic polymor-
phisms affect both traits (fig. 5). The modest value of the
correlation, however, suggests that these traits are also largely
Figure 3. Violin plots of preference behavior. Each element contains a Tukey box plot showing the median (white dot), 75% quartile (thick line)
and range excluding outliers (thin line). Surrounding the box plot is a kernel density trace, plotted symmetrically on both sides of the boxplot, which
provides a graphical comparison of each distribution (following ). Inbred = distribution of inbred RAL genotypes; Outbred = the F8population
started from these inbred lines; y-1 and y-2= populations selected for a single generation in the direction of 1.00; y+1 and y+2= populations after
two generations of selection in the direction of 0.00.
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To explain the preference of most genotypes for non-nutritious
media, we hypothesized that females of these lines choose to
oviposit near yeast, rather than choose to avoid yeast altogether.
Under this hypothesis, preference for y-media in these lines would
be eliminated if media containing yeast were not adjacent. We
therefore designed an additional experiment, wherein the
preferences of four genotypes were tested with increased distances
between the y+and y-media. For this assay, the media was
prepared in the same manner as above, but the two substrates
were then moved to a large (150 ml) square petri plate. The two
substrates were either placed in contact with one another in the
center of the plate (0-cm distance), or a gap was left between
options (1-cm to 8-cm distance). Mated females from each
genotype were then allowed to oviposit in each petri plate
overnight. We assayed four RAL genotypes with a range of
preferences from the bottle assay (y-proportions 0.989, 0.774,
0.475, and 0.284). Four females from each genotype were used in
each replicate, rather then a single female, to increase the
proportion of replicates with large numbers of eggs.
In all genotypes, the distance between y-and y+media had a
considerable effect on oviposition behavior. When analyzing each
genotype independently, distance explained 63%–78% of the
variance in each line (fig. 6; permutation performed as explained
above, p,1.0e25in each case). For the two lines that oviposited
primarily on y-in the bottle assay (red and orange in fig. 6), the
proportion of eggs on the y-media decreased with distance until, at
8-cm, females laid approximately half of all eggs on y+. For two
lines that did not prefer y-in the bottle assay, distance had an even
more dramatic effect, with nearly all eggs on the y+media by 6-
To determine whether these genotypes respond significantly
differently to distance, we fit a Generalized Linear Mixed Model
(GLMM) using SAS Proc GLIMMIX (v9.2; SAS Institute, Cary,
NC 2009). Because the data were proportions, a binomial
distribution and logit link function were specified. Initial tests
indicated that genotypes differed significantly in variance (test of
homogeneity based on residual pseudo-likelihoods: x2=168.55,
p,0.0001), so the model specified individual covariance param-
eters for each genotype . The resulting model showed no
evidence of overdispersion (Generalized x2/DF
genotypes were chosen non-randomly after the initial screen of
213 genotypes, genotype was considered a fixed factor in the
analysis. The distance between oviposition choices was a
continuous fixed factor. Denominator degrees of freedom for F-
tests were estimated using the Kenward-Rogers method, which is
appropriate for models with complex covariance structures
The GLMM verified a strong effect of distance on the
proportion of eggs laid on the y-side (F1,83.5=29.68, p,0.0001).
Specifically, odds ratio estimates showed that females were 25.5
times (95% CL: 14.6–44.2) more likely to lay on the y-side when
the two oviposition substrates were adjacent than when they were
8 cm apart (fig. 6). The GLMM also confirmed the strong effect of
p=0.0019). Further, a significant genotype-by-distance effect
illustrated that genotypes differed in how the distance between
choices affected their oviposition preferences (F3,77.97= 3.65,
Surprisingly, at the 0-cm distance, the range of preference
variation across genotypes was compressed in the petri-plates
compared to the bottle assay. While average preference of the five
genotypes tested varied from 28%–99% of eggs on y-media in
the bottle assay, the same lines varied from only 73%–98% in the
petri plates. This effect was not due to changing the number of
females in the assay from one to four: we assayed these genotypes
with four flies in the bottle assay, and found no significant
differences compared to the single-female data (permutation
p.0.05 for all genotypes). Instead, this difference seems to be due
to an unknown effect of assay condition, as two of the four lines
tested have significantly different preferences between bottle and
plate assays (Bonferonni-adjusted permutation p,0.05). The
150 ml petri plate is of a similar volume as the bottle assay
(177 ml), so the shape of the container would seem the primary
difference between them. Despite this assay-effect, preferences
were highly correlated between assays (r=0.94), though with only
four lines tested, this correlation is only marginally significant
Figure 4. The average number of eggs laid for 282 inbred lines.
Minimum sample size per line =5 females, mean =16.1 females.
Variance and sample sizes vary considerably between genotypes (see
text), and only means are shown for each genotype, for clarity. On the
right, a histogram of the same data is shown.
Figure 5. The relationship between average egg number and
average preference for each line.
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Other environmental effects
The modification of oviposition-related decisions with distance
suggests that flies integrate multiple sensory modalities when
choosing where to oviposit. To further investigate the plasticity of
these decisions, a subset of genotypes was tested at different
concentrations of ethanol and acetic acid (while keeping the other
ingredients in the media, water and agar, at standard concentra-
When the amount of ethanol in both oviposition substrates is
simultaneously reduced, all genotypes oviposit more eggs on the y+
media (fig. 7). To quantify this effect, we again fit a GLMM with a
binomial distribution and a logit link. Again, genotypes differed
significantly in oviposition preferences (x2=33.25, p=0.0009); the
model specified individual covariance parameters for each
genotype, resulting in no apparent overdispersion (Generalized
x2/DF =1.00). Ethanol concentration significantly predicted
female preference for the y-side (F1,562.4=100.36, p,0.0001).
Females were 2.5 times (95% CL: 1.7–3.8) more likely to lay on y-
when both sides contained 0.8% ethanol, relative to their
preferences when there was no ethanol present. Genotypes also
differed additively in oviposition preference (F12,301.3=14.46,
p,0.0001). There was a significant genotype-by-ethanol effect
(F12,301.3=3.01, p=0.0005), indicating that the relationship
between ethanol concentration and preference for y-differed
across genotypes (fig. 7).
Finally, ten genotypes were assayed at varying concentrations of
acetic acid (0.4% and 0.0%). The relative preferences for y-and y+
media were difficult to assess, however, as flies laid very few eggs in
either media with reduced acetic acid. Seven of the genotypes
tested laid zero eggs in all replicates in the 0.0% condition,
Figure 6. The effect of distance on oviposition preference. A Tukey box plot is shown for each genotype * distance combination; red = RAL-
555, orange = RAL-437, green = RAL-208, blue = RAL-365.
Figure 7. The effect of ethanol on oviposition preference. A: The effect of ethanol on behavior towards yeast is shown for 13 RAL genotypes
at three concentrations of ethanol, where each line is a genotype. B: Plot of mean preference of genotypes in A, at two ethanol concentrations, shows
that preferences are highly correlated between ethanol concentrations, with more avoidance of yeast substrate at higher ethanol concentration.
Natural Decision-Making Variation
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whereas these genotypes all oviposited in the 0.8% acetic acid
condition. We therefore considered acetic acid to be indispensable,
and did not attempt to quantify genotype and genotype-by-
environment effects for this variable.
Here, we have used a simple assay to quantify the oviposition
behaviors of many natural genotypes of Drosophila melanogaster.
Surprisingly, when presented with two options, nutritious substrate
(y+) and non-nutritious substrate (y-), we find that most genotypes
prefer to oviposit in the less nutritious substrate. This behavior is
highly polymorphic, however, with genotypes varying from 100%
to nearly 10% of their eggs in y-substrate. Estimates of heritability
among inbred lines suggest that a considerable fraction (48.8%) of
this variation is genetic, and artificial selection among outbred
individuals demonstrates very high evolvability. This may indicate
that variation in oviposition preferences in this generalist species is
maintained by variable or frequency-dependent selection in
nature, with trade-offs resulting from a balance between the risk
of larvae not finding food and the risk that they will fail to develop
in rotting substrate. However, other explanations are certainly
possible. The simplicity of the assay conditions, which makes it
possible to quantify this behavior in a large number of individuals,
also means that any hypotheses regarding the significance of this
variation in nature are tentative. For example, it may be that this
variation is ‘‘cryptic’’ in the wild, and only becomes additive
(selectable) in laboratory conditions . In any case, determining
the genes, gene networks, and neural substrates involved in
decision-making in the lab would be extremely useful for
understanding analogous variation in nature. If the molecular
mechanisms which contribute to these behaviors could be
discovered using high-throughput laboratory quantification, tar-
geted studies of these same processes could then assess the genetic
basis of oviposition variation in nature, even if the effects of
individual genetic polymorphisms was variable.
The data presented here suggest that, when female D.
melanogaster decide where to deposit their eggs, they are making a
complex decision, and integrating many aspects of environmental
variation. For females to prefer y-media, but only when it is
adjacent to y+media, flies must either compare short-range
sensory modalities with long-range modalities (e.g. smelling yeast
but not tasting it), or compare short-range sensory indicators with
spatial memory of the position of other substrates. We feel the
second explanation is more likely, as some genotypes behaved very
differently when options were only 1-cm apart compared to 0-cm,
and again very differently at 6-cm compared to 1-cm (fig. 6). This
hypothesis is perhaps supported by the apparent effect of the shape
of the assay container on preference at 0-cm as well. In addition,
females alter their decisions regarding yeast extract when the
overall ethanol concentration changes, indicating that the
concentration of ethanol alters their assessment regarding yeast.
These interactions between environmental variables highlight the
utility of first using a minimal media to quantify the molecular
basis of decision-making behavior, and increasing ecological
complexity as interactions are subsequently understood.
Recent advances in sequencing technology have created the
opportunity to amass impressive amounts of data regarding
genetic polymorphisms [31,32,33]. Understanding how this
variation is maintained, and how it is utilized (or tolerated) by
biological systems, depends on linking it to variation in phenotype.
Our ability to mechanistically understand the morphology,
behavior, and development of organisms also depends on our
ability to analyze perturbations to the system, which are readily
provided by natural polymorphisms. Here, we have taken the first
steps towards understanding the basis of natural variation in
decision-making behavior in Drosophila by quantifying genetic and
environmental effects on these decisions.
Inbred genotypes are maintained in non-overlapping genera-
tions in 37 ml polypropylene vials on agar-cornmeal-molasses-
killed yeast medium (,6 ml per vial). To acquire females for the
oviposition assay, 5 to 8 females and males were selected and
placed in a fresh food vial with a small amount of live yeast. The
flies were allowed to lay eggs for 2 to 3 days at 25uC on a 12 hour
light:dark cycle; the adult flies were then destroyed, and vials were
kept at 25uC on a 12 hour light:dark cycle. Twelve to thirteen days
post egg laying, mature offspring were anesthetized with CO2and
females were selected for the subsequent assays.
An outbred population was created by cross-mating virgin
females and males from 173 of the inbred lines from the RAL
collection. One to four males and one to four virgin females were
collected from each inbred genotype (540 flies in total), and these
males and females were haphazardly mixed into vials with five
males and five females per vial (no males were placed in vials with
females from their own genotype, insuring that all F1 offspring
were mixed genotypes). For the following seven generations, all
offspring were collected and mixed, and approximately 500 males
and 500 females were haphazardly allocated across 100 individual
vials. These vials were maintained in the same manner described
above for inbred lines.
All female flies to be used in assays were anesthetized 24 hours
before testing began and placed singly in 8 ml polypropylene test
tubes containing 0.5 ml of agar-cornmeal-molasses-killed yeast
medium. To test oviposition choices, female flies were then gently
tapped into a 170 cc square bottom polypropylene bottle. A
35 mm petri dish lid, containing the two oviposition media, was
fitted to the mouth of this bottle. The petri dish then served as both
a bottle closure and an oviposition substrate container. This bottle
was then placed in an inverted position (so that the petri dish lid
was the base).
To prepare each petri dish lid, a steel razor blade was used as a
divider: 2 ml of media were pipetted into each side of the divided
lid, and blades were removed after media hardened. This left no
gap between the two substrates, as the agar media expanded to
occupy the space where the blade had been. Media were prepared
in large batches; non-yeast media were prepared with 1% Bacto
agar by weight (Difco), 0.8% ethanol by volume, and 0.8% acetic
acid by volume in water; ethanol and acetic acid were added after
media had cooled. Yeast-containing media was prepared the same,
but contained 1% Bacto yeast extract by weight (Difco). Flies were
allowed to oviposit for ,16 hours from 5 pm to 9 am at 25uC and
,50% humidity. The eggs laid on each type media were then
counted by hand under magnification.
Distance Oviposition Assay
Female flies to be used in the assay were collected in the same
manner described above, except 4 females were placed in each test
tube rather than one. The media were prepared as above and
added to petri dish lids but only one media was placed on each
side of the razor blade in each dish. This insured that no yeast
media would contact the yeast-free media on any surface. The two
media were carefully removed from the small petri dish lids and
Natural Decision-Making Variation
PLoS ONE | www.plosone.org6 January 2011 | Volume 6 | Issue 1 | e16436
placed in the bottom half of a 150 ml square petri dish. They were Download full-text
separated by a distance of 0 cm (in contact, as in the other assay)
to 8 cm. The square petri dish lid was placed on top and the
female flies were aspirated into the dish through a small hole that
was then sealed. Flies were allowed to oviposit overnight for
,16 hours at 25uC at ,50% humidity. The eggs laid on each type
media were then counted by hand under magnification.
Conceived and designed the experiments: TLT. Performed the experi-
ments: PMM VAC CMM RM TLT. Analyzed the data: PMM JBS TLT.
Wrote the paper: PMM JBS TLT.
1. Evans AT (1916) Some observations on the breeding habits of the common
house-fly. Journal of Economic Entomology 9: 354–362.
2. Jaenike J (1983) Induction of host preference in Drosophila melanogaster. Oecologia
3. Lutz FE (1914) Biological notes concerning Drosophila ampelophila. Journal of
the New York Entomological Society 22: 134–138.
4. Coyne JA, Boussy IA, Prout T, Bryant SH, Jones JS, et al. (1982) Long-Distance
Migration of Drosophila. American Naturalist 119: 589–595.
5. Hoffmann AA, McKechnie SW (1991) Heritable variation in resource utilization
and response in a winery population of Drosophila melanogaster. Evolution 45:
6. Wertheim B, Dicke M, Vet LEM (2002) Behavioral plasticity in support of a
benefit for aggregation pheromone use in Drosophila melanogaster. Entomologia
Experimentalis et Applicata 103: 61–71.
7. Yang C-h, Belawat P, Hafen E, Jan LY, Jan Y-N (2008) Drosophila egg-laying site
selection as a system to study simple decision-making processes. Science 319:
8. Eisses KT (1997) The influence of 2-propanol and acetone on oviposition rate
and ovoposition site preference for acetic acid and ethanol of Drosophila
melanogaster. Behavior Genetics 27: 171–179.
9. Barker JS, Starmer WT (1999) Environmental effects and the genetics of
oviposition site preference for natural yeast substrates in Drosophila buzzatii.
Hereditas 130: 145–175.
10. Possidente B, Mustafa M, Collins L (1999) Quantitative genetic variation for
oviposition preference with respect to phenylthiocarbamide in Drosophila
melanogaster. Behavior Genetics 29: 193–198.
11. Ruiz-Dubreuil G, Burnet B, Connolly K (1994) Behavioral correlates of selection
for oviposition by Drosophila melanogaster females in a patchy environment.
Heredity 73: 103–110.
12. Garcia-Dorado A, Martin P, Garcia N (1991) Soft selection and quantitative
genetic variation - a laboratory experiment. Heredity 66: 313–323.
13. van Delden W, Kamping A (1990) Genetic variation for oviposition behavior in
Drosophila melanogaster. 2. Oviposition preferences and differential survival.
Behavior Genetics 20: 661–673.
14. Gonzalez D (1989) Genetics of factors affecting the life history of Drosophila
melanogaster. 3. Egg insertion behavior. Behavior Genetics 19: 301–313.
15. Gonzalez D (1990) Genetics of factors affecting the life history of Drosophila
melanogaster. 4. Cytoplasmic maternal factors affect egg insertion behavior.
Behavior Genetics 20: 675–686.
16. Albornoz J, Dominguez A (1987) Genetic analysis of Drosophila melanogaster egg
insertion behavior. Behavior Genetics 17: 257–262.
17. Courtney SP, Chen GK (1988) Genetic and environmental variation in
oviposition behaviour in the mycophagous Drosophila suboccidentalis Spcr.
Functional Ecology 2: 521–528.
18. Del Solar E (1968) Selection for and against gregariousness in choice of
oviposition sites by Drosophilapseudoobscura. Genetics 58: 275–282.
19. Mery F, Kawecki TJ (2002) Experimental evolution of learning ability in fruit
flies. Proceedings of the National Academy of Sciences 99: 14274–14279.
20. Hoffmann AA (1985) Effects of experience on oviposition and attraction in
Drosophila - comparing apples and oranges. American Naturalist 126: 41–51.
21. Jaenike J (1982) Evironmental modification of oviposition behavior in Drosophila.
The American Naturalist 119: 784–802.
22. Fogleman JC (1979) Oviposition site preference for substrate temperature in
Drosophila melanogaster. Behavior Genetics 9: 407–412.
23. Tatum EL (1939) Nutritional requirements of Drosophila melanogaster. Proceedings
of the National Academy of Sciences 25: 490–496.
24. Joseph RM, Devineni AV, King IFG, Heberlein U (2009) Oviposition
preference for and positional avoidance of acetic acid provide a model for
competing behavioral drives in Drosophila. Proceedings of the National Academy
of Sciences 106: 11352–11357.
25. Mackay TFC, Richards S, Gibbs R (2008) Proposal to Sequence a Drosophila
Genetic Reference Panel: A Community Resource for the Study of Genotypic
and Phenotypic Variation White Paper.
26. Nuzhdin SV, Wayne ML, Harmon KL, McIntyre LM (2004) Common pattern
of evolution of gene expression level and protein sequence in Drosophila.
Molecular Biology and Evolution 21: 1308–1317.
27. Schabenberger O (2007) Introducing the GLIMMIX Procedure for Generalized
Linear Models. SUGI (SAS User’s Group International) 196-30: Cary, NC: SAS
28. Schaalje GB, McBride JB, Fellingham GW (2001) Approximations to
distributions of test statistics in complex mixed linear models using SAS Proc
MIXED. SUGI (SAS User’s Group International) 26-262: Cary, NC: SAS
29. Littell RC, Milliken GA, Stroup WW, Schabenberger O (2006) SAS for Mixed
Models, Second Edition. Cary, NC: SAS Institute.
30. Gibson G, Dworkin I (2004) Uncovering cryptic genetic variation. Nature
Reviews Genetics 5: 681–690.
31. Frazer KA, Eskin E, Kang HM, Bogue MA, Hinds DA, et al. (2007) A sequence-
based variation map of 8.27 million SNPs in inbred mouse strains. Nature 448:
32. Begun DJ, Holloway AK, Stevens K, Hiller LW, Poh Y-P, et al. (2007)
Population genomics: Whole-genome analysis of polymorphism and divergence
in Drosophila simulans. Plos Biology 5: e310.
33. Turner TL, Bourne EC, von Wettberg EJ, Hu TT, Nuzhdin S (2010) Population
resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils.
Nature Genetics 42: 260–263.
34. Hintze JL, Nelson RD (1998) Violin plots: A box plot-density trace synergism.
The American Statistician 52: 181–184.
Natural Decision-Making Variation
PLoS ONE | www.plosone.org7 January 2011 | Volume 6 | Issue 1 | e16436